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Hacking the Cis-tem Transgender Citizens and the Early Digital State

IEEE ANNALS OF THE HISTORY OF COMPUTING 2019年第1期41卷 20-33页

作者： Hicks, Mar IIT Hist Technol Chicago IL 60616 USA

This paper looks at the case of transgender Britons who tried to correct the gender listed on their government-issued ID cards, but ran up against the British government's increasingly computerized methods for tracking, identifying, and defining citizens. These newly computerizing systems show some of the earliest examples of transphobic algorithmic bias: explicit attempts to program trans people out of the system can be seen in the programming of the early Ministry of Pensions computer system designed to apportion benefits to all tax paying British citizens. Transgender citizens pushed back against these developments, attempting to hack the bureaucratic avenues and categories available to them, laying the groundwork for a coalescing political movement. This paper argues that uncovering the deep prehistory of algorithmic bias and investigating instances of resistance within this history is essential to understanding current debates about algorithmic bias, and how computerized systems have long functioned to create and enforce norms and hierarchies.

关键词： algorithm design and analysis Economics Gender issues Government Pensions Programming

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Multivariable Electromagnetic Optimization design Exploiting Hybrid Kriging

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COMPUTING IN SCIENCE & ENGINEERING 2019年第5期21卷 46-54页

作者： Xiao, Song Zhang, Kunlun Liu, Guoqing Wang, Ying Duan, Jiaheng Kong, Lingxing Southwest Jiaotong Univ Sch Elect Engn Chengdu Sichuan Peoples R China Southwest Jiaotong Univ Chengdu Sichuan Peoples R China

Electromagnetic optimization utilizing finite element or similar numerical techniques always carries a heavy burden of computation;therefore, an efficient optimizer reducing the number of objective function calls to find the optimum accurately is essential. Kriging as a regression model is able to locate the optimum;meanwhile, it also can produce the response surface of objective function only based on the spatial correlation of limited information. However, the storage of correlation matrices generated by a kriging optimizer, along with the iterative optimization process, is an issue in the context of the electromagnetic optimization problems with many design variables and multiple optimal objectives. The proposed hybrid kriging methodology incorporating a direct algorithm is able to maintain memory occupation of the optimizer as a nearly constant level. It performs efficiently and reliably while coping with the large-scale multivariable optimization tasks. The feasibility and efficiency of the proposed hybrid kriging are verified via a classic analytic function and the multivariable benchmark TEAM Workshop problem 22.

关键词： Electromagnetic Devices Finite Element analysis Iterative Methods Matrix Algebra Optimisation Regression Model Correlation Matrices Kriging Optimizer Iterative Optimization Process Electromagnetic Optimization Problems Hybrid Kriging Methodology Multivariable Benchmark TEAM Workshop Problem Multivariable Electromagnetic Optimization design Large Scale Multivariable Optimization Finite Element Electromagnetics Optimization Magnetic Levitation Linear Programming Suspensions algorithm design and analysis Computational Modeling Kriging Correlation Matrices Hybrid Kriging Direct algorithm Benchmark TEAM Workshop Problem 22

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Quantum Search algorithms for Wireless Communications

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IEEE COMMUNICATIONS SURVEYS AND TUTORIALS 2019年第2期21卷 1209-1242页

作者： Botsinis, Panagiotis Alanis, Dimitrios Babar, Zunaira Hung Viet Nguyen Chandra, Daryus Ng, Soon Xin Hanzo, Lajos Univ Southampton Sch Elect & Comp Sci Southampton SO17 1BJ Hants England

