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Computing and Information Technology (ICCIT-1441), 2020 International Conference on

作者： Mansour Alsulaiman Mohammed Algabri Hassan Mathkour Mohamed A. Bencherif Ghulam Muhammad Saad Al-Gahtani Mohammed Faisal Mohamed Amine Mekhtiche Taha Alfakih Computer Engineering Department College of Computer and Information Sciences King Saud University Riyadh Saudi Arabia Computer Science and Information Systems Department College of Applied Sciences AlMaarefa University Riyadh Saudi Arabia Computer Science Department College of Computer and Information Sciences King Saud University Riyadh Saudi Arabia Centre of Smart Robotics Research (CS2R) King Saud University Riyadh Saudi Arabia Arabic Language Institute King Saud University Saudi Arabia Center of AI & Robotics Kuwait College of Science and Technology (KCST) Kuwait

computer-Aided Pronunciation Training (CAPT) systems are gaining popularity recently due to the advancements in deep neural networks (DNN) and machine learning and the availability of databases of speech of language learners. Unfortunately, research in Arabic CAPT systems suffer from the lack of CAPT datasets compared to other languages. In this paper, we present the details of and the ideas used in the development of a versatile dataset of speech, real and synthesized, of Arabic Learners. To develop the dataset, we utilized an existing Arabic speech corpus, King Saud University Speech Database (KSU-SD). KSU-SD's main application was a speaker recognition system, but it was designed to be useful in other applications such as CAPT systems. KSU-SD includes a large number of speakers from diverse nationalities (Saudis, Arabs, and Non-Arabs). KSU-SD contains the recording of about 60 non-native speakers from more than 20 nationalities, hence we selected it to build the non-native Arabic-CAPT corpus. The developed corpus consists of transcribed, segmented, and annotated speech, which makes it suitable for building Arabic CAPT systems. In addition to presenting the details of developing the dataset, we also present an analysis of the text and speech errors of the dataset. The dataset was verified by many CAPT systems.

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Privacy Impact Assessments in the Wild: A Scoping Review

arXiv

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arXiv 2024年

作者： Iwaya, Leonardo Horn Alaqra, Ala Sarah Hansen, Marit Fischer-Hübner, Simone Department of Mathematics and Computer Science Karlstad University Universitetsgatan 2 Värmland Karlstad651 88 Sweden Information Systems Karlstad Business School Karlstad University Universitetsgatan 2 Värmland Karlstad651 88 Sweden Unabhängiges Landeszentrum für Datenschutz Schleswig-Holstein Holstenstraße 98 Schleswig-Holstein Kiel24103 Germany Department of Computer Science and Engineering Chalmers University of Technology Chalmersplatsen 4 Västra Götaland Gothenburg412 96 Sweden

Privacy Impact Assessments (PIAs) offer a process for assessing the privacy impacts of a project or system. As a privacy engineering strategy, they are one of the main approaches to privacy by design, supporting the early identification of threats and controls. However, there is still a shortage of empirical evidence on their use and proven effectiveness in practice. To better understand the current literature and research, this paper provides a comprehensive Scoping Review (ScR) on the topic of PIAs "in the wild," following the well-established Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines. This ScR includes 45 studies, providing an extensive synthesis of the existing body of knowledge, classifying types of research and publications, appraising the methodological quality of primary research, and summarising the positive and negative aspects of PIAs in practice, as reported by those studies. This ScR also identifies significant research gaps (e.g., evidence gaps from contradictory results and methodological gaps from research design deficiencies), future research pathways, and implications for researchers, practitioners, and policymakers developing and using PIA frameworks. As we conclude, there is still a significant need for more primary research on the topic, both qualitative and quantitative. A critical appraisal of qualitative studies revealed deficiencies in the methodological quality, and only four quantitative studies were identified, suggesting that current primary research remains incipient. Nonetheless, PIAs can be regarded as a prominent sub-area in the broader field of empirical privacy engineering, in which further scientific research to support existing practices is needed. Copyright © 2024, The Authors. All rights reserved.

