OpenRaiser/Intern-Atlas huggingface dataset:
A Systematic Review of Uncertainties in Software Project Management
Venue: arXiv cs.SE 2014
Year: 2014

It is no secret that many projects fail, regardless of the business sector, software projects are notoriously disaster victims, not necessarily because of technological failure, but more often due to their uncertainties. The threats identified by uncertainty in day-to-day of a project are real and immediate and the stakes in a project are often high. This paper presents a systematic review about software project management uncertainties. It helps to identify the difficulties and the actions that can minimize the uncertainties effects in the projects and how managers and teams can prepare themselves for the challenges of their projects scenario, with the aim of contributing to the improvement of project management in organizations as well as contributing to project success.
Feature Weight Tuning for Recursive Neural Networks
Venue: arXiv cs.NE 2014
Year: 2014

This paper addresses how a recursive neural network model can automatically leave out useless information and emphasize important evidence, in other words, to perform "weight tuning" for higher-level representation acquisition. We propose two models, Weighted Neural Network (WNN) and Binary-Expectation Neural Network (BENN), which automatically control how much one specific unit contributes to the higher-level representation. The proposed model can be viewed as incorporating a more powerful compositional function for embedding acquisition in recursive neural networks. Experimental results demonstrate the significant improvement over standard neural models.
Size sensitive packing number for Hamming cube and its consequences
Venue: arXiv cs.DM 2014
Year: 2014

We prove a size-sensitive version of Haussler's Packing lemma~\cite{Haussler92spherepacking} for set-systems with bounded primal shatter dimension, which have an additional {\em size-sensitive property}. This answers a question asked by Ezra~\cite{Ezra-sizesendisc-soda-14}. We also partially address another point raised by Ezra regarding overcounting of sets in her chaining procedure. As a consequence of these improvements, we get an improvement on the size-sensitive discrepancy bounds for set systems with the above property. Improved bounds on the discrepancy for these special set systems also imply an improvement in the sizes of {\em relative $(\varepsilon, δ)$-approximations} and $(ν, α)$-samples.
The OCDF diagram. A metamodel for object-oriented systems visual design
Venue: arXiv cs.SE 2014
Year: 2014

We present a metamodel for modeling control and data flows on subclass scales in object-oriented systems. UML Profiles were used as a representation mean and a complete metamodel definition was provided with an example of a diagram application.
An Experimental Evaluation of Machine-to-Machine Coordination Middleware: Extended Version
Venue: arXiv cs.DC 2014
Year: 2014

The vision of the Internet-of-Things (IoT) embodies the seam- less discovery, configuration, and interoperability of networked devices in various settings, ranging from home automation and multimedia to autonomous vehicles and manufacturing equipment. As these ap- plications become increasingly critical, the middleware coping with Machine-to-Machine (M2M) communication and coordination has to deal with fault tolerance and increasing complexity, while still abiding to resource constraints of target devices. In this report, we focus on configuration management and coordi- nation of services in a M2M scenario. On one hand, we consider Zoo- Keeper, originally developed for cloud data centers, offering a simple file-system abstraction, and embodying replication for fault-tolerance and scalability based on a consensus protocol. On the other hand, we consider the Devices Profile for Web Services (DPWS) stack with replicated services based on our implementation of the Raft consensus protocol. We show that the latter offers adequate performance for the targeted applications while providing increasing flexibility.
The application of the Bayes Ying Yang harmony based GMMs in on-line signature verification
Venue: arXiv cs.CV 2014
Year: 2014

In this contribution, a Bayes Ying Yang(BYY) harmony based approach for on-line signature verification is presented. In the proposed method, a simple but effective Gaussian Mixture Models(GMMs) is used to represent for each user's signature model based on the prior information collected. Different from the early works, in this paper, we use the Bayes Ying Yang machine combined with the harmony function to achieve Automatic Model Selection(AMS) during the parameter learning for the GMMs, so that a better approximation of the user model is assured. Experiments on a database from the First International Signature Verification Competition(SVC 2004) confirm that this combined algorithm yields quite satisfactory results.
Millimeter Wave MIMO Channel Tracking Systems
Venue: arXiv cs.IT 2014
Year: 2014

