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A Post-benchmarking Framework Towards Evaluating and Ranking Deep Learning Models for Breast Cancer Detection Using Hybrid MCDM 3rd

A Post-benchmarking Framework Towards Evaluating and Ranking...

引用

3rd International Conference on Network Security and Blockchain Technology

作者： Gupta, Aditya Kumar, Ravi Kumar, Rupesh Roychowdhury, Saptarshi Singh, Binod Kumar NIT Jamshedpur Dept Comp Sci & Engn Jamshedpur Bihar India

ISBN: (纸本)9789819780501;9789819780518

In the modern digital society, the deep learning models are used by researchers for detection of human breast cancer. Those models are initially tested on various standard datasets. The performance of those detection models is measured by the test results and pre-defined metrics. On the other hand, Multi-criteria DecisionMaking (MCDM) algorithms are also used together to enhance the performance of breast cancer detection methods by effective decision-making. To find the performance of significant deep learning models for efficient detection of breast cancer, benchmarking methods are executed by the researchers on standard datasets. As the benchmarking methods generate data of various metrics, it becomes difficult to find out suitable deep learning model for this purpose. This study introduces a complete methodology for post-benchmarking, specifically developed to evaluate and rank four significant deep learning models used in the detection of breast cancer. By utilizing a comprehensive benchmark dataset, we systematically assess the performance of the models through the application of well-established measures. In order to optimize the decision-making process, two different MCDM methodologies are utilized together, namely, the first one is Analytic Hierarchy Process (AHP) and the other one is Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Findings of our study reveal the advantages and disadvantages of each model, offering a great resource for professionals and scholars in the field to make informed decisions when choosing the most effective deep learning approaches for detection of breast cancer.

关键词： Breast cancer detection Deep learning MCDM AHP TOPSIS

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Zero Trust Network Access (ZTNA) Architecture: A Novel Perspective to Cloud Security 3rd

Zero Trust Network Access (ZTNA) Architecture: A Novel Persp...

引用

3rd International Conference on Network Security and Blockchain Technology

作者： Das, Priyanka Ray, Sangram Govil, Mahesh Chandra Natl Inst Technol Sikkim Dept Comp Sci & Engn Ravangla 737139 Sikkim India

ISBN: (纸本)9789819780501;9789819780518

Cloud computing is the development drift of the IT industry. This modern cloud computing has grabbed remarkable attention in recent days owing to its high-quality on-demand service accessibility and flexible nature. It not only has huge advantages but also has numerous security shortcomings that no organization can afford to overlook. The security perspective of cloud computing infrastructure is often viewed to be the prime element, as data and services of the cloud are not confined to a single organization. Therefore, cloud security plays a crucial role to establish trust among the cloud service providers and the multiple cloud service consumers. Subsequently, trust management ensures both security and privacy in the cloud computing infrastructure. However, in the traditional cloud computing infrastructure all the cloud entities once authorized can get access to the cloud services throughout the life cycle of the session. As a result, it is vulnerable to insider attack. Therefore, in this paper, we have proposed a Zero Trust Network Access (ZTNA) architecture that intends to continuously verify a cloud entity throughout the lifecycle of the session, regardless of the fact that the entity is inside/outside the cloud computing infrastructure. Further, we have analyzed the security aspects of the proposed architecture that ensure our architecture is well-secured against relevant security attacks.

关键词： Cloud computing Security Privacy Trust Computing resources

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Chat GPT in Supporting Education Instruction Sector: An Empirical Literature Review 9th

Chat GPT in Supporting Education Instruction Sector: An Empi...

引用

9th International Congress on Information and Communication Technology (ICICT)

作者： Tan, Azlini Anuar Huda, Miftachul Rohim, Moh Abdul Hassan, Tuan Rusmawati Raja Ismail, Azman Siregar, Maragustam Univ Pendidikan Sultan Idris Fac Commun & Language Tanjong Malim 35900 Malaysia Univ Pendidikan Sultan Idris Fac Human Sci Tanjong Malim 35900 Malaysia Univ Malaysia Kelantan Malaysia Fac Language Studies & Human Dev Kota Baharu 16100 Kelantan Malaysia Natl Acad Arts Culture & Heritage Kuala Lumpur 50480 Malaysia Univ Islam Negeri Sunan Kalijaga Yogyakarta 55281 Indonesia

ISBN: (纸本)9789819750344;9789819750351

ChatGPT technology has the potential to provide several benefits for an educational institution, including increasing engagement, collaboration, and student accessibility. The further innovations emerged in the development of education, such as strengthening students' writing abilities in schools or universities as a new learning approach. Not many studies are trying to elaborate more on looking into detail about supporting or disturbing. In order to maximize the benefits of adopting ChatGPT while addressing existing constraints, it is imperative to carry out ongoing research and development. GPT Chat technology can support and enhance the learning process, both individually and collectively. As such, this paper aims to examine the chat GPT in education instruction sector, supporting or disturbing pathway. The finding revealed that this concept has the potential to be a valuable tool both in the classroom and in self-study situations outside of the classroom.

