OpenRaiser/Intern-Atlas huggingface dataset:
The Minimal Compression Rate for Similarity Identification
Venue: arXiv cs.IT 2013
Year: 2013

Traditionally, data compression deals with the problem of concisely representing a data source, e.g. a sequence of letters, for the purpose of eventual reproduction (either exact or approximate). In this work we are interested in the case where the goal is to answer similarity queries about the compressed sequence, i.e. to identify whether or not the original sequence is similar to a given query sequence. We study the fundamental tradeoff between the compression rate and the reliability of the queries performed on compressed data. For i.i.d. sequences, we characterize the minimal compression rate that allows query answers, that are reliable in the sense of having a vanishing false-positive probability, when false negatives are not allowed. The result is partially based on a previous work by Ahlswede et al., and the inherently typical subset lemma plays a key role in the converse proof. We then characterize the compression rate achievable by schemes that use lossy source codes as a building block, and show that such schemes are, in general, suboptimal. Finally, we tackle the problem of evaluating the minimal compression rate, by converting the problem to a sequence of convex programs that can be solved efficiently.
Applying the Apriori algorithm for investigating the relationships between demographic characteristics of Iranian top 100 enterprises and the strcture of their commercial website
Venue: arXiv cs.DB 2013
Year: 2013

This study was conducted with the main aim to investigate the relationships between demographic characteristics of companies and the facilities required for their commercial websites. The research samples are the top 100 Iranian companies as ranked by the Iranian Industrial Management Institute; the method applied is datamining, using Association Rules throught the Apriori algorithms. To collect the data, an aithor-modified check list has been utilized, coverig the three areas of faclities within commercial websites, i.e. fundamental, information-providing, and service-delivering facilities. having extracted the association rules between the mentioned two sets of variables, 68 rules with a confidence rate of 90% and above were obtained, and based on their significance were classified into two groups of must-have and should-have requirements; a recommended package of facilities is hitherto offered to other companies which intend to enter e-commerce through their commerical websites with regards to each company's unique demographic characteristics.
Harbinger: An Analyzing and Predicting System for Online Social Network Users' Behavior
Venue: arXiv cs.SI 2013
Year: 2013

Online Social Network (OSN) is one of the hottest innovations in the past years, and the active users are more than a billion. For OSN, users' behavior is one of the important factors to study. This demonstration proposal presents Harbinger, an analyzing and predicting system for OSN users' behavior. In Harbinger, we focus on tweets' timestamps (when users post or share messages), visualize users' post behavior as well as message retweet number and build adjustable models to predict users' behavior. Predictions of users' behavior can be performed with the discovered behavior models and the results can be applied to many applications such as tweet crawler and advertisement.
CLIC: A Framework for Distributed, On-Demand, Human-Machine Cognitive Systems
Venue: arXiv cs.AI 2013
Year: 2013

Traditional Artificial Cognitive Systems (for example, intelligent robots) share a number of limitations. First, they are usually made up only of machine components; humans are only playing the role of user or supervisor. And yet, there are tasks in which the current state of the art of AI has much worse performance or is more expensive than humans: thus, it would be highly beneficial to have a systematic way of creating systems with both human and machine components, possibly with remote non-expert humans providing short-duration real-time services. Second, their components are often dedicated to only one system, and underutilized for a big part of their lifetime. Third, there is no inherent support for robust operation, and if a new better component becomes available, one cannot easily replace the old component. Fourth, they are viewed as a resource to be developed and owned, not as a utility. Thus, we are presenting CLIC: a framework for constructing cognitive systems that overcome the above limitations. The architecture of CLIC provides specific mechanisms for creating and operating cognitive systems that fulfill a set of desiderata: First, that are distributed yet situated, interacting with the physical world though sensing and actuation services, and that are also combining human as well as machine services. Second, that are made up of components that are time-shared and re-usable. Third, that provide increased robustness through self-repair. Fourth, that are constructed and reconstructed on the fly, with components that dynamically enter and exit the system during operation, on the basis of availability, pricing, and need. Importantly, fifth, the cognitive systems created and operated by CLIC do not need to be owned and can be provided on demand, as a utility; thus transforming human-machine situated intelligence to a service, and opening up many interesting opportunities.
A Risk-driven Model for Work Allocation in Global Software Development Projects
Venue: arXiv cs.SE 2013
Year: 2013

