OpenRaiser/Intern-Atlas huggingface dataset:
The Art of Software Design, a Video Game for Learning Software Design Principles
Venue: arXiv cs.HC 2014
Year: 2014

This paper introduces our gamification of a part of our software design curriculum. Based on typical design principles a motivating learning game is developed to train students in software design. We use Bloom's taxonomy to determine learning objectives. We keep the player engaged with direct feedback in a challenging level based game with increasing complexity. Players can evaluate their design actions with the help of the visualisation of control and data flows. The main learning objective: applying design principles, fits the game's main activity. This supports the learning by doing approach of lecturers. A user test indicates possible learning effects and a playable game.
A Unifying Framework for Typical Multi-Task Multiple Kernel Learning Problems
Venue: arXiv cs.LG 2014
Year: 2014

Over the past few years, Multi-Kernel Learning (MKL) has received significant attention among data-driven feature selection techniques in the context of kernel-based learning. MKL formulations have been devised and solved for a broad spectrum of machine learning problems, including Multi-Task Learning (MTL). Solving different MKL formulations usually involves designing algorithms that are tailored to the problem at hand, which is, typically, a non-trivial accomplishment. In this paper we present a general Multi-Task Multi-Kernel Learning (Multi-Task MKL) framework that subsumes well-known Multi-Task MKL formulations, as well as several important MKL approaches on single-task problems. We then derive a simple algorithm that can solve the unifying framework. To demonstrate the flexibility of the proposed framework, we formulate a new learning problem, namely Partially-Shared Common Space (PSCS) Multi-Task MKL, and demonstrate its merits through experimentation.
Multi-hop Energy-efficient Control for Heterogeneous Wireless Sensor Networks Using Fuzzy Logic
Venue: arXiv cs.NI 2014
Year: 2014

Wireless Sensor Networks (WSN) have severe energy constraints imposed by limited capacity of the internal battery of sensor nodes. These restrictions stimulate the development of energy-efficient strategies aimed at increasing the period of stability and lifetime of these networks. In this paper, we propose a centralized control to elect more appropriate Cluster Heads, assuming three levels of heterogeneity and multi-hop communication between Cluster Heads. The centralized control uses the k-means algorithm, responsible for the division of clusters and Fuzzy Logic to elect the Cluster Head and selecting the best route of communication. The study results indicate that the proposed approach can increase the period of stability and lifetime in WSN.
Distributed Storage Schemes over Unidirectional Ring Networks
Venue: arXiv cs.IT 2014
Year: 2014

In this paper, we study distributed storage problems over unidirectional ring networks. A lower bound on the reconstructing bandwidth to recover total original data for each user is proposed, and it is achievable for arbitrary parameters. If a distributed storage scheme can achieve this lower bound with equality for each user, we say it an optimal reconstructing distributed storage scheme (ORDSS). Furthermore, the repair problem for a failed storage node in ORDSSes is under consideration and a tight lower bound on the repair bandwidth for each storage node is obtained. Particularly, we indicate the fact that for any ORDSS, every storage node can be repaired with repair bandwidth achieving the lower bound with equality. In addition, we present an efficient approach to construct ORDSSes for arbitrary parameters by using the concept of Euclidean division. Finally, we take an example to characterize the above approach.
Detecting Requirements Defects Utilizing A Mathematical Framework for Behavior Engineering
Venue: arXiv cs.SE 2014
Year: 2014

