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An Abstract Domain of Linear Templates with Disjunctive Right-Hand-Side Intervals 9th

An Abstract Domain of Linear Templates with Disjunctive Ri...

引用

9th International Symposium on Dependable software engineering: Theories, Tools and Applications, SETTA 2023

作者： Xu, Han Chen, Liqian Fan, Guangsheng Yin, Banghu Wang, Ji College of Computer National University of Defense Technology Changsha410073 China Hunan Key Laboratory of Software Engineering for Complex Systems Changsha410073 China HPCL National University of Defense Technology Changsha410073 China College of Systems Engineering National University of Defense Technology Changsha410073 China

ISBN: (纸本)9789819986637

Abstract interpretation provides a general framework for analyzing the value ranges of program variables while ensuring soundness. Abstract domains are at the core of the abstract interpretation framework, and the numerical abstract domains aiming at analyzing numerical properties have received extensive attention. The template constraint matrix domain (also called the template polyhedra domain) is widely used due to its configurable constraint matrix (describing limited but user-concerned linear relationships among variables) and its high efficiency. However, it cannot express non-convex properties that appear naturally due to the inherent disjunctive behaviors in a program. In this paper, we introduce a new abstract domain, namely the abstract domain of linear templates with disjunctive right-hand-side intervals, in the form of ∑iaixi∈⋁j=0p[cj,dj] (where ai ’s and p are configurable and fixed before conducting analysis). Experimental results of our prototype are encouraging: In practice, the new abstract domain can find interesting non-convex invariants that are out of the expressiveness of the classic template constraint matrix abstract domain. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Abstract domain Abstract interpretation Invariant Template constraint matrix

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Distributionally Robust Control for Chance-Constrained Signal Temporal Logic Specifications 63

Distributionally Robust Control for Chance-Constrained Signa...

引用

63rd IEEE Conference on Decision and Control, CDC 2024

作者： Kordabad, Arash Bahari Vlahakis, Eleftherios E. Lindemann, Lars Dimarogonas, Dimos V. Soudjani, Sadegh Max Planck Institute for Software Systems Kaiserslautern Germany Kth Royal Institute of Technology Division of Decision and Control Systems Stockholm Sweden University of Southern California Viterbi School of Engineering Thomas Lord Department of Computer Science Los Angeles United States

ISBN: (纸本)9798350316339

We consider distributionally robust optimal control of stochastic linear systems under signal temporal logic (STL) chance constraints when the disturbance distribution is unknown. By assuming that the underlying predicate functions are Lipschitz continuous and the noise realizations are drawn from a distribution having a concentration of measure property, we first formulate the underlying chance-constrained control problem as stochastic programming with constraints on expectations and propose a solution using a distributionally robust approach based on the Wasserstein metric. We show that by choosing a proper Wasserstein radius, the original chance-constrained optimization can be satisfied with a user-defined confidence level. A numerical example illustrates the efficacy of the method. © 2024 IEEE.

关键词： Stochastic systems

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W-restrained Bidirectional Bounded-Suboptimal Heuristic Search 33

W-restrained Bidirectional Bounded-Suboptimal Heuristic Sear...

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33rd International Conference on Automated Planning and Scheduling, ICAPS 2023

作者： Atzmon, Dor Shperberg, Shahaf S. Sabah, Netanel Felner, Ariel Sturtevant, Nathan R. Department of Computer Science Royal Holloway University of London United Kingdom Department of Software and Information Systems Engineering Ben-Gurion University Israel University of Alberta Canada

ISBN: (纸本)1577358813

In this paper, we develop theoretical foundations for bidirectional bounded-suboptimal search (BiBSS) based on recent advancements in optimal bidirectional search. In addition, we introduce a BiBSS variant of the prominent meet-in-the-middle (MM) algorithm, called Weighted MM (WMM). We show that WMM has an interesting property of being Wrestrained, and study it empirically. Copyright © 2023, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Artificial intelligence

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Design of a Smart and Green Industry 4.0 Architecture 24

Design of a Smart and Green Industry 4.0 Architecture

引用

24th International Arab Conference on Information Technology, ACIT 2023

作者： Hamdan, Khaled Kazar, Okba College of It Uaeu Dept. of Computer Science and Software Engineering United Arab Emirates College of It Uaeu Dept. of Information Systems & Security United Arab Emirates

ISBN: (纸本)9798350384307

The industrial sector has entered a phase of profound change which sees digital technologies being integrated into the heart of industrial processes. This fourth industrial era gives birth to a new generation of factory called 'Digital Factory', 'Industry 4.0'. This industrial change is the result of the integration of new digital technologies into manufacturing processes and the optimization of energy consumption. The commitment to the environment is also a key and success factor of Industry 4.0 and green in particular the reduction of carbon emissions and pollution. This is how smart green industry try to take in charge the problem of energy consumption and to reduce the Co2 pollution. The goal of this paper is to present the new model of smart green industry using distributed artificial intelligence based on multi-agent system (MAS). The motivation to use the intelligent approach based on MAS is based on the similarity between the fundamental concepts of the cyber-physical system and those contained in the architecture and operation of MAS such as communication, coordination, decision and cooperation. © 2023 IEEE.

