OpenRaiser/Intern-Atlas huggingface dataset:
Delta Modeling for Software Architectures
Venue: arXiv cs.SE 2014
Year: 2014

Architectural modeling is an integral part of modern software development. In particular, diverse systems benefit from precise architectural models since similar components can often be reused between different system variants. However, during all phases of diverse system development, system variability has to be considered and modeled by appropriate means. Delta modeling is a language-independent approach for modeling system variability. A set of diverse systems is represented by a core system and a set of deltas specifying modifications to the core system. In this paper, we give a first sketch of how to apply delta modeling in MontiArc, an existing architecture description language, in order to obtain an integrated modeling language for architectural variability. The developed language, MontiArc, allows the modular modeling of variable software architectures and supports proactive as well as extractive product line development.
Model Evolution and Management
Venue: arXiv cs.SE 2014
Year: 2014

As complex software and systems development projects need models as an important planning, structuring and development technique, models now face issues resolved for software earlier: models need to be versioned, differences captured, syntactic and semantic correctness checked as early as possible, documented, presented in easily accessible forms, etc. Quality management needs to be established for models as well as their relationship to other models, to code and to requirement documents precisely clarified and tracked. Business and product requirements, product technologies as well as development tools evolve. This also means we need evolutionary technologies both for models within a language and if the language evolves also for an upgrade of the models. This chapter discusses the state of the art in model management and evolution and sketches what is still necessary for models to become as usable and used as software.
The Energy Navigator - A Web based Platform for functional Quality Mangement in Buildings
Venue: arXiv cs.SE 2014
Year: 2014

Energy efficient buildings require high quality standards for all their technical equipment to enable their efficient and successful operation and management. Building simulations enable engineers to design integrated HVAC systems with complex building automation systems to control all their technical functions. Numerous studies show that especially these supposedly innovative buildings often do not reach their energy efficiency targets when in operation. Key reasons for the suboptimal performance are imprecise functional descriptions and a lack of commissioning and monitoring of the technical systems that leave suboptimal operation undetected. In the research project "Energy Navigator" we create a web-based platform that enables engineers to create a comprehensive and precise functional description for the buildings services. The system reuses this functional description - written in an appropriate domain specific language - to control the building operation, to signal malfunctions or faults, and in particular to measure energy efficiency over time. The innovative approach of the platform is the combination of design and control within one artifact linking the phases of design and operation and improving the cost effectiveness for both services. The paper will describe the concept of the platform, the technical innovation and first application examples of the research project.
ProcDSL + ProcEd - a Web-based Editing Solution for Domain Specific Process-Engineering
Venue: arXiv cs.SE 2014
Year: 2014

In a high-tech country products are becoming rapidly more complex. To manage the development process as well as to encounter unforeseen challenges, the understanding and thus the explicit modeling of organizational workflows is more important than ever. However, available tools to support this work, in most cases force a new notation upon the company or cannot be adapted to a given publication layout in a reasonable amount of time. Additionally, collaboration among colleagues as well as different business units is complicated and less supported. Since it is of vital importance for a company to be able to change its processes fast and adapt itself to new market situations, the need for tools supporting this evolution is equally crucial. In this paper we present a domain specific language (DSL) developed for modeling a company's workflows. Furthermore, the DSL is embedded in a web-based editor providing transparent access using modern web 2.0 technologies. Results of the DSL's as well as the editor's application to document, model, and improve selected workflows of a German automotive manufacturer are presented.
Design Guidelines for Domain Specific Languages
Venue: arXiv cs.SE 2014
Year: 2014

Designing a new domain specific language is as any other complex task sometimes error-prone and usually time consuming, especially if the language shall be of high-quality and comfortably usable. Existing tool support focuses on the simplification of technical aspects but lacks support for an enforcement of principles for a good language design. In this paper we investigate guidelines that are useful for designing domain specific languages, largely based on our experience in developing languages as well as relying on existing guidelines on general purpose (GPLs) and modeling languages. We defined guidelines to support a DSL developer to achieve better quality of the language design and a better acceptance among its users.
A Parameterized Study of Maximum Generalized Pattern Matching Problems
Venue: arXiv cs.CC 2014
Year: 2014

