OpenRaiser/Intern-Atlas huggingface dataset:
Fractional Order Modeling of Human Operator Behavior with Second Order Controlled Plant and Experiment Research
Venue: arXiv cs.SY 2016
Year: 2016

Modeling human operator's dynamic plays a very important role in the manual closed-loop control system, and it is an active research area for several decades. Based on the characteristics of human brain and behaviour, a new kind of fractional order mathematical model for human operator in SISO systems is proposed. Compared with the traditional models based on the commonly used quasi-linear transfer function method or the optimal control theory method, the proposed fractional order model has simple structure with only few parameters, and each parameter has explicit physical meanings. The actual data and experiment results with the second-order controlled element illustrate the effectiveness of the proposed method.
On the definition of the classical connectives and quantifiers
Venue: arXiv cs.LO 2016
Year: 2016

Classical logic is embedded into constructive logic, through a definition of the classical connectives and quantifiers in terms of the constructive ones.
Path computation in multi-layer networks: Complexity and algorithms
Venue: arXiv cs.NI 2016
Year: 2016

Carrier-grade networks comprise several layers where different protocols coexist. Nowadays, most of these networks have different control planes to manage routing on different layers, leading to a suboptimal use of the network resources and additional operational costs. However, some routers are able to encapsulate, decapsulate and convert protocols and act as a liaison between these layers. A unified control plane would be useful to optimize the use of the network resources and automate the routing configurations. Software-Defined Networking (SDN) based architectures, such as OpenFlow, offer a chance to design such a control plane. One of the most important problems to deal with in this design is the path computation process. Classical path computation algorithms cannot resolve the problem as they do not take into account encapsulations and conversions of protocols. In this paper, we propose algorithms to solve this problem and study several cases: Path computation without bandwidth constraint, under bandwidth constraint and under other Quality of Service constraints. We study the complexity and the scalability of our algorithms and evaluate their performances on real topologies. The results show that they outperform the previous ones proposed in the literature.
Dense Bag-of-Temporal-SIFT-Words for Time Series Classification
Venue: arXiv cs.LG 2016
Year: 2016

Time series classification is an application of particular interest with the increase of data to monitor. Classical techniques for time series classification rely on point-to-point distances. Recently, Bag-of-Words approaches have been used in this context. Words are quantized versions of simple features extracted from sliding windows. The SIFT framework has proved efficient for image classification. In this paper, we design a time series classification scheme that builds on the SIFT framework adapted to time series to feed a Bag-of-Words. We then refine our method by studying the impact of normalized Bag-of-Words, as well as densely extract point descriptors. Proposed adjustements achieve better performance. The evaluation shows that our method outperforms classical techniques in terms of classification.
A comparative performance study of the routing protocols RPL, LOADng and LOADng-CTP with bidirectional traffic for AMI scenario
Venue: arXiv cs.NI 2016
Year: 2016

With the introduction of the smart grid, Advanced Metering Infrastructure (AMI) has become a main component in the present power system. The effective implementation of AMI depends widely on its communication infrastructure and protocols providing trustworthy two-way communications. In this paper we study two routing protocols philosophies for low power and lossy networks (LLNs) and their application for a smart metering scenario. This study purposes a detailed evaluation of two routing protocols proposed by IETF the proactive candidate namely RPL (IPv6 Routing Protocol for Low-Power and Lossy Networks) and the reactive candidate named LOADng (LLN On-demand Ad-hoc Distance vector routing protocol - next generation) recently proposed as an Internet Draft, still in its design phase and is part of the ITU-T G.9903 recommendation. In the course of this study, we also implemented an extension version of LOADng named LOADng-CTP specified by an IETF draft extended with a collection tree for efficient data acquisition in LLNs. We performed checks on control overhead; End to End Delay and Packet delivery ratio for the two protocols related to multipoint-to-point (MP2P), and point-to-multi point (P2MP) traffic flow in a realistic smart metering architecture.
The Cost of Global Broadcast in Dynamic Radio Networks
Venue: arXiv cs.DC 2016
Year: 2016

