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18th IEEE International Conference on Emerging Technologies, ICET 2023

作者： Bashir, Asima Latif, Niha Khan, Arisha Masood Sohail, Muhammad Mcs National University of Science and Technology Department of Computer Software Engineering Islamabad Pakistan

ISBN: (纸本)9798350328172

Effective requirements gathering and management tools are key factors for sustainable smart cities. These tools enable stakeholders including government officials, private sector partners, and citizens to identify and prioritize requirements, manage changes, and make sure that the product is as per their expectations. In the context of smart cities, these tools must be able to capture the requirements for a wide range of systems, including transport, energy sector, citizens safety, and environment maintenance. Overall, effective requirements gathering and management tools are critical to the success of smart cities, enabling them to be more efficient, sustainable and responsive. With the advent of new technologies, there is a growing need for advanced tools to support the RE process for smart cities. This paper investigates different artificial in-telligence (AI) based requirements gathering and management tools. Amongst those techniques dependent on natural language processing (NLP) and machine learning (ML) in recommendation systems for requirements gathering and ReQtest, ReqSuite, Jama Connect, Visure, Xabrio, and IBM DOORS as management tools have been proposed. Their summarized performance revealed different scores across parameters highlighting their impact as effective tools for smart city paradigm. The study concludes that AI-based techniques and tools can be employed in smart cities, with selection based on project requirements and constraints. © 2023 IEEE.

关键词： Recurrent neural networks

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Internet of Things (IoT) applications security trends and challenges

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Discover Internet of Things 2024年第1期4卷 1-22页

作者： Laghari, Asif Ali Li, Hang Khan, Abdullah Ayub Shoulin, Yin Karim, Shahid Khani, Muhammad Adnan Kaim Software College Shenyang Normal University Shenyang China Department of Computer Science Bahria University Karachi Campus Karachi75000 Pakistan School of Information Engineering Xi’an Eurasia University Shaanxi Xian710065 China Department of Computer Science Ilma University Karachi Pakistan

The idea behind layered design is the foundation of the Internet of Things. Each tier uses a variety of technologies for capacity, preparation, and information transmission. With regard to the risks and vulnerabilities related to IoT-enabled devices, as well as potential assurance mechanisms in light of equipment constraints and novel information transfer techniques, this study attempts to analyze the current architecture of the Internet of Things. After that, we talk about IoT architecture and applications. The following is a list of effective real-time IoT applications that are now in use: Self-driving cars, traffic management systems, smart grids, logistic management hierarchies, environment monitoring, building safety applications, and many more are examples of emerging technologies. Specifically, we highlight the latest improvements and challenges associated with IoT security. Finally, we discuss the state-of-the-art research and its conclusions, as well as the outstanding problems for future IoT security research. © The Author(s) 2024.

关键词： Cloud security

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A survey for light field super-resolution

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High-Confidence Computing 2024年第1期4卷 118-129页

作者： Mingyuan Zhao Hao Sheng Da Yang Sizhe Wang Ruixuan Cong Zhenglong Cui Rongshan Chen Tun Wang Shuai Wang Yang Huang Jiahao Shen State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijing 100191China Key Laboratory of Data Science and Intelligent Computing International Innovation InstituteBeihang UniversityHangzhou 311115China State Key Laboratory of Software Development Environment School of Computer Science and EngineeringBeihang UniversityBeijing 100191China

Compared to 2D imaging data,the 4D light field(LF)data retains richer scene’s structure information,which can significantly improve the computer’s perception capability,including depth estimation,semantic segmentation,and LF ***,there is a contradiction between spatial and angular resolution during the LF image acquisition *** overcome the above problem,researchers have gradually focused on the light field super-resolution(LFSR).In the traditional solutions,researchers achieved the LFSR based on various optimization frameworks,such as Bayesian and Gaussian *** learning-based methods are more popular than conventional methods because they have better performance and more robust generalization *** this paper,the present approach can mainly divided into conventional methods and deep learning-based *** discuss these two branches in light field spatial super-resolution(LFSSR),light field angular super-resolution(LFASR),and light field spatial and angular super-resolution(LFSASR),***,this paper also introduces the primary public datasets and analyzes the performance of the prevalent approaches on these ***,we discuss the potential innovations of the LFSR to propose the progress of our research field.