The generalized function matching (GFM) problem has been intensively studied starting with [Ehrenfeucht and Rozenberg, 1979]. Given a pattern p and a text t, the goal is to find a mapping from the letters of p to non-empty substrings of t, such that applying the mapping to p results in t. Very recently, the problem has been investigated within the framework of parameterized complexity [Fernau, Schmid, and Villanger, 2013]. In this paper we study the parameterized complexity of the optimization variant of GFM (called Max-GFM), which has been introduced in [Amir and Nor, 2007]. Here, one is allowed to replace some of the pattern letters with some special symbols "?", termed wildcards or don't cares, which can be mapped to an arbitrary substring of the text. The goal is to minimize the number of wildcards used. We give a complete classification of the parameterized complexity of Max-GFM and its variants under a wide range of parameterizations, such as, the number of occurrences of a letter in the text, the size of the text alphabet, the number of occurrences of a letter in the pattern, the size of the pattern alphabet, the maximum length of a string matched to any pattern letter, the number of wildcards and the maximum size of a string that a wildcard can be mapped to.
A theoretical contribution to the fast implementation of null linear discriminant analysis method using random matrix multiplication with scatter matrices
Venue: arXiv cs.NA 2014
Year: 2014

The null linear discriminant analysis method is a competitive approach for dimensionality reduction. The implementation of this method, however, is computationally expensive. Recently, a fast implementation of null linear discriminant analysis method using random matrix multiplication with scatter matrices was proposed. However, if the random matrix is chosen arbitrarily, the orientation matrix may be rank deficient, and some useful discriminant information will be lost. In this paper, we investigate how to choose the random matrix properly, such that the two criteria of the null LDA method are satisfied theoretically. We give a necessary and sufficient condition to guarantee full column rank of the orientation matrix. Moreover, the geometric characterization of the condition is also described.
On Spatial Capacity of Wireless Ad Hoc Networks with Threshold Based Scheduling
Venue: arXiv cs.IT 2014
Year: 2014

This paper studies spatial capacity in a stochastic wireless ad hoc network, where multi-stage probing and data transmission are sequentially performed. We propose a novel signal-to-interference-ratio (SIR) threshold based scheduling scheme, where by starting with the first probing, each transmitter iteratively decides to further probe or stay idle, depending on whether the estimated SIR in the proceeding probing is larger or smaller than a predefined threshold. Although one can assume that the transmitters are initially deployed according to a homogeneous Poisson point process (PPP), the SIR based scheduling makes the PPP no longer applicable to model the locations of retained transmitters in the subsequent probing and data transmission phases, due to the interference induced coupling in their decisions. We first focus on single-stage probing and find that when the SIR threshold is set sufficiently small to assure an acceptable interference level in the network, the proposed scheme can greatly outperform the non-scheduling reference scheme in terms of spatial capacity. We clearly characterize the spatial capacity and obtain exact/approximate closed-form expressions, by proposing a new approximate approach to deal with the correlated SIR distributions over non-Poisson point processes. Then we successfully extend to multi-stage probing by properly designing the multiple SIR thresholds to assure gradual improvement of the spatial capacity. Furthermore, we analyze the impact of multi-stage probing overhead and present a probing-capacity tradeoff in scheduling design. Finally, extensive numerical results are presented to demonstrate the performance of the proposed scheduling as compared to existing schemes.
Parallel and Distributed Collaborative Filtering: A Survey
Venue: arXiv cs.IR 2014
Year: 2014

Collaborative filtering is amongst the most preferred techniques when implementing recommender systems. Recently, great interest has turned towards parallel and distributed implementations of collaborative filtering algorithms. This work is a survey of the parallel and distributed collaborative filtering implementations, aiming not only to provide a comprehensive presentation of the field's development, but also to offer future research orientation by highlighting the issues that need to be further developed.
Verification of Reachability Problems for Time Basic Petri Nets
Venue: arXiv cs.LO 2014
Year: 2014

Time-Basic Petri nets, is a powerful formalism for model- ing real-time systems where time constraints are expressed through time functions of marking's time description associated with transition, representing possible firing times. We introduce a technique for reachability analysis based on the building of finite contraction of the infinite state space associated with such a models. The technique constructs a finite symbolic reachability graph relying on a sort of time coverage, and over- comes the limitations of the existing available analyzers for Time-Basic nets, based in turn on a time-bounded inspection of a (possibly infinite) reachability-tree. A key feature of the technique is the introduction of the Time Anonymous concept, which allows the identification of components not influencing the evolution of a model. A running example is used throughout the paper to sketch the symbolic graph construction. The graph construction algorithm has been automated by a Java tool-set, described in the paper together with its main functionality and analysis capability. A use case describing a real-world example has been employed to benchmark the technique and the tool-set. The main outcome of this test are also presented in the paper.
Ambiguity-Driven Fuzzy C-Means Clustering: How to Detect Uncertain Clustered Records
Venue: arXiv cs.AI 2014
Year: 2014