We study the single-message broadcast problem in dynamic radio networks. We show that the time complexity of the problem depends on the amount of stability and connectivity of the dynamic network topology and on the adaptiveness of the adversary providing the dynamic topology. More formally, we model communication using the standard graph-based radio network model. To model the dynamic network, we use a generalization of the synchronous dynamic graph model introduced in [Kuhn et al., STOC 2010]. For integer parameters $T\geq 1$ and $k\geq 1$, we call a dynamic graph $T$-interval $k$-connected if for every interval of $T$ consecutive rounds, there exists a $k$-vertex-connected stable subgraph. Further, for an integer parameter $τ\geq 0$, we say that the adversary providing the dynamic network is $τ$-oblivious if for constructing the graph of some round $t$, the adversary has access to all the randomness (and states) of the algorithm up to round $t-τ$. As our main result, we show that for any $T\geq 1$, any $k\geq 1$, and any $τ\geq 1$, for a $τ$-oblivious adversary, there is a distributed algorithm to broadcast a single message in time $O\big(\big(1+\frac{n}{k\cdot\min\left\{τ,T\right\}}\big)\cdot n\log^3 n\big)$. We further show that even for large interval $k$-connectivity, efficient broadcast is not possible for the usual adaptive adversaries. For a $1$-oblivious adversary, we show that even for any $T\leq (n/k)^{1-\varepsilon}$ (for any constant $\varepsilon>0$) and for any $k\geq 1$, global broadcast in $T$-interval $k$-connected networks requires at least $Ω(n^2/(k^2\log n))$ time. Further, for a $0$ oblivious adversary, broadcast cannot be solved in $T$-interval $k$-connected networks as long as $T<n-k$.
The life and work of Marvin Kenneth Simon
Venue: arXiv cs.IT 2016
Year: 2016

It is a measure of the importance and profundity of Marvin Kenneth Simon's contributions to communication theory that this tribute article and tutorial about his life and work is of current research relevance in spite of the continually accelerating rate of evolution in this area. Marv, as the entire community affectionately knew him, was one of the most prolific and influential communications researchers of his generation. Moreover, he laid the foundation for many of the techniques used in communication systems today. Marv's tragic death on September 23, 2007 continues to engender pangs not only of sadness at the passing of a great friend to many in our community, but also of regret that he is no longer with us to help in resolving the many challenges facing communication systems today.
Optimized Integral Controller Searching Prime Number Orders
Venue: arXiv cs.SY 2016
Year: 2016

The concept of integration is generally applicable to automatic control of processes. As shown in this paper, integral controller performs efficient searches in the extensive prime sets, too. An inspiration by the simple analytic rules for PID controller tuning results in integral controller that ensures predictable work regardless of the cardinality of primes. It gives an innovative application of the feedback control which relates to a gradient method.
Sentiment Visualisation Widgets for Exploratory Search
Venue: arXiv cs.HC 2016
Year: 2016

This paper proposes the usage of \emph{visualisation widgets} for exploratory search with \emph{sentiment} as a facet. Starting from specific design goals for depiction of ambivalence in sentiment, two visualization widgets were implemented: \emph{scatter plot} and \emph{parallel coordinates}. Those widgets were evaluated against a text baseline in a small-scale usability study with exploratory tasks using Wikipedia as dataset. The study results indicate that users spend more time browsing with scatter plots in a positive way. A post-hoc analysis of individual differences in behavior revealed that when considering two types of users, \emph{explorers} and \emph{achievers}, engagement with scatter plots is positive and significantly greater \textit{when users are explorers}. We discuss the implications of these findings for sentiment-based exploratory search and personalised user interfaces.
Multicuts and Perturb & MAP for Probabilistic Graph Clustering
Venue: arXiv cs.CV 2016
Year: 2016