Behavior Engineering (BE) provides a rigorous way to derive a formal specification of a software system from the requirements written in natural language. Its graphical specification language, Behavior Tree (BT), has been used with success in industry to systematically translate large, complex, and often erroneous requirements into an integrated model of the software system. BE's process, the Behavior Modeling Process (BMP), allows requirements to be translated into individual requirement BTs one at a time, which are then integrated to form a holistic view of the system. The integrated BT then goes through a series of modifications to construct a specification BT, which is used for validation and verification. The BMP also addresses different types of defects in the requirements throughout its process. However, BT itself is a graphical modeling notation, and the types of integration relations, how they correspond to particular issues, how they should be integrated and how to get formal specification have not been clearly defined. As a result, the BMP is informal, and provides guidelines to perform all these tasks on an ad-hoc basis. In this paper, we first introduce a mathematical framework which defines the graphical form of BTs which we use to define the integration relationships of BTs and to formalize the integration strategy of the BMP. We then formulate semi-automated requirements defects detection techniques by utilizing this underlying mathematical framework, which may be extended to formalize the BMP, develop change management framework for it, build techniques for round-trip engineering and so on.
ShAppliT: A Novel Broker-mediated Solution to Generic Application Sharing in a Cluster of Closed Operating Systems
Venue: arXiv cs.DC 2014
Year: 2014

With advances in hardware and networking technologies and mass manufacturing, the cost of high end hardware had fall dramatically in recent years. However, software cost still remains high and is the dominant fraction of the overall computing budget. Application sharing is a promising solution to reduce the overall IT cost. Currently software licenses are still based on the number of copies installed. An organization can thus reduce the IT cost if the users are able to remotely access the software that is installed on certain computer servers instead of running the software on every local computer. In this paper, we propose a generic application sharing architecture for users' application sharing in a cluster of closed operating systems such as Microsoft Windows. We also propose a broker-mediated solution where we allow multiple users to access a single user software license on a time multiplex basis through a single logged in user. An application sharing tool called ShAppliT has been introduced and implemented in Microsoft Windows operating system. We evaluated their performance on CPU usage and memory consumption when a computer is hosting multiple concurrent shared application sessions.
Bio-inspired friction switches: adaptive pulley systems
Venue: arXiv cs.RO 2014
Year: 2014

Frictional influences in tendon-driven robotic systems are generally unwanted, with efforts towards minimizing them where possible. In the human hand however, the tendon-pulley system is found to be frictional with a difference between high-loaded static post-eccentric and post-concentric force production of 9-12% of the total output force. This difference can be directly attributed to tendon-pulley friction. Exploiting this phenomenon for robotic and prosthetic applications we can achieve a reduction of actuator size, weight and consequently energy consumption. In this study, we present the design of a bio-inspired friction switch. The adaptive pulley is designed to minimize the influence of frictional forces under low and medium-loading conditions and maximize it under high-loading conditions. This is achieved with a dual-material system that consists of a high-friction silicone substrate and low-friction polished steel pins. The system, designed to switch its frictional properties between the low-loaded and high-loaded conditions, is described and its behavior experimentally validated with respect to the number and spacing of pins. The results validate its intended behavior, making it a viable choice for robotic tendon-driven systems.
Valuations in Gödel Logic, and the Euler Characteristic
Venue: arXiv cs.LO 2014
Year: 2014

Using the lattice-theoretic version of the Euler characteristic introduced by V. Klee and G.-C. Rota in the Sixties, we define the Euler characteristic of a formula in Gödel logic (over finitely or infinitely many truth-values). We then prove that the information encoded by the Euler characteristic is classical, i.e. coincides with the analogous notion defined over Boolean logic. Building on this, we define many-valued versions of the Euler characteristic of a formula $φ$, and prove that they indeed provide information about the logical status of $φ$ in Gödel logic. Specifically, our first main result shows that the many-valued Euler characteristics are invariants that separate many-valued tautologies from non-tautologies. Further, we offer an initial investigation of the linear structure of these generalised characteristics. Our second main result is that the collection of many-valued characteristics forms a linearly independent set in the real vector space of all valuations of Gödel logic over finitely many propositional variables.
A Mobile Device Prototype Application for the Detection and Prediction of Node Faults in Wireless Sensor Networks
Venue: arXiv cs.NI 2014
Year: 2014