关键词： Differential privacy

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Dog nose-print recognition based on the shape and spatial features of scales

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Expert systems with Applications 2024年 240卷

作者： Chan, Yung-Kuan Lin, Chuen-Horng Ben, Yuan-Rong Wang, Ching-Lin Yang, Shu-Chun Tsai, Meng-Hsiun Yu, Shyr-Shen Department of Management Information Systems National Chung Hsing University 145 Xingda Rd. South Dist. Taichung City402 Taiwan Department of Computer Science and Information Engineering National Taichung University of Science and Technology No. 129 Sec. 3 Sanmin Rd Taichung Taiwan Department of Computer Science and Engineering National Chung Hsing University 145 Xingda Rd. South Dist. Taichung City402 Taiwan Department of Information Management National Chin-Yi University of Technology No.57 Sec. 2 Zhongshan Rd. Taiping Dist. Taichung411030 Taiwan

This study proposes a novel method for dog identification using nose-print recognition, with applications in controlling stray dogs, locating lost pets, and pet insurance verification. Nose prints offer a unique and safer means of recognition than implanted chips. Accurate positioning of the dog's nose print (DNP) region and comparing its features can enhance recognition accuracy. The two-stage segmentation method effectively segments dog nostrils and nose boundaries in the DNP image. It combines brightness and texture enhancement with the U-Net model to generate a dog nose-print mask (DNPMask) and extracts scale-like features using a genetic algorithm. Experiments comparing one-stage and two-stage segmentation methods demonstrate the latter's superiority, with higher recall, precision, accuracy, and F1 score values. The DNPMask method achieves an average recognition rate of 94.93%, 97.10%, and 97.10% for Top1, Top2, and Top3, respectively, significantly improving dog recognition accuracy. However, its performance may be affected by poor-quality images. Nevertheless, the proposed dog recognition method effectively identifies most dog identities and holds promise for real-life applications, enhancing overall accuracy. The research findings provide a valuable reference for developing dog recognition systems and offer new ideas and directions for related research fields. The improved performance of dog nose-print recognition based on scale-like shape and spatial features (DNPISSFS) supports its superiority over Texture Feature-based Dog Noseprint Image Matching (TFDNPIM), suggesting enhanced dog recognition capabilities with broader implications in animal tracking, pet management, and wildlife conservation. Further analysis and experimentation on a larger dataset will ascertain the method's generalizability and robustness, addressing potential challenges and limitations for future research and practical implementation in various domains. The source code and trained mod

关键词： Animals

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Verification and Enforcement of Strong State-Based Opacity for Discrete-Event systems

arXiv

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arXiv 2024年

作者： Han, Xiaoguan Zhang, Kuize Li, Zhiwu College of Electronic Information and Automation Tianjin University of Science and Technology Tianjin300222 China Department of Computer Science University of Surrey GuildfordGU2 7XH United Kingdom Institute of Systems Engineering Macau University of Science and Technology Taipa999078 China School of Electro-Mechanical Engineering Xidian University Xi’an710071 China

In this paper, we investigate the verification and enforcement of strong state-based opacity (SBO) in discrete-event systems modeled as partially-observed (nondeterministic) finite-state automata, including strongK-step opacity (K-SSO), strong current-state opacity (SCSO), strong initialstate opacity (SISO), and strong infinite-step opacity (Inf-SSO). They are stronger versions of four widely-studied standard opacity notions, respectively. We firstly propose a new notion of K-SSO, and then we construct a concurrent-composition structure that is a variant of our previously-proposed one to verify it. Based on this structure, a verification algorithm for the proposed notion of K-SSO is designed. Also, an upper bound on K in the proposed K-SSO is derived. Secondly, we propose a distinctive opacity-enforcement mechanism that has better scalability than the existing ones (such as supervisory control). The basic philosophy of this newmechanism is choosing a subset of controllable transitions to disable before an original system starts to run in order to cut off all its runs that violate a notion of strong SBO of interest. Accordingly, the algorithms for enforcing the above-mentioned four notions of strong SBO are designed using the proposed two concurrent-composition structures. In particular, the designed algorithm for enforcing Inf-SSO has lower time complexity than the existing one in the literature, and does not depend on any assumption. Finally, we illustrate the applications of the designed algorithms using examples. Copyright © 2024, The Authors. All rights reserved.

关键词： Opacity

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Distributed Constrained Online Nonconvex Optimization with Compressed Communication

arXiv

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arXiv 2025年

作者： Zhang, Kunpeng Xu, Lei Yi, Xinlei Cao, Ming Johansson, Karl H. Chai, Tianyou Yang, Tao State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China Department of Mechanical Engineering University of Victoria VictoriaBCV8W 2Y2 Canada Shanghai Institute of Intelligent Science and Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Shanghai201210 China Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen GroningenAG 9747 Netherlands Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Digital Futures Stockholm10044 Sweden

This paper considers distributed online nonconvex optimization with time-varying inequality constraints over a network of agents. For a time-varying graph, we propose a distributed online primal–dual algorithm with compressed communication to efficiently utilize communication resources. We show that the proposed algorithm establishes an O(T max{1−θ1,θ1}) network regret bound and an O(T 1−θ1/2) network cumulative constraint violation bound, where T is the number of iterations and θ1 ∈ (0, 1) is a user-defined trade-off parameter. When Slater’s condition holds (i.e, there is a point that strictly satisfies the inequality constraints at all iterations), the network cumulative constraint violation bound is reduced to O(T 1−θ1). These bounds are comparable to the state-of-the-art results established by existing distributed online algorithms with perfect communication for distributed online convex optimization with (time-varying) inequality constraints. Finally, a simulation example is presented to validate the theoretical results. Copyright © 2025, The Authors. All rights reserved.