We present a probabilistic graphical model formulation for the graph clustering problem. This enables to locally represent uncertainty of image partitions by approximate marginal distributions in a mathematically substantiated way, and to rectify local data term cues so as to close contours and to obtain valid partitions. We exploit recent progress on globally optimal MAP inference by integer programming and on perturbation-based approximations of the log-partition function, in order to sample clusterings and to estimate marginal distributions of node-pairs both more accurately and more efficiently than state-of-the-art methods. Our approach works for any graphically represented problem instance. This is demonstrated for image segmentation and social network cluster analysis. Our mathematical ansatz should be relevant also for other combinatorial problems.
A Grouped System Architecture for Smart Grids Based AMI Communications Over LTE
Venue: arXiv cs.NI 2016
Year: 2016

A smart grid based Advanced Metering Infrastructure (AMI), is a technology that enables the utilities to monitor and control the electricity consumption through a set of various smart meters (SMs) connected via a two way communication infrastructure. One of the key challenges for smart grids is how to connect a large number of devices. On the other hand, 4G Long Term Evolution (LTE), the latest standard for mobile communications, was developed to provide stable service performance and higher data rates for a large number of mobile users. Therefore, LTE is considered a promising solution for wide area connectivity for SMs. In this paper, a grouped hierarchal architecture for SMs communications over LTE is introduced. Then, an efficient grouped scheduling technique is proposed for SMs transmissions over LTE. The proposed architecture efficiently solves the overload problem due to AMI traffic and guarantees a full monitoring and control for energy consumption. The results of our suggested solution showed that LTE can serve better for smart grids based AMI with particular grouping and scheduling scheme. In addition, the presented technique can able to be used in urban areas having high density of SMs.
A complex network theory approach for optimizing contamination warning sensor location in water distribution networks
Venue: arXiv cs.SI 2016
Year: 2016

Drinking water for human health and well-being is crucial. Accidental and intentional water contamination can pose great danger to consumers. Optimal design of a system that can quickly detect the presence of contamination in a water distribution network is very challenging for technical and operational reasons. However, on the one hand improvement in chemical and biological sensor technology has created the possibility of designing efficient contamination detection systems. On the other hand, methods and tools from complex network theory, which was primarily the domain of mathematicians and physicists, provide analytical output for engineers to design, optimize, operate, and maintain complex network systems such as power grids, water distribution networks, telecommunication systems, internet, roads, supply chains, traffic and transportation systems. In this work, we develop a new modeling approach for the optimal placement of sensors for contamination detection in a water distribution network. The approach originally combines classical optimization and complex systems theory.
Physical Layer Security in Three-Tier Wireless Sensor Networks: A Stochastic Geometry Approach
Venue: arXiv cs.IT 2016
Year: 2016

This paper develops a tractable framework for exploiting the potential benefits of physical layer security in three-tier wireless sensor networks using stochastic geometry. In such networks, the sensing data from the remote sensors are collected by sinks with the help of access points, and the external eavesdroppers intercept the data transmissions.We focus on the secure transmission in two scenarios: i) the active sensors transmit their sensing data to the access points, and ii) the active access points forward the data to the sinks. We derive new compact expressions for the average secrecy rate in these two scenarios. We also derive a new compact expression for the overall average secrecy rate. Numerical results corroborate our analysis and show that multiple antennas at the access points can enhance the security of three-tier wireless sensor networks. Our results show that increasing the number of access points decreases the average secrecy rate between the access point and its associated sink. However, we find that increasing the number of access points first increases the overall average secrecy rate, with a critical value beyond which the overall average secrecy rate then decreases. When increasing the number of active sensors, both the average secrecy rate between the sensor and its associated access point and the overall average secrecy rate decrease. In contrast, increasing the number of sinks improves both the average secrecy rate between the access point and its associated sink, as well as the overall average secrecy rate.
Parallel Stroked Multi Line: a model-based method for compressing large fingerprint databases
Venue: arXiv cs.CV 2016
Year: 2016