We consider channel/subspace tracking systems for temporally correlated millimeter wave (e.g., E-band) multiple-input multiple-output (MIMO) channels. Our focus is given to the tracking algorithm in the non-line-of-sight (NLoS) environment, where the transmitter and the receiver are equipped with hybrid analog/digital precoder and combiner, respectively. In the absence of straightforward time-correlated channel model in the millimeter wave MIMO literature, we present a temporal MIMO channel evolution model for NLoS millimeter wave scenarios. Considering that conventional MIMO channel tracking algorithms in microwave bands are not directly applicable, we propose a new channel tracking technique based on sequentially updating the precoder and combiner. Numerical results demonstrate the superior channel tracking ability of the proposed technique over independent sounding approach in the presented channel model and the spatial channel model (SCM) adopted in 3GPP specification.
Reachability in Two-Dimensional Vector Addition Systems with States is PSPACE-complete
Venue: arXiv cs.FL 2014
Year: 2014

Determining the complexity of the reachability problem for vector addition systems with states (VASS) is a long-standing open problem in computer science. Long known to be decidable, the problem to this day lacks any complexity upper bound whatsoever. In this paper, reachability for two-dimensional VASS is shown PSPACE-complete. This improves on a previously known doubly exponential time bound established by Howell, Rosier, Huynh and Yen in 1986. The coverability and boundedness problems are also noted to be PSPACE-complete. In addition, some complexity results are given for the reachability problem in two-dimensional VASS and in integer VASS when numbers are encoded in unary.
Spectral Anomaly Detection in Very Large Graphs: Models, Noise, and Computational Complexity
Venue: arXiv cs.SI 2014
Year: 2014

Anomaly detection in massive networks has numerous theoretical and computational challenges, especially as the behavior to be detected becomes small in comparison to the larger network. This presentation focuses on recent results in three key technical areas, specifically geared toward spectral methods for detection. We first discuss recent models for network behavior, and how their structure can be exploited for efficient computation of the principal eigenspace of the graph. In addition to the stochasticity of background activity, a graph of interest may be observed through a noisy or imperfect mechanism, which may hinder the detection process. A few simple noise models are discussed, and we demonstrate the ability to fuse multiple corrupted observations and recover detection performance. Finally, we discuss the challenges in scaling the spectral algorithms to large-scale high-performance computing systems, and present preliminary recommendations to achieve good performance with current parallel eigensolvers.
Asymptotics and Non-asymptotics for Universal Fixed-to-Variable Source Coding
Venue: arXiv cs.IT 2014
Year: 2014

Universal fixed-to-variable lossless source coding for memoryless sources is studied in the finite blocklength and higher-order asymptotics regimes. Optimal third-order coding rates are derived for general fixed-to-variable codes and for prefix codes. It is shown that the non-prefix Type Size code, in which codeword lengths are chosen in ascending order of type class size, achieves the optimal third-order rate and outperforms classical Two-Stage codes. Converse results are proved making use of a result on the distribution of the empirical entropy and Laplace's approximation. Finally, the fixed-to-variable coding problem without a prefix constraint is shown to be essentially the same as the universal guessing problem.
Generating Graphical Chain by Mutual Matching of Bayesian Network and Extracted Rules of Bayesian Network Using Genetic Algorithm
Venue: arXiv cs.AI 2014
Year: 2014

With the technology development, the need of analyze and extraction of useful information is increasing. Bayesian networks contain knowledge from data and experts that could be used for decision making processes But they are not easily understandable thus the rule extraction methods have been used but they have high computation costs. To overcome this problem we extract rules from Bayesian network using genetic algorithm. Then we generate the graphical chain by mutually matching the extracted rules and Bayesian network. This graphical chain could shows the sequence of events that lead to the target which could help the decision making process. The experimental results on small networks show that the proposed method has comparable results with brute force method which has a significantly higher computation cost.
Modeling Hybrid Systems in Hy-tccp
Venue: arXiv cs.PL 2014
Year: 2014

