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2023 International Symposium on Networks, Computers and Communications, ISNCC 2023

作者： Shahin, Nada Ismail, Leila Lab UAE University Department of CS and Software Engineering Al-Ain United Arab Emirates School of Computing and Information Systems CLOUDS Lab The University of Melbourne Melbourne Australia

ISBN: (纸本)9798350335590

ChatGPT is a language model based on Generative AI. Existing research work on ChatGPT focused on its use in various domains. However, its potential for Sign Language Translation (SLT) is yet to be explored. This paper addresses this void. Therefore, we present GPT's evolution aiming a retrospective analysis of the improvements to its architecture for SLT. We explore ChatGPT's capabilities in translating different sign languages in paving the way to better accessibility for deaf and hard-of-hearing community. Our experimental results indicate that ChatGPT can accurately translate from English to American (ASL), Australian (AUSLAN), and British (BSL) sign languages and from Arabic Sign Language (ArSL) to English with only one prompt iteration. However, the model failed to translate from Arabic to ArSL and ASL, AUSLAN, and BSL to Arabic. Consequently, we present challenges and derive insights for future research directions. © 2023 IEEE.

关键词： Audition

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Improving Network Efficiency in Clustered Tree Topology through PSO Optimization in IEEE 802.15.4-DSME based IoT Networks 18

Improving Network Efficiency in Clustered Tree Topology thro...

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18th IEEE International Conference on Advanced Networks and Telecommunications systems, ANTS 2024

作者： Anand, Sonali Choudhury, Nikumani Ojha, Tamoghna Hazarika, Anakhi Dave, Jay Birla Institute of Technology & Science Dept. of Computer Science & Information Systems Pilani Hyderabad India Indian Institute of Technology Indian School of Mines Dept. of Mathematics & Computing Dhanbad India

ISBN: (纸本)9798350391725

The IEEE 802.15.4 standard is designed for low-rate wireless personal area networks (LR-WPANs). Deterministic and Synchronous Multi-channel Extension (DSME) is one of the key Medium Access Control (MAC) modes of the IEEE 802.15.4 standard that was introduced to address the need for higher reliability, lower latency, and better scalability in network communication in Internet of Things (IoT) applications. However, in dynamic network conditions (topology and channel traffic), the network suffers from several limitations, such as low packet delivery ratio, high latency and packet collisions, and finally, higher power consumption. This is because of sub-optimal parameter settings. The standard does not define any mechanism to adapt the parameters based on network conditions. In this paper, we propose a mechanism to adapt/fine-tune the network parameters DSME along with the optimization of QoS using an algorithm based on Particle Swarm Optimization(PSO) for dense and dynamic DSME-based IoT networks. Through simulations, the proposed mechanisms' performance is analyzed in terms of energy efficiency, transmission overhead, throughput, and latency and is shown to outperform the existing DSME MAC scheme. © 2024 IEEE.

关键词： Internet of things

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Social Enterprise Logic and the Sustainability of Community Networks in Sub-Sahara Africa: Lessons from the Zaria Community Network in Nigeria 28

Social Enterprise Logic and the Sustainability of Community ...

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28th Americas Conference on information systems, AMCIS 2022

作者： Tata, Auwal Alhassan Avemaria Utulu, Samuel C. Department of Information Systems School of Information Technology and Computing American University of Nigeria Adamawa State Yola Nigeria

ISBN: (纸本)9781958200001

Abstract: There are conflicting views about how social enterprise logic impacts community networks' sustainability (CNs). Some authors believe that running with the social enterprise logic spells doom on CNs. Conversely, some believe that it does not necessarily spell doom on CNs. However, CNs, particularly those implemented in sub-Saharan Africa, cannot be implemented with an alternative logic, such as the for-profit business logic. Consequently, there is a need to develop a framework for making CNs sustainable, although they run with the social enterprise logic. This research develops a framework that will enable those involved in CN implementation in sub-Saharan Africa to understand how to instil sustainability factors into every stage of CN implementation. The study uses the Zaria Community Network (ZCN), Zaria, Nigeria, as a case study and adopts the inductive approach. The study data were derived from the chat messages from a WhatsApp group used as a platform for communication by those implementing the ZCN and from secondary sources. The study findings revealed that sustainable participation was a primary factor that comes to bear in the sustainability of the ZCN. It also revealed how sustainable participation influences sustainable infrastructure, sustainable stakeholders' support, and sustainable funding. We conclude that the framework helps implement sustainable CNs in sub-Saharan Africa and other regions with similar socio-technical similarities. © 2022 28th Americas Conference on information systems, AMCIS 2022. All Rights Reserved.

关键词： Sustainable development

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Automatic Deployment to Kubernetes Cluster by Applying a New Learning Tool and Learning Processes 10

Automatic Deployment to Kubernetes Cluster by Applying a New...