Faster, ultra-reliable, low-power, and secure communications has always been high on the wireless evolutionary agenda. However, the appetite for faster, more reliable, greener, and more secure communications continues to grow. The state-of-the-art methods conceived for achieving the performance targets of the associated processes may be accompanied by an increase in computational complexity. Alternatively, a degraded performance may have to be accepted due to the lack of jointly optimized system components. In this survey we investigate the employment of quantum computing for solving problems in wireless communication systems. By exploiting the inherent parallelism of quantum computing, quantum algorithms may be invoked for approaching the optimal performance of classical wireless processes, despite their reduced number of cost-function evaluations. In this contribution we discuss the basics of quantum computing using linear algebra, before presenting the operation of the major quantum algorithms, which have been proposed in the literature for improving wireless communications systems. Furthermore, we investigate a number of optimization problems encountered both in the physical and network layer of wireless communications, while comparing their classical and quantum-assisted solutions. Finally, we state a number of open problems in wireless communications that may benefit from quantum computing.

关键词： algorithm design and analysis channel estimation localization multiuser detection non-orthogonal multiple access optimization precoding quantum algorithms quantum computing routing visible light communication wireless communication

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Scalable clustering and mapping algorithm for application distribution on heterogeneous and irregular FPGA clusters

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JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING 2019年 133卷 367-376页

作者： Kalms, Lester Goehringer, Diana Tech Univ Dresden Dresden Germany

The high flexibility of FPGAs predestines them for emulation and prototyping of ASIC designs. To increase the available amount of resources or to reduce costs, multiple low cost mainstream FPGA boards can be combined into one cluster. This paper presents a new algorithm for the distribution of application tasks into a cluster of FPGAs. This algorithm focuses on both clustering and mapping in one single step, which can be split into two phases. The first phase uses load balancing techniques, to achieve scalability for the number of tasks in the application and the number of FPGAs in the cluster. In the second phase different heuristic search techniques are used, to solve optimization problems, like the reduction of the maximum dilation and the maximum capacity utilization. In order to be applicable to many different topologies, the algorithm supports heterogeneous and irregular structures for FPGA clusters. (C) 2018 Elsevier Inc. All rights reserved.

关键词： Field programmable gate arrays Workload balancing Clustering & mapping algorithms Application distribution Heuristic search techniques Heterogeneity Irregular graphs algorithm design and analysis

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Stochastic Source Seeking for Mobile Robots in Obstacle Environments Via the SPSA Method

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2019年第4期64卷 1732-1739页

作者： Ramirez-Llanos, Eduardo Martinez, Sonia Univ Calif San Diego Dept Mech & Aerosp Engn La Jolla CA 92093 USA

This paper considers a class of stochastic source-seeking problems to drive a mobile robot to the minimizer of a source signal. Our approach is first analyzed in an obstacle-free scenario, where measurements of the signal at the robot location and information of a contact sensor are required. We extend our results to environments with obstacles under mild assumptions on the step size. Our approach builds on the simultaneous perturbation stochastic approximation idea to obtain information of the signal field. We prove the practical convergence of the algorithms to a ball whose size depends on the step size that contains the location of the source. The novelty relies in that we consider nondifferentiable convex functions, a fixed step size, and the environment may contain obstacles. Our proof methods employ nonsmooth Lyapunov function theory, tools from convex analysis, and stochastic difference inclusions. Finally, we illustrate the applicability of the proposed algorithms in a two-dimensional scenarios.

关键词： algorithm design and analysis intelligent robots nonlinear dynamical systems optimization stochastic systems

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A Fast PC algorithm for High Dimensional Causal Discovery with Multi-Core PCs

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IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2019年第5期16卷 1483-1495页

作者： Thuc Duy Le Hoang, Tao Li, Jiuyong Liu, Lin Liu, Huawen Hu, Shu Univ South Australia Sch Informat Technol & Math Sci Mawson Lakes SA 5095 Australia Zhejiang Normal Univ Dept Comp Sci Jinhua 321004 Zhejiang Peoples R China USTC Dept Comp Sci Hefei 230026 Anhui Peoples R China

