OpenRaiser/Intern-Atlas huggingface dataset:
On logical hierarchies within FO^2-definable languages
Venue: arXiv cs.LO 2012
Year: 2012

We consider the class of languages defined in the 2-variable fragment of the first-order logic of the linear order. Many interesting characterizations of this class are known, as well as the fact that restricting the number of quantifier alternations yields an infinite hierarchy whose levels are varieties of languages (and hence admit an algebraic characterization). Using this algebraic approach, we show that the quantifier alternation hierarchy inside FO^{2}[<] is decidable within one unit. For this purpose, we relate each level of the hierarchy with decidable varieties of languages, which can be defined in terms of iterated deterministic and co-deterministic products. A crucial notion in this process is that of condensed rankers, a refinement of the rankers of Weis and Immerman and the turtle languages of Schwentick, Thérien and Vollmer.
Web based e-learning in india: the cumulative views of different aspects
Venue: arXiv cs.CY 2012
Year: 2012

In the presence of great social diversity in India, it is difficult to change the social background of students, parents and their economical conditions. Therefore the only option left for us is to provide uniform or standardize teaching learning resources or methods. For high quality education throughout India there must be some nation-wide network, which provides equal quality education to all students, including the student from the rural areas and villages. The one and only simple solution to this is Web Based e-Learning. In this paper we try to give some innovative ideas to spread the Web Based e-Learning (WBeL) concept in to the minds of young India along with various approaches taken or to be taken, associated to it till date besides of instructional design models, different course developmental models, the role of technical writing and merit-demerit of WBeL till date.
A Framework of Value Exchange and Role Playing in Web 2.0 WebSites
Venue: arXiv cs.CY 2012
Year: 2012

Digitally engaged communities can be described as communities created and evolved within Web 2.0 Websites such as Facebook, Bebo, and Twitter. The growing importance of digitally engaged communities calls for the need to efficiently manage the building blocks of sustaining a healthy community. The initial operation of any digitally-engaged community depends on the existence of its own members, the beneficial values created and exchanged, and the relationships interlinking both. However, the level of contribution and involvement might vary depending on the benefits being gratified from engaging in such communities. In other words, motivations for participating and getting involved are purposive; individuals are driven into joining and /or taking part in any digitallyengaged network for capturing and purtaining certain beneficial values. Accordingly, this paper proposes a framework that classifies the values created and exchanged within these communities as well as the roles adopted and played by users of these communities. Utilizing ethnography as the primay methodological strategy to study Bebo digitally-engaged community, this research identifies five different roles of users: Newbie, Lurker, Novice, Insider, and Leader. Moreover, the research also identifies five value elements that could be captured by different users: Social, Hedonic, Epistemic, Gift, and Utilitarian. The results of this study provides insights for decision and policy makers, service providers, and developers; as it inspires them in knowing and meeting the needs and values of participants based on the roles adopted by users.
Portals and Task Innovation: A Theoretical Framework Founded on Business Intelligence Thinking
Venue: arXiv cs.OH 2012
Year: 2012

The main aim of this study is to develop a theoretical framework for the success of Web portals in promoting task innovation. This is deemed significant as yet little research has tackled this important domain from the business intelligence perspective. The D&M IS Success Model was used as a foundational theory and then was refined to match the context of the current research. Importantly, in this study, system quality and information quality constructs were defined on the basis of portals' characteristics since a mapping was conducted between the most significant functions and features of Web portals and quality constructs. The developed framework is deemed useful for theory and practice. From theoretical perspective, the dimensions that affect the perceived quality of Web portals are identified, and the measures that affect each quality dimension are also defined. On the practical level, contributions gained by this study can be observed in terms of the benefits decision makers, strategists, operational employees and IT developers can gain. Assessing portals success in improving task innovation is important to help managers (i.e. decision makers) in making appropriate decisions concerning the adoption of portals' technology, by weighing its benefits against the costs needed to establish and run such a technology. Moreover, assessing Web portals' success gives some insight to IT developers and designers concerning what aspects should be taken when designing and establishing high quality portals, and what functions and features should be contained that would affect the perceived quality of portals and therefore users' intention to use portals.
A Session based Multiple Image Hiding Technique using DWT and DCT
Venue: arXiv cs.CR 2012
Year: 2012

This work proposes Steganographic technique for hiding multiple images in a color image based on DWT and DCT. The cover image is decomposed into three separate color planes namely R, G and B. Individual planes are decomposed into subbands using DWT. DCT is applied in HH component of each plane. Secret images are dispersed among the selected DCT coefficients using a pseudo random sequence and a Session key. Secret images are extracted using the session key and the size of the images from the planer decomposed stego image. In this approach the stego image generated is of acceptable level of imperceptibility and distortion compared to the cover image and the overall security is high.
APRIL: Active Preference-learning based Reinforcement Learning
Venue: arXiv cs.LG 2012
Year: 2012