Various implementations of wireless sensor networks (i.e. personal area-, wireless body area- networks) are prone to node and network failures by such characteristics as limited node energy resources and hardware damage incurred from their surrounding environment (i.e. flooding, forest fires, a patient falling). This may jeopardize their reliability to act as early warning systems, monitoring systems for patients and athletes, and industrial and environmental observation networks. Following the current trend and widespread use of hand held, mobile communication devices, we outline an application architecture designed to detect and predict faulty nodes in wireless sensor networks. Furthermore, we implement our design as a proof of concept prototype for Android-based smartphones, which may be extended to develop other applications used for monitoring networked wireless personal area and body sensors used in other capacities. We have conducted several preliminary experiments to demonstrate the use of our design, which is capable of monitoring networks of wireless sensor devices and predicting node faults based on several localized metrics. As attributes of such networks may change over time, any models generated when the application is initialized must be updated periodically such that the applied machine learning algorithm maintains high levels of both accuracy and precision. The application is designed to discover node faults and, once identified, alert the user so that appropriate action may be taken.
Game Semantics for Access Control
Venue: arXiv cs.LO 2014
Year: 2014

We introduce a semantic approach to the study of logics for access control and dependency analysis, based on Game Semantics. We use a variant of AJM games with explicit justification (but without pointers). Based on this, we give a simple and intuitive model of the information flow constraints underlying access control. This is used to give strikingly simple proofs of \emph{non-interference theorems} in robust, semantic versions.
Ranking Function Synthesis for Linear Lasso Programs
Venue: arXiv cs.LO 2014
Year: 2014

The scope of this work is the constraint-based synthesis of termination arguments for the restricted class of programs called linear lasso programs. A termination argument consists of a ranking function as well as a set of supporting invariants. We extend existing methods in several ways. First, we use Motzkin's Transposition Theorem instead of Farkas' Lemma. This allows us to consider linear lasso programs that can additionally contain strict inequalities. Existing methods are restricted to non-strict inequalities and equalities. Second, we consider several kinds of ranking functions: affine-linear, piecewise and lexicographic ranking functions. Moreover, we present a novel kind of ranking function called multiphase ranking function which proceeds through a fixed number of phases such that for each phase, there is an affine-linear ranking function. As an abstraction to the synthesis of specific ranking functions, we introduce the notion ranking function template. This enables us to handle all ranking functions in a unified way. Our method relies on non-linear algebraic constraint solving as a subroutine which is known to scale poorly to large problems. As a mitigation we formalize an assessment of the difficulty of our constraints and present an argument why they are of an easier kind than general non-linear constraints. We prove our method to be complete: if there is a termination argument of the form specified by the given ranking function template with a fixed number of affine-linear supporting invariants, then our method will find a termination argument. To our knowledge, the approach we propose is the most powerful technique of synthesis-based discovery of termination arguments for linear lasso programs and encompasses and enhances several methods having been proposed thus far.
HMACA: Towards Proposing a Cellular Automata Based Tool for Protein Coding, Promoter Region Identification and Protein Structure Prediction
Venue: arXiv cs.CE 2014
Year: 2014

Human body consists of lot of cells, each cell consist of DeOxaRibo Nucleic Acid (DNA). Identifying the genes from the DNA sequences is a very difficult task. But identifying the coding regions is more complex task compared to the former. Identifying the protein which occupy little place in genes is a really challenging issue. For understating the genes coding region analysis plays an important role. Proteins are molecules with macro structure that are responsible for a wide range of vital biochemical functions, which includes acting as oxygen, cell signaling, antibody production, nutrient transport and building up muscle fibers. Promoter region identification and protein structure prediction has gained a remarkable attention in recent years. Even though there are some identification techniques addressing this problem, the approximate accuracy in identifying the promoter region is closely 68% to 72%. We have developed a Cellular Automata based tool build with hybrid multiple attractor cellular automata (HMACA) classifier for protein coding region, promoter region identification and protein structure prediction which predicts the protein and promoter regions with an accuracy of 76%. This tool also predicts the structure of protein with an accuracy of 80%.
Which Clustering Do You Want? Inducing Your Ideal Clustering with Minimal Feedback
Venue: arXiv cs.IR 2014
Year: 2014