Discovering causal relationships from observational data is a crucial problem and it has applications in many research areas. The PC algorithm is the state-of-the-art constraint based method for causal discovery. However, runtime of the PC algorithm, in the worst-case, is exponential to the number of nodes (variables), and thus it is inefficient when being applied to high dimensional data, e.g., gene expression datasets. On another note, the advancement of computer hardware in the last decade has resulted in the widespread availability of multi-core personal computers. There is a significant motivation for designing a parallelized PC algorithm that is suitable for personal computers and does not require end users' parallel computing knowledge beyond their competency in using the PC algorithm. In this paper, we develop parallel-PC, a fast and memory efficient PC algorithm using the parallel computing technique. We apply our method to a range of synthetic and real-world high dimensional datasets. Experimental results on a dataset from the DREAM 5 challenge show that the original PC algorithm could not produce any results after running more than 24 hours;meanwhile, our parallel-PC algorithm managed to finish within around 12 hours with a 4-core CPU computer, and less than six hours with a 8-core CPU computer. Furthermore, we integrate parallel-PC into a causal inference method for inferring miRNA-mRNA regulatory relationships. The experimental results show that parallel-PC helps improve both the efficiency and accuracy of the causal inference algorithm.

关键词： algorithm design and analysis Gene expression Inference algorithms Microcomputers Parallel processing Runtime Causal discovery gene expression data high dimensional data miRNA targets parallel computing PC algorithm

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Interactive Context-Aware Anomaly Detection Guided by User Feedback

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IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS 2019年第6期49卷 550-559页

作者： Shi, Yang Xu, Maoran Zhao, Rongwen Fu, Hao Wu, Tongshuang Cao, Nan Tongji Univ Intelligent Big Data Visualizat Lab Shanghai 201804 Peoples R China Univ Florida Gainesville FL 32611 USA Univ Calif Santa Cruz Santa Cruz CA 95064 USA Univ Washington Seattle WA 98195 USA

Automatic anomaly detection techniques have been extensively used to support decision making in abnormal situations. However, existing approaches are limited in their capacity of effectively identifying anomalies due to the complexity of the real-world environment, the uncertainty of the data input, and the unavailability of ground truth. In this paper, we propose an interactive context-aware anomaly detection algorithm framework that incorporates human judgment in searching for anomalous regions within a large geographic environment. In specific, our framework, 1) estimates a focal region and detect anomalous situations in real time, through which the user can observe and analyze suspicious entities, 2) leverages user feedback to refine results and guide further analysis, and 3) tolerates potential fault feedback provided by the users and resignal dubious anomalous points. Based on the framework, we propose two algorithm implementations, respectively, employ Bayes' theorem and metric learning. We demonstrate the effectiveness of the proposed framework and corresponding implementations through two controlled user studies and a case study with a domain expert.

关键词： Anomaly detection Complexity theory Monitoring algorithm design and analysis Anomaly detection interaction techniques

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Sub-Sync: Automatic Synchronization of Subtitles in the Broadcasting of True Live programs in Spanish

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IEEE ACCESS 2019年 7卷 60968-60983页

作者： Gonzalez-Carrasco, I Puente, L. Ruiz-Mezcua, B. Lopez-Cuadrado, J. L. Univ Carlos III Madrid Comp Sci Dept Leganes 28911 Spain Spanish Ctr Captioning & Audiodescript Leganes 28919 Spain