This paper focuses on reinforcement learning (RL) with limited prior knowledge. In the domain of swarm robotics for instance, the expert can hardly design a reward function or demonstrate the target behavior, forbidding the use of both standard RL and inverse reinforcement learning. Although with a limited expertise, the human expert is still often able to emit preferences and rank the agent demonstrations. Earlier work has presented an iterative preference-based RL framework: expert preferences are exploited to learn an approximate policy return, thus enabling the agent to achieve direct policy search. Iteratively, the agent selects a new candidate policy and demonstrates it; the expert ranks the new demonstration comparatively to the previous best one; the expert's ranking feedback enables the agent to refine the approximate policy return, and the process is iterated. In this paper, preference-based reinforcement learning is combined with active ranking in order to decrease the number of ranking queries to the expert needed to yield a satisfactory policy. Experiments on the mountain car and the cancer treatment testbeds witness that a couple of dozen rankings enable to learn a competent policy.
Credal nets under epistemic irrelevance
Venue: arXiv cs.AI 2012
Year: 2012

We present a new approach to credal nets, which are graphical models that generalise Bayesian nets to imprecise probability. Instead of applying the commonly used notion of strong independence, we replace it by the weaker notion of epistemic irrelevance. We show how assessments of epistemic irrelevance allow us to construct a global model out of given local uncertainty models and mention some useful properties. The main results and proofs are presented using the language of sets of desirable gambles, which provides a very general and expressive way of representing imprecise probability models.
Average redundancy of the Shannon code for Markov sources
Venue: arXiv cs.IT 2012
Year: 2012

It is known that for memoryless sources, the average and maximal redundancy of fixed-to-variable length codes, such as the Shannon and Huffman codes, exhibit two modes of behavior for long blocks. It either converges to a limit or it has an oscillatory pattern, depending on the irrationality or rationality, respectively, of certain parameters that depend on the source. In this paper, we extend these findings, concerning the Shannon code, to the case of a Markov source, which is considerably more involved. While this dichotomy, of convergent vs. oscillatory behavior, is well known in other contexts (including renewal theory, ergodic theory, local limit theorems and large deviations of discrete distributions), in information theory (e.g., in redundancy analysis) it was recognized relatively recently. To the best of our knowledge, no results of this type were reported thus far for Markov sources. We provide a precise characterization of the convergent vs. oscillatory behavior of the Shannon code redundancy for a class of irreducible, periodic and aperiodic, Markov sources. These findings are obtained by analytic methods, such as Fourier/Fejer series analysis and spectral analysis of matrices.
Scaling Behaviors of Wireless Device-to-Device Communications with Distributed Caching
Venue: arXiv cs.NI 2012
Year: 2012

We analyze a novel architecture for caching popular video content to enable wireless device-to-device collaboration. We focus on the asymptotic scaling characteristics and show how they depends on video content popularity statistics. We identify a fundamental conflict between collaboration distance and interference and show how to optimize the transmission power to maximize frequency reuse. Our main result is a closed form expression of the optimal collaboration distance as a function of the model parameters. Under the common assumption of a Zipf distribution for content reuse, we show that if the Zipf exponent is greater than 1, it is possible to have a number of D2D interference-free collaboration pairs that scales linearly in the number of nodes. If the Zipf exponent is smaller than 1, we identify the best possible scaling in the number of D2D collaborating links. Surprisingly, a very simple distributed caching policy achieves the optimal scaling behavior and therefore there is no need to centrally coordinate what each node is caching.
Tracing scientist's research trends realtimely
Venue: arXiv cs.DL 2012
Year: 2012

In this research, we propose a method to trace scientists' research trends realtimely. By monitoring the downloads of scientific articles in the journal of Scientometrics for 744 hours, namely one month, we investigate the download statistics. Then we aggregate the keywords in these downloaded research papers, and analyze the trends of article downloading and keyword downloading. Furthermore, taking both the download of keywords and articles into consideration, we design a method to detect the emerging research trends. We find that in scientometrics field, social media, new indices to quantify scientific productivity (g-index), webometrics, semantic, text mining, open access are emerging fields that scientometrics researchers are focusing on.
Fuel Efficient Computation in Passive Self-Assembly
Venue: arXiv cs.DS 2012
Year: 2012