关键词： Convex optimization

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Radiance+: A Case Tool for Green Software Design

SSRN

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SSRN 2024年

作者： Larracoechea, Jorge Andrés Ilarri, Sergio Roose, Philippe LIUPPA E2S University of Pau 2 Allée du Parc Montaury Anglet Nouvelle-Aquitaine64600 France Department of Computer Science and Systems Engineering I3A Universidad de Zaragoza C. María de Luna 3 Aragón Zaragoza50018 Spain

Regardless of the improvements in the efficiency of energy consumption of informationand communication technology, electric energy consumption will forever be a requi-site for software execution. Consequently, researchers have promoted the developmentof green and sustainable software with new development methods and tools. These,however, have been adopted with limited success, due to technicalities and specificlanguage/platform requirements. In this paper, we present RADIANCE+: a proof ofconcept web app for designing greener software with a model-driven approach basedon a Domain-Specific Modeling Language. RADIANCE+, in contrast to other tools,welcomes users with different levels of knowledge on green software and software ar-chitecture. Moreover, RADIANCE+ assesses and rates the prospective hardware andbehavioral consumption of the profiles created by the user, assisting them in identify-ing possible design changes that result in greener software from the initial stages ofsoftware development. It includes a Behavioral Load Simulator (BLS), which trans-lates the profiles into a multi-agents simulation, whose evolving prospective hardwareconsumption can be translated into the evolution of energy consumption. The resultsof the BLS can be further used by deployment simulators so that software designersand architects can experiment with different software architectures, load balancing,and scheduling or orchestration algorithms, all from the initial stages of the SoftwareDevelopment Life-Cycle. © 2024, The Authors. All rights reserved.

关键词： Energy utilization

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A Multi-population Integrated Approach for Capacitated Location Routing

arXiv

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arXiv 2024年

作者： He, Pengfei Hao, Jin-Kao Wu, Qinghua School of Automation Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing210096 China Department of Computer Science LERIA University of Angers 2 Boulevard Lavoisier Angers49045 France School of Management Huazhong University of Science and Technology No. 1037 Luoyu Road Wuhan China

The capacitated location-routing problem involves determining the depots from a set of candidate capacitated depot locations and finding the required routes from the selected depots to serve a set of customers whereas minimizing a cost function that includes the cost of opening the chosen depots, the fixed utilization cost per vehicle used, and the total cost (distance) of the routes. This paper presents a multi-population integrated framework in which a multi-depot edge assembly crossover generates promising offspring solutions from the perspective of both depot location and route edge assembly. The method includes an effective neighborhood-based local search, a feasibility-restoring procedure and a diversification-oriented mutation. Of particular interest is the multi-population scheme which organizes the population into multiple subpopulations based on depot configurations. Extensive experiments on 281 benchmark instances from the literature show that the algorithm performs remarkably well, by improving 101 best-known results (new upper bounds) and matching 84 best-known results. Additional experiments are presented to gain insight into the role of the key elements of the algorithm. © 2024, CC BY-NC-ND.

关键词： Cost functions

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Cybersecurity Threat Detection in the Behavior of IoT Devices: Analysis of Data Mining Competition Results 18

Cybersecurity Threat Detection in the Behavior of IoT Device...

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18th Conference on computer science and Intelligence systems, FedCSIS 2023

作者： Czerwinski, Michal Michalak, Marcin Biczyk, Piotr Adamczyk, Blazej Iwanicki, Daniel Kostorz, Iwona Brzeczek, Maksym Janusz, Andrzej Hermansa, Marek Wawrowski, Lukasz Kozlowski, Artur Qed Software Mazowiecka 11/49 Warsaw0-052 Poland Ukasiewicz Research Network - Institute of Innovative Technologies Emag Leopolda 31 Katowice40-189 Poland Efigo Sp. Z O.o. M.Kopernika 8/6 Katowice40-064 Poland Faculty of Mathematics University of Warsaw Banacha 2 Warsaw02-097 Poland Department of Computer Networks and Systems Faculty of Automatic Control University of Technology Electronics and Computer Science Akademicka 16 Gliwice44-100 Poland

ISBN: (纸本)9788396744784

The paper discusses a data science competition centered around the development of an anomaly detection system for IoT devices. The competition utilized a unique environment that allowed for the operation and monitoring of real IoT devices, including scheduling of attacks on these devices. The environment was used to collect the data, which included both normal and attack-induced behavior of IoT devices. The paper presents the background of the competition, the top models submitted, and the competition results. The paper also includes a discussion about restrictions related to the use of synthetic attack data as input for constructing anomaly detection systems. © 2023 Polish Information Processing Society.