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10th Workshop on software Quality Analysis, Monitoring, Improvement, and Applications, SQAMIA 2023

作者： Golis, Tomáš Dakić, Pavle Vranić, Valentino Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology in Bratislava Ilkovičova 2 Bratislava842 16 4 Slovakia Faculty of Informatics and Computing Singidunum University Danijelova 32 Belgrade Serbia

The rapid growth and widespread adoption of containerization technologies, such as Docker, and the increasing popularity of Kubernetes as a container orchestration platform have significantly shaped the landscape of modern software development and deployment. Containers have created a paradigm shift in application packaging, offering a consistent and portable environment across diverse infrastructure setups. Meanwhile, Kubernetes has emerged as the dominant choice for managing containerized applications at scale, providing features such as automated scaling, load balancing, and fault tolerance. However, despite the numerous advantages containers and Kubernetes offer, deploying applications to a Kubernetes cluster often poses challenges due to the steep learning curve and complex configuration requirements. To address these challenges, this paper aims to introduce a comprehensive learning tool that automates and simplifies the deployment process on Kubernetes clusters. © 2023 Copyright for this paper by its authors.

关键词： CI/CD Container orchestration Docker image Kubernetes

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Visual-Text Cross Alignment: Refining the Similarity Score in Vision-Language Models

arXiv

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arXiv 2024年

作者： Li, Jinhao Li, Haopeng Erfani, Sarah M. Feng, Lei Bailey, James Liu, Feng School of Computing and Information Systems University of Melbourne Australia Information Systems Technology and Design Pillar Singapore University of Technology and Design Singapore

MSC Codes 68T45, 68T10It has recently been discovered that using a pretrained vision-language model (VLM), e.g., CLIP, to align a whole query image with several finer text descriptions generated by a large language model can significantly enhance zero-shot performance. However, in this paper, we empirically find that the finer descriptions tend to align more effectively with local areas of the query image rather than the whole image, and then we theoretically validate this finding. Thus, we present a method called weighted visual-text cross alignment (WCA). This method begins with a localized visual prompting technique, designed to identify local visual areas within the query image. The local visual areas are then cross-aligned with the finer descriptions by creating a similarity matrix using the pre-trained VLM. To determine how well a query image aligns with each category, we develop a score function based on the weighted similarities in this matrix. Extensive experiments demonstrate that our method significantly improves zero-shot performance across various datasets, achieving results that are even comparable to few-shot learning methods. The code is available at ***/tmlr-group/WCA. © 2024, CC BY.

关键词： Image enhancement

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AI and Machine Learning Based E - Learning System For Secondary Education 7

AI and Machine Learning Based E - Learning System For Second...

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7th IEEE International conference for Convergence in technology, I2CT 2022

作者： Wijayawardena, G.C.S. Subasinghe, S.G.T.S. Bismi, K.H.P. Gamage, Anjalie Sri Lanka Institute of Information Technology Faculty of Computing Department of Information Systems Engineering Malabe Sri Lanka

ISBN: (纸本)9781665421683

One of the key functions directly shifted to online platforms under COVID-19 is education. The paper is about an E-learning system for secondary education in Sri Lanka. Learners and teachers can access information, resources, and tools through an E-Learning system, which is a Learning Management System that integrates a number of online activities. The main functions provided through the proposed system are chatbot, final grade prediction and weak area prediction of the students. Chatbots are becoming increasingly popular in a wide range of applications, especially in those that provide intelligence support to the user, according to recent research. So, in order to speed up the aid process, these systems are often integrated with Chatbots, which can quickly and accurately read the user's questions. This paper describes the implementation of a Chatbot prototype in the educational domain: a system for providing support to students. In the beginning, the goal was to design a special architecture and communication model that would help students get the proper answers. The final grade prediction component plays major role in the system. Because when the students are graded by their marks, they can review which areas that they have to improve and work on them. This is helpful for students as well as teachers. Weak area prediction also plays a significant role, because it can help to find out the weak areas of each subject and generate Individual Student Progress Plans to predict the students' weak subjects and the subject areas of the students. This motivates students to get higher marks easily because this part is mainly focused on weak areas of students and improve those weak areas by providing several learning activities. These are the major parts of this system to have a good E-learning system for both students and Teachers. © 2022 IEEE.

关键词： Students

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Financial Sustainability of Automotive software Compliance and Industry Quality Standards 8th

Financial Sustainability of Automotive Software Compliance ...