With increasing usage of fingerprints as an important biometric data, the need to compress the large fingerprint databases has become essential. The most recommended compression algorithm, even by standards, is JPEG2K. But at high compression rates, this algorithm is ineffective. In this paper, a model is proposed which is based on parallel lines with same orientations, arbitrary widths and same gray level values located on rectangle with constant gray level value as background. We refer to this algorithm as Parallel Stroked Multi Line (PSML). By using Adaptive Geometrical Wavelet and employing PSML, a compression algorithm is developed. This compression algorithm can preserve fingerprint structure and minutiae. The exact algorithm of computing the PSML model take exponential time. However, we have proposed an alternative approximation algorithm, which reduces the time complexity to $O(n^3)$. The proposed PSML alg. has significant advantage over Wedgelets Transform in PSNR value and visual quality in compressed images. The proposed method, despite the lower PSNR values than JPEG2K algorithm in common range of compression rates, in all compression rates have nearly equal or greater advantage over JPEG2K when used by Automatic Fingerprint Identification Systems (AFIS). At high compression rates, according to PSNR values, mean EER rate and visual quality, the encoded images with JPEG2K can not be identified from each other after compression. But, images encoded by the PSML alg. retained the sufficient information to maintain fingerprint identification performances similar to the ones obtained by raw images without compression. One the U.are.U 400 database, the mean EER rate for uncompressed images is 4.54%, while at 267:1 compression ratio, this value becomes 49.41% and 6.22% for JPEG2K and PSML, respectively. This result shows a significant improvement over the standard JPEG2K algorithm.
Improper Twin Edge Coloring of Graphs
Venue: arXiv cs.DM 2016
Year: 2016

Let $G$ be a graph whose each component has order at least 3. Let $s : E(G) \rightarrow \mathbb{Z}_k$ for some integer $k\geq 2$ be an improper edge coloring of $G$ (where adjacent edges may be assigned the same color). If the induced vertex coloring $c : V (G) \rightarrow \mathbb{Z}_k$ defined by $c(v) = \sum_{e\in E_v} s(e) \mbox{ in } \mathbb{Z}_k,$ (where the indicated sum is computed in $\mathbb{Z}_k$ and $E_v$ denotes the set of all edges incident to $v$) results in a proper vertex coloring of $G$, then we refer to such a coloring as an improper twin $k$-edge coloring. The minimum $k$ for which $G$ has an improper twin $k$-edge coloring is called the improper twin chromatic index of $G$ and is denoted by $χ'_{it}(G)$. In this paper, we show that if $G$ is a graph with vertex chromatic number $χ(G)$, then $χ'_{it}(G)=χ(G)$, unless $χ(G)=2 \pmod 4$ and in this case $χ'_{it}(G)\in \{χ(G), χ(G)+1\}$. Moreover, we show that it is NP-hard to decide whether $χ'_{it}(G)=χ(G)$ or $χ'_{it}(G)=χ(G)+1$ and give some examples of perfect graph classes for which the problem is polynomial.
How to Incentivize Data-Driven Collaboration Among Competing Parties
Venue: arXiv cs.GT 2016
Year: 2016

The availability of vast amounts of data is changing how we can make medical discoveries, predict global market trends, save energy, and develop educational strategies. In some settings such as Genome Wide Association Studies or deep learning, sheer size of data seems critical. When data is held distributedly by many parties, they must share it to reap its full benefits. One obstacle to this revolution is the lack of willingness of different parties to share data, due to reasons such as loss of privacy or competitive edge. Cryptographic works address privacy aspects, but shed no light on individual parties' losses/gains when access to data carries tangible rewards. Even if it is clear that better overall conclusions can be drawn from collaboration, are individual collaborators better off by collaborating? Addressing this question is the topic of this paper. * We formalize a model of n-party collaboration for computing functions over private inputs in which participants receive their outputs in sequence, and the order depends on their private inputs. Each output "improves" on preceding outputs according to a score function. * We say a mechanism for collaboration achieves collaborative equilibrium if it ensures higher reward for all participants when collaborating (rather than working alone). We show that in general, computing a collaborative equilibrium is NP-complete, yet we design efficient algorithms to compute it in a range of natural model settings. Our collaboration mechanisms are in the standard model, and thus require a central trusted party; however, we show this assumption is unnecessary under standard cryptographic assumptions. We show how to implement the mechanisms in a decentralized way with new extensions of secure multiparty computation that impose order/timing constraints on output delivery to different players, as well as privacy and correctness.
Wavelet speech enhancement based on nonnegative matrix factorization
Venue: arXiv cs.SD 2016
Year: 2016