关键词： Light field super-resolution Convolutional neural network Transformer Sub-aperture image Epipolar-plane image

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"i look like a gorilla, but don't move like one!": Impact of Avatar-Locomotion Congruence in Virtual Reality

"i look like a gorilla, but don't move like one!": Impact of...

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2025 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2025

作者： Khan, Omar Nam, Hyeongil Kim, Kangsoo University of Calgary Department of Computer Science Canada University of Calgary Department of Electrical and Software Engineering Canada

ISBN: (纸本)9798331514846

As virtual reality (VR) continues to expand, particularly in social VR platforms and immersive gaming, understanding the factors that shape user experience is becoming increasingly important. Avatars and locomotion methods play central roles in influencing how users identify with their virtual representations and navigate virtual spaces. However, little is known about the impact of congruence between these two factors. We conducted a user study with 30 participants, employing two avatar types (human and gorilla) and two locomotion methods (human-like arm-swing and gorilla-like arm-roll), to assess the effects of avatar-locomotion congruence. Our results indicate that congruent avatar-locomotion conditions enhance avatar identification and user experience. © 2025 IEEE.

关键词： Gamification

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K Semantics for Security Policy Enforcement on Android Applications with Practical Cases 2nd

K Semantics for Security Policy Enforcement on Android Appli...

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2nd EAI International Conference on Computational Intelligence and Communications, CICom 2021

作者： Ziadia, Marwa Mejri, Mohamed Fattahi, Jaouhar Department of Computer Science and Software Engineering Laval University QuébecQC Canada

ISBN: (纸本)9783031195228

As much as they have positioned Android among the most widely used operating systems, Android applications have helped malware creators to break in and infect its devices. A long list of threats caused by downloaded applications targets the integrity of the system and the privacy of the users. To protect Android users from such applications, we propose a formal environment for security policy enforcement. The main idea is to establish a synergy between the aspect-oriented paradigm and formal methods such as the program rewriting technique. The purpose of our approach is to rewrite the application program by adding control tests at certain carefully selected points to ensure that the security policy is respected. The new version of the program preserves all the good behaviors of the original version that comply with the security policy and acts against the bad ones. The particularity of this approach is that all the steps for security policy enforcement are performed automatically using the K-framework. This semantic engineering framework handles the whole process, from the formal specification of the policy and the program to the enforcement technique. Two practical cases are fully discussed in this paper. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Semantics

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Iterative Segmentation and Propagation Based Interactive Video Object Segmentation

Iterative Segmentation and Propagation Based Interactive Vid...

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2023 International Conference on Algorithm, Imaging Processing, and Machine Vision, AIPMV 2023

作者： Luo, Sihan Yang, Sizhe Yuan, Xia School of Computer Science and Engineering Nanjing University of Science and Technology Jiangsu Nanjing China School of Information and Software Engineering University of Electronic Science and Technology of China Sichuan Chengdu China

ISBN: (纸本)9781510672444

Interactive video object segmentation (iVOS), which aims to efficiently produce high-quality segmentation masks of the target object in a video with user interactions. Recently, numerous works are proposed to advance the task of iVOS. However, their usages on user intent are limited. First, typical modules usually try to direct generate the segmentation without any further exploration on the input interaction, which misses valuable information. Second, recent iVOS approaches also do not consider the raw interactive information. As a result, the final segmentation results will be poisoned by the erroneous information given by the previous round’s segmentation masks. To solve the aforementioned weaknesses, in this paper, an Iterative Segmentation and Propagation based iVOS method is proposed to conduct better user intent exploration, namely ISP. ISP directly models user intent into the PGI2M module and TP module. Specifically, ISP first extracts a coarse-grained segmentation mask by analyzing the user’s input. Subsequently, this mask is used as a prior to aid the PGI2M module. Secondly, ISP presents a new interaction-driven self-attention module to recall the user’s intent in the TP module. Extensive experiments on two public datasets show the superiority of ISP over existing methods. © 2024 SPIE.

