OpenRaiser/Intern-Atlas huggingface dataset:
How Advanced Change Patterns Impact the Process of Process Modeling
Venue: arXiv cs.SE 2015
Year: 2015

Process model quality has been an area of considerable research efforts. In this context, correctness-by-construction as enabled by change patterns provides promising perspectives. While the process of process modeling (PPM) based on change primitives has been thoroughly investigated, only little is known about the PPM based on change patterns. In particular, it is unclear what set of change patterns should be provided and how the available change pattern set impacts the PPM. To obtain a better understanding of the latter as well as the (subjective) perceptions of process modelers, the arising challenges, and the pros and cons of different change pattern sets we conduct a controlled experiment. Our results indicate that process modelers face similar challenges irrespective of the used change pattern set (core pattern set versus extended pattern set, which adds two advanced change patterns to the core patterns set). An extended change pattern set, however, is perceived as more difficult to use, yielding a higher mental effort. Moreover, our results indicate that more advanced patterns were only used to a limited extent and frequently applied incorrectly, thus, lowering the potential benefits of an extended pattern set.
Deep Gaussian Conditional Random Field Network: A Model-based Deep Network for Discriminative Denoising
Venue: arXiv cs.CV 2015
Year: 2015

We propose a novel deep network architecture for image\\ denoising based on a Gaussian Conditional Random Field (GCRF) model. In contrast to the existing discriminative denoising methods that train a separate model for each noise level, the proposed deep network explicitly models the input noise variance and hence is capable of handling a range of noise levels. Our deep network, which we refer to as deep GCRF network, consists of two sub-networks: (i) a parameter generation network that generates the pairwise potential parameters based on the noisy input image, and (ii) an inference network whose layers perform the computations involved in an iterative GCRF inference procedure.\ We train the entire deep GCRF network (both parameter generation and inference networks) discriminatively in an end-to-end fashion by maximizing the peak signal-to-noise ratio measure. Experiments on Berkeley segmentation and PASCALVOC datasets show that the proposed deep GCRF network outperforms state-of-the-art image denoising approaches for several noise levels.
A Continuous-time Mutually-Exciting Point Process Framework for Prioritizing Events in Social Media
Venue: arXiv cs.SI 2015
Year: 2015

The overwhelming amount and rate of information update in online social media is making it increasingly difficult for users to allocate their attention to their topics of interest, thus there is a strong need for prioritizing news feeds. The attractiveness of a post to a user depends on many complex contextual and temporal features of the post. For instance, the contents of the post, the responsiveness of a third user, and the age of the post may all have impact. So far, these static and dynamic features has not been incorporated in a unified framework to tackle the post prioritization problem. In this paper, we propose a novel approach for prioritizing posts based on a feature modulated multi-dimensional point process. Our model is able to simultaneously capture textual and sentiment features, and temporal features such as self-excitation, mutual-excitation and bursty nature of social interaction. As an evaluation, we also curated a real-world conversational benchmark dataset crawled from Facebook. In our experiments, we demonstrate that our algorithm is able to achieve the-state-of-the-art performance in terms of analyzing, predicting, and prioritizing events. In terms of interpretability of our method, we observe that features indicating individual user profile and linguistic characteristics of the events work best for prediction and prioritization of new events.
On the Control of Self-Balancing Unicycles
Venue: arXiv cs.SY 2015
Year: 2015

This paper discusses the problem of designing a self-balancing unicycle where pedals are used for both power generation and speed control. After developing the principal physical aspects (in the longitudinal dimension), we describe an abstract model in the form of a collection of hybrid automata, together with design requirements to be met by an ideal controller. We discuss simplifications and assumptions that make this model amenable to verification and validation tools such as SpaceEx. To enable experimentation with different prototypical controllers and user behaviours in concrete scenarios, we also develop a simple simulation framework using digital time.
Timed Automata for Modelling Caches and Pipelines
Venue: arXiv cs.FL 2015
Year: 2015

In this paper, we focus on modelling the timing aspects of binary programs running on architectures featuring caches and pipelines. The objective is to obtain a timed automaton model to compute tight bounds for the worst-case execution time (WCET) of the programs using model-checking techniques.
Proof Outlines as Proof Certificates: A System Description
Venue: arXiv cs.LO 2015
Year: 2015

We apply the foundational proof certificate (FPC) framework to the problem of designing high-level outlines of proofs. The FPC framework provides a means to formally define and check a wide range of proof evidence. A focused proof system is central to this framework and such a proof system provides an interesting approach to proof reconstruction during the process of proof checking (relying on an underlying logic programming implementation). Here, we illustrate how the FPC framework can be used to design proof outlines and then to exploit proof checkers as a means for expanding outlines into fully detailed proofs. In order to validate this approach to proof outlines, we have built the ACheck system that allows us to take a sequence of theorems and apply the proof outline "do the obvious induction and close the proof using previously proved lemmas".
An Index for SSRN Downloads
Venue: arXiv cs.DL 2015
Year: 2015

