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6th International Conference on Cybernetics, Cognition and Machine Learning Applications, ICCCMLA 2024

作者： Voigt, Frederic Calero, Jose Alcarez Dahal, Keshav Wang, Qi Luck, Kai Von Stelldinger, Peer University of the West of Scotland United Kingdom Hamburg University of Applied Sciences Department of Computer Science Hamburg Germany University of the West of Scotland School of Computing Engineering & Physical Sciences Paisley United Kingdom

ISBN: (纸本)9798331505790

Large language models (LLMs) have demonstrated remarkable success in the field of natural language processing (NLP). Despite their origins in NLP, these algorithms possess the theoretical capability to process any data type represented in an NLP-like format. In this study, we use stock data to illustrate three methodologies for processing regression data with LLMs, employing tokenization and contextualized embeddings. By leveraging the well-known LLM algorithm Bidirectional Encoder Representations from Transformers (BERT) [1], we apply quantitative stock price prediction methodologies to predict stock prices and stock price movements, showcasing the versatility and potential of LLMs in financial data analysis. © 2024 IEEE.

关键词： Prediction models

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Modified pentagonal fractal antenna for ultra-wideband applications in communication systems

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International Journal of Electronics Letters 2024年第4期12卷 413-421页

作者： Singh, Gurmeet Kumar, Ashish Jit Singh, Mandeep Singh, A.P. School of Computing Science and Engineering Galgotias University Greater Noida India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Department of Electrical Electronic and Systems Engineering Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia UKM Selangor Bangi Malaysia Department of Electronics and Communication Engineering Sant Longowal Institute of Engineering and Technology Punjab Longowal India

Due to the recent expansion in the generations of the communications systems, it is utmost priority to transmit a large amount of data over a wideband frequency spectrum. For this single ultra-wideband (UWB) antennas are the prime choice as compared to the multiple narrow band antennas. A modified pentagonal fractal patch antenna with a modified ground plane covering ultra-wideband has been proposed. The antenna has a compact size of 25 mm × 25 mm × 1.6 mm with peak gain of 2.2 dB. The UWB coverage of the design is achieved by implementing modified co-planar ground, modified fractal geometry and coplanar feed. The proposed design possesses the significant resonance and radiation performance with very compact size on low-cost substrate while covering the whole UWB. Finally, the simulated resonating and radiation characteristics have been validated with the measured characteristics of the fabricated prototype and the results are quite promising. © 2024 Informa UK Limited, trading as Taylor & Francis Group.

关键词： antenna co-planer feed fractal Ultra-wideband

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3D printing of PEEK–cHAp scaffold formedical bone implant

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Bio-Design and Manufacturing 2021年第1期4卷 44-59页

作者： Bankole I.Oladapo SAbolfazl Zahedi Sikiru O.Ismail Francis T.Omigbodun Oluwole K.Bowoto Mattew A.Olawumi Musa A.Muhammad School of Engineering and Sustainable Development De Montfort UniversityLeicesterUK Centre for Engineering Research School of PhysicsEngineering and Computer ScienceUniversity of HertfordshireHatfieldUK Mechanical Engineering Loughborough UniversityLoughboroughUK Faculty of Engineering Computing and mediaDe Montfort UniversityLeicesterUK Faculty of Engineering Environment and ComputingCoventry UniversityCoventryUK

The major drawback associated with PEEK implants is their biologically inert surface,which caused unsatisfactory cellular response and poor adhesion between the implants and surrounding soft tissues against proper bone *** this study,polyetheretherketone(PEEK)was incorporated with calcium hydroxyapatite