In this paper we show that passive self-assembly in the context of the tile self-assembly model is capable of performing fuel efficient, universal computation. The tile self-assembly model is a premiere model of self-assembly in which particles are modeled by four-sided squares with glue types assigned to each tile edge. The assembly process is driven by positive and negative force interactions between glue types, allowing for tile assemblies floating in the plane to combine and break apart over time. We refer to this type of assembly model as passive in that the constituent parts remain unchanged throughout the assembly process regardless of their interactions. A computationally universal system is said to be fuel efficient if the number of tiles used up per computation step is bounded by a constant. Work within this model has shown how fuel guzzling tile systems can perform universal computation with only positive strength glue interactions. Recent work has introduced space-efficient, fuel-guzzling universal computation with the addition of negative glue interactions and the use of a powerful non-diagonal class of glue interactions. Other recent work has shown how to achieve fuel efficient computation within active tile self-assembly. In this paper we utilize negative interactions in the tile self-assembly model to achieve the first computationally universal passive tile self-assembly system that is both space and fuel-efficient. In addition, we achieve this result using a limited diagonal class of glue interactions.
Low-Cost Bluetooth Mobile Positioning for Location-based Application
Venue: arXiv cs.NI 2012
Year: 2012

Bluetooth is a promising short-range radio network technology. We present a low cost and easily deployed, scalable infrastructure for indoor location-based computing of mobile devices based on Bluetooth technology. The system consists of 2 main components, namely the Bluetooth (BT) Sensor System and the Central Navigation System which have been developed using the JDK 6.0. The Bluetooth Sensor System allows mobile devices whose Bluetooth mode is set to discoverable, to be scanned and detected, and they receive customizable text message of their positioning information, e.g. room identity. The positioning information is also sent to the Central Navigation System which in turn displays and updates the navigation map. The system is also used to track the movement of different BT mobile devices within the implemented environment.
A Dynamic Phase Selection Strategy for Satisfiability Solvers
Venue: arXiv cs.LO 2012
Year: 2012

The phase selection is an important of a SAT Solver based on conflict-driven DPLL. This paper presents a new phase selection strategy, in which the weight of each literal is defined as the sum of its implied-literals static weights. The implied literals of each literal is computed dynamically during the search. Therefore, it is call a dynamic phase selection strategy. In general, computing dynamically a weight is time-consuming. Hence, so far no SAT solver applies successfully a dynamic phase selection. Since the implied literal of our strategy conforms to that of the search process, the usual two watched-literals scheme can be applied here. Thus, the cost of our dynamic phase selection is very low. To improve Glucose 2.0 which won a Gold Medal for application category at SAT 2011 competition, we build five phase selection schemes using the dynamic phase selection policy. On application instances of SAT 2011, Glucose improved by the dynamic phase selection is significantly better than the original Glucose. We conduct also experiments on Lingeling, using the dynamic phase selection policy, and build two phase selection schemes. Experimental results show that the improved Lingeling is better than the original Lingeling.
An Efficient Automatic Attendance System Using Fingerprint Reconstruction Technique
Venue: arXiv cs.CV 2012
Year: 2012

Biometric time and attendance system is one of the most successful applications of biometric technology. One of the main advantage of a biometric time and attendance system is it avoids "buddy-punching". Buddy punching was a major loophole which will be exploiting in the traditional time attendance systems. Fingerprint recognition is an established field today, but still identifying individual from a set of enrolled fingerprints is a time taking process. Most fingerprint-based biometric systems store the minutiae template of a user in the database. It has been traditionally assumed that the minutiae template of a user does not reveal any information about the original fingerprint. This belief has now been shown to be false; several algorithms have been proposed that can reconstruct fingerprint images from minutiae templates. In this paper, a novel fingerprint reconstruction algorithm is proposed to reconstruct the phase image, which is then converted into the grayscale image. The proposed reconstruction algorithm reconstructs the phase image from minutiae. The proposed reconstruction algorithm is used to automate the whole process of taking attendance, manually which is a laborious and troublesome work and waste a lot of time, with its managing and maintaining the records for a period of time is also a burdensome task. The proposed reconstruction algorithm has been evaluated with respect to the success rates of type-I attack (match the reconstructed fingerprint against the original fingerprint) and type-II attack (match the reconstructed fingerprint against different impressions of the original fingerprint) using a commercial fingerprint recognition system. Given the reconstructed image from our algorithm, we show that both types of attacks can be effectively launched against a fingerprint recognition system.
Stereo Acoustic Perception based on Real Time Video Acquisition for Navigational Assistance
Venue: arXiv cs.CV 2012
Year: 2012