We propose a new index to quantify SSRN downloads. Unlike the SSRN downloads rank, which is based on the total number of an author's SSRN downloads, our index also reflects the author's productivity by taking into account the download numbers for the papers. Our index is inspired by - but is not the same as - Hirsch's h-index for citations, which cannot be directly applied to SSRN downloads. We analyze data for about 30,000 authors and 367,000 papers. We find a simple empirical formula for the SSRN author rank via a Gaussian function of the log of the number of downloads.
HackAttack: Game-Theoretic Analysis of Realistic Cyber Conflicts
Venue: arXiv cs.CR 2015
Year: 2015

Game theory is appropriate for studying cyber conflict because it allows for an intelligent and goal-driven adversary. Applications of game theory have led to a number of results regarding optimal attack and defense strategies. However, the overwhelming majority of applications explore overly simplistic games, often ones in which each participant's actions are visible to every other participant. These simplifications strip away the fundamental properties of real cyber conflicts: probabilistic alerting, hidden actions, unknown opponent capabilities. In this paper, we demonstrate that it is possible to analyze a more realistic game, one in which different resources have different weaknesses, players have different exploits, and moves occur in secrecy, but they can be detected. Certainly, more advanced and complex games are possible, but the game presented here is more realistic than any other game we know of in the scientific literature. While optimal strategies can be found for simpler games using calculus, case-by-case analysis, or, for stochastic games, Q-learning, our more complex game is more naturally analyzed using the same methods used to study other complex games, such as checkers and chess. We define a simple evaluation function and ploy multi-step searches to create strategies. We show that such scenarios can be analyzed, and find that in cases of extreme uncertainty, it is often better to ignore one's opponent's possible moves. Furthermore, we show that a simple evaluation function in a complex game can lead to interesting and nuanced strategies.
Influence of Personality Types in Software Tasks Choices
Venue: arXiv cs.CY 2015
Year: 2015

According to psychology, not everybody can excel at all kinds of tasks. Thus, chances of a successful outcome of software development increase if people with particular personality types are assigned to their preferred tasks in the project. Likewise, software development depends significantly on how software practitioners perform their tasks. This empirical study surveys 100 Cuban software developers, who also teach or study at the University of Informatics Sciences in Havana, Cuba. This work aims to find possible patterns that link personality types to role preferences in a software life cycle. Among the various roles, system analyst, software designer, and programmer are found to be the most preferred among the participants. In contrast, software tester and software maintainer happen to be the least popular roles among software engineers.
Detection of multiple and overlapping bidirectional communities within large, directed and weighted networks of neurons
Venue: arXiv cs.SI 2015
Year: 2015

With the recent explosion of publicly available biological data, the analysis of networks has gained significant interest. In particular, recent promising results in Neuroscience show that the way neurons and areas of the brain are connected to each other plays a fundamental role in cognitive functions and behaviour. Revealing pattern and structures within such an intricate volume of connections is a hard problem that has its roots in Graph and Network Theory. Since many real world situations can be modelled through networks, structures detection algorithms find application in almost every field of Science. These are NP-complete problems; therefore the generally used approach is through heuristic algorithms. Here, we formulate the problem of finding structures in networks of neurons in terms of a community detection problem. We introduce a definition of community and we construct a statistics-based heuristic algorithm for directed and weighted networks aiming at identifying overlapping bidirectional communities in large networks. We carry out a systematic analysis of the algorithm's performance, showing excellent results over a wide range of parameters (successful detection percentages almost $100\%$ all the time). Also, we show results on the computational time needed and we suggest future directions on how to improve computational performance.
Coefficient of Restitution based Cross Layer Interference Aware Routing Protocol in Wireless Mesh Networks
Venue: arXiv cs.NI 2015
Year: 2015

In Multi-Radio Multi-Channel (MRMC) Wireless Mesh Networks (WMN), Partially Overlapped Channels (POC) has been used to increase the parallel transmission. But adjacent channel interference is very severe in MRMC environment; it decreases the network throughput very badly. In this paper, we propose a Coefficient of Restitution based Cross layer Interference aware Routing protocol (CoRCiaR) to improve TCP performance in Wireless Mesh Networks. This approach comprises of two-steps: Initially, the interference detection algorithm is developed at MAC layer by enhancing the RTS/CTS method. Based on the channel interference, congestion is identified by Round Trip Time (RTT) measurements, and subsequently the route discovery module selects the alternative path to send the data packet. The packets are transmitted to the congestion free path seamlessly by the source. The performance of the proposed CoRCiaR protocol is measured by Coefficient of Restitution (COR) parameter. The impact of the rerouting is experienced on the network throughput performance. The simulation results show that the proposed cross layer interference aware dynamic routing enhances the TCP performance on WMN. Keywords: Coefficient of Restitution, Wireless Mesh Networks, Partially Overlapped Channels, Round Trip Time, Multi-Radio, Multi-Channel.
Four-dimensional signalling schemes - Application to satellite communications
Venue: arXiv cs.IT 2015
Year: 2015