Risks and potential benefits of distributing software development projects globally depend to a large extent on how to allocate work to different development sites and regions. Existing methods in task allocation are likely to omit the relevance of considering a multitude of criteria and the impact of task distribution on risks and potential benefits. To assess risks stemming from specific work distributions and to exploit organization-specific experience, we have developed a customizable risk-driven model. It consists of two main steps: Suggesting a set of task allocation alternatives based on project- and site-specific characteristics and analyzing it with respect to possible project risks stemming from the work distribution. To evaluate the model, we conducted a series of semi-structured interviews in a multinational IT company. The results of the evaluation show that the suggestions of the model mostly comply with the retrospective views voiced by the involved experienced managers.
Visitor Pattern: Implementation of Enquiry Pattern for Internet Banking
Venue: arXiv cs.SE 2013
Year: 2013

This paper brings out the design patterns according to the various services involved in internet banking. The Pattern oriented Software Architecture uses the pattern which eliminates the difficulty of reusability in a particular context. The patterns are to be designed using BPM (Business Process Model) for effective cross cutting on process level. For implementing the above said BPM, the Internet banking has been taken to implement the pattern into it. The Analysis and identification of various processes in Internet Banking have been done, to identify the effective cross cutting features. With this process the pattern has been designed, as a reusability component to be used by the Software Architect. The pattern help us to resolve recurring problems constructively and based on proven solutions and also support us in understanding the architecture of a given software system. Once the model is finalized by analyzing we found enquiry pattern as the visitor pattern and implement the pattern.
Evaluation of Software Architecture Quality Attribute for an Internet Banking System
Venue: arXiv cs.SE 2013
Year: 2013

The design phase plays a vital role than all other phases in the software development. Software Architecture has to meet both the functional and non-functional quality requirements. The Evaluation of Architecture has to be performed, so that the developers are assured that their selected Architecture will reduce the cost and effort and also enhances the various quality attributes like Availability, Reusability, Performance, Modifiability and Extendibility. The success of the system depends upon the Architecture Evaluation by the essential method to the system. The overall ranking of the candidate architecture is ascertained by assigning weight to the scenario and scenario interaction. In this paper, SAAM method is taken to evaluate the two architectures from the various available method and techniques to achieve the various quality attributes by weight metric.
Request and notification Pattern for an internet banking System
Venue: arXiv cs.SE 2013
Year: 2013

The quality of software is enhanced by using the design patterns. The design patterns are the reusable component used in the development of the software, which delivers improved quality software to the end users. The researchers have developed design patterns for user interface, e-commerce applications, mobile applications, text classification and so on. There are no design patterns for internet banking applications, but there is analysis pattern for banking. This motivated to mine the design patterns for internet banking application. It can be mined from the document of Business Process Management (BPM). In this paper the request and notification are two patterns, that have been presented, which have been mined from internet banking.
A preliminary survey on optimized multiobjective metaheuristic methods for data clustering using evolutionary approaches
Venue: arXiv cs.NE 2013
Year: 2013