关键词： Chat GPT Education instruction sector Supporting Disturbing

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Real-Time AI and IoT-Based systems for Home Monitoring 9th

Real-Time AI and IoT-Based Systems for Home Monitoring

引用

9th International Congress on Information and Communication Technology (ICICT)

作者： Alex, Adoumadji Benoudjita Hanyurwimfura, Damien Bakunzibake, Pierre Univ Rwanda UR African Ctr Excellence Internet Things ACE IoT Kigali Rwanda

ISBN: (纸本)9789819754403;9789819754410

The global significance of home security has escalated in recent years due to the surging demand for improved safety measures. Many residential properties lack adequate security measures, resulting in an increased occurrence of unauthorized access and theft. Contemporary security systems employ motion detectors and cameras, but they grapple with distinguishing between authorized individuals and potential intruders. Consequently, these systems often fail to identify and report suspicious activities to homeowners or relevant authorities. This study aims to design and implement an innovative residential security system that leverages artificial intelligence (AI) and Internet of Things (IoT) technologies. This novel system integrates object detection algorithms with camera technology to fortify residential security measures. Unlike traditional systems, this technology excels at detecting human movement, prompting camera activation for recording and image capture, thereby bolstering home security. Advanced AI models, such as deep learning, analyze various aspects, including movement patterns, gestures, and photographs, to differentiate between household members, guests, and potential intruders. By utilizing a convolutional neural network (CNN) algorithm, the system enhances its ability to identify trespassers while reducing false alarms. Through visual surveillance, the security camera distinguishes between authorized individuals and unauthorized trespassers. The study's goal is to enhance residential security by offering unmatched reliability, convenience, and efficiency. The primary aim of this system is to augment domestic security through the precise identification of authorized and unauthorized individuals and the prompt notification of homeowners and authorities regarding any suspicious activities, such as break-ins or intrusions.

关键词： Artificial intelligence Internet of things Home security systems Deep learning Convolutional neural networks and cloud computing

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Unmasking the Threat: Analyzing and Mitigating SMS Smishing Attacks 1

引用

9th International Congress on Information and Communication Technology (ICICT)

作者： Blancaflor, Eric B. Cruz, Ken Jeremy R. Monta, France Junnifer C. Flores, Paolo E. Mapua Univ Sch Informat Technol Manila Philippines

ISBN: (数字)9789819754410

ISBN: (纸本)9789819754403;9789819754410

The increasing use and dependency on mobile devices and the widespread usage of Short Message Service or SMS communication have given rise to a new cybersecurity challenge: SMS phishing, informally known as "Smishing." Cybercriminals today use text messages to trick people into giving out personal information, downloading harmful software, or engaging in actions that compromise their digital security. This paper presents a research effort to uncover the complexities of smishing, analyze its tactics, outline the consequences for victims, and offer practical strategies to mitigate this evolving security threat. The effects of smishing are severe and have repercussions. Individuals who fall victim to these attacks may experience data breaches, identity theft, financial losses, and damage to their personal and professional reputations. Besides the visible losses, the emotional toll of being deceived and having one's personal information compromised can be significant.

关键词： SMS Smishing Mitigate Smishers

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Designing and Deploying Blockchain with Truffle and Smart Contracts 3rd

Designing and Deploying Blockchain with Truffle and Smart Co...

引用

3rd International Conference on Network Security and Blockchain Technology

作者： Kaur, Samandeep Singh, Jaswinder Punjabi Univ Patiala Dept Comp Sci & Engn Patiala Punjab India

ISBN: (纸本)9789819780501;9789819780518

The immutability and veracity of blockchain transactions in the digital world have propelled it to the forefront of next-generation financial technology. It adds safety features like hashing and encryption in addition to authenticating peers who are exchanging virtual currency. Global finance sector forecasts put the blockchain market value at $469.49B by 2030. Additionally, blockchain-related uses are growing quickly. Also, blockchain-related applications are expanding at a rapid pace. Security issues, such as blockchain settlement, transaction security, wallet security, etc., are outlined in depth in this paper, which is written in response to the fast growth of blockchain as a form of cyber money. Smart contracts are deployed using Truffle and Ganache framework. This paper adds the implementation and advantages that smart contracts and blockchain bring in an integrated manner in terms of security.

