Rule-weighted and terminal-weighted context-free grammars have identical expressivity

Abstract: Two formalisms, both based on context-free grammars, have recently been proposed as a basis for a non-uniform random generation of combinatorial objects. The former, introduced by Denise et al, associates weights with letters, while the latter, recently explored by Weinberg et al in the context of random generation, associates weights to transitions. In this short note, we use a simple modification of the Greibach Normal Form transformation algorithm, due to Blum and Koch, to show the equivalent expressivities, in term of their induced distributions, of these two formalisms.


On Exploiting Hotspot and Entropy for Data Forwarding in Delay Tolerant Networks

Abstract: Performance of data forwarding in Delay Tolerant Networks (DTNs) benefits considerably if one can make use of human mobility in terms of social structures. However, it is difficult and time-consuming to calculate the centrality and similarity of nodes by using solutions for traditional social networks, this is mainly because of the transient node contact and the intermittently connected environment. In this work, we are interested in the following question: Can we explore some other stable social attributes to quantify the centrality and similarity of nodes? Taking GPS traces of human walks from the real world, we find that there exist two known phenomena. One is public hotspot, the other is personal hotspot. Motivated by this observation, we present Hoten (hotspot and entropy), a novel routing metric to improve routing performance in DTNs. First, we use the relative entropy between the public hotspots and the personal hotspots to compute the centrality of nodes. Then we utilize the inverse symmetrized entropy of the personal hotspots between two nodes to compute the similarity between them. Third, we exploit the entropy of personal hotspots of a node to estimate its personality. Besides, we propose a method to ascertain the optimized size of hotspot. Finally, we compare our routing strategy with other state-of-the-art routing schemes through extensive trace-driven simulations, the results show that Hoten largely outperforms other solutions, especially in terms of combined overhead/packet delivery ratio and the average number of hops per message.


How Can Journal Impact Factors be Normalized across Fields of Science? An Assessment in terms of Percentile Ranks and Fractional Counts

Abstract: Using the CD-ROM version of the Science Citation Index 2010 (N = 3,705 journals), we study the (combined) effects of (i) fractional counting on the impact factor (IF) and (ii) transformation of the skewed citation distributions into a distribution of 100 percentiles and six percentile rank classes (top-1%, top-5%, etc.). Do these approaches lead to field-normalized impact measures for journals? In addition to the two-year IF (IF2), we consider the five-year IF (IF5), the respective numerators of these IFs, and the number of Total Cites, counted both as integers and fractionally. These various indicators are tested against the hypothesis that the classification of journals into 11 broad fields by PatentBoard/National Science Foundation provides statistically significant between-field effects. Using fractional counting the between-field variance is reduced by 91.7% in the case of IF5, and by 79.2% in the case of IF2. However, the differences in citation counts are not significantly affected by fractional counting. These results accord with previous studies, but the longer citation window of a fractionally counted IF5 can lead to significant improvement in the normalization across fields.


Lower Bounds for Existential Pebble Games and k-Consistency Tests

Abstract: The existential k-pebble game characterizes the expressive power of the existential-positive k-variable fragment of first-order logic on finite structures. The winner of the existential k-pebble game on two given finite structures can be determined in time O(n2k) by dynamic programming on the graph of game configurations. We show that there is no O(n(k-3)/12)-time algorithm that decides which player can win the existential k-pebble game on two given structures. This lower bound is unconditional and does not rely on any complexity-theoretic assumptions. Establishing strong k-consistency is a well-known heuristic for solving the constraint satisfaction problem (CSP). By the game characterization of Kolaitis and Vardi our result implies that there is no O(n(k-3)/12)-time algorithm that decides if strong k-consistency can be established for a given CSP-instance.


Generalized Complexity of ALC Subsumption

Abstract: The subsumption problem with respect to terminologies in the description logic ALC is EXPTIME-complete. We investigate the computational complexity of fragments of this problem by means of allowed Boolean operators. Hereto we make use of the notion of clones in the context of Post's lattice. Furthermore we consider all four possible quantifier combinations for each fragment parameterized by a clone. We will see that depending on what quantifiers are available the classification will be either tripartite or a quartering.


Using Data Warehouse to Support Building Strategy or Forecast Business Tend

Abstract: The data warehousing is becoming increasingly important in terms of strategic decision making through their capacity to integrate heterogeneous data from multiple information sources in a common storage space, for querying and analysis. So it can evolve into a multi-tier structure where parts of the organization take information from the main data warehouse into their own systems. These may include analysis databases or dependent data marts. As the data warehouse evolves and the organization gets better at capturing information on all interactions with the customer. Data warehouse can track customer interactions over the whole of the customer's lifetime.


Reed's conjecture on some special classes of graphs

Abstract: Reed conjectured that for any graph $G$, $\chi(G) \leq \lceil \frac{\omega(G)+\Delta(G)+1}{2}\rceil$, where $\chi(G)$, $\omega(G)$, and $\Delta(G)$ respectively denote the chromatic number, the clique number and the maximum degree of $G$. In this paper, we verify this conjecture for some special classes of graphs, in particular for subclasses of $P_5$-free graphs or $Chair$-free graphs.


Reed's Conjecture on hole expansions

Abstract: In 1998, Reed conjectured that for any graph $G$, $\chi(G) \leq \lceil \frac{\omega(G) + \Delta(G)+1}{2}\rceil$, where $\chi(G)$, $\omega(G)$, and $\Delta(G)$ respectively denote the chromatic number, the clique number and the maximum degree of $G$. In this paper, we study this conjecture for some expansions of graphs, that is graphs obtained with the well known operation composition of graphs. We prove that Reed's Conjecture holds for expansions of bipartite graphs, for expansions of odd holes where the minimum chromatic number of the components is even, when some component of the expansion has chromatic number 1 or when a component induces a bipartite graph. Moreover, Reed's Conjecture holds if all components have the same chromatic number, if the components have chromatic number at most 4 and when the odd hole has length 5. Finally, when $G$ is an odd hole expansion, we prove $\chi(G)\leq\lceil\frac{\omega(G)+\Delta(G)+1}{2}\rceil+1$.


Discretization of a matrix in the problem of quadratic functional binary minimization

Abstract: The capability of discretization of matrix elements in the problem of quadratic functional minimization with linear member built on matrix in N-dimensional configuration space with discrete coordinates is researched. It is shown, that optimal procedure of replacement matrix elements by the integer quantities with the limited number of gradations exist, and the efficient of minimization does not reduce. Parameter depends on matrix properties, which allows estimate the capability of using described procedure for given type of matrix, is found. Computational complexities of algorithm and RAM requirements are reduced by 16 times, correct using of integer elements allows increase minimization algorithm speed by the orders.


Towards a new metamodel for the Task Flow Model of the Discovery Method

Abstract: This paper presents our proposal for the evolution of the metamodel for the Task Algebra in the Task Flow model for the Discovery Method. The original Task Algebra is based on simple and compound tasks structured using operators such as sequence, selection, and parallel composition. Recursion and encapsulation were also considered. We propose additional characteristics to improve the capabilities of the metamodel to represent accurately the Task Flow Model.


Integrated Development Environment Gesture for modeling workflow diagrams

Abstract: The current software development tools show the same form of interaction as when they started back, in the mid 70's. However, since the appearance of visual languages and due to their own nature, they can be handled by tools which have different input methods to conventional ones. By incorporating new motion detection technology, it is intended that new forms of interaction are established. Interactions which respond to the free movement of hands, therefore the software's developer will have a substantial improvement in the user experience.


Automating embedded analysis capabilities and managing software complexity in multiphysics simulation part I: template-based generic programming

Abstract: An approach for incorporating embedded simulation and analysis capabilities in complex simulation codes through template-based generic programming is presented. This approach relies on templating and operator overloading within the C++ language to transform a given calculation into one that can compute a variety of additional quantities that are necessary for many state-of-the-art simulation and analysis algorithms. An approach for incorporating these ideas into complex simulation codes through general graph-based assembly is also presented. These ideas have been implemented within a set of packages in the Trilinos framework and are demonstrated on a simple problem from chemical engineering.


DNS-based Ingress Load Balancing: An Experimental Evaluation

Abstract: Multihomed services can load-balance their incoming connection requests using DNS, resolving the name of the server with different addresses depending on the link load that corresponds to each address. Previous work has studied a number of problems with this approach, e.g., due to Time-to-Live duration violations and client proximity to local DNS servers. In this paper, we experimentally evaluate a DNS-based ingress traffic engineering system that we deployed at Georgia Tech. Our objective is to understand whether simple and robust load balancing algorithms can be accurate in practice, despite aforementioned problems with DNS-based load balancing methods. In particular, we examine the impact of various system parameters and of the main workload characteristics. We show that a window-based measurement scheme can be fairly accurate in practice, as long as its window duration has been appropriately configured.


Indexing Reverse Top-k Queries

Abstract: We consider the recently introduced monochromatic reverse top-k queries which ask for, given a new tuple q and a dataset D, all possible top-k queries on D union {q} for which q is in the result. Towards this problem, we focus on designing indexes in two dimensions for repeated (or batch) querying, a novel but practical consideration. We present the insight that by representing the dataset as an arrangement of lines, a critical k-polygon can be identified and used exclusively to respond to reverse top-k queries. We construct an index based on this observation which has guaranteed worst-case query cost that is logarithmic in the size of the k-polygon. We implement our work and compare it to related approaches, demonstrating that our index is fast in practice. Furthermore, we demonstrate through our experiments that a k-polygon is comprised of a small proportion of the original data, so our index structure consumes little disk space.