A smart navigation system (an Electronic Travel Aid) based on an object detection mechanism has been designed to detect the presence of obstacles that immediately impede the path, by means of real time video processing. The algorithm can be used for any general purpose navigational aid. This paper is discussed, keeping in mind the navigation of the visually impaired, and is not limited to the same. A video camera feeds images of the surroundings to a Da- Vinci Digital Media Processor, DM642, which works on the video, frame by frame. The processor carries out image processing techniques whose result contains information about the object in terms of image pixels. The algorithm aims to select the object which, among all others, poses maximum threat to the navigation. A database containing a total of three sounds is constructed. Hence, each image translates to a beep, where every beep informs the navigator of the obstacles directly in front of him. This paper implements an algorithm that is more efficient as compared to its predecessors.
Batch Spreadsheet for C Programmers
Venue: arXiv cs.SE 2012
Year: 2012

A computing environment is proposed, based on batch spreadsheet processing, which produces a spreadsheet display from plain text input files of commands, similar to the way documents are created using LaTeX. In this environment, besides the usual spreadsheet rows and columns of cells, variables can be defined and are stored in a separate symbol table. Cell and symbol formulas may contain cycles, and cycles which converge can be used to implement iterative algorithms. Formulas are specified using the syntax of the C programming language, and all of C's numeric operators are supported, with operators such as ++, +=, etc. being implicitly cyclic. User-defined functions can be written in C and are accessed using a dynamic link library. The environment can be combined with a GUI front-end processor to enable easier interaction and graphics including plotting.
Heuristic based task scheduling in multiprocessor systems with genetic algorithm by choosing the eligible processor
Venue: arXiv cs.DC 2012
Year: 2012

In multiprocessor systems, one of the main factors of systems' performance is task scheduling. The well the task be distributed among the processors the well be the performance. Again finding the optimal solution of scheduling the tasks into the processors is NP-complete, that is, it will take a lot of time to find the optimal solution. Many evolutionary algorithms (e.g. Genetic Algorithm, Simulated annealing) are used to reach the near optimal solution in linear time. In this paper we propose a heuristic for genetic algorithm based task scheduling in multiprocessor systems by choosing the eligible processor on educated guess. From comparison it is found that this new heuristic based GA takes less computation time to reach the suboptimal solution.
Inferring SQL Queries Using Program Synthesis
Venue: arXiv cs.PL 2012
Year: 2012

Developing high-performance applications that interact with databases is a difficult task, as developers need to understand both the details of the language in which their applications are written in, and also the intricacies of the relational model. One popular solution to this problem is the use of object-relational mapping (ORM) libraries that provide transparent access to the database using the same language that the application is written in. Unfortunately, using such frameworks can easily lead to applications with poor performance because developers often end up implementing relational operations in application code, and doing so usually does not take advantage of the optimized implementations of relational operations, efficient query plans, or push down of predicates that database systems provide. In this paper we present QBS, an algorithm that automatically identifies fragments of application logic that can be pushed into SQL queries. The QBS algorithm works by automatically synthesizing invariants and postconditions for the original code fragment. The postconditions and invariants are expressed using a theory of ordered relations that allows us to reason precisely about the contents and order of the records produced even by complex code fragments that compute joins and aggregates. The theory is close in expressiveness to SQL, so the synthesized postconditions can be readily translated to SQL queries. Using 40 code fragments extracted from over 120k lines of open-source code written using the Java Hibernate ORM, we demonstrate that our approach can convert a variety of imperative constructs into relational specifications.
A study on non-destructive method for detecting Toxin in pepper using Neural networks
Venue: arXiv cs.NE 2012
Year: 2012

Mycotoxin contamination in certain agricultural systems have been a serious concern for human and animal health. Mycotoxins are toxic substances produced mostly as secondary metabolites by fungi that grow on seeds and feed in the field, or in storage. The food-borne Mycotoxins likely to be of greatest significance for human health in tropical developing countries are Aflatoxins and Fumonisins. Chili pepper is also prone to Aflatoxin contamination during harvesting, production and storage periods.Various methods used for detection of Mycotoxins give accurate results, but they are slow, expensive and destructive. Destructive method is testing a material that degrades the sample under investigation. Whereas, non-destructive testing will, after testing, allow the part to be used for its intended purpose. Ultrasonic methods, Multispectral image processing methods, Terahertz methods, X-ray and Thermography have been very popular in nondestructive testing and characterization of materials and health monitoring. Image processing methods are used to improve the visual quality of the pictures and to extract useful information from them. In this proposed work, the chili pepper samples will be collected, and the X-ray, multispectral images of the samples will be processed using image processing methods. The term "Computational Intelligence" referred as simulation of human intelligence on computers. It is also called as "Artificial Intelligence" (AI) approach. The techniques used in AI approach are Neural network, Fuzzy logic and evolutionary computation. Finally, the computational intelligence method will be used in addition to image processing to provide best, high performance and accurate results for detecting the Mycotoxin level in the samples collected.