关键词： Blockchain Ethereum Ganache Truffle Smart contracts

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Estimation of Energy Consumption in Case of a Special Off-Road Vehicle for People with Special Needs 20th

Estimation of Energy Consumption in Case of a Special Off-Ro...

引用

20th Transport systems Theory and Practice Conference

作者： Sierpinski, Grzegorz Staniek, Marcin Silesian Tech Univ Fac Transport & Aviat Engn Katowice Poland

ISBN: (纸本)9783031857508;9783031857515

Transport solutions in cities are improving and opening up to people with special needs. Increasingly, you can see low-floor buses, and specially profiled pavements and platforms for public transport stops. These changes concern the needs of traveling in cities and pursuing selected life activities. However, traveling outside the city for tourist purposes and communing with nature with a sense of being able to overcome the trail on your own is a challenge and a significant barrier. The article presents concept of overcome exclusion barrier of mountain trails travelling for people with special needs. To realize travel by the new electric vehicle model of energy consumption is needed. Proposed research approach to estimate model parameters has been also described.

关键词： Energy consumption people with special needs mountain tourism transport accessibility spatial analysis

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Assessing BERT Models for Arabic Named Entity Recognition in a Multi-dialectal Context 3rd

Assessing BERT Models for Arabic Named Entity Recognition in...

引用

3rd International Conference on Language Processing and Knowledge Management-LPKM

作者： Kessentini, Bassem Alimi, Tahar Boujelben, Rahma Belguith, Lamia Hadrich Univ Sfax ANLP Res Grp MIRACL Lab FSEGS Sfax Tunisia

ISBN: (纸本)9783031850660;9783031850677

Named Entity Recognition (NER) is a crucial task in Natural Language Processing (NLP), enabling the identification of key entities within texts such as names, locations, and organizations. However, for Arabic, this task is particularly challenging due to its rich morphology, complex syntax, and diverse dialects. This study addresses these challenges by fine-tuning AraBERTv2, a BERT-based model specifically designed for Arabic. We prepare a diverse dataset that covers both Modern Standard Arabic (MSA) and various regional dialects, ensuring broad linguistic coverage. Our results show that the fine-tuned model achieves an F1 Score of 0.859, demonstrating its robustness across different Arabic text forms.

关键词： Arabic Named Entity Recognition (NER) Transformer Models BERT for NLP Cross-Dialectal NER

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Insights into Quantitative Evaluation Techniques for AI Explainability 21st

Insights into Quantitative Evaluation Techniques for AI Expl...

引用

21st International Symposium on Distributed Computing and Artificial Intelligence

作者： Gomes, Hugo Ferreira, Joao Rodrigues, Manuel Univ Minho LASI ALGORITMI Ctr Braga Portugal

ISBN: (纸本)9783031820724;9783031820731

The field of Artificial Intelligence (AI) has seen an exponential growth in recent years, with new models being created that achieve almost human-level accuracy in various tasks. However, this increase in accuracy sacrifices a key aspect for critical fields like medicine and finance, which is interpretability. This led to the rise of Explainability in Artificial Intelligence (XAI), which works towards giving more trustworthiness and transparency to these black-box models by generating explanations that translate the decision-making process of these models. One of the posing challenges in this field is to properly quantitatively evaluate these XAI methods due to limited research. This systematic review gives an overview of the current trends in the state-of-the-art for quantitative evaluation methods for evaluating XAI methods, giving more insight on what a good explanation should be and what properties it should meet. Then, we propose an evaluation benchmark based on the reviewed literature, comprising the properties we deemed most important to be met by an explanation. Finally, we present the limitations and challenges this field still poses and directions for future research.

关键词： Explainability in Artificial Intelligence XAI Quantitative evaluation

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PochIoT: Design and Implementation of an IoT-Based System for Tank Barrel Inspection 9th

PochIoT: Design and Implementation of an IoT-Based System fo...

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9th International Congress on Information and Communication Technology (ICICT)

作者： Rivadeneira, Franco Ruiz, Sebastian Santos, Felix Balbuena, Jose Pontif Catholic Univ Peru Lima Peru

ISBN: (纸本)9789819754403;9789819754410

The inspection of confined spaces has been a common area of interest for various studies. However, the inspection of tank barrels and the management of the data obtained using current cloud technologies is a topic that has not been fully explored. Regarding the information collected by a tank barrel inspection robot belonging to entities such as the army, it needs to be stored and shared with a high level of security. Hence, this study proposes the design and implementation of a tank barrel inspector system focusing on data ingesting and storing on a database. As a result of the design and implementation, the objective of storing the data on a safety database using Amazon Web Services was achieved successfully.

关键词： Tank inspection IoT Communications AWS

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