Development of application for discovering and binding to published geospatial processes in distributed environments

Abstract: Nowadays, society has recognized that the lack of access to spatial data and tools for their analysis is the limiting factor of economic development. It came to the realization that without the single information space, which is implemented in the form of spatial data infrastructures, a progressive business development is impossible. Spatial data infrastructures will support a variety of tasks, which requires the binding of geospatial information from multiple sources. In the last few years, the rate of progress in spatial data collection was higher, than in management and analysis of data. Infrastructures allow the accumulated data to be available to large groups of users, and infrastructure of analysis allows the data to be effectively used for such tasks as municipal planning, science research, etc. Moreover, free access to the information resources and instruments of analysis will serve as an additional impulse to development of application models in corresponding areas of expertise. The goal of this paper is to indicate possible solutions to the client-side problems of spatial data analysis in distributed environments, using the developing application for data analysis as an example.


Method Study on the 3x+1 Problem

Abstract: The 3x+1 problem is one of the most classical problems in computer science, related to many fields. As it is thought by scientists a highly hard problem, resolving it successfully not only can improve the research in many relating fields, but also be meaningful to the method study. By deep analyzing the 3x+1 calculation process with the input positive integer becoming greater, we find a useful way for solving this problem with high probability. By making use of the greater calculating ability of great computers and the internet, our way is a valid and powerful way for utterly solving the 3x+1 problem. This way can be expressed in three points: 1) If we can find a positive integer N, for any positive integer less than 2N, the times of dividing 2 out of its stopping time is less than or equal to N, then the 3x+1 conjecture is true; 2) This N may be big, so the calculation may be too big. Our way for solving this is: to find a positive integer K, for all positive integers less than 2K, not all the times of dividing 2 out of their stopping time for these integers are less than or equal to K, some part of these are greater than K, but the number of this part becomes less and less with the K increasing; 3) This K and the calculation may also be too big, our way for solving this is: to find a positive integer R, for all positive integers less than 2R, as above, out of their stopping time, the times of dividing 2 of some part of these integers are greater than R, also the number of this part integers does not become less immediately with the R increasing, but the increasing rate of this number is less and less until to below zero.


On the Parameterized Complexity and Kernelization of the Workflow Satisfiability Problem

Abstract: A workflow specification defines a set of steps and the order in which those steps must be executed. Security requirements may impose constraints on which groups of users are permitted to perform subsets of those steps. A workflow specification is said to be satisfiable if there exists an assignment of users to workflow steps that satisfies all the constraints. An algorithm for determining whether such an assignment exists is important, both as a static analysis tool for workflow specifications, and for the construction of run-time reference monitors for workflow management systems. Finding such an assignment is a hard problem in general, but work by Wang and Li in 2010 using the theory of parameterized complexity suggests that efficient algorithms exist under reasonable assumptions about workflow specifications. In this paper, we improve the complexity bounds for the workflow satisfiability problem. We also generalize and extend the types of constraints that may be defined in a workflow specification and prove that the satisfiability problem remains fixed-parameter tractable for such constraints. Finally, we consider preprocessing for the problem and prove that in an important special case, in polynomial time, we can reduce the given input into an equivalent one, where the number of users is at most the number of steps. We also show that no such reduction exists for two natural extensions of this case, which bounds the number of users by a polynomial in the number of steps, provided a widely-accepted complexity-theoretical assumption holds.


Fast Computation of Common Left Multiples of Linear Ordinary Differential Operators

Abstract: We study tight bounds and fast algorithms for LCLMs of several linear differential operators with polynomial coefficients. We analyze the arithmetic complexity of existing algorithms for LCLMs, as well as the size of their outputs. We propose a new algorithm that recasts the LCLM computation in a linear algebra problem on a polynomial matrix. This algorithm yields sharp bounds on the coefficient degrees of the LCLM, improving by one order of magnitude the best bounds obtained using previous algorithms. The complexity of the new algorithm is almost optimal, in the sense that it nearly matches the arithmetic size of the output.


Interleaving Commands: a Threat to the Interoperability of Smartcard Based Security Applications

Abstract: Although smartcards are widely used, secure smartcard interoperability has remained a significant challenge. Usually each manufacturer provides a closed environment for their smartcard based applications including the microchip, associated firmware and application software. While the security of this "package" can be tested and certified for example based on the Common Criteria, the secure and convenient interoperability with other smartcards and smartcard applications is not guaranteed. Ideally one would have a middleware that can support various smartcards and smartcard applications. In our ongoing research we study this scenario with the goal to develop a way to certify secure smartcard interoperability in such an environment. Here we discuss and experimentally demonstrate one critical security problem: if several smartcards are connected via a middleware it is possible that a smartcard of type S receives commands that were supposed to be executed on a different smartcard of type S'. Such "external commands" can interleave with the commands that were supposed to be executed on S. Here we demonstrate this problem experimentally with a Common Criteria certified digital signature process on two commercially available smartcards. Importantly, in some of these cases the digital signature processes terminate without generating an error message or warning to the user.


A note on a problem in communication complexity

Abstract: In this note, we prove a version of Tarui's Theorem in communication complexity, namely $PH^{cc} \subseteq BP\cdot PP^{cc}$. Consequently, every measure for $PP^{cc}$ leads to a measure for $PH^{cc}$, subsuming a result of Linial and Shraibman that problems with high mc-rigidity lie outside the polynomial hierarchy. By slightly changing the definition of mc-rigidity (arbitrary instead of uniform distribution), it is then evident that the class $M^{cc}$ of problems with low mc-rigidity equals $BP\cdot PP^{cc}$. As $BP\cdot PP^{cc} \subseteq PSPACE^{cc}$, this rules out the possibility, that had been left open, that even polynomial space is contained in $M^{cc}$.


Pebble games with algebraic rules

Abstract: We define a general framework of partition games for formulating two-player pebble games over finite structures. We show that one particular such game, which we call the invertible-map game, yields a family of polynomial-time approximations of graph isomorphism that is strictly stronger than the well-known Weisfeiler-Lehman method. The general framework we introduce includes as special cases the pebble games for finite-variable logics with and without counting. It also includes a matrix-equivalence game, introduced here, which characterises equivalence in the finite-variable fragments of matrix-rank logic. We show that the equivalence defined by the invertible-map game is a refinement of the equivalence defined by each of these games for finite-variable logics.


VIQI: A New Approach for Visual Interpretation of Deep Web Query Interfaces

Abstract: Deep Web databases contain more than 90% of pertinent information of the Web. Despite their importance, users don't profit of this treasury. Many deep web services are offering competitive services in term of prices, quality of service, and facilities. As the number of services is growing rapidly, users have difficulty to ask many web services in the same time. In this paper, we imagine a system where users have the possibility to formulate one query using one query interface and then the system translates query to the rest of query interfaces. However, interfaces are created by designers in order to be interpreted visually by users, machines can not interpret query from a given interface. We propose a new approach which emulates capacity of interpretation of users and extracts query from deep web query interfaces. Our approach has proved good performances on two standard datasets.


ViQIE: A New Approach for Visual Query Interpretation and Extraction

Abstract: Web services are accessed via query interfaces which hide databases containing thousands of relevant information. User's side, distant database is a black box which accepts query and returns results, there is no way to access database schema which reflect data and query meanings. Hence, web services are very autonomous. Users view this autonomy as a major drawback because they need often to combine query capabilities of many web services at the same time. In this work, we will present a new approach which allows users to benefit of query capabilities of many web services while respecting autonomy of each service. This solution is a new contribution in Information Retrieval research axe and has proven good performances on two standard datasets.


A note on the bivariate distribution representation of two perfectly correlated random variables by Dirac's $\delta$-function

Abstract: In this paper we discuss the representation of the joint probability density function of perfectly correlated continuous random variables, i.e., with correlation coefficients $\rho=pm1$, by Dirac's $\delta$-function. We also show how this representation allows to define Dirac's $\delta$-function as the ratio between bivariate distributions and the marginal distribution in the limit $\rho\rightarrow \pm1$, whenever this limit exists. We illustrate this with the example of the bivariate Rice distribution


Constraint LTL Satisfiability Checking without Automata

Abstract: This paper introduces a novel technique to decide the satisfiability of formulae written in the language of Linear Temporal Logic with Both future and past operators and atomic formulae belonging to constraint system D (CLTLB(D) for short). The technique is based on the concept of bounded satisfiability, and hinges on an encoding of CLTLB(D) formulae into QF-EUD, the theory of quantifier-free equality and uninterpreted functions combined with D. Similarly to standard LTL, where bounded model-checking and SAT-solvers can be used as an alternative to automata-theoretic approaches to model-checking, our approach allows users to solve the satisfiability problem for CLTLB(D) formulae through SMT-solving techniques, rather than by checking the emptiness of the language of a suitable automaton A_{\phi}. The technique is effective, and it has been implemented in our Zot formal verification tool.


Source Unfoldings of Convex Polyhedra via Certain Closed Curves

Abstract: We extend the notion of a source unfolding of a convex polyhedron P to be based on a closed polygonal curve Q in a particular class rather than based on a point. The class requires that Q "lives on a cone" to both sides; it includes simple, closed quasigeodesics. Cutting a particular subset of the cut locus of Q (in P) leads to a non-overlapping unfolding of the polyhedron. This gives a new general method to unfold the surface of any convex polyhedron to a simple, planar polygon.