While traditional research on text clustering has largely focused on grouping documents by topic, it is conceivable that a user may want to cluster documents along other dimensions, such as the authors mood, gender, age, or sentiment. Without knowing the users intention, a clustering algorithm will only group documents along the most prominent dimension, which may not be the one the user desires. To address the problem of clustering documents along the user-desired dimension, previous work has focused on learning a similarity metric from data manually annotated with the users intention or having a human construct a feature space in an interactive manner during the clustering process. With the goal of reducing reliance on human knowledge for fine-tuning the similarity function or selecting the relevant features required by these approaches, we propose a novel active clustering algorithm, which allows a user to easily select the dimension along which she wants to cluster the documents by inspecting only a small number of words. We demonstrate the viability of our algorithm on a variety of commonly-used sentiment datasets.
License Plate Recognition (LPR): A Review with Experiments for Malaysia Case Study
Venue: arXiv cs.CV 2014
Year: 2014

Most vehicle license plate recognition use neural network techniques to enhance its computing capability. The image of the vehicle license plate is captured and processed to produce a textual output for further processing. This paper reviews image processing and neural network techniques applied at different stages which are preprocessing, filtering, feature extraction, segmentation and recognition in such way to remove the noise of the image, to enhance the image quality and to expedite the computing process by converting the characters in the image into respective text. An exemplar experiment has been done in MATLAB to show the basic process of the image processing especially for license plate in Malaysia case study. An algorithm is adapted into the solution for parking management system. The solution then is implemented as proof of concept to the algorithm.
A Novel Proof for the DoF Region of the MIMO Broadcast Channel with No CSIT
Venue: arXiv cs.IT 2014
Year: 2014

In this paper, a new proof for the degrees of freedom (DoF) region of the K-user multiple-input multiple-output (MIMO) broadcast channel (BC) with no channel state information at the transmitter (CSIT) and perfect channel state information at the receivers (CSIR) is provided. Based on this proof, the capacity region of a certain class of MIMO BC with channel distribution information at the transmitter (CDIT) and perfect CSIR is derived. Finally, an outer bound for the DoF region of the MIMO interference channel (IC) with no CSIT is provided.
Fast LTL Satisfiability Checking by SAT Solvers
Venue: arXiv cs.LO 2014
Year: 2014

Satisfiability checking for Linear Temporal Logic (LTL) is a fundamental step in checking for possible errors in LTL assertions. Extant LTL satisfiability checkers use a variety of different search procedures. With the sole exception of LTL satisfiability checking based on bounded model checking, which does not provide a complete decision procedure, LTL satisfiability checkers have not taken advantage of the remarkable progress over the past 20 years in Boolean satisfiability solving. In this paper, we propose a new LTL satisfiability-checking framework that is accelerated using a Boolean SAT solver. Our approach is based on the variant of the \emph{obligation-set method}, which we proposed in earlier work. We describe here heuristics that allow the use of a Boolean SAT solver to analyze the obligations for a given LTL formula. The experimental evaluation indicates that the new approach provides a a significant performance advantage.
Unsupervised Methods for Determining Object and Relation Synonyms on the Web
Venue: arXiv cs.CL 2014
Year: 2014