The present survey provides the state-of-the-art of research, copiously devoted to Evolutionary Approach (EAs) for clustering exemplified with a diversity of evolutionary computations. The Survey provides a nomenclature that highlights some aspects that are very important in the context of evolutionary data clustering. The paper missions the clustering trade-offs branched out with wide-ranging Multi Objective Evolutionary Approaches (MOEAs) methods. Finally, this study addresses the potential challenges of MOEA design and data clustering, along with conclusions and recommendations for novice and researchers by positioning most promising paths of future research. MOEAs have substantial success across a variety of MOP applications, from pedagogical multifunction optimization to real-world engineering design. The survey paper noticeably organizes the developments witnessed in the past three decades for EAs based metaheuristics to solve multiobjective optimization problems (MOP) and to derive significant progression in ruling high quality elucidations in a single run. Data clustering is an exigent task, whose intricacy is caused by a lack of unique and precise definition of a cluster. The discrete optimization problem uses the cluster space to derive a solution for Multiobjective data clustering. Discovery of a majority or all of the clusters (of illogical shapes) present in the data is a long-standing goal of unsupervised predictive learning problems or exploratory pattern analysis.
High Dimensional Expanders and Property Testing
Venue: arXiv cs.CC 2013
Year: 2013

We show that the high dimensional expansion property as defined by Gromov, Linial and Meshulam, for simplicial complexes is a form of testability. Namely, a simplicial complex is a high dimensional expander iff a suitable property is testable. Using this connection, we derive several testability results.
Unsupervised classification of uncertain data objects in spatial databases using computational geometry and indexing techniques
Venue: arXiv cs.DB 2013
Year: 2013

Unsupervised classification called clustering is a process of organizing objects into groups whose members are similar in some way. Clustering of uncertain data objects is a challenge in spatial data bases. In this paper we use Probability Density Functions (PDF) to represent these uncertain data objects, and apply Uncertain K-Means algorithm to generate the clusters. This clustering algorithm uses the Expected Distance (ED) to compute the distance between objects and cluster representatives. To further improve the performance of UK-Means we propose a novel technique called Voronoi Diagrams from Computational Geometry to prune the number of computations of ED. This technique works efficiently but results pruning overheads. In order to reduce these in pruning overhead we introduce R*-tree indexing over these uncertain data objects, so that it reduces the computational cost and pruning overheads. Our novel approach of integrating UK-Means with voronoi diagrams and R* Tree applied over uncertain data objects generates imposing outcome when compared with the accessible methods.
Compressed Quantitative MRI: Bloch Response Recovery through Iterated Projection
Venue: arXiv cs.IT 2013
Year: 2013

Inspired by the recently proposed Magnetic Resonance Fingerprinting technique, we develop a principled compressed sensing framework for quantitative MRI. The three key components are: a random pulse excitation sequence following the MRF technique; a random EPI subsampling strategy and an iterative projection algorithm that imposes consistency with the Bloch equations. We show that, as long as the excitation sequence possesses an appropriate form of persistent excitation, we are able to achieve accurate recovery of the proton density, $T_1$, $T_2$ and off-resonance maps simultaneously from a limited number of samples.
A Key Set Cipher for Wireless Sensor Networks
Venue: arXiv cs.CR 2013
Year: 2013

This paper proposes the use of sets of keys, together with corresponding identifiers, for use in wireless sensor networks and similar resource-constrained applications. A specific cryptographic scheme described in the paper is based on the use of a family of self-inverting matrices derived from the number theoretic Hilbert transform in conjunction with the Blom's scheme. In a randomized version of this scheme, the users change their published IDs at will but the parties can still reach agreement on the key by using individual scaling factors. The random protocol increases the security of the system.
On the approximability of covering points by lines and related problems
Venue: arXiv cs.CG 2013
Year: 2013