关键词： environmental impact Industry 4.0 smart and green Industry 4.0

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On Configuration Sequences in Feature Models 24

On Configuration Sequences in Feature Models

引用

18th International Working Conference on Variability Modelling of software-Intensive systems, VaMoS 2024

作者： Meixner, Kristof Feichtinger, Kevin Greiner, Sandra Rabiser, Rick Cdl Sqi Ise Tu Wien Austria Crc 1608 Kastel Dependability of Software-intensive Systems Karlsruhe Institute of Technology Germany Software Engineering Group Institute of Computer Science University of Bern Switzerland Cdl VaSiCS Lit Cps Lab Jku Linz Austria

ISBN: (纸本)9798400708770

Feature models are the de-facto standard in product line engineering to capture the commonalities and variability of systems. However, feature models provide little user guidance during configuration and are unable to represent configuration sequences. A configuration sequence refers to the specific order and combination of features that can be selected when configuring a product line. While mechanisms, such as staged configuration and configuration workflows, exist, we argue that the effort to implement these mechanisms does not pay off for small feature models. This paper motivates the use of configuration sequences for feature models to support better user guidance even for a single feature model. We highlight the need for such user guidance and configuration sequences with a real-world use case. © 2024 ACM.

关键词： Configuration Sequence Feature Models User Guidance.

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Using Gamification to Increase Healthcare Professionals’ Cybersecurity Awareness

Using Gamification to Increase Healthcare Professionals’ Cy...

引用

International Conference on Smart Applications and Sustainability in the Artificial Intelligence of Things, SAS-AIoT 2024

作者： Salama, Ramiz Alturjman, Sinem Altrjman, Chadi Al-Turjman, Fadi Department of Computer Engineering AI and Robotics Institute Research Center for AI and IoT Near East University Nicosia Cyprus Artificial Intelligence Software Information Systems Engineering Departments AI and Robotics Institute Near East University Nicosia Cyprus

ISBN: (纸本)9783031782756

Cybersecurity knowledge is essential in today’s increasingly digital healthcare environment to protect sensitive patient data and guarantee the integrity of healthcare systems. But conventional cybersecurity training approaches frequently fail to hold healthcare professionals’ attention, which results in inadequate application and retention of the material. In order to increase cybersecurity awareness among healthcare professionals, this study investigates the use of gamification—a technological technique that incorporates game design aspects into non-gaming contexts—as an innovative method. A mixed-methods research methodology is used in the study to assess the effectiveness of a cybersecurity training program that is gamified. To encourage user involvement and motivation, the program incorporates aspects like leaderboards, interactive scenarios, badges, and points. The study included a total of 100 healthcare professionals from various departments, offering a thorough understanding of the program’s effects across a range of positions and experience levels. Pre- and post-training surveys were used to gather quantitative data on participant changes in knowledge, attitudes, and behaviors pertaining to cybersecurity procedures. Furthermore, semi-structured interviews yielded qualitative insights that further elucidated the participants’ perspectives and experiences with the gamified training method. Comparing gamification to conventional training approaches, the results show that gamification dramatically improves engagement and knowledge retention. The willingness of the participants to acquire and use cybersecurity techniques in their daily lives has reportedly increased. Additionally, the gamified components strengthened the training objectives by fostering a competitive yet cooperative learning environment. The potential of gamification as a game-changing instrument for cybersecurity education in healthcare settings is highlighted by this study. Healthcare busines

关键词： Cybersecurity

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computer-Vision-Based Non-Contact Paste Concentration Measurement*

Computer-Vision-Based Non-Contact Paste Concentration Measur...

引用

2024 International Conference on Automation in Manufacturing, Transportation and Logistics, ICaMaL 2024

作者： Liang, Tailin Yuan, Zhaolin School of Computer Science and Engineering Beihang University State Key Laboratory of Software Development Environment Beijing China Research Institute of Advanced Manufacturing Hong Kong Polytechnic University Department of Industrial and Systems Engineering Hong Kong Hong Kong

ISBN: (纸本)9798350378658

For monitoring the paste concentration, existing techniques, such as ultrasonic concentration meters and neutron meters, suffer from radiation hazards and low precision in high concentrations. This paper proposes a novel non-contact concentration measurement method based on deep learning. With the dataset collected by preparing the paste with different concentrations and taking photographs from the paste surface, a convolutional neural network is trained to extract the features from images and predict the concentration. The experiments indicate that the measurement accuracy is close to 88.79 % for the manual stirring paste dataset and 91.42 % for the automatic stirring paste dataset, which are sufficient in industrial applications. As a substitution of traditional concentration measurement instruments, the proposed vision-based concentration measurement method is non-contact and its accuracy is sufficient in industrial applications. © 2024 IEEE.