For most of the state-of-the-art speech enhancement techniques, a spectrogram is usually preferred than the respective time-domain raw data since it reveals more compact presentation together with conspicuous temporal information over a long time span. However, the short-time Fourier transform (STFT) that creates the spectrogram in general distorts the original signal and thereby limits the capability of the associated speech enhancement techniques. In this study, we propose a novel speech enhancement method that adopts the algorithms of discrete wavelet packet transform (DWPT) and nonnegative matrix factorization (NMF) in order to conquer the aforementioned limitation. In brief, the DWPT is first applied to split a time-domain speech signal into a series of subband signals without introducing any distortion. Then we exploit NMF to highlight the speech component for each subband. Finally, the enhanced subband signals are joined together via the inverse DWPT to reconstruct a noise-reduced signal in time domain. We evaluate the proposed DWPT-NMF based speech enhancement method on the MHINT task. Experimental results show that this new method behaves very well in prompting speech quality and intelligibility and it outperforms the convnenitional STFT-NMF based method.
Repetitive Transients Extraction Algorithm for Detecting Bearing Faults
Venue: arXiv cs.SD 2016
Year: 2016

This paper addresses the problem of noise reduction with simultaneous components extrac- tion in vibration signals for faults diagnosis of bearing. The observed vibration signal is modeled as a summation of two components contaminated by noise, and each component composes of repetitive transients. To extract the two components simultaneously, an approach by solving an optimization problem is proposed in this paper. The problem adopts convex sparsity-based regularization scheme for decomposition, and non-convex regularization is used to further promote the sparsity but preserving the global convexity. A synthetic example is presented to illustrate the performance of the proposed approach for repetitive feature extraction. The performance and effectiveness of the proposed method are further demonstrated by applying to compound faults and single fault diagnosis of a locomotive bearing. The results show the proposed approach can effectively extract the features of outer and inner race defects.
Assessing and Improving the Mutation Testing Practice of PIT
Venue: arXiv cs.SE 2016
Year: 2016

Mutation testing is used extensively to support the experimentation of software engineering studies. Its application to real-world projects is possible thanks to modern tools that automate the whole mutation analysis process. However, popular mutation testing tools use a restrictive set of mutants which do not conform to the community standards as supported by the mutation testing literature. This can be problematic since the effectiveness of mutation depends on its mutants. We therefore examine how effective are the mutants of a popular mutation testing tool, named PIT, compared to comprehensive ones, as drawn from the literature and personal experience. We show that comprehensive mutants are harder to kill and encode faults not captured by the mutants of PIT for a range of 11% to 62% of the Java classes of the considered projects.
New Integrality Gap Results for the Firefighters Problem on Trees
Venue: arXiv cs.DM 2016
Year: 2016

The firefighter problem is NP-hard and admits a $(1-1/e)$ approximation based on rounding the canonical LP. In this paper, we first show a matching integrality gap of $(1-1/e+ε)$ on the canonical LP. This result relies on a powerful combinatorial gadget that can be used to prove integrality gap results for many problem settings. We also consider the canonical LP augmented with simple additional constraints (as suggested by Hartke). We provide several evidences that these constraints improve the integrality gap of the canonical LP: (i) Extreme points of the new LP are integral for some known tractable instances and (ii) A natural family of instances that are bad for the canonical LP admits an improved approximation algorithm via the new LP. We conclude by presenting a $5/6$ integrality gap instance for the new LP.