Given a set $P$ of $n$ points in the plane, {\sc Covering Points by Lines} is the problem of finding a minimum-cardinality set $Ł$ of lines such that every point $p \in P$ is incident to some line $\ell \in Ł$. As a geometric variant of {\sc Set Cover}, {\sc Covering Points by Lines} is still NP-hard. Moreover, it has been proved to be APX-hard, and hence does not admit any polynomial-time approximation scheme unless P $=$ NP\@. In contrast to the small constant approximation lower bound implied by APX-hardness, the current best approximation ratio for {\sc Covering Points by Lines} is still $O(\log n)$, namely the ratio achieved by the greedy algorithm for {\sc Set Cover}. In this paper, we give a lower bound of $Ω(\log n)$ on the approximation ratio of the greedy algorithm for {\sc Covering Points by Lines}. We also study several related problems including {\sc Maximum Point Coverage by Lines}, {\sc Minimum-Link Covering Tour}, {\sc Minimum-Link Spanning Tour}, and {\sc Min-Max-Turn Hamiltonian Tour}. We show that all these problems are either APX-hard or at least NP-hard. In particular, our proof of APX-hardness of {\sc Min-Max-Turn Hamiltonian Tour} sheds light on the difficulty of {\sc Bounded-Turn-Minimum-Length Hamiltonian Tour}, a problem proposed by Aggarwal et al.\ at SODA 1997.
Abstract Interpretation of Temporal Concurrent Constraint Programs
Venue: arXiv cs.LO 2013
Year: 2013

Timed Concurrent Constraint Programming (tcc) is a declarative model for concurrency offering a logic for specifying reactive systems, i.e. systems that continuously interact with the environment. The universal tcc formalism (utcc) is an extension of tcc with the ability to express mobility. Here mobility is understood as communication of private names as typically done for mobile systems and security protocols. In this paper we consider the denotational semantics for tcc, and we extend it to a "collecting" semantics for utcc based on closure operators over sequences of constraints. Relying on this semantics, we formalize a general framework for data flow analyses of tcc and utcc programs by abstract interpretation techniques. The concrete and abstract semantics we propose are compositional, thus allowing us to reduce the complexity of data flow analyses. We show that our method is sound and parametric with respect to the abstract domain. Thus, different analyses can be performed by instantiating the framework. We illustrate how it is possible to reuse abstract domains previously defined for logic programming to perform, for instance, a groundness analysis for tcc programs. We show the applicability of this analysis in the context of reactive systems. Furthermore, we make also use of the abstract semantics to exhibit a secrecy flaw in a security protocol. We also show how it is possible to make an analysis which may show that tcc programs are suspension free. This can be useful for several purposes, such as for optimizing compilation or for debugging.
E-learning for ungraded schools of Kazakhstan: experience, implementation, and innovation
Venue: arXiv cs.CY 2013
Year: 2013

The modernization of the educational process in the ungraded schools of the Republic of Kazakhstan requires the provision of affordable quality education for students in rural areas on information technology, the creation of e-learning. It was important to consider two points: how does e-learning influence the educational process in ungraded schools, and directly on the quality of teaching, and what results can thus be achieved. The significance of the work is also to explore innovative approaches to e-learning system of ungraded schools.
A New Variable Step-size Zero-point Attracting Projection Algorithm
Venue: arXiv cs.OH 2013
Year: 2013

This paper proposes a new variable step-size (VSS) scheme for the recently introduced zero-point attracting projection (ZAP) algorithm. The proposed variable step-size ZAPs are based on the gradient of the estimated filter coefficients sparseness that is approximated by the difference between the sparseness measure of current filter coefficients and an averaged sparseness measure. Simulation results demonstrate that the proposed approach provides both faster convergence rate and better tracking ability than previous ones.
DeltaTree: A Practical Locality-aware Concurrent Search Tree
Venue: arXiv cs.DC 2013
Year: 2013