Concurrent,reactive and hybrid systems require quality modeling languages to be described and analyzed. The Timed Concurrent Constraint Language (tccp) was introduced as a simple but powerful model for reactive systems. In this paper, we present hybrid tccp (hy-tccp), an extension of tccp over continuous time which includes new con- structs to model the continuous dynamics of hybrid systems.
Kadupul: Livin' on the Edge with Virtual Currencies and Time-Locked Puzzles
Venue: arXiv cs.NI 2014
Year: 2014

Devices connected to the Internet today have a wide range of local communication channels available, such as wireless Wifi, Bluetooth or NFC, as well as wired backhaul. In densely populated areas it is possible to create heterogeneous, multihop communication paths using a combination of these technologies, and often transmit data with lower latency than via a wired Internet connection. However, the potential for sharing meshed wireless radios in this way has never been realised due to the lack of economic incentives to do so on the part of individual nodes. In this paper, we explore how virtual currencies such as Bitcoin might be used to provide an end-to-end incentive scheme to convince forwarding nodes that it is profitable to send packets on via the lowest latency mechanism available. Clients inject a small amount of money to transmit a datagram, and forwarding engines compete to solve a time-locked puzzle that can be claimed by the node that delivers the result in the lowest latency. This approach naturally extends congestion control techniques to a surge pricing model when available bandwidth is low. We conclude by discussing several latency-sensitive applications that would benefit for this, such as video streaming and local augmented reality systems.
Variable Selection is Hard
Venue: arXiv cs.CC 2014
Year: 2014

Variable selection for sparse linear regression is the problem of finding, given an m x p matrix B and a target vector y, a sparse vector x such that Bx approximately equals y. Assuming a standard complexity hypothesis, we show that no polynomial-time algorithm can find a k'-sparse x with ||Bx-y||^2<=h(m,p), where k'=k*2^{log^{1-delta} p} and h(m,p)<=p^(C_1)*m^(1-C_2), where delta>0, C_1>0,C_2>0 are arbitrary. This is true even under the promise that there is an unknown k-sparse vector x^* satisfying Bx^*=y. We prove a similar result for a statistical version of the problem in which the data are corrupted by noise. To the authors' knowledge, these are the first hardness results for sparse regression that apply when the algorithm simultaneously has k'>k and h(m,p)>0.
GPU accelerated Nature Inspired Methods for Modelling Large Scale Bi-Directional Pedestrian Movement
Venue: arXiv cs.DC 2014
Year: 2014

Pedestrian movement, although ubiquitous and well-studied, is still not that well understood due to the complicating nature of the embedded social dynamics. Interest among researchers in simulating pedestrian movement and interactions has grown significantly in part due to increased computational and visualization capabilities afforded by high power computing. Different approaches have been adopted to simulate pedestrian movement under various circumstances and interactions. In the present work, bi-directional crowd movement is simulated where an equal numbers of individuals try to reach the opposite sides of an environment. Two movement methods are considered. First a Least Effort Model (LEM) is investigated where agents try to take an optimal path with as minimal changes from their intended path as possible. Following this, a modified form of Ant Colony Optimization (ACO) is proposed, where individuals are guided by a goal of reaching the other side in a least effort mode as well as a pheromone trail left by predecessors. The basic idea is to increase agent interaction, thereby more closely reflecting a real world scenario. The methodology utilizes Graphics Processing Units (GPUs) for general purpose computing using the CUDA platform. Because of the inherent parallel properties associated with pedestrian movement such as proximate interactions of individuals on a 2D grid, GPUs are well suited. The main feature of the implementation undertaken here is that the parallelism is data driven. The data driven implementation leads to a speedup up to 18x compared to its sequential counterpart running on a single threaded CPU. The numbers of pedestrians considered in the model ranged from 2K to 100K representing numbers typical of mass gathering events. A detailed discussion addresses implementation challenges faced and averted.
Virtual Machine Migration Planning in Software-Defined Networks
Venue: arXiv cs.NI 2014
Year: 2014