Individuals with sensory impairment (hearing or visual) encounter serious communication barriers within society and the world around them. These barriers hinder the communication process and make access to information an obstacle they must overcome on a daily basis. In this context, one of the most common complaints made by the Television (TV) users with sensory impairment is the lack of synchronism between audio and subtitles in some types of programs. In addition, synchronization remains one of the most significant factors in audience perception of quality in live-originated TV subtitles for the deaf and hard of hearing. This paper introduces the Sub-Sync framework intended for use in automatic synchronization of audio-visual contents and subtitles, taking advantage of current well-known techniques used in symbol sequences alignment. In this particular case, these symbol sequences are the subtitles produced by the broadcaster subtitling system and the word flow generated by an automatic speech recognizing the procedure. The goal of Sub-Sync is to address the lack of synchronism that occurs in the subtitles when produced during the broadcast of live TV programs or other programs that have some improvised parts. Furthermore, it also aims to resolve the problematic interphase of synchronized and unsynchronized parts of mixed type programs. In addition, the framework is able to synchronize the subtitles even when they do not correspond literally to the original audio and/or the audio cannot be completely transcribed by an automatic process. Sub-Sync has been successfully tested in different live broadcasts, including mixed programs, in which the synchronized parts (recorded, scripted) are interspersed with desynchronized (improvised) ones.

关键词： Accessibility TV broadcasting algorithm design and analysis automatic speech recognition

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The Statistical Saliency Model Can Choose Colors for Items on Maps

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IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS 2019年第6期49卷 569-578页

作者： Shive, Joshua Rosichan, Sharra Davis, Sherika Wade, Christena Ellison, James Santoni-Sanchez, Santos Tennessee State Univ Dept Psychol Nashville TN 37209 USA Univ Tennessee Sch Informat Sci Knoxville TN 37996 USA Middle Tennessee State Univ Dept Psychol Murfreesboro TN 37132 USA

We show how a model of visual salience that was originally developed to explain human visual search performance can suggest display design choices that reduce search time for items. The statistical saliency model proposes that the time to find an item on a visual display depends on the similarity between a target items features and the statistical distribution of display features. In the present study, observers rated the amount of display clutter on a set of MapQuest maps containing colored pushpins. We identified a group of "high-clutter" maps and a group of "low-clutter" maps. Next, we used the statistical saliency model to choose colors for new pushpins placed on those maps. We show that the models color assignments depend on the colors the display contains. Map designs produced using this method were tested in a visual search experiment. Search time decreased as a pushpins predicted salience increased. In addition, choosing low salience colors led to slower search times for items on high-clutter displays than for items on low-clutter displays. The method we describe works with real images and does not require any parameter fitting. This study provides evidence that computational models of visual perception have potential as display design tools.

关键词： algorithm design and analysis Visualization Clutter Color Predictive models Computational modeling Display clutter display design human-computer interface human performance modeling information visualization visual search scanning

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Mining the Enriched Subgraphs for Specific Vertices in a Biological Graph

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IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2019年第5期16卷 1496-1507页

作者： Meysman, Pieter Saeys, Yvan Sabaghian, Ehsan Bittremieux, Wout Van de Peer, Yves Goethals, Bart Laukens, Kris Univ Antwerp Adv Database Res & Modeling ADReM B-2000 Antwerp Belgium Biomed Informat Res Ctr Antwerpen B-2000 Antwerp Belgium Univ Ghent VIB Inflammat Res Ctr B-9000 Ghent Belgium Univ Ghent Dept Resp Med B-9000 Ghent Belgium Univ Ghent Dept Plant Biotechnol & Bioinformat B-9000 Ghent Belgium VIB Dept Plant Syst Biol B-9000 Ghent Belgium

In this paper, we present a subgroup discovery method to find subgraphs in a graph that are associated with a given set of vertices. The association between a subgraph pattern and a set of vertices is defined by its significant enrichment based on a Bonferroni-corrected hypergeometric probability value. This interestingness measure requires a dedicated pruning procedure to limit the number of subgraph matches that must be calculated. The presented mining algorithm to find associated subgraph patterns in large graphs is therefore designed to efficiently traverse the search space. We demonstrate the operation of this method by applying it on three biological graph data sets and show that we can find associated subgraphs for a biologically relevant set of vertices and that the found subgraphs themselves are biologically interesting.

关键词： Proteins Data mining Protein engineering Diseases algorithm design and analysis Life sciences Subgraph mining single graph subgroup discovery transcriptional regulatory network protein graph

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