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8th International Congress on information and Communication technology, ICICT 2023

作者： Dakić, Pavle Todorović, Vladimir Vranić, Valentino Faculty of Informatics and Computing Singidunum University Belgrade Serbia Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology in Bratislava Bratislava Slovakia Faculty of Business Studies and Law MB University Belgrade Serbia

ISBN: (纸本)9789819930906

Achieving a high level of quality in the AV industry involves understanding the complexity of the production cycle with the constant challenges of applying appropriate standards. The need for compliance based on relevant certificates implies the creation of an environment of trust between manufacturers, component suppliers, and end customers. Research should sublimate the most current standards from various fields related to data protection, security, system sustainability, environmental management, financial sustainability, and business transparency. The success of a complex parts supply system is impossible without a stable approach to IT security. The control of production processes sometimes involves using non-standardized techniques, and one of the applicable ones is work-in-progress (WIP), which describes the use of partially finished raw materials in the stages of obtaining final products. Key points and the contribution of the current study are in getting a better overview of the situation within this area related to standards and the financial problems that can arise due to a lack of understanding of standards compliance. The main limitations within the study itself refer to the consideration of the theoretical foundations that should be used during future research related to the practical part during implementation. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Automotive industry

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Towards Modeling Functional Requirements From Tacit Knowledge

Towards Modeling Functional Requirements From Tacit Knowledg...

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2023 Congress in Computer Science, Computer Engineering, and Applied computing, CSCE 2023

作者： Jafar, Rameen Almufareh, Maram Fahaad Ashraf, Sundas Khan, Bushra Butt, Wasi Haider Humayun, Mamoona National University of Sciences and Technology Department of Computer and Software Engineering Pakistan College of Computer and Information Sciences Jouf University Department of Information Systems Sakakah Saudi Arabia

ISBN: (纸本)9798350327595

Requirements Elicitation is the process of identifying system needs by talking with stakeholders who have a direct or indirect effect on the requirements. Requirements may be derived from several sources and are one of the most important phases of requirement engineering. We need to perform different elicitation techniques to find out the user's needs. Pre-requirements tracing is the process of determining the origins of a specific demand. Typically, certain needs arise that have no apparent source, but stakeholders will testify to their importance. Such criteria, however, are most likely dependent on tacit or tacit-like information entrenched in the issue domain. Tacit knowledge is one of the most common challenges for requirement analysts. This study contributes to constructing a systematic literature review for exploring multiple ways to model functional requirements using tacit knowledge. We have identified and analyzed 10 studies. In these research papers, different authors have discussed different methods to gather functional requirements from tacit knowledge. © 2023 IEEE.

关键词： Elicitation Techniques Requirement Engineering Tacit-knowledge

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Sample-specific Masks for Visual Reprogramming-based Prompting

arXiv

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arXiv 2024年

作者： Cai, Chengyi Ye, Zesheng Feng, Lei Qi, Jianzhong Liu, Feng School of Computing and Information Systems The University of Melbourne Australia Information Systems Technology and Design Pillar Singapore University of Technology and Design Singapore

Visual reprogramming (VR) is a prompting technique that aims to re-purpose a pre-trained model (e.g., a classifier on ImageNet) to target tasks (e.g., medical data prediction) by learning a small-scale pattern added into input images instead of tuning considerable parameters within the model. The location of the pattern within input samples is usually determined by a pre-defined mask shared across all samples. In this paper, we show that the shared mask potentially limits VR’s generalization and increases its approximation error due to the lack of sample-level adaptation. Motivated by this finding, we design a new framework for VR called sample-specific multi-channel masks (SMM). Specifically, SMM employs a lightweight ConvNet and patch-wise interpolation to generate sample-specific three-channel masks instead of a shared and pre-defined mask. Since we generate different masks for individual samples, SMM is theoretically shown to reduce approximation error for the target tasks compared with existing state-of-the-art VR methods. We also empirically demonstrate its performance gain on both ResNet and ViT. The success of SMM further highlights the broader applicability of VR in leveraging the latent knowledge of pre-trained models for various target tasks. Our code is available at https://***/tmlr-group/SMM. © 2024, CC BY.

关键词： Knowledge management

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Establishing Pattern Sequences Using Artificial Neural Networks with an Application to Organizational Patterns 10

Establishing Pattern Sequences Using Artificial Neural Netwo...

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10th Workshop on software Quality Analysis, Monitoring, Improvement, and Applications, SQAMIA 2023

作者： Matovič, Viktor Vranić, Valentino Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology in Bratislava Ilkovičova 2 Bratislava84216 4 Slovakia

Explicit relationships included in textual description of patterns are insufficient to establish pattern sequences. This article brings a new method of establishing pattern sequences using artificial neural networks. The method is based on extracting implicit relationships between organizational patterns using the softmax regression model by Zhang et al., which are learned by the artificial neural network and encoded in its weights. The implementation of the method is based on the mini-batch stochastic gradient descent method by Zhang et al. and the Keras application programming interface of the TensorFlow framework. To evaluate the method, we conducted four experiments on selected organizational patterns documented by Coplien and Harrison. Two pattern sequences were established in each experiment. For each pattern sequence, a pattern story was created in order to check its meaningfulness. © 2023 Copyright for this paper by its authors.

关键词： artificial neural networks organizational pattern pattern relationships pattern sequence softmax regression

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