关键词： Iterative methods

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Performance Optimization of SAC-OCDMA Network Based on 2-D CS Code Utilizing Two Light Sources 6

Performance Optimization of SAC-OCDMA Network Based on 2-D C...

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6th International Symposium on Advanced Electrical and Communication Technologies, ISAECT 2024

作者： Alayedi, Mohanad Jaradat, Ahmad M. Elgammal, Ziad Malkawi, Malek Haliç University Department of Software Engineering Istanbul Turkey University of Detroit Mercy Department of Electrical and Computer Engineering and Computer Science MI United States Istanbul Medipol University Department of Computer Engineering Istanbul Turkey

ISBN: (纸本)9798331529987

This study introduces a novel 2-dimensional (2D) spectral/temporal code, termed 2D-cyclic shift (2D-CS) code, optimized for non-coherent Spectral Amplitude Coding Optical Code Division Multiple Access (SAC-OCDMA) systems. Computational results demonstrate that the 2D-CS code has fostered the SAC-OCDMA system's performance whence spectral efficiency (SE), phase induced intensity noise (PIIN), and cardinality. Specifically, the 2D-CS code can increase cardinality by up to 117%, 89%, and 61% compared to one-dimensional CS (1D-CS), 2D-multi service (2D-MS), and 2D-diluted perfect difference (2D-DPD) codes, respectively. The system's performance was evaluated using Optisystem software, showing significant improvements in quality factor (QF) and bit error rate (BER) with LED and laser light sources for four active users at 115 dBm transmitted power and 20,000 m distance. © 2024 IEEE.

关键词： Code division multiple access

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From Faces to Traffic Lights: A Multi-Scale Approach for Emotional State Representation 25

From Faces to Traffic Lights: A Multi-Scale Approach for Emo...

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25th IEEE International Conferences on High Performance Computing and Communications, 9th International Conference on Data science and Systems, 21st IEEE International Conference on Smart City and 9th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Nguyen, Minh Yan, Wei Qi Auckland University of Technology Department Computer Science and Software Engineering Auckland New Zealand

ISBN: (纸本)9798350330014

This paper presents an innovative Smart Traffic Light System designed to assess Emotional Expression in enclosed settings such as corporate offices and educational facilities. The system combines artificial intelligence, super-resolution algorithms, and facial recognition to provide both real-time and longitudinal insights into the collective emotional atmosphere. Utilizing a three-tier light indicator, the system visualizes emotional trends in the short-term (immediate), medium-term (daily or weekly), and long-term (semi-annual or annual) contexts, employing a color-coded scheme to denote positive or negative emotional states. This augments situational awareness and contributes to the emotional well-being of individuals in these settings. The underlying technology leverages closed-circuit television (CCTV) footage and introduces a state-of-the-art temporal expression recognition mechanism to capture a broad spectrum of human emotions. A notable innovation is the incorporation of facial super-resolution techniques to enhance the quality of low-resolution facial data, thereby boosting the system's overall accuracy and robustness. This enhancement is accomplished while maintaining adherence to ethical standards for data collection and usage. This system has implications that reach far beyond simple emotional recognition. It serves as a cornerstone for the development of emotionally intelligent smart cities. Providing both immediate feedback and historical data on community emotional states, it enables more informed decision-making, streamlined resource allocation, and ultimately, an improvement in the overall quality of life. This research contributes to the evolving discussion on how smart cities can foster communities that are not just more efficient, but also more emotionally resilient. © 2023 IEEE.