Scheduling Unrelated Machines of Few Different Types

Abstract: A very well-known machine model in scheduling allows the machines to be unrelated, modelling jobs that might have different characteristics on each machine. Due to its generality, many optimization problems of this form are very difficult to tackle and typically APX-hard. However, in many applications the number of different types of machines, such as processor cores, GPUs, etc. is very limited. In this paper, we address this point and study the assignment of jobs to unrelated machines in the case that each machine belongs to one of a fixed number of types and the machines of each type are identical. We present polynomial time approximation schemes (PTASs) for minimizing the makespan for multidimensional jobs with a fixed number of dimensions and for minimizing the L_p-norm. In particular, our results subsume and generalize the existing PTASs for a constant number of unrelated machines and for an arbitrary number of identical machines for these problems. We employ a number of techniques which go beyond the previously known results, including a new counting argument and a method for making the concept of sparse extreme point solutions usable for a convex program.


Robot Navigation using Reinforcement Learning and Slow Feature Analysis

Abstract: The application of reinforcement learning algorithms onto real life problems always bears the challenge of filtering the environmental state out of raw sensor readings. While most approaches use heuristics, biology suggests that there must exist an unsupervised method to construct such filters automatically. Besides the extraction of environmental states, the filters have to represent them in a fashion that support modern reinforcement algorithms. Many popular algorithms use a linear architecture, so one should aim at filters that have good approximation properties in combination with linear functions. This thesis wants to propose the unsupervised method slow feature analysis (SFA) for this task. Presented with a random sequence of sensor readings, SFA learns a set of filters. With growing model complexity and training examples, the filters converge against trigonometric polynomial functions. These are known to possess excellent approximation capabilities and should therfore support the reinforcement algorithms well. We evaluate this claim on a robot. The task is to learn a navigational control in a simple environment using the least square policy iteration (LSPI) algorithm. The only accessible sensor is a head mounted video camera, but without meaningful filtering, video images are not suited as LSPI input. We will show that filters learned by SFA, based on a random walk video of the robot, allow the learned control to navigate successfully in ca. 80% of the test trials.


Communication Analysis modelling techniques

Abstract: This report describes and illustrates several modelling techniques proposed by Communication Analysis; namely Communicative Event Diagram, Message Structures and Event Specification Templates. The Communicative Event Diagram is a business process modelling technique that adopts a communicational perspective by focusing on communicative interactions when describing the organizational work practice, instead of focusing on physical activities1; at this abstraction level, we refer to business activities as communicative events. Message Structures is a technique based on structured text that allows specifying the messages associated to communicative events. Event Specification Templates are a means to organise the requirements concerning a communicative event. This report can be useful to analysts and business process modellers in general, since, according to our industrial experience, it is possible to apply many Communication Analysis concepts, guidelines and criteria to other business process modelling notations such as BPMN. Also, Message Structures can complement business process models created with other notations different than Communicative Event Diagram.


On the Complexity of Recognizing S-composite and S-prime Graphs

Abstract: S-prime graphs are graphs that cannot be represented as nontrivial subgraphs of nontrivial Cartesian products of graphs, i.e., whenever it is a subgraph of a nontrivial Cartesian product graph it is a subgraph of one the factors. A graph is S-composite if it is not S-prime. Although linear time recognition algorithms for determining whether a graph is prime or not with respect to the Cartesian product are known, it remained unknown if a similar result holds also for the recognition of S-prime and S-composite graphs. In this contribution the computational complexity of recognizing S-composite and S-prime graphs is considered. Klav{\v{z}}ar \emph{et al.} [\emph{Discr.\ Math.} \textbf{244}: 223-230 (2002)] proved that a graph is S-composite if and only if it admits a nontrivial path-$k$-coloring. The problem of determining whether there exists a path-$k$-coloring for a given graph is shown to be NP-complete even for $k=2$. This in turn is utilized to show that determining whether a graph is S-composite is NP-complete and thus, determining whether a graph is S-prime is CoNP-complete. Many other problems are shown to be NP-hard, using the latter results.


A Wronskian Approach to the real \tau-conjecture

Abstract: According to the real \tau-conjecture, the number of real roots of a sum of products of sparse polynomials should be polynomially bounded in the size of such an expression. It is known that this conjecture implies a superpolynomial lower bound on the arithmetic circuit complexity of the permanent. In this paper, we use the Wronksian determinant to give an upper bound on the number of real roots of sums of products of sparse polynomials. The proof technique is quite versatile; it can in particular be applied to some sparse geometric problems that do not originate from arithmetic circuit complexity. The paper should therefore be of interest to researchers from these two communities (complexity theory and sparse polynomial systems).


Reliable Generation of High-Performance Matrix Algebra

Abstract: Scientific programmers often turn to vendor-tuned Basic Linear Algebra Subprograms (BLAS) to obtain portable high performance. However, many numerical algorithms require several BLAS calls in sequence, and those successive calls result in suboptimal performance. The entire sequence needs to be optimized in concert. Instead of vendor-tuned BLAS, a programmer could start with source code in Fortran or C (e.g., based on the Netlib BLAS) and use a state-of-the-art optimizing compiler. However, our experiments show that optimizing compilers often attain only one-quarter the performance of hand-optimized code. In this paper we present a domain-specific compiler for matrix algebra, the Build to Order BLAS (BTO), that reliably achieves high performance using a scalable search algorithm for choosing the best combination of loop fusion, array contraction, and multithreading for data parallelism. The BTO compiler generates code that is between 16% slower and 39% faster than hand-optimized code.


Towards Ecology Inspired Software Engineering

Abstract: Ecosystems are complex and dynamic systems. Over billions of years, they have developed advanced capabilities to provide stable functions, despite changes in their environment. In this paper, we argue that the laws of organization and development of ecosystems provide a solid and rich source of inspiration to lay the foundations for novel software construction paradigms that provide stability as much as openness.


A Durable Flash Memory Search Tree

Abstract: We consider the task of optimizing the B-tree data structure, used extensively in operating systems and databases, for sustainable usage on multi-level flash memory. Empirical evidence shows that this new flash memory tree, or FM Tree, extends the operational lifespan of each block of flash memory by a factor of roughly 27 to 70 times, while still supporting logarithmic-time search tree operations.


An Overview on Clustering Methods

Abstract: Clustering is a common technique for statistical data analysis, which is used in many fields, including machine learning, data mining, pattern recognition, image analysis and bioinformatics. Clustering is the process of grouping similar objects into different groups, or more precisely, the partitioning of a data set into subsets, so that the data in each subset according to some defined distance measure. This paper covers about clustering algorithms, benefits and its applications. Paper concludes by discussing some limitations.


Application Of Data Mining In Bioinformatics

Abstract: This article highlights some of the basic concepts of bioinformatics and data mining. The major research areas of bioinformatics are highlighted. The application of data mining in the domain of bioinformatics is explained. It also highlights some of the current challenges and opportunities of data mining in bioinformatics.


A Comprehensive Study of CRM through Data Mining Techniques

Abstract: In today's competitive scenario in corporate world, "Customer Retention" strategy in Customer Relationship Management (CRM) is an increasingly pressed issue. Data mining techniques play a vital role in better CRM. This paper attempts to bring a new perspective by focusing the issue of data mining applications, opportunities and challenges in CRM. It covers the topic such as customer retention, customer services, risk assessment, fraud detection and some of the data mining tools which are widely used in CRM.


Interactive Learning through Hands-on Practice using Electronic Mini - Lab (EML): a Case Study

Abstract: -- In this paper, a new approach to impart practical skill based technical education is presented in comprehensive manner. An Electronic Mini-Lab (EML) is devised containing basic design and test instruments with electronic components, ICs, connecting wires and battery. Using the EML, students perform various formal and informal digital and analog circuit practicals as well as design prototype of projects. This gives them a hands-on experience, sense of belonging and sense of cooperation. The EML is useful for performing many practicals of various subjects. The EML also reduces the workload of college laboratories. Students have their own individual EML at their disposal anytime, which can be used to design hobby projects as a fun too. This will make them skilled engineers. This provides tremendous benefits in teaching learning process. It also boosted the interest, confidence of students and teachers. Incorporating active/ cooperative learning into traditional instruction can be a useful pedagogical tool to help students to perform practicals and project work any time anywhere. This concept is remarkably simple and cost effective but the dividends can be profound.


Recommendation on Academic Networks using Direction Aware Citation Analysis

Abstract: The literature search has always been an important part of an academic research. It greatly helps to improve the quality of the research process and output, and increase the efficiency of the researchers in terms of their novel contribution to science. As the number of published papers increases every year, a manual search becomes more exhaustive even with the help of today's search engines since they are not specialized for this task. In academics, two relevant papers do not always have to share keywords, cite one another, or even be in the same field. Although a well-known paper is usually an easy pray in such a hunt, relevant papers using a different terminology, especially recent ones, are not obvious to the eye. In this work, we propose paper recommendation algorithms by using the citation information among papers. The proposed algorithms are direction aware in the sense that they can be tuned to find either recent or traditional papers. The algorithms require a set of papers as input and recommend a set of related ones. If the user wants to give negative or positive feedback on the suggested paper set, the recommendation is refined. The search process can be easily guided in that sense by relevance feedback. We show that this slight guidance helps the user to reach a desired paper in a more efficient way. We adapt our models and algorithms also for the venue and reviewer recommendation tasks. Accuracy of the models and algorithms is thoroughly evaluated by comparison with multiple baselines and algorithms from the literature in terms of several objectives specific to citation, venue, and reviewer recommendation tasks. All of these algorithms are implemented within a publicly available web-service framework (http://theadvisor.osu.edu/) which currently uses the data from DBLP and CiteSeer to construct the proposed citation graph.