The task of identifying synonymous relations and objects, or synonym resolution, is critical for high-quality information extraction. This paper investigates synonym resolution in the context of unsupervised information extraction, where neither hand-tagged training examples nor domain knowledge is available. The paper presents a scalable, fully-implemented system that runs in O(KN log N) time in the number of extractions, N, and the maximum number of synonyms per word, K. The system, called Resolver, introduces a probabilistic relational model for predicting whether two strings are co-referential based on the similarity of the assertions containing them. On a set of two million assertions extracted from the Web, Resolver resolves objects with 78% precision and 68% recall, and resolves relations with 90% precision and 35% recall. Several variations of resolvers probabilistic model are explored, and experiments demonstrate that under appropriate conditions these variations can improve F1 by 5%. An extension to the basic Resolver system allows it to handle polysemous names with 97% precision and 95% recall on a data set from the TREC corpus.
Relations between automata and the simple k-path problem
Venue: arXiv cs.DS 2014
Year: 2014

Let $G$ be a directed graph on $n$ vertices. Given an integer $k<=n$, the SIMPLE $k$-PATH problem asks whether there exists a simple $k$-path in $G$. In case $G$ is weighted, the MIN-WT SIMPLE $k$-PATH problem asks for a simple $k$-path in $G$ of minimal weight. The fastest currently known deterministic algorithm for MIN-WT SIMPLE $k$-PATH by Fomin, Lokshtanov and Saurabh runs in time $O(2.851^k\cdot n^{O(1)}\cdot \log W)$ for graphs with integer weights in the range $[-W,W]$. This is also the best currently known deterministic algorithm for SIMPLE k-PATH- where the running time is the same without the $\log W$ factor. We define $L_k(n)\subseteq [n]^k$ to be the set of words of length $k$ whose symbols are all distinct. We show that an explicit construction of a non-deterministic automaton (NFA) of size $f(k)\cdot n^{O(1)}$ for $L_k(n)$ implies an algorithm of running time $O(f(k)\cdot n^{O(1)}\cdot \log W)$ for MIN-WT SIMPLE $k$-PATH when the weights are non-negative or the constructed NFA is acyclic as a directed graph. We show that the algorithm of Kneis et al. and its derandomization by Chen et al. for SIMPLE $k$-PATH can be used to construct an acylic NFA for $L_k(n)$ of size $O^*(4^{k+o(k)})$. We show, on the other hand, that any NFA for $L_k(n)$ must be size at least $2^k$. We thus propose closing this gap and determining the smallest NFA for $L_k(n)$ as an interesting open problem that might lead to faster algorithms for MIN-WT SIMPLE $k$-PATH. We use a relation between SIMPLE $k$-PATH and non-deterministic xor automata (NXA) to give another direction for a deterministic algorithm with running time $O^*(2^k)$ for SIMPLE $k$-PATH.
Data Mining Cultural Aspects of Social Media Marketing
Venue: arXiv cs.SI 2014
Year: 2014

For marketing to function in a globalized world it must respect a diverse set of local cultures. With marketing efforts extending to social media platforms, the crossing of cultural boundaries can happen in an instant. In this paper we examine how culture influences the popularity of marketing messages in social media platforms. Text mining, automated translation and sentiment analysis contribute largely to our research. From our analysis of 400 posts on the localized Google+ pages of German car brands in Germany and the US, we conclude that posting time and emotions are important predictors for reshare counts.
Towards a Software Architecture Maturity Model for Improving Ultra-Large-Scale Systems Interoperability
Venue: arXiv cs.SE 2014
Year: 2014

For the last two decades, software architecture has been adopted as one of the main viable solutions to address the ever-increasing demands in the design and development of software systems. Nevertheless, the rapidly growing utilization of communication networks and interconnections among software systems have introduced some critical challenges, which need to be handled in order to fully unleash the potential of these systems. In this respect, Ultra-Large-Scale (ULS) systems, generally considered as a system of systems, have gained considerable attention, since their scale is incomparable to the traditional systems. The scale of ULS systems makes drastic changes in various aspects of system development. As a result, it requires that we broaden our understanding of software architectures and the ways we structure them. In this paper, we investigate the lack of an architectural maturity model framework for ULS system interoperability, and propose an architectural maturity model framework to improve ULS system interoperability.