关键词： Smart city

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Deep Learning with a Novel Concoction Loss Function for Identification of Ophthalmic Disease

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computers, Materials & Continua 2023年第9期76卷 3763-3781页

作者： Sayyid Kamran Hussain Ali Haider Khan Malek Alrashidi Sajid Iqbal Qazi Mudassar Ilyas Kamran Shah Department of Computer Science TIMES InstituteMultan60000Pakistan Department of Software Engineering Faculty of Computer ScienceLahore Garrison UniversityLahore54000Pakistan Department of Computer Science Applied CollegeUniversity of TabukTabukSaudi Arabia Department of Information Systems College of Computer Sciences and Information TechnologyKing Faisal UniversityAl Hofuf31982Saudi Arabia Department of Mechanical Engineering College of EngineeringKing Faisal UniversityAl HofufSaudi Arabia

As ocular computer-aided diagnostic(CAD)tools become more widely accessible,many researchers are developing deep learning(DL)methods to aid in ocular disease(OHD)*** eye diseases like cataracts(CATR),glaucoma(GLU),and age-related macular degeneration(AMD)are the focus of this study,which uses DL to examine their *** imbalance and outliers are widespread in fundus images,which can make it difficult to apply manyDL algorithms to accomplish this analytical *** creation of efficient and reliable DL algorithms is seen to be the key to further enhancing detection *** the analysis of images of the color of the retinal fundus,this study offers a DL model that is combined with a one-of-a-kind concoction loss function(CLF)for the automated identification of *** study presents a combination of focal loss(FL)and correntropy-induced loss functions(CILF)in the proposed DL model to improve the recognition performance of classifiers for biomedical *** is done because of the good generalization and robustness of these two types of losses in addressing complex datasets with class imbalance and *** classification performance of the DL model with our proposed loss function is compared to that of the baseline models using accuracy(ACU),recall(REC),specificity(SPF),Kappa,and area under the receiver operating characteristic curve(AUC)as the evaluation *** testing shows that the method is reliable and efficient.

关键词： Deep learning multi-classification focal loss CNN eye disease

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Variational Collective Graph AutoEncoder for Multi-behavior Recommendation 23

Variational Collective Graph AutoEncoder for Multi-behavior ...

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23rd IEEE International Conference on Data Mining, ICDM 2023

作者： Liu, Yang Rao, Qianzhen Pan, Weike Ming, Zhong Shenzhen University College of Computer Science and Software Engineering Shenzhen China Shenzhen China

ISBN: (纸本)9798350307887

Variational autoencoder (VAE) is known as a classic and effective method in modeling users' homogeneous behaviors in recommender systems. In recent years, graph neural networks (GNNs) have achieved promising performance in learning users' preferences by modeling complex relationships between users and items. However, most VAE- and GNN-based methods are for single-behavior recommendation, rather than the more prevalent counterpart in real-world applications, i.e., multi-behavior recommendation. This motivates us to leverage VAE and GNNs to address the more important and challenging problem of multi-behavior recommendation. Traditional multi-behavior recommendation models have not captured the complex transition relationships across different types of behaviors well. Moreover, they often ignore the varying semantic strength of different types of behaviors. To tackle the above two challenges, we propose a novel multi-behavior recommendation framework named VCGAE (short for Variational Collective Graph AutoEncoder), which inherits the advantages of VAE and GNNs to fully exploit the multi-behavior data. Specifically, we design a behavior transition network that considers different transition relationships across different types of behaviors in order to learn users' personal preferences. In addition, we introduce a behavior contrastive regularization module that extracts different correlations between users' auxiliary behaviors and target behavior. By doing so, we gain a deeper understanding of the semantic strength of different behaviors, thereby improving the overall recommendation performance. Extensive experiments on three real-world datasets clearly demonstrate the effectiveness of our VCGAE compared with the state-of-the-art methods. © 2023 IEEE.

关键词： Graph neural networks

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