Divide-and-Conquer 3D Convex Hulls on the GPU

Abstract: We describe a pure divide-and-conquer parallel algorithm for computing 3D convex hulls. We implement that algorithm on GPU hardware, and find a significant speedup over comparable CPU implementations.


On the Complexity of Trial and Error

Abstract: Motivated by certain applications from physics, biochemistry, economics, and computer science, in which the objects under investigation are not accessible because of various limitations, we propose a trial-and-error model to examine algorithmic issues in such situations. Given a search problem with a hidden input, we are asked to find a valid solution, to find which we can propose candidate solutions (trials), and use observed violations (errors), to prepare future proposals. In accordance with our motivating applications, we consider the fairly broad class of constraint satisfaction problems, and assume that errors are signaled by a verification oracle in the format of the index of a violated constraint (with the content of the constraint still hidden). Our discoveries are summarized as follows. On one hand, despite the seemingly very little information provided by the verification oracle, efficient algorithms do exist for a number of important problems. For the Nash, Core, Stable Matching, and SAT problems, the unknown-input versions are as hard as the corresponding known-input versions, up to a factor of polynomial. We further give almost tight bounds on the latter two problems' trial complexities. On the other hand, there are problems whose complexities are substantially increased in the unknown-input model. In particular, no time-efficient algorithms exist (under standard hardness assumptions) for Graph Isomorphism and Group Isomorphism problems. The tools used to achieve these results include order theory, strong ellipsoid method, and some non-standard reductions. Our model investigates the value of information, and our results demonstrate that the lack of input information can introduce various levels of extra difficulty. The model exhibits intimate connections with (and we hope can also serve as a useful supplement to) certain existing learning and complexity theories.


An Approach For Robots To Deal With Objects

Abstract: Understanding object and its context are very important for robots when dealing with objects for completion of a mission. In this paper, an Affordance-based Ontology (ABO) is proposed for easy robot dealing with substantive and non-substantive objects. An ABO is a machine-understandable representation of objects and their relationships by what it's related to and how it's related. By using ABO, when dealing with a substantive object, robots can understand the representation of its object and its relation with other non-substantive objects. When the substantive object is not available, the robots have the understanding ability, in term of objects and their functions to select a non substantive object in order to complete the mission, such as giving raincoat or hat instead of getting stuck due to the unavailability of substantive object, e.g. umbrella. The experiment is done in the Ubiquitous Robotics Technology (u-RT) Space of National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan.


Sequential-Access FM-Indexes

Abstract: Previous authors have shown how to build FM-indexes efficiently in external memory, but querying them efficiently remains an open problem. Searching na\"{i}vely for a pattern $P$ requires (\Theta (|P|)) random access. In this paper we show how, by storing a few small auxiliary tables, we can access data only in the order in which they appear on disk, which should be faster.


Capacity Allocation and Pricing Strategies for Wireless Femtocell Services

Abstract: Indoor cell phone users often suffer from poor connectivity. One promising solution, femtocell technology, has been rapidly developed and deployed over the past few years. One of the biggest challenges for femtocell deployment is lack of a clear business model. This paper investigates the economic incentive for the cellular operator (also called macrocell operator) to enable femtocell service by leasing spectrum resource to an independent femtocell operator. On the one hand, femtocell services can increase communication service quality and thus increase the efficiency of the spectrum resource. On the other hand, femtocell services may introduce more competition to the market. We model the interactions between a macrocell operator, a femtocell operator, and users as a three-stage dynamic game, and derive the equilibrium pricing and capacity allocation decisions. We show that when spectrum resources are very limited, the macrocell operator has incentive to lease spectrum to femtocell operators, as femtocell service can provide access to more users and efficiently increase the coverage. However, when the total spectrum resource is large, femtocell service offers significant competition to macrocell service. Macrocell operator thus has less incentive to enable femtocell service. We also investigate the issue of additional operational cost and limited coverage of femtocell service on equilibrium decisions, consumer surplus and social welfare.


Hierarchical Range Sectoring and Bidirectional Link Quality Estimation for On-demand Collections in WSNs

Abstract: The paper presents two mechanisms for designing an on-demand, reliable and efficient collection protocol for Wireless Sensor Networks. The former is the Bidirectional Link Quality Estimation, which allows nodes to easily and quickly compute the quality of a link between a pair of nodes. The latter, Hierarchical Range Sectoring, organizes sensors in different sectors based on their location within the network. Based on this organization, nodes from each sector are coordinated to transmit in specific periods of time to reduce the hidden terminal problem. To evaluate these two mechanisms, a protocol called HBCP (Hierarchical-Based Collection Protocol), that implements both mechanisms, has been implemented in TinyOS 2.1, and evaluated in a testbed using TelosB motes. The results show that the HBCP protocol is able to achieve a very high reliability, especially in large networks and in scenarios with bottlenecks.


Volumetric Mapping of Genus Zero Objects via Mass Preservation

Abstract: In this work, we present a technique to map any genus zero solid object onto a hexahedral decomposition of a solid cube. This problem appears in many applications ranging from finite element methods to visual tracking. From this, one can then hopefully utilize the proposed technique for shape analysis, registration, as well as other related computer graphics tasks. More importantly, given that we seek to establish a one-to-one correspondence of an input volume to that of a solid cube, our algorithm can naturally generate a quality hexahedral mesh as an output. In addition, we constrain the mapping itself to be volume preserving allowing for the possibility of further mesh simplification. We demonstrate our method both qualitatively and quantitatively on various 3D solid models


Are e-readers suitable tools for scholarly work?

Abstract: This paper aims to offer insights into the usability, acceptance and limitations of e-readers with regard to the specific requirements of scholarly text work. To fit into the academic workflow non-linear reading, bookmarking, commenting, extracting text or the integration of non-textual elements must be supported. A group of social science students were questioned about their experiences with electronic publications for study purposes. This same group executed several text-related tasks with the digitized material presented to them in two different file formats on four different e-readers. Their performances were subsequently evaluated by means of frequency analyses in detail. Findings - e-Publications have made advances in the academic world; however e-readers do not yet fit seamlessly into the established chain of scholarly text-processing focusing on how readers use material during and after reading. Our tests revealed major deficiencies in these techniques. With a small number of participants (n=26) qualitative insights can be obtained, not representative results. Further testing with participants from various disciplines and of varying academic status is required to arrive at more broadly applicable results. Practical implications - Our test results help to optimize file conversion routines for scholarly texts. We evaluated our data on the basis of descriptive statistics and abstained from any statistical significance test. The usability test of e-readers in a scientific context aligns with both studies on the prevalence of e-books in the sciences and technical test reports of portable reading devices. Still, it takes a distinctive angle in focusing on the characteristics and procedures of textual work in the social sciences and measures the usability of e-readers and file-features against these standards.


Directed Subset Feedback Vertex Set is Fixed-Parameter Tractable

Abstract: Given a graph $G$ and an integer $k$, the Feedback Vertex Set (FVS) problem asks if there is a vertex set $T$ of size at most $k$ that hits all cycles in the graph. The fixed-parameter tractability status of FVS in directed graphs was a long-standing open problem until Chen et al. (STOC '08) showed that it is FPT by giving a $4^{k}k!n^{O(1)}$ time algorithm. In the subset versions of this problems, we are given an additional subset $S$ of vertices (resp., edges) and we want to hit all cycles passing through a vertex of $S$ (resp. an edge of $S$). Recently, the Subset Feedback Vertex Set in undirected graphs was shown to be FPT by Cygan et al. (ICALP '11) and independently by Kakimura et al. (SODA '12). We generalize the result of Chen et al. (STOC '08) by showing that Subset Feedback Vertex Set in directed graphs can be solved in time $2^{O(k^3)}n^{O(1)}$. By our result, we complete the picture for feedback vertex set problems and their subset versions in undirected and directed graphs. Besides proving the fixed-parameter tractability of Directed Subset Feedback Vertex Set, we reformulate the random sampling of important separators technique in an abstract way that can be used for a general family of transversal problems. Moreover, we modify the probability distribution used in the technique to achieve better running time; in particular, this gives an improvement from $2^{2^{O(k)}}$ to $2^{O(k^2)}$ in the parameter dependence of the Directed Multiway Cut algorithm of Chitnis et al. (SODA '12).


LP-rounding Algorithms for the Fault-Tolerant Facility Placement Problem

Abstract: The Fault-Tolerant Facility Placement problem (FTFP) is a generalization of the classic Uncapacitated Facility Location Problem (UFL). In FTFP we are given a set of facility sites and a set of clients. Opening a facility at site $i$ costs $f_i$ and connecting client $j$ to a facility at site $i$ costs $d_{ij}$. We assume that the connection costs (distances) $d_{ij}$ satisfy the triangle inequality. Multiple facilities can be opened at any site. Each client $j$ has a demand $r_j$, which means that it needs to be connected to $r_j$ different facilities (some of which could be located on the same site). The goal is to minimize the sum of facility opening cost and connection cost. The main result of this paper is a 1.575-approximation algorithm for FTFP, based on LP-rounding. The algorithm first reduces the demands to values polynomial in the number of sites. Then it uses a technique that we call adaptive partitioning, which partitions the instance by splitting clients into unit demands and creating a number of (not yet opened) facilities at each site. It also partitions the optimal fractional solution to produce a fractional solution for this new instance. The partitioned instance satisfies a number of properties that allow us to exploit existing LP-rounding methods for UFL to round our partitioned solution to an integral solution, preserving the approximation ratio. In particular, our 1.575-approximation algorithm is based on the ideas from the 1.575-approximation algorithm for UFL by Byrka et al., with changes necessary to satisfy the fault-tolerance requirement.