关键词： Radiation hazards

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A Sparsifier Model for Efficient Information Retrieval

A Sparsifier Model for Efficient Information Retrieval

引用

International Conference on Application of Information and Communication Technologies (AICT)

作者： Viacheslav Dobrynin Mark Sherman Roman Abramovich Alexey Platonov Faculty of Software Engineering and Computer Systems ITMO University Saint Petersburg Russian Federation

ISBN: (数字)9798350387537

ISBN: (纸本)9798350387544

The constant development of dense neural models leads to improved search quality. It is crucial to adapt these models to meet performance requirements. Solutions like SPLADE or SparseEmbed address this by solving the ranking task, whereas our work proposes addressing the simplified task of sparsifying dense vector representations. This approach facilitates the faster adaptation of new dense models for use with efficient inverted indexes. The importance of the independence property for sparse space features, achieved through the use of iVAE, is demonstrated. Additionally, the model is trained to maintain the ranking properties of the dense model, which in our case was a BERT model. As a result, the obtained model showed search quality close to the original BERT model. The proposed sparsification approach can be applied to other tasks requiring sparse spaces by adding new or replacing existing properties of the sparse space. Thus, the paper describes the main aspects of a sparsifier model applied to the task of information retrieval.

关键词： Adaptation models Information retrieval Transformers Vectors Information and communication technology Indexes

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IoT Based Drip Infusion Monitoring System

IoT Based Drip Infusion Monitoring System

引用

2022 IEEE Delhi Section Conference, DELCON 2022

作者： Maniktalia, Riddhi Tanwar, Satwik Billa, Ritvik Deepa, K. School of Computer Science and Engineering Vellore Institute of Technology Vellore India School of Computer Science and Engineering Vellore Institute of Technology Department of Software Systems Vellore India

ISBN: (纸本)9781665458832

During recent years, we have seen many technological advancements which help to take better care of patient's health and assure them fast and safe recovery. The most basic item necessary is competent patient care in hospitals, as well as proper management of fluid and electrolytes. In hospital almost all patients, mainly ICU patients, have to regulate the volume of fluids and electrolyte into the bloodstream 247 which is done using drip. These drips need regular monitoring or changing to maintain constant flow of fluids or to prevent any infection to patients. Though this system is simple, overcrowded hospitals and the risk of deficiency of nurses can put patients at health risk which can deteriorate patients' health more aggressively or in worse case it can lead to death. Almost in all hospitals, nurses or the hospital staff are responsible for monitoring the drip level. But unfortunately, because of their hectic schedule, the observer may forget to change the bottle at the appropriate time. During the pandemic, hospitals were overrun with patients, and nurses were unable to do manual regular checks on the drip conditions and drip level of every patient, even after working extra shifts. Many patients even died due to not being able to get proper care from nurses. The next step in providing more effective and easy healthcare is to automate such vital procedures. To overcome this critical situation, we are proposing an IoT (Internet of Things) based Drip Monitor System using Arduino UNO which eases the process of measuring and solves the issues of bubble formation in drips. © 2022 IEEE.

关键词： Health risks

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Classification of Helpful and Unhelpful Online Customer Reviews Using XLNet and BERT Variants 1

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International Conference on Green Energy, Computing, and Intelligent Technology, GEn-CITy 2023

作者： Bilal, Muhammad Arshad, Muhammad Haseeb Ramzan, Muhammad Department of Computing and Information Systems School of Engineering and Technology Sunway University Petaling Jaya Malaysia Department of Computer Science National University of Computer and Emerging Sciences Chiniot-Faisalabad Campus Chiniot Pakistan Department of Software Engineering University of Sargodha Sargodha Pakistan School of Electronics and Computer Science University of Southampton Malaysia Iskandar Puteri Malaysia

ISBN: (数字)9789819998333

ISBN: (纸本)9789819998326

The majority of businesses have made public appearances on various social media platforms as a result of recent advances in e-commerce and the popularity of social media websites. Customers can share their experiences in the form of online customer reviews, which can assist potential customers in determining the quality of a company and making purchasing decisions. Due to the large volume of published reviews, it becomes difficult for customers to read all of the reviews and assess the quality of the business, resulting in the problem of information overload. Several solutions have been proposed in the literature by researchers using statistical and machine learning techniques to predict the helpfulness of online customer reviews. However, most of the existing solutions are based on the use of various business, review, and reviewer features, which lead to generalizability issues. Moreover, very limited studies have examined the effectiveness of state-of-the-art pre-trained language models for the classification of helpful and unhelpful reviews. Therefore, this study aims to examine the effectiveness of XLNet, Albert, DistilBert, and Roberta for review helpfulness prediction using textual features. The models were fine-tuned using a publicly available dataset of Yelp reviews. The results showed that XLNet achieved the highest F1-score of 0.730 compared to a benchmark of 0.717 achieved by the BERT base model. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Sales

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