In this paper, we examine the problem of how to schedule the migrations and how to allocate network resources for migration when multiple VMs need to be migrated at the same time. We consider the problem in the Software-defined Network (SDN) context since it provides flexible control on routing. More specifically, we propose a method that computes the optimal migration sequence and network bandwidth used for each migration. We formulate this problem as a mixed integer programming, which is NP-hard. To make it computationally feasible for large scale data centers, we propose an approximation scheme via linear approximation plus fully polynomial time approximation, and obtain its theoretical performance bound. Through extensive simulations, we demonstrate that our fully polynomial time approximation (FPTA) algorithm has a good performance compared with the optimal solution and two state of-the-art algorithms. That is, our proposed FPTA algorithm approaches to the optimal solution with less than 10% variation and much less computation time. Meanwhile, it reduces the total migration time and the service downtime by up to 40% and 20% compared with the state-of-the-art algorithms, respectively.
DDSAT: Distributed Dynamic Spectrum Access Protocol Implementation Using GNURadio and USRP
Venue: arXiv cs.NI 2014
Year: 2014

Frequency spectrum is one of the valuable resources in wireless communications. Using cognitive radio, spectrum efficiency will increase by making use of the spectrum holes. Dynamic Spectrum Access techniques allows secondary users to transmit on an empty channel not used by a primary user for a given time. In this paper, a Distributed Dynamic Spectrum Access based TDMA protocol (DDSAT) is designed and implemented on USRP. The proposed protocol performs two main functions: Spectrum Sensing, and Spectrum Management. Spectrum Sensing is performed to find spectrum holes in a co-operative manner using the contributing secondary users. Spectrum Management works distributively on the secondary users to allocate the spectrum holes in a fairly and efficient utilization. The DDSAT protocol is implemented using Software Defined Radio (SDR) and Universal Software Radio Peripheral (USRP). Evaluation and performance tests are conducted to show throughput and fairness of the system.
Belief as Willingness to Bet
Venue: arXiv cs.LO 2014
Year: 2014

We investigate modal logics of high probability having two unary modal operators: an operator $K$ expressing probabilistic certainty and an operator $B$ expressing probability exceeding a fixed rational threshold $c\geq\frac 12$. Identifying knowledge with the former and belief with the latter, we may think of $c$ as the agent's betting threshold, which leads to the motto "belief is willingness to bet." The logic $\mathsf{KB.5}$ for $c=\frac 12$ has an $\mathsf{S5}$ $K$ modality along with a sub-normal $B$ modality that extends the minimal modal logic $\mathsf{EMND45}$ by way of four schemes relating $K$ and $B$, one of which is a complex scheme arising out of a theorem due to Scott. Lenzen was the first to use Scott's theorem to show that a version of this logic is sound and complete for the probability interpretation. We reformulate Lenzen's results and present them here in a modern and accessible form. In addition, we introduce a new epistemic neighborhood semantics that will be more familiar to modern modal logicians. Using Scott's theorem, we provide the Lenzen-derivative properties that must be imposed on finite epistemic neighborhood models so as to guarantee the existence of a probability measure respecting the neighborhood function in the appropriate way for threshold $c=\frac 12$. This yields a link between probabilistic and modal neighborhood semantics that we hope will be of use in future work on modal logics of qualitative probability. We leave open the question of which properties must be imposed on finite epistemic neighborhood models so as to guarantee existence of an appropriate probability measure for thresholds $c\neq\frac 12$.
Multi-criteria neutrosophic decision making method based on score and accuracy functions under neutrosophic environment
Venue: arXiv cs.AI 2014
Year: 2014

A neutrosophic set is a more general platform, which can be used to present uncertainty, imprecise, incomplete and inconsistent. In this paper a score function and an accuracy function for single valued neutrosophic sets is firstly proposed to make the distinction between them. Then the idea is extended to interval neutrosophic sets. A multi-criteria decision making method based on the developed score-accuracy functions is established in which criterion values for alternatives are single valued neutrosophic sets and interval neutrosophic sets. In decision making process, the neutrosophic weighted aggregation operators (arithmetic and geometric average operators) are adopted to aggregate the neutrosophic information related to each alternative. Thus, we can rank all alternatives and make the selection of the best of one(s) according to the score-accuracy functions. Finally, some illustrative examples are presented to verify the developed approach and to demonstrate its practicality and effectiveness.
Are We Ready for Driver-less Vehicles? Security vs. Privacy- A Social Perspective
Venue: arXiv cs.CY 2014
Year: 2014