Converting online algorithms to local computation algorithms

Abstract: We propose a general method for converting online algorithms to local computation algorithms by selecting a random permutation of the input, and simulating running the online algorithm. We bound the number of steps of the algorithm using a query tree, which models the dependencies between queries. We improve previous analyses of query trees on graphs of bounded degree, and extend the analysis to the cases where the degrees are distributed binomially, and to a special case of bipartite graphs. Using this method, we give a local computation algorithm for maximal matching in graphs of bounded degree, which runs in time and space O(log^3 n). We also show how to convert a large family of load balancing algorithms (related to balls and bins problems) to local computation algorithms. This gives several local load balancing algorithms which achieve the same approximation ratios as the online algorithms, but run in O(log n) time and space. Finally, we modify existing local computation algorithms for hypergraph 2-coloring and k-CNF and use our improved analysis to obtain better time and space bounds, of O(log^4 n), removing the dependency on the maximal degree of the graph from the exponent.


Approximation Algorithms for Wireless Link Scheduling with Flexible Data Rates

Abstract: We consider scheduling problems in wireless networks with respect to flexible data rates. That is, more or less data can be transmitted per time depending on the signal quality, which is determined by the signal-to-interference-plus-noise ratio (SINR). Each wireless link has a utility function mapping SINR values to the respective data rates. We have to decide which transmissions are performed simultaneously and (depending on the problem variant) also which transmission powers are used. In the capacity-maximization problem, one strives to maximize the overall network throughput, i.e., the summed utility of all links. For arbitrary utility functions (not necessarily continuous ones), we present an O(log n)-approximation when having n communication requests. This algorithm is built on a constant-factor approximation for the special case of the respective problem where utility functions only consist of a single step. In other words, each link has an individual threshold and we aim at maximizing the number of links whose threshold is satisfied. On the way, this improves the result in [Kesselheim, SODA 2011] by not only extending it to individual thresholds but also showing a constant approximation factor independent of assumptions on the underlying metric space or the network parameters. In addition, we consider the latency-minimization problem. Here, each link has a demand, e.g., representing an amount of data. We have to compute a schedule of shortest possible length such that for each link the demand is fulfilled, that is the overall summed utility (or data transferred) is at least as large as its demand. Based on the capacity-maximization algorithm, we show an O(log^2 n)-approximation for this problem.


Detecting Spammers via Aggregated Historical Data Set

Abstract: The battle between email service providers and senders of mass unsolicited emails (Spam) continues to gain traction. Vast numbers of Spam emails are sent mainly from automatic botnets distributed over the world. One method for mitigating Spam in a computationally efficient manner is fast and accurate blacklisting of the senders. In this work we propose a new sender reputation mechanism that is based on an aggregated historical data-set which encodes the behavior of mail transfer agents over time. A historical data-set is created from labeled logs of received emails. We use machine learning algorithms to build a model that predicts the \emph{spammingness} of mail transfer agents in the near future. The proposed mechanism is targeted mainly at large enterprises and email service providers and can be used for updating both the black and the white lists. We evaluate the proposed mechanism using 9.5M anonymized log entries obtained from the biggest Internet service provider in Europe. Experiments show that proposed method detects more than 94% of the Spam emails that escaped the blacklist (i.e., TPR), while having less than 0.5% false-alarms. Therefore, the effectiveness of the proposed method is much higher than of previously reported reputation mechanisms, which rely on emails logs. In addition, the proposed method, when used for updating both the black and white lists, eliminated the need in automatic content inspection of 4 out of 5 incoming emails, which resulted in dramatic reduction in the filtering computational load.


Image Enhancement with Statistical Estimation

Abstract: Contrast enhancement is an important area of research for the image analysis. Over the decade, the researcher worked on this domain to develop an efficient and adequate algorithm. The proposed method will enhance the contrast of image using Binarization method with the help of Maximum Likelihood Estimation (MLE). The paper aims to enhance the image contrast of bimodal and multi-modal images. The proposed methodology use to collect mathematical information retrieves from the image. In this paper, we are using binarization method that generates the desired histogram by separating image nodes. It generates the enhanced image using histogram specification with binarization method. The proposed method has showed an improvement in the image contrast enhancement compare with the other image.


Quasi-Polynomial Local Search for Restricted Max-Min Fair Allocation

Abstract: The restricted max-min fair allocation problem (also known as the restricted Santa Claus problem) is one of few problems that enjoys the intriguing status of having a better estimation algorithm than approximation algorithm. Indeed, Asadpour et al. proved that a certain configuration LP can be used to estimate the optimal value within a factor ${1}/{(4+\epsilon)}$, for any $\epsilon>0$, but at the same time it is not known how to efficiently find a solution with a comparable performance guarantee. A natural question that arises from their work is if the difference between these guarantees is inherent or because of a lack of suitable techniques. We address this problem by giving a quasi-polynomial approximation algorithm with the mentioned performance guarantee. More specifically, we modify the local search of Asadpour et al. and provide a novel analysis that lets us significantly improve the bound on its running time: from $2^{O(n)}$ to $n^{O(\log n)}$. Our techniques also have the interesting property that although we use the rather complex configuration LP in the analysis, we never actually solve it and therefore the resulting algorithm is purely combinatorial.


An Integrated Impact Indicator (I3): A New Definition of "Impact" with Policy Relevance

Abstract: Allocation of research funding, as well as promotion and tenure decisions, are increasingly made using indicators and impact factors drawn from citations to published work. A debate among scientometricians about proper normalization of citation counts has resolved with the creation of an Integrated Impact Indicator (I3) that solves a number of problems found among previously used indicators. The I3 applies non-parametric statistics using percentiles, allowing highly-cited papers to be weighted more than less-cited ones. It further allows unbundling of venues (i.e., journals or databases) at the article level. Measures at the article level can be re-aggregated in terms of units of evaluation. At the venue level, the I3 creates a properly weighted alternative to the journal impact factor. I3 has the added advantage of enabling and quantifying classifications such as the six percentile rank classes used by the National Science Board's Science & Engineering Indicators.


Efficient and reliable network tomography in heterogeneous networks using BitTorrent broadcasts and clustering algorithms

Abstract: In the area of network performance and discovery, network tomography focuses on reconstructing network properties using only end-to-end measurements at the application layer. One challenging problem in network tomography is reconstructing available bandwidth along all links during multiple source/multiple destination transmissions. The traditional measurement procedures used for bandwidth tomography are extremely time consuming. We propose a novel solution to this problem. Our method counts the fragments exchanged during a BitTorrent broadcast. While this measurement has a high level of randomness, it can be obtained very efficiently, and aggregated into a reliable metric. This data is then analyzed with state-of-the-art algorithms, which reliably reconstruct logical clusters of nodes inter-connected by high bandwidth, as well as bottlenecks between these logical clusters. Our experiments demonstrate that the proposed two-phase approach efficiently solves the presented problem for a number of settings on a complex grid infrastructure.


A Group Key Management Protocol Based on Weight-Balanced 2-3 Tree for Wireless Sensor Networks

Abstract: Multicast in Wireless Sensor Networks (WSNs) is an attractive mechanism for delivering data to multiple receivers as it saves bandwidth. To guarantee the security of multicast, the group key is used to encrypt and decrypt the packages. However, providing key management services in WSNs is complicated because sensor nodes possess limited resources of computing, storage and communication. To address the balance between security and limited resources, a multicast group key management protocol based on the weight-balanced 2-3 tree is proposed to generate, distribute, and update the group key securely and efficiently. The decentralized group key management method is employed. A weight-balanced 2-3 key tree is formed in every subgroup. Instead of using the conventional symmetric and non-symmetric encryption algorithms, the Maximum Distance Separable (MDS) code technique is used to distribute the multicast key dynamically. During the key updating, a series of adjustment rules are summarized to keep the tree weight-balanced, where pseudo-nodes as leaves are added to reduce the computation and communication complexity. Compared with some other group key management protocols, our scheme shows higher superiority on security and performance.


Minimizing Expected Termination Time in One-Counter Markov Decision Processes

Abstract: We consider the problem of computing the value and an optimal strategy for minimizing the expected termination time in one-counter Markov decision processes. Since the value may be irrational and an optimal strategy may be rather complicated, we concentrate on the problems of approximating the value up to a given error epsilon > 0 and computing a finite representation of an epsilon-optimal strategy. We show that these problems are solvable in exponential time for a given configuration, and we also show that they are computationally hard in the sense that a polynomial-time approximation algorithm cannot exist unless P=NP.


Approximation Algorithms for Online Weighted Rank Function Maximization under Matroid Constraints

Abstract: Consider the following online version of the submodular maximization problem under a matroid constraint: We are given a set of elements over which a matroid is defined. The goal is to incrementally choose a subset that remains independent in the matroid over time. At each time, a new weighted rank function of a different matroid (one per time) over the same elements is presented; the algorithm can add a few elements to the incrementally constructed set, and reaps a reward equal to the value of the new weighted rank function on the current set. The goal of the algorithm as it builds this independent set online is to maximize the sum of these (weighted rank) rewards. As in regular online analysis, we compare the rewards of our online algorithm to that of an offline optimum, namely a single independent set of the matroid that maximizes the sum of the weighted rank rewards that arrive over time. This problem is a natural extension of two well-studied streams of earlier work: the first is on online set cover algorithms (in particular for the max coverage version) while the second is on approximately maximizing submodular functions under a matroid constraint. In this paper, we present the first randomized online algorithms for this problem with poly-logarithmic competitive ratio. To do this, we employ the LP formulation of a scaled reward version of the problem. Then we extend a weighted-majority type update rule along with uncrossing properties of tight sets in the matroid polytope to find an approximately optimal fractional LP solution. We use the fractional solution values as probabilities for a online randomized rounding algorithm. To show that our rounding produces a sufficiently large reward independent set, we prove and use new covering properties for randomly rounded fractional solutions in the matroid polytope that may be of independent interest.