As a well-known clustering algorithm, Fuzzy C-Means (FCM) allows each input sample to belong to more than one cluster, providing more flexibility than non-fuzzy clustering methods. However, the accuracy of FCM is subject to false detections caused by noisy records, weak feature selection and low certainty of the algorithm in some cases. The false detections are very important in some decision-making application domains like network security and medical diagnosis, where weak decisions based on such false detections may lead to catastrophic outcomes. They are mainly emerged from making decisions about a subset of records that do not provide enough evidence to make a good decision. In this paper, we propose a method for detecting such ambiguous records in FCM by introducing a certainty factor to decrease invalid detections. This approach enables us to send the detected ambiguous records to another discrimination method for a deeper investigation, thus increasing the accuracy by lowering the error rate. Most of the records are still processed quickly and with low error rate which prevents performance loss compared to similar hybrid methods. Experimental results of applying the proposed method on several datasets from different domains show a significant decrease in error rate as well as improved sensitivity of the algorithm.
Non-Convex Boosting Overcomes Random Label Noise
Venue: arXiv cs.LG 2014
Year: 2014

The sensitivity of Adaboost to random label noise is a well-studied problem. LogitBoost, BrownBoost and RobustBoost are boosting algorithms claimed to be less sensitive to noise than AdaBoost. We present the results of experiments evaluating these algorithms on both synthetic and real datasets. We compare the performance on each of datasets when the labels are corrupted by different levels of independent label noise. In presence of random label noise, we found that BrownBoost and RobustBoost perform significantly better than AdaBoost and LogitBoost, while the difference between each pair of algorithms is insignificant. We provide an explanation for the difference based on the margin distributions of the algorithms.
From Small Space to Small Width in Resolution
Venue: arXiv cs.CC 2014
Year: 2014

In 2003, Atserias and Dalmau resolved a major open question about the resolution proof system by establishing that the space complexity of CNF formulas is always an upper bound on the width needed to refute them. Their proof is beautiful but somewhat mysterious in that it relies heavily on tools from finite model theory. We give an alternative, completely elementary proof that works by simple syntactic manipulations of resolution refutations. As a by-product, we develop a "black-box" technique for proving space lower bounds via a "static" complexity measure that works against any resolution refutation---previous techniques have been inherently adaptive. We conclude by showing that the related question for polynomial calculus (i.e., whether space is an upper bound on degree) seems unlikely to be resolvable by similar methods.
The Conceptual Idea of Online Social Media Site (SMS) User Account Penetration Testing System
Venue: arXiv cs.SI 2014
Year: 2014

Social Media Site (SMS) usage has grown rapidly in the last few years. This sudden increase in SMS usage creates an opportunity for data leakage which could compromise personal and/or professional life. In this work, we have reviewed traditional penetration testing process and discussed the failures of traditional penetration testing process to test the 'People' layer of Simple Enterprise Security Architecture (SESA) model. In order to overcome these failures, we have developed the conceptual idea of online SMS user account penetration testing system that could be applied to online SMS user account and the user account could be categorised based on the rating points. This could help us to avoid leaking information that is sensitive and/or damage their reputation. Finally, we have also listed the best practice guidelines of online SMS usage.
Slepian-Wolf Coding for Broadcasting with Cooperative Base-Stations
Venue: arXiv cs.IT 2014
Year: 2014

We propose a base-station (BS) cooperation model for broadcasting a discrete memoryless source in a cellular or heterogeneous network. The model allows the receivers to use helper BSs to improve network performance, and it permits the receivers to have prior side information about the source. We establish the model's information-theoretic limits in two operational modes: In Mode 1, the helper BSs are given information about the channel codeword transmitted by the main BS, and in Mode 2 they are provided correlated side information about the source. Optimal codes for Mode 1 use \emph{hash-and-forward coding} at the helper BSs; while, in Mode 2, optimal codes use source codes from Wyner's \emph{helper source-coding problem} at the helper BSs. We prove the optimality of both approaches by way of a new list-decoding generalisation of [8, Thm. 6], and, in doing so, show an operational duality between Modes 1 and 2.
An improved genetic algorithm with a local optimization strategy and an extra mutation level for solving traveling salesman problem
Venue: arXiv cs.NE 2014
Year: 2014

The Traveling salesman problem (TSP) is proved to be NP-complete in most cases. The genetic algorithm (GA) is one of the most useful algorithms for solving this problem. In this paper a conventional GA is compared with an improved hybrid GA in solving TSP. The improved or hybrid GA consist of conventional GA and two local optimization strategies. The first strategy is extracting all sequential groups including four cities of samples and changing the two central cities with each other. The second local optimization strategy is similar to an extra mutation process. In this step with a low probability a sample is selected. In this sample two random cities are defined and the path between these cities is reversed. The computation results show that the proposed method also finds better paths than the conventional GA within an acceptable computation time.
Strategies for Utility Maximization in Social Groups with Preferential Exploration
Venue: arXiv cs.GT 2014
Year: 2014