At this moment Autonomous cars are probably the biggest and most talked about technology in the Robotics Research Community. In spite of great technological advances over past few years a full edged autonomous car is still far from reality. This article talks about the existing system and discusses the possibility of a Computer Vision enabled driving being superior than the LiDar based system. A detailed overview of privacy violations that might arise from autonomous driving has been discussed in detail both from a technical as well as legal perspective. It has been proved through evidence and arguments that efficient and accurate estimation and efficient solution of the constraint satisfaction problem addressed in the case of autonomous cars are negatively correlated with the preserving the privacy of the user. It is a very difficult trade-off since both are very important aspects and has to be taken into account. The fact that one cannot compromise with the safety issues of the car makes it inevitable to run into serious privacy concerns that might have adverse social and political effects.
Robust MMSE Precoding for Multiuser MIMO Relay Systems using Switched Relaying and Side Information
Venue: arXiv cs.IT 2014
Year: 2014

This study proposes a novel precoding scheme for multiuser multiple-input multiple-output (MIMO) relay systems in the presence of imperfect channel state information (CSI). The base station (BS) and the MIMO relay station (RS) are both equipped with the same codebook of unitary matrices. According to each element of the codebook, we create a latent precoding matrix pair, namely a BS precoding matrix and an RS precoding matrix. The RS precoding matrix is formed by multiplying the appropriate unitary matrix from the codebook by a power scaling factor. Based on the given CSI and a block of transmit symbols, the optimum precoding matrix pair, within the class of all possible latent precoding matrix pairs derived from the various unitary matrices, is selected by a suitable selection mechanism for transmission, which is designed to minimize the squared Euclidean distance between the pre-estimated received vector and the true transmit symbol vector. We develop a minimum mean square error (MMSE) design algorithm for the construction of the latent precoding matrix pairs. In the proposed scheme, rather than sending the complete processing matrix, only the index of the unitary matrix and its power scaling factor are sent by the BS to the RS. This significantly reduces the overhead. Simulation results show that compared to other recently reported precoding algorithms the proposed precoding scheme is capable of providing improved robustness against the effects of CSI estimation errors and multiuser interference.
Directional Tensor Product Complex Tight Framelets with Low Redundancy
Venue: arXiv cs.IT 2014
Year: 2014

Though high redundancy rate of a tight frame can improve performance in applications, as the dimension increases, it also makes the computational cost skyrocket and the storage of frame coefficients increase exponentially. This seriously restricts the usefulness of such tight frames for problems in moderately high dimensions such as video processing in dimension three. Inspired by the directional tensor product complex tight framelets ${TP-CTF}_m$ with $m\ge 3$ in [14,18] and their impressive performance for image processing in [18,30] in this paper we introduce a directional tensor product complex tight framelet ${TP-CTF}^!_6$ (called reduced ${TP-CTF}_6$) with low redundancy. Such ${TP-CTF}_6^!$ is a particular example of tight framelet filter banks with mixed sampling factors. The ${TP-CTF}^!_6$ in $d$ dimensions not only offers good directionality but also has the low redundancy rate $\frac{3^d-1}{2^d-1}$ (e.g., the redundancy rates are $2, 2\mathord{\frac{2}{3}}, 3\mathord{\frac{5}{7}}, 5\mathord{\frac{1}{3}}$ and $7\mathord{\frac{25}{31}}$ for dimension $d=1,..., 5$, respectively). Moreover, our numerical experiments on image/video denoising and inpainting show that the performance using our proposed ${TP-CTF}^!_6$ is often comparable or sometimes better than several state-of-the-art frame-based methods which have much higher redundancy rates than that of ${TPCTF}^!_6$.