Approximating Majority Depth

Abstract: We consider the problem of approximating the majority depth (Liu and Singh, 1993) of a point q with respect to an n-point set, S, by random sampling. At the heart of this problem is a data structures question: How can we preprocess a set of n lines so that we can quickly test whether a randomly selected vertex in the arrangement of these lines is above or below the median level. We describe a Monte-Carlo data structure for this problem that can be constructed in O(nlog n) time, can answer queries O((log n)^{4/3}) expected time, and answers correctly with high probability.


Optimal Algorithms for Near-Hitless Network Restoration via Diversity Coding

Abstract: Diversity coding is a network restoration technique which offers near-hitless restoration, while other state-of-the art techniques are significantly slower. Furthermore, the extra spare capacity requirement of diversity coding is competitive with the others. Previously, we developed heuristic algorithms to employ diversity coding structures in networks with arbitrary topology. This paper presents two algorithms to solve the network design problems using diversity coding in an optimal manner. The first technique pre-provisions static traffic whereas the second technique carries out the dynamic provisioning of the traffic on-demand. In both cases, diversity coding results in smaller restoration time, simpler synchronization, and much reduced signaling complexity than the existing techniques in the literature. A Mixed Integer Programming (MIP) formulation and an algorithm based on Integer Linear Programming (ILP) are developed for pre-provisioning and dynamic provisioning, respectively. Simulation results indicate that diversity coding has significantly higher restoration speed than Shared Path Protection (SPP) and p-cycle techniques. It requires more extra capacity than the p-cycle technique and SPP. However, the increase in the total capacity is negligible compared to the increase in the restoration speed.


Locating a single facility and a high-speed line

Abstract: In this paper we study a facility location problem in the plane in which a single point (facility) and a rapid transit line (highway) are simultaneously located in order to minimize the total travel time from the clients to the facility, using the $L_1$ or Manhattan metric. The rapid transit line is given by a segment with any length and orientation, and is an alternative transportation line that can be used by the clients to reduce their travel time to the facility. We study the variant of the problem in which clients can enter and exit the highway at any point. We provide an $O(n^3)$-time algorithm that solves this variant, where $n$ is the number of clients. We also present a detailed characterization of the solutions, which depends on the speed given in the highway.


Anonymous Card Shuffling and its Applications to Parallel Mixnets

Abstract: We study the question of how to shuffle $n$ cards when faced with an opponent who knows the initial position of all the cards {\em and} can track every card when permuted, {\em except} when one takes $K< n$ cards at a time and shuffles them in a private buffer "behind your back," which we call {\em buffer shuffling}. The problem arises naturally in the context of parallel mixnet servers as well as other security applications. Our analysis is based on related analyses of load-balancing processes. We include extensions to variations that involve corrupted servers and adversarially injected messages, which correspond to an opponent who can peek at some shuffles in the buffer and who can mark some number of the cards. In addition, our analysis makes novel use of a sum-of-squares metric for anonymity, which leads to improved performance bounds for parallel mixnets and can also be used to bound well-known existing anonymity measures.


Testing Coverage Functions

Abstract: A coverage function f over a ground set [m] is associated with a universe U of weighted elements and m subsets A_1,..., A_m of U, and for any subset T of [m], f(T) is defined as the total weight of the elements in the union $\cup_{j\in T} A_j$. Coverage functions are an important special case of submodular functions, and arise in many applications, for instance as a class of utility functions of agents in combinatorial auctions. Set functions such as coverage functions often lack succinct representations, and in algorithmic applications, an access to a value oracle is assumed. In this paper, we ask whether one can test if a given oracle is that of a coverage function or not. We demonstrate an algorithm which makes O(m|U|) queries to an oracle of a coverage function and completely reconstructs it. This gives a polytime tester for succinct coverage functions for which |U$ is polynomially bounded in m. In contrast, we demonstrate a set function which is "far" from coverage, but requires 2^{\tilde{\Theta}(m)} queries to distinguish it from the class of coverage functions.


Smart handover based on fuzzy logic trend in IEEE802.11 mobile IPv6 networks

Abstract: A properly designed handoff algorithm is essential in reducing the connection quality deterioration when a mobile node moves across the cell boundaries. Therefore, to improve communication quality, we identified three goals in our paper. The first goal is to minimize unnecessary handovers and increase communication quality by reducing misrepresentations of RSSI readings due to multipath and shadow effect with the use of additional parameters. The second goal is to control the handover decisions depending on the users' mobility by utilizing location factors as one of the input parameters in a fuzzy logic handover algorithm. The third goal is to minimize false handover alarms caused by sudden fluctuations of parameters by monitoring the trend of fuzzy logic outputs for a period of time before making handover decision. In this paper, we use RSSI, speed and distance as the input decision criteria of a handover trigger algorithm by means of fuzzy logic. The fuzzy logic output trend is monitored for a period of time before handover is triggered. Finally, through simulations, we show the effectiveness of the proposed handover algorithm in achieving better communication quality.


Indexing of Arabic documents automatically based on lexical analysis

Abstract: The continuous information explosion through the Internet and all information sources makes it necessary to perform all information processing activities automatically in quick and reliable manners. In this paper, we proposed and implemented a method to automatically create and Index for books written in Arabic language. The process depends largely on text summarization and abstraction processes to collect main topics and statements in the book. The process is developed in terms of accuracy and performance and results showed that this process can effectively replace the effort of manually indexing books and document, a process that can be very useful in all information processing and retrieval applications.


Parsing of Myanmar sentences with function tagging

Abstract: This paper describes the use of Naive Bayes to address the task of assigning function tags and context free grammar (CFG) to parse Myanmar sentences. Part of the challenge of statistical function tagging for Myanmar sentences comes from the fact that Myanmar has free-phrase-order and a complex morphological system. Function tagging is a pre-processing step for parsing. In the task of function tagging, we use the functional annotated corpus and tag Myanmar sentences with correct segmentation, POS (part-of-speech) tagging and chunking information. We propose Myanmar grammar rules and apply context free grammar (CFG) to find out the parse tree of function tagged Myanmar sentences. Experiments show that our analysis achieves a good result with parsing of simple sentences and three types of complex sentences.


ACO based routing for MANETs

Abstract: Mobile ad hoc network (MANET) is a collection of wireless mobile nodes. It dynamically forms a temporary network without using any pre existing network infrastructure or centralized administration i.e. with minimal prior planning. All nodes have routing capabilities and forward data packets to other nodes in multi-hop fashion. As the network is dynamic, the network topology continuously experiences alterations during deployment. The biggest challenge in MANETs is to find a path between communicating nodes. The considerations of the MANET environment and the nature of the mobile nodes create further complications which results in the need to develop special routing algorithms to meet these challenges. Swarm intelligence, a bio-inspired technique, which has proven to be very adaptable in other problem domains, has been applied to the MANET routing problem as it forms a good fit to the problem. In ant societies the activities of the individuals are not regulated by any explicit form of centralized control but are the result of self-organizing dynamics driven by local interactions and communications among a number of relatively simple individuals. This unique characteristic has made ant societies an attractive and inspiring model for building new algorithms and new multi-agent systems. In this paper, we have studied and reviewed Ant Colony based routing algorithms and its variants. Finally, a performance evaluation of the original ARA and the EARA is carried out with respect to each other.


CSHURI - Modified HURI algorithm for Customer Segmentation and Transaction Profitability

Abstract: Association rule mining (ARM) is the process of generating rules based on the correlation between the set of items that the customers purchase.Of late, data mining researchers have improved upon the quality of association rule mining for business development by incorporating factors like value (utility), quantity of items sold (weight) and profit. The rules mined without considering utility values (profit margin) will lead to a probable loss of profitable rules. The advantage of wealth of the customers' needs information and rules aids the retailer in designing his store layout[9]. An algorithm CSHURI, Customer Segmentation using HURI, is proposed, a modified version of HURI [6], finds customers who purchase high profitable rare items and accordingly classify the customers based on some criteria; for example, a retail business may need to identify valuable customers who are major contributors to a company's overall profit. For a potential customer arriving in the store, which customer group one should belong to according to customer needs, what are the preferred functional features or products that the customer focuses on and what kind of offers will satisfy the customer, etc., finds the key in targeting customers to improve sales [9], which forms the base for customer utility mining.


A Novel Window Function Yielding Suppressed Mainlobe Width and Minimum Sidelobe Peak

Abstract: In many applications like FIR filters, FFT, signal processing and measurements, we are required (~45 dB) or less side lobes amplitudes. However, the problem is usual window based FIR filter design lies in its side lobes amplitudes that are higher than the requirement of application. We propose a window function, which has better performance like narrower main lobe width, minimum side lobe peak compared to the several commonly used windows. The proposed window has slightly larger main lobe width of the commonly used Hamming window, while featuring 6.2\ sim 22.62 dB smaller side lobe peak. The proposed window maintains its maximum side lobe peak about -58.4 \sim -52.6 dB compared to -35.8 \sim -38.8 dB of Hamming window for M=10~14, while offering roughly equal main lobe width. Our simulated results also show significant performance upgrading of the proposed window compared to the Kaiser, Gaussian, and Lanczos windows. The proposed window also shows better performance than Dolph-Chebyshev window. Finally, the example of designed low pass FIR filter confirms the efficiency of the proposed window.