We consider a \emph{Social Group} of networked nodes, seeking a "universe" of segments for maximization of their utility. Each node has a subset of the universe, and access to an expensive link for downloading data. Nodes can also acquire the universe by exchanging copies of segments among themselves, at low cost, using inter-node links. While exchanges over inter-node links ensure minimum or negligible cost, some nodes in the group try to exploit the system. We term such nodes as `non-reciprocating nodes' and prohibit such behavior by proposing the "Give-and-Take" criterion, where exchange is allowed iff each participating node has segments unavailable with the other. Following this criterion for inter-node links, each node wants to maximize its utility, which depends on the node's segment set available with the node. Link activation among nodes requires mutual consent of participating nodes. Each node tries to find a pairing partner by preferentially exploring nodes for link formation and unpaired nodes choose to download a segment using the expensive link with segment aggressive probability. We present various linear complexity decentralized algorithms based on \emph{Stable Roommates Problem} that can be used by nodes (as per their behavioral nature) for choosing the best strategy based on available information. Then, we present decentralized randomized algorithm that performs close to optimal for large number of nodes. We define \emph{Price of Choices} for benchmarking performance for social groups (consisting of non-aggressive nodes only). We evaluate performances of various algorithms and characterize the behavioral regime that will yield best results for node and social group, spending the minimal on expensive link. We consider social group consisting of non-aggressive nodes and benchmark performances of proposed algorithms with the optimal.
Efficient Soft-Input Soft-Output MIMO Chase Detectors for arbitrary number of streams
Venue: arXiv cs.IT 2014
Year: 2014

We present novel soft-input soft-output (SISO) multiple-input multiple-output (MIMO) detectors based on the Chase detection principle [1] in the context of iterative and decoding (IDD). The proposed detector complexity is linear in the signal modulation constellation size and the number of spatial streams. Two variants of the SISO detector are developed, referred to as SISO B-Chase and SISO L-Chase. An efficient method is presented that uses the decoder output to modulate the signal constellation decision boundaries inside the detector leading to the SISO detector architecture. The performance of these detectors significantly improves with just a few number of IDD iterations. The effect of transmit and receive antenna correlation is simulated. For the high-correlation case, the superiority of SISO B-Chase over the SISO L-Chase is demonstrated.
Infinitary Classical Logic: Recursive Equations and Interactive Semantics
Venue: arXiv cs.LO 2014
Year: 2014

In this paper, we present an interactive semantics for derivations in an infinitary extension of classical logic. The formulas of our language are possibly infinitary trees labeled by propositional variables and logical connectives. We show that in our setting every recursive formula equation has a unique solution. As for derivations, we use an infinitary variant of Tait-calculus to derive sequents. The interactive semantics for derivations that we introduce in this article is presented as a debate (interaction tree) between a test << T >> (derivation candidate, Proponent) and an environment << not S >> (negation of a sequent, Opponent). We show a completeness theorem for derivations that we call interactive completeness theorem: the interaction between << T >> (test) and << not S >> (environment) does not produce errors (i.e., Proponent wins) just in case << T >> comes from a syntactical derivation of << S >>.
Heavy Traffic Limits for GI/H/n Queues: Theory and Application
Venue: arXiv cs.PF 2014
Year: 2014

We consider a GI/H/n queueing system. In this system, there are multiple servers in the queue. The inter-arrival time is general and independent, and the service time follows hyper-exponential distribution. Instead of stochastic differential equations, we propose two heavy traffic limits for this system, which can be easily applied in practical systems. In applications, we show how to use these heavy traffic limits to design a power efficient cloud computing environment based on different QoS requirements.
DeepID-Net: multi-stage and deformable deep convolutional neural networks for object detection
Venue: arXiv cs.CV 2014
Year: 2014

In this paper, we propose multi-stage and deformable deep convolutional neural networks for object detection. This new deep learning object detection diagram has innovations in multiple aspects. In the proposed new deep architecture, a new deformation constrained pooling (def-pooling) layer models the deformation of object parts with geometric constraint and penalty. With the proposed multi-stage training strategy, multiple classifiers are jointly optimized to process samples at different difficulty levels. A new pre-training strategy is proposed to learn feature representations more suitable for the object detection task and with good generalization capability. By changing the net structures, training strategies, adding and removing some key components in the detection pipeline, a set of models with large diversity are obtained, which significantly improves the effectiveness of modeling averaging. The proposed approach ranked \#2 in ILSVRC 2014. It improves the mean averaged precision obtained by RCNN, which is the state-of-the-art of object detection, from $31\%$ to $45\%$. Detailed component-wise analysis is also provided through extensive experimental evaluation.