关键词： Quality control

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The Transferable Belief Model for Failure Prediction in Wireless Sensor Networks

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SN computer science 2021年第4期2卷 269页

作者： Kamdjou, Hugues Marie Tagne Fute, Elie El Amraoui, Adnen Nzeukou, Armand Department of Mathematics and Computer Science University of Dschang Dschang Cameroon Department of Mathematics and Computer Science University of Dschang Dschang Cameroon Department of Computer Engineering Faculty of Engineering and Technology University of Buea Buea Cameroon Laboratoire de Génie Informatique et d’Automatique de l’Artois (LGI2A) University of Artois U.R. 3926 Béthune 62400 France Laboratory of Industrial Systems and Environmental Engineering Faculty of Science Fotso Victor University Institute of Technology University of Dschang Dschang Cameroon

In recent years, with the advent of smart sensors, the design and deployment of Wireless Sensor Networks (WSN) have become an active area of research. Sensor nodes are typically deployed to sense, measure and gather parameters/conditions such as temperature, pressure, humidity, vibration, etc. Then, the Industrial Internet of Things (IIoT) applies WSN to improve the productivity and efficiency of existing and prospective manufacturing industries. The measured values are transmitted to a data fusion centre for further processing. However, the set of learning data on which the processing must be based for decision making is not always complete due to some failures such as security attack, packet leak, collision, interference, congestion, channel fading, devices errors, incorrect deployment, synchronization issues, environmental blockages or unknown errors. The management of missing data is a common and widespread problem in smart factory using WSN. It is a more common topic in monitoring systems. The matter is to define a Transferable Belief Model (TBM) for failures prediction in WSN. However, most of the existing prediction methods are based on deterministic probabilistic approaches. These approaches are not adapted for representation of imprecise knowledge common in WSN. To remedy these issues, the ultimate goal of this paper is to propose a non-deterministic approach for building a predictive belief function from statistical data for decision making. The fundamental point of methodology is to transfer uncertainties by transforming masses function into densities function, and then belief functions, plausibility functions and commonality functions into integrals of these densities function. The efficiency of the approach is demonstrated using a simulated WSN problem and Monte Carlo simulation. The simulation’s results have shown that the proposed approach achieves satisfactory performance compared to data imputation methods. © 2021, The Author(s), under exclusive lic

关键词： Belief functions Decision making Missing data Wireless sensor networks

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Hardware Implementation of a Two-dimensional Fractional Map with Hidden Attractors

Hardware Implementation of a Two-dimensional Fractional Map ...

引用

2023 International Conference on Fractional Differentiation and Its Applications, ICFDA 2023

作者： Ouannas, Adel Khennaoui, Amina Aicha Grassi, Giuseppe Pham, Viet-Thanh Dibi, Zohir Momani, Shaher University of Oum El-Bouaghi Department of Mathematics and Computer Science Oum El Bouaghi Algeria University of Constantine 2 Ntic Faculty Tlsi Department Constantine Algeria Universita Del Salento Dipartimento Ingegneria Innovazione Lecce Italy Ton DucThang University Nonlinear Systems and Applications Faculty of Electrical and Electronics Engineering Ho Chi Minh City Viet Nam University of Oum El-Bouaghi Oum El Bouaghi Algeria Ajman University College of Humanities and Sciences Department of Mathematics and Sciencesi Ajman United Arab Emirates

ISBN: (纸本)9798350321685

Several efforts have been recently devoted to the hardware implementations of fractional systems. This manuscript makes a contribution to the topic by introducing the first example of hardware implementation of a 2D fractional map with hidden. Specifically, the paper presents first a new class of two-dimensional fractional map with no equilibruim points using the Grunwald-Letnikov difference operator. Then, the system dynamics are analyzed via numerical simulation, such as bifurcation diagrams, Lyapunov exponents and phase portraits. Finally, the paper illustrates a hardware implementation of the 2D fractional map via a microcontroller, with the aim to show the real presence of chaotic hidden attractors in physical systems described by non-integer order maps. © 2023 IEEE.

关键词： Lyapunov methods

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