An optimal consensus tracking control algorithm for autonomous underwater vehicles with disturbances

Abstract: The optimal disturbance rejection control problem is considered for consensus tracking systems affected by external persistent disturbances and noise. Optimal estimated values of system states are obtained by recursive filtering for the multiple autonomous underwater vehicles modeled to multi-agent systems with Kalman filter. Then the feedforward-feedback optimal control law is deduced by solving the Riccati equations and matrix equations. The existence and uniqueness condition of feedforward-feedback optimal control law is proposed and the optimal control law algorithm is carried out. Lastly, simulations show the result is effectiveness with respect to external persistent disturbances and noise.


Performance Measurement of Cloud Computing Services

Abstract: Cloud computing today has now been growing as new technologies and new business models. In distributed technology perspective, cloud computing most like client-server services like web-based or web-service but it used virtual resources to execute. Currently, cloud computing relies on the use of an elastic virtual machine and the use of network for data exchange. We conduct an experimental setup to measure the quality of service received by cloud computing customers. Experimental setup done by creating a HTTP service that runs in the cloud computing infrastructure. We interest to know about the impact of increasing the number of users on the average quality received by users. The qualities received by user measured within two parameters consist of average response times and the number of requests time out. Experimental results of this study show that increasing the number of users has increased the average response time. Similarly, the number of request time out increasing with increasing number of users. It means that the qualities of service received by user are decreasing also. We found that the impact of the number of users on the quality of service is no longer in linear trend. The results of this study can be used as a reference model for the network operator in performing services in which a certain number of users in order to obtain optimal quality services.


Visitor schedule management system- an intelligent decision support system

Abstract: Travelling salesman problem is a problem which is of high interest for researchers, industry professionals, and academicians. Visitor or salesman used to face lot of problems with respect to scheduling based on meeting top ranked clients. Even excel sheet made the work tedious. So these flaws propelled us to design an intelligent decision support system. This paper reports the problem definition we tried to address and possible solution to this problem. We even explained the project design and implementation of our visitor schedule management system.. Our system made a major contribution in terms of valuable resources such as time and satisfying high ranked clients efficiently. We used optimization via mathematical programming to solve these issues.


Precise positioning systems for Vehicular Ad-Hoc Networks

Abstract: Vehicular Ad Hoc Networks (VANET) is a very promising research venue that can offers many useful and critical applications including the safety applications. Most of these applications require that each vehicle knows precisely its current position in real time. GPS is the most common positioning technique for VANET. However, it is not accurate. Moreover, the GPS signals cannot be received in the tunnels, undergrounds, or near tall buildings. Thus, no positioning service can be obtained in these locations. Even if the Deferential GPS (DGPS) can provide high accuracy, but still no GPS converge in these locations. In this paper, we provide positioning techniques for VANET that can provide accurate positioning service in the areas where GPS signals are hindered by the obstacles. Experimental results show significant improvement in the accuracy. This allows when combined with DGPS the continuity of a precise positioning service that can be used by most of the VANET applications.


Document summarization using positive pointwise mutual information

Abstract: The degree of success in document summarization processes depends on the performance of the method used in identifying significant sentences in the documents. The collection of unique words characterizes the major signature of the document, and forms the basis for Term-Sentence-Matrix (TSM). The Positive Pointwise Mutual Information, which works well for measuring semantic similarity in the Term-Sentence-Matrix, is used in our method to assign weights for each entry in the Term-Sentence-Matrix. The Sentence-Rank-Matrix generated from this weighted TSM, is then used to extract a summary from the document. Our experiments show that such a method would outperform most of the existing methods in producing summaries from large documents.


Spectral Analysis of Projection Histogram for Enhancing Close matching character Recognition in Malayalam

Abstract: The success rates of Optical Character Recognition (OCR) systems for printed Malayalam documents is quite impressive with the state of the art accuracy levels in the range of 85-95% for various. However for real applications, further enhancement of this accuracy levels are required. One of the bottle necks in further enhancement of the accuracy is identified as close-matching characters. In this paper, we delineate the close matching characters in Malayalam and report the development of a specialised classifier for these close-matching characters. The output of a state of the art of OCR is taken and characters falling into the close-matching character set is further fed into this specialised classifier for enhancing the accuracy. The classifier is based on support vector machine algorithm and uses feature vectors derived out of spectral coefficients of projection histogram signals of close-matching characters.


Content based video retrieval systems

Abstract: With the development of multimedia data types and available bandwidth there is huge demand of video retrieval systems, as users shift from text based retrieval systems to content based retrieval systems. Selection of extracted features play an important role in content based video retrieval regardless of video attributes being under consideration. These features are intended for selecting, indexing and ranking according to their potential interest to the user. Good features selection also allows the time and space costs of the retrieval process to be reduced. This survey reviews the interesting features that can be extracted from video data for indexing and retrieval along with similarity measurement methods. We also identify present research issues in area of content based video retrieval systems.


Traductor Writing System Web

Abstract: A compilator is a program which is development in a programming language that read a file known as source. After this file have to translate and have to convert in other program known as object or to generate a exit. The best way for to know any programming language is analizing a compilation process which is same in all programming paradigm existents. To like to generate a tool that permit a learning in university course. This course could explain in any plataform such as Linux o Windows. This goal is posible through development a Web aplication which is unite with a compilator, it is Traductor Writing System (Sistema de Escritura de Traductores). This system is complete and permit extend and modify the compilator. The system is a module in Moodle which is a Course Management System (CMS) that help teachers for to create comunities of learning in line. This software is in free software license (GPL).


The necessities for building a model to evaluate Business Intelligence projects- Literature Review

Abstract: In recent years Business Intelligence (BI) systems have consistently been rated as one of the highest priorities of Information Systems (IS) and business leaders. BI allows firms to apply information for supporting their processes and decisions by combining its capabilities in both of organizational and technical issues. Many of companies are being spent a significant portion of its IT budgets on business intelligence and related technology. Evaluation of BI readiness is vital because it serves two important goals. First, it shows gaps areas where company is not ready to proceed with its BI efforts. By identifying BI readiness gaps, we can avoid wasting time and resources. Second, the evaluation guides us what we need to close the gaps and implement BI with a high probability of success. This paper proposes to present an overview of BI and necessities for evaluation of readiness. Key words: Business intelligence, Evaluation, Success, Readiness


DBC based Face Recognition using DWT

Abstract: The applications using face biometric has proved its reliability in last decade. In this paper, we propose DBC based Face Recognition using DWT (DBC- FR) model. The Poly-U Near Infra Red (NIR) database images are scanned and cropped to get only the face part in pre-processing. The face part is resized to 100*100 and DWT is applied to derive LL, LH, HL and HH subbands. The LL subband of size 50*50 is converted into 100 cells with 5*5 dimention of each cell. The Directional Binary Code (DBC) is applied on each 5*5 cell to derive 100 features. The Euclidian distance measure is used to compare the features of test image and database images. The proposed algorithm render better percentage recognition rate compared to the existing algorithm.


Publishing and linking transport data on the Web

Abstract: Without Linked Data, transport data is limited to applications exclusively around transport. In this paper, we present a workflow for publishing and linking transport data on the Web. So we will be able to develop transport applications and to add other features which will be created from other datasets. This will be possible because transport data will be linked to these datasets. We apply this workflow to two datasets: NEPTUNE, a French standard describing a transport line, and Passim, a directory containing relevant information on transport services, in every French city.


The impact of pharmacybernetic in reducing medication error

Abstract: Doctors and Pharmacists play a foremost role in safe, effective use of medication in health care. Still, there is no database available through which Doctor can communicate with all field of pharmacy such as hospital Pharmacy, Clinical Pharmacy, Community Pharmacy, Nutrition Pharmacy and Drug research center so that they would like to cooperate with pharmacists in Medication error prevention, Drug-Disease management, Nutrition management, and pharmacotherapy. The authors examined the comprehensive project of implementing Electronic Drug Information Record (EDIR), introduce the new term Pharmacybernetic and how to reduce the medication error by integrated management system (IMS). This paper presented EDIR conceptual model and the flow sheet of the Pharmacybernetic system, which describes the integration of different Pharmaceutical related aspect in the field of Cybernetic.


Power control in reactive routing protocol for Mobile Ad Hoc Network

Abstract: The aim of this work is to change the routing strategy of AODV protocol (Ad hoc On Demand Vector) in order to improve the energy consumption in mobile ad hoc networks (MANET). The purpose is to minimize the regular period of HELLO messages generated by the AODV protocol used for the research, development and maintenance of routes. This information is useful to have an idea about battery power levels of different network hosts. After storing this information, the node elect the shortest path following the classical model used this information to elect safest path (make a compromise) in terms of energy. Transmitter node does not select another node as its battery will be exhausted soon. Any node of the network can have the same information's about the neighborhoods as well as other information about the energy level of the different terminal to avoid routing using a link that will be lost due to an exhausted battery of a node in this link. Analytical study and simulations by Jist/SWANS have been conducted to note that no divergence relatively to the classical AODV, a node can have this type of information that improves the energy efficiency in ad hoc networks.