As other fundamental programming abstractions in energy-efficient computing, search trees are expected to support both high parallelism and data locality. However, existing highly-concurrent search trees such as red-black trees and AVL trees do not consider data locality while existing locality-aware search trees such as those based on the van Emde Boas layout (vEB-based trees), poorly support concurrent (update) operations. This paper presents DeltaTree, a practical locality-aware concurrent search tree that combines both locality-optimisation techniques from vEB-based trees and concurrency-optimisation techniques from non-blocking highly-concurrent search trees. DeltaTree is a $k$-ary leaf-oriented tree of DeltaNodes in which each DeltaNode is a size-fixed tree-container with the van Emde Boas layout. The expected memory transfer costs of DeltaTree's Search, Insert, and Delete operations are $O(\log_B N)$, where $N, B$ are the tree size and the unknown memory block size in the ideal cache model, respectively. DeltaTree's Search operation is wait-free, providing prioritised lanes for Search operations, the dominant operation in search trees. Its Insert and {\em Delete} operations are non-blocking to other Search, Insert, and Delete operations, but they may be occasionally blocked by maintenance operations that are sometimes triggered to keep DeltaTree in good shape. Our experimental evaluation using the latest implementation of AVL, red-black, and speculation friendly trees from the Synchrobench benchmark has shown that DeltaTree is up to 5 times faster than all of the three concurrent search trees for searching operations and up to 1.6 times faster for update operations when the update contention is not too high.
Cellular Automata based Feedback Mechanism in Strengthening biological Sequence Analysis Approach to Robotic Soccer
Venue: arXiv cs.MA 2013
Year: 2013

This paper reports on the application of sequence analysis algorithms for agents in robotic soccer and a suitable representation is proposed to achieve this mapping. The objective of this research is to generate novel better in-game strategies with the aim of faster adaptation to the changing environment. A homogeneous non-communicating multi-agent architecture using the representation is presented. To achieve real-time learning during a game, a bucket brigade algorithm is used to reinforce Cellular Automata Based Classifier. A technique for selecting strategies based on sequence analysis is adopted.
Structural Induction Principles for Functional Programmers
Venue: arXiv cs.PL 2013
Year: 2013

User defined recursive types are a fundamental feature of modern functional programming languages like Haskell, Clean, and the ML family of languages. Properties of programs defined by recursion on the structure of recursive types are generally proved by structural induction on the type. It is well known in the theorem proving community how to generate structural induction principles from data type declarations. These methods deserve to be better know in the functional programming community. Existing functional programming textbooks gloss over this material. And yet, if functional programmers do not know how to write down the structural induction principle for a new type - how are they supposed to reason about it? In this paper we describe an algorithm to generate structural induction principles from data type declarations. We also discuss how these methods are taught in the functional programming course at the University of Wyoming. A Haskell implementation of the algorithm is included in an appendix.
Phishing Detection by determining reliability factor using rough set theory
Venue: arXiv cs.AI 2013
Year: 2013

Phishing is a common online weapon, used against users, by Phishers for acquiring a confidential information through deception. Since the inception of internet, nearly everything, ranging from money transaction to sharing information, is done online in most parts of the world. This has also given rise to malicious activities such as Phishing. Detecting Phishing is an intricate process due to complexity, ambiguity and copious amount of possibilities of factors responsible for phishing . Rough sets can be a powerful tool, when working on such kind of Applications containing vague or imprecise data. This paper proposes an approach towards Phishing Detection Using Rough Set Theory. The Thirteen basic factors, directly responsible towards Phishing, are grouped into four Strata. Reliability Factor is determined on the basis of the outcome of these strata, using Rough Set Theory . Reliability Factor determines the possibility of a suspected site to be Valid or Fake. Using Rough set Theory most and the least influential factors towards Phishing are also determined.
OntoVerbal: a Generic Tool and Practical Application to SNOMED CT
Venue: arXiv cs.AI 2013
Year: 2013

Ontology development is a non-trivial task requiring expertise in the chosen ontological language. We propose a method for making the content of ontologies more transparent by presenting, through the use of natural language generation, naturalistic descriptions of ontology classes as textual paragraphs. The method has been implemented in a proof-of- concept system, OntoVerbal, that automatically generates paragraph-sized textual descriptions of ontological classes expressed in OWL. OntoVerbal has been applied to ontologies that can be loaded into Protégé and been evaluated with SNOMED CT, showing that it provides coherent, well-structured and accurate textual descriptions of ontology classes.