In satellite communications both polarizations of an electromagnetic wave are used to transmit two separate signals. These two independent signals can be merged to form one dual-polarization, four-dimensional signal. The present article pursues this idea and proposes different signal constellations to be used for four-dimensional signalling in satellite links. Analytical methods and simulations predict an increased power efficiency of these constellations with respect to currently used transmission methods. The cost of this advantage is evaluated considering the limited applicability in non-linear channels. Four-dimensional signalling also implies simultaneous reception on both polarizations. Such a combined reception allows the precision of timing and carrier recovery loops to be doubled. This claim is derived analytically and illustrated by simulating an example case. An experimental transmitter/receiver pair was implemented and used to demonstrate a satellite transmission using a four-dimensional, bi-orthogonal signal in the dual-polarization channel. The experimental verification confirms the presented simulation results.
Compressive Sensing of Sparse Signals in the Hermite Transform Basis: Analysis and Algorithm for Signal Reconstruction
Venue: arXiv cs.IT 2015
Year: 2015

An analysis of the influence of missing samples in signals exhibiting sparsity in the Hermite transform domain is provided. Based on the statistical properties derived for the Hermite coefficients of randomly undersampled signal, the probability of success in detection of signal components support is determined. Based on the probabilistic analysis, a threshold for the detection of signal components is provided. It is a crucial step in the definition of a simple non-iterative algorithm for compressive sensing signal reconstruction. The derived theoretical concepts are proved on several examples using different statistical tests.
Uncovering Temporal Context for Video Question and Answering
Venue: arXiv cs.CV 2015
Year: 2015

In this work, we introduce Video Question Answering in temporal domain to infer the past, describe the present and predict the future. We present an encoder-decoder approach using Recurrent Neural Networks to learn temporal structures of videos and introduce a dual-channel ranking loss to answer multiple-choice questions. We explore approaches for finer understanding of video content using question form of "fill-in-the-blank", and managed to collect 109,895 video clips with duration over 1,000 hours from TACoS, MPII-MD, MEDTest 14 datasets, while the corresponding 390,744 questions are generated from annotations. Extensive experiments demonstrate that our approach significantly outperforms the compared baselines.
Applying Semantic Web Technologies for Improving the Visibility of Tourism Data
Venue: arXiv cs.IR 2015
Year: 2015

Tourism industry is an extremely information-intensive, complex and dynamic activity. It can benefit from semantic Web technologies, due to the significant heterogeneity of information sources and the high volume of on-line data. The management of semantically diverse annotated tourism data is facilitated by ontologies that provide methods and standards, which allow flexibility and more intelligent access to on-line data. This paper provides a description of some of the early results of the Tourinflux project which aims to apply semantic Web technologies to support tourist actors in effectively finding and publishing information on the Web.
Power Distribution of Device-to-Device Communications in Underlaid Cellular Networks
Venue: arXiv cs.NI 2015
Year: 2015

Device-to-device (D2D) communications have recently emerged as a novel transmission paradigm in wireless cellular networks. D2D transmissions take place concurrently with the usual cellular connections, and thus, controlling the interference brought to the macro-cellular user equipment (UE) is of vital importance. In this paper, we consider the uplink transmission of a tier of D2D users that operates as an underlay for the traditional cellular network. Using network model based on stochastic geometry, we derive the equilibrium cumulative distribution function (CDF) of the D2D transmit power. Considering interference-limited and relatively lossy environment cases, closed form equations are derived for the power CDF. Finally, a tight closed-form upper-bound for the derived power distribution is proposed, and the analytical results are validated via simulation.
Evaluation of Channel Assignment Performance Prediction Techniques in Random Wireless Mesh Networks
Venue: arXiv cs.NI 2015
Year: 2015

Performance of wireless mesh networks (WMNs) in terms of network capacity, end-to-end latency, and network resilience depends upon the prevalent levels of interference. Thus, interference alleviation is a fundamental design concern in multi-radio multi-channel (MRMC) WMNs, and is achieved through a judicious channel assignment (CA) to the radios in a WMN. In our earlier works we have tried to address the problem of estimating the intensity of interference in a wireless network and predicting the performance of CA schemes based on the measure of the interference estimate. We have proposed reliable CA performance prediction approaches which have proven effective in grid WMNs. In this work, we further assess the reliability of these CA performance prediction techniques in a large MRMC WMN which comprises of randomly placed mesh routers. We perform exhaustive simulations on an ns-3 802.11n environment. We obtain conclusive results to demonstrate the efficacy of proposed schemes in random WMNs as well.
Graph Theory Applications in Network Security
Venue: arXiv cs.CR 2015
Year: 2015