Improved Fair-Zone technique using Mobility Prediction in WSN

Abstract: The self-organizational ability of ad-hoc Wireless Sensor Networks (WSNs) has led them to be the most popular choice in ubiquitous computing. Clustering sensor nodes organizing them hierarchically have proven to be an effective method to provide better data aggregation and scalability for the sensor network while conserving limited energy. It has some limitation in energy and mobility of nodes. In this paper we propose a mobility prediction technique which tries overcoming above mentioned problems and improves the life time of the network. The technique used here is Exponential Moving Average for online updates of nodal contact probability in cluster based network.


A Network-Coded Diversity Protocol for Collision Recovery in Slotted ALOHA Networks

Abstract: We propose a collision recovery scheme for symbol-synchronous slotted ALOHA (SA) based on physical layer network coding over extended Galois Fields. Information is extracted from colliding bursts allowing to achieve higher maximum throughput with respect to previously proposed collision recovery schemes. An energy analysis is also performed, and it is shown that, by adjusting the transmission probability, high energy efficiency can be achieved. The paper also addresses several practical aspects, namely frequency, phase, and amplitude estimation, as well as partial symbol asynchronism. A performance evaluation is carried out using the proposed algorithms, revealing remarkable performance in terms of normalized throughput.


A comparative study of clusterhead selection algorithms in wireless sensor networks

Abstract: In Wireless Sensor Network, sensor nodes life time is the most critical parameter. Many researches on these lifetime extension are motivated by LEACH scheme, which by allowing rotation of cluster head role among the sensor nodes tries to distribute the energy consumption over all nodes in the network. Selection of clusterhead for such rotation greatly affects the energy efficiency of the network. Different communication protocols and algorithms are investigated to find ways to reduce power consumption. In this paper brief survey is taken from many proposals, which suggests different clusterhead selection strategies and a global view is presented. Comparison of their costs of clusterhead selection in different rounds, transmission method and other effects like cluster formation, distribution of clusterheads and creation of clusters shows a need of a combined strategy for better results.


Age Based User Interface in Mobile Operating System

Abstract: This paper proposes the creation of different interfaces in the mobile operating system for different age groups. The different age groups identified are kids, elderly people and all others. The motive behind creating different interfaces is to make the smartphones of today's world usable to all age groups.


Comparison of CSMA based MAC protocols of wireless sensor networks

Abstract: Energy conservation has been an important area of interest in Wireless Sensor networks (WSNs). Medium Access Control (MAC) protocols play an important role in energy conservation. In this paper, we describe CSMA based MAC protocols for WSN and analyze the simulation results of these protocols. We implemented S-MAC, T-MAC, B-MAC, B-MAC+, X-MAC, DMAC and Wise-MAC in TOSSIM, a simulator which unlike other simulators simulates the same code running on real hardware. Previous surveys mainly focused on the classification of MAC protocols according to the techniques being used or problem dealt with and presented a theoretical evaluation of protocols. This paper presents the comparative study of CSMA based protocols for WSNs, showing which MAC protocol is suitable in a particular environment and supports the arguments with the simulation results. The comparative study can be used to find the best suited MAC protocol for wireless sensor networks in different environments.


Matching with Commitments

Abstract: We consider the following stochastic optimization problem first introduced by Chen et al. in \cite{chen}. We are given a vertex set of a random graph where each possible edge is present with probability p_e. We do not know which edges are actually present unless we scan/probe an edge. However whenever we probe an edge and find it to be present, we are constrained to picking the edge and both its end points are deleted from the graph. We wish to find the maximum matching in this model. We compare our results against the optimal omniscient algorithm that knows the edges of the graph and present a 0.573 factor algorithm using a novel sampling technique. We also prove that no algorithm can attain a factor better than 0.898 in this model.


A simple 1-byte 1-clock RC4 design and its efficient implementation in FPGA coprocessor for secured ethernet communication

Abstract: In the field of cryptography till date the 1-byte in 1-clock is the best known RC4 hardware design [1], while the 1-byte in 3clocks is the best known implementation [2,3]. The design algorithm in [1] considers two consecutive bytes together and processes them in 2 clocks. The design of 1-byte in 3-clocks is too much modular and clock hungry. In this paper considering the RC4 algorithm, as it is, a simpler RC4 hardware design providing higher throughput is proposed in which 1-byte is processed in 1-clock. In the design two sequential tasks are executed as two independent events during rising and falling edges of the same clock and the swapping is directly executed using a MUX-DEMUX combination. The power consumed in behavioral and structural designs of RC4 are estimated and a power optimization technique is proposed. The NIST statistical test suite is run on RC4 key streams in order to know its randomness property. The encryption and decryption designs are respectively embedded on two FPGA boards with RC4 in a custom coprocessor followed by Ethernet communication.


Reconfigurable Controller Design For Actuator Faults In A Four-Tank System Benchmark

Abstract: The purpose of this work is to design a state feedback controller using Parametric Eigenstructure Assignment (PAE) technique that has the capacity to be reconfigured in the case that partial actuator faults occur. The proposed controller is capable of compensating the gain losses in actuators and maintaining the control performance in faulty situations. Simulations show the performance enhancement in comparison to the non-reconfigurable controller through Integral Absolute Error (IAE) index for different fault scenarios.


Faster Algorithms for Privately Releasing Marginals

Abstract: We study the problem of releasing $k$-way marginals of a database $D \in (\{0,1\}^d)^n$, while preserving differential privacy. The answer to a $k$-way marginal query is the fraction of $D$'s records $x \in \{0,1\}^d$ with a given value in each of a given set of up to $k$ columns. Marginal queries enable a rich class of statistical analyses of a dataset, and designing efficient algorithms for privately releasing marginal queries has been identified as an important open problem in private data analysis (cf. Barak et. al., PODS '07). We give an algorithm that runs in time $d^{O(\sqrt{k})}$ and releases a private summary capable of answering any $k$-way marginal query with at most $\pm .01$ error on every query as long as $n \geq d^{O(\sqrt{k})}$. To our knowledge, ours is the first algorithm capable of privately releasing marginal queries with non-trivial worst-case accuracy guarantees in time substantially smaller than the number of $k$-way marginal queries, which is $d^{\Theta(k)}$ (for $k \ll d$).


Chaotic multi-objective optimization based design of fractional order PI{\lambda}D{\mu} controller in AVR system

Abstract: In this paper, a fractional order (FO) PI{\lambda}D\mu controller is designed to take care of various contradictory objective functions for an Automatic Voltage Regulator (AVR) system. An improved evolutionary Non-dominated Sorting Genetic Algorithm II (NSGA II), which is augmented with a chaotic map for greater effectiveness, is used for the multi-objective optimization problem. The Pareto fronts showing the trade-off between different design criteria are obtained for the PI{\lambda}D\mu and PID controller. A comparative analysis is done with respect to the standard PID controller to demonstrate the merits and demerits of the fractional order PI{\lambda}D\mu controller.


A Common Evaluation Setting for Just.Ask, Open Ephyra and Aranea QA systems

Abstract: Question Answering (QA) is not a new research field in Natural Language Processing (NLP). However in recent years, QA has been a subject of growing study. Nowadays, most of the QA systems have a similar pipelined architecture and each system use a set of unique techniques to accomplish its state of the art results. However, many things are not clear in the QA processing. It is not clear the extend of the impact of tasks performed in earlier stages in following stages of the pipelining process. It is not clear, if techniques used in a QA system can be used in another QA system to improve its results. And finally, it is not clear in what setting should be these systems tested in order to properly analyze their results.


Tight Lower Bounds on Envy-Free Makespan Approximation

Abstract: In this work we give a tight lower bound on makespan approximations for envy-free allocation mechanism dedicated to scheduling tasks on unrelated machines. Specifically, we show that no mechanism exists that can guarantee an envy-free allocation of jobs to $m$ machines with a makespan of less than a factor of $O(\log m)$ of the minimal makespan. Combined with previous results, this paper definitively proves that the optimal algorithm for obtaining a minimal makespan for any envy-free division can at best approximate the makespan to a factor of $O(\log m)$.


A Novel Method For Speech Segmentation Based On Speakers' Characteristics

Abstract: Speech Segmentation is the process change point detection for partitioning an input audio stream into regions each of which corresponds to only one audio source or one speaker. One application of this system is in Speaker Diarization systems. There are several methods for speaker segmentation; however, most of the Speaker Diarization Systems use BIC-based Segmentation methods. The main goal of this paper is to propose a new method for speaker segmentation with higher speed than the current methods - e.g. BIC - and acceptable accuracy. Our proposed method is based on the pitch frequency of the speech. The accuracy of this method is similar to the accuracy of common speaker segmentation methods. However, its computation cost is much less than theirs. We show that our method is about 2.4 times faster than the BIC-based method, while the average accuracy of pitch-based method is slightly higher than that of the BIC-based method.


Moving Object Trajectories Meta-Model And Spatio-Temporal Queries

Abstract: In this paper, a general moving object trajectories framework is put forward to allow independent applications processing trajectories data benefit from a high level of interoperability, information sharing as well as an efficient answer for a wide range of complex trajectory queries. Our proposed meta-model is based on ontology and event approach, incorporates existing presentations of trajectory and integrates new patterns like space-time path to describe activities in geographical space-time. We introduce recursive Region of Interest concepts and deal mobile objects trajectories with diverse spatio-temporal sampling protocols and different sensors available that traditional data model alone are incapable for this purpose.