Graph theory has become a very critical component in many applications in the computing field including networking and security. Unfortunately, it is also amongst the most complex topics to understand and apply. In this paper, we review some of the key applications of graph theory in network security. We first cover some algorithmic aspects, then present network coding and its relation to routing.
Hadoop Mapreduce Performance Enhancement Using In-node Combiners
Venue: arXiv cs.DC 2015
Year: 2015

While advanced analysis of large dataset is in high demand, data sizes have surpassed capabilities of conventional software and hardware. Hadoop framework distributes large datasets over multiple commodity servers and performs parallel computations. We discuss the I/O bottlenecks of Hadoop framework and propose methods for enhancing I/O performance. A proven approach is to cache data to maximize memory-locality of all map tasks. We introduce an approach to optimize I/O, the in-node combining design which extends the traditional combiner to a node level. The in-node combiner reduces the total number of intermediate results and curtail network traffic between mappers and reducers.
Coarse-to-fine Face Alignment with Multi-Scale Local Patch Regression
Venue: arXiv cs.CV 2015
Year: 2015

Facial landmark localization plays an important role in face recognition and analysis applications. In this paper, we give a brief introduction to a coarse-to-fine pipeline with neural networks and sequential regression. First, a global convolutional network is applied to the holistic facial image to give an initial landmark prediction. A pyramid of multi-scale local image patches is then cropped to feed to a new network for each landmark to refine the prediction. As the refinement network outputs a more accurate position estimation than the input, such procedure could be repeated several times until the estimation converges. We evaluate our system on the 300-W dataset [11] and it outperforms the recent state-of-the-arts.
Joining Transition Systems of Records: Some Congruency and Language-Theoretic Results
Venue: arXiv cs.FL 2015
Year: 2015

Büchi automaton of records (BAR) has been proposed as a basic operational semantics for Reo coordination language. It is an extension of Büchi automaton by using a set of records as its alphabet or transition labels. Records are used to express the synchrony between the externally visible actions of coordinated components modeled by BARs. The main composition operator on the set of BARs is called as join which is the semantics of its counterpart in Reo. In this paper, we define the notion of labeled transition systems of records as a generalization of the notion of BAR, abstracting away from acceptance or rejection of strings. Then, we consider four equivalence relations (semantics) over the set of labeled transition systems of records and investigate their congruency with respect to the join composition operator. In fact, we prove that the finite-traces-based, infinite-traces-based, and nondeterministic finite automata (NFA)-based equivalence relations all are congruence relations over the set of all labeled transition systems of records with respect to the join operation. However, the equivalence relation using Büchi acceptance condition is not so. In addition, using these results, we introduce the language-theoretic definitions of the join operation considering both finite and infinite strings notions. Also, we show that there is no language-based and structure-independent definition of the join operation on Büchi automata of records.
On the Weakness of Fully Homomorphic Encryption
Venue: arXiv cs.CR 2015
Year: 2015

Fully homomorphic encryption (FHE) allows anyone to perform computations on encrypted data, despite not having the secret decryption key. Since the Gentry's work in 2009, the primitive has interested many researchers. In this paper, we stress that any computations performed on encrypted data are constrained to the encrypted domain (finite fields or rings). This restriction makes the primitive useless for most computations involving common arithmetic expressions and relational expressions. It is only applicable to the computations related to modular arithmetic. We want to reaffirm that cryptography uses modular arithmetic a lot in order to obscure and dissipate the redundancies in a plaintext message, not to perform any numerical calculations. We think it might be an overstated claim that FHE is of great importance to client-server computing or cloud computing.
Behavioral Compatibility of Simulink Models for Product Line Maintenance and Evolution
Venue: arXiv cs.SE 2015
Year: 2015

Embedded software systems, e.g. automotive, robotic or automation systems are highly configurable and consist of many software components being available in different variants and versions. To identify the degree of reusability between these different occurrences of a component, it is necessary to determine the functional backward and forward compatibility between them. Based on this information it is possible to identify in which system context a component can be replaced safely by another version, e.g. exchanging an older component, or variant, e.g. introducing new features, to achieve the same functionality. This paper presents a model checking approach to determine behavioral compatibility of Simulink models, obtained from different component variants or during evolution. A prototype for automated compatibility checking demonstrates its feasibility. In addition implemented optimizations make the analysis more efficient, when the compared variants or versions are structurally similar. A case study on a driver assistance system provided by Daimler AG shows the effectiveness of the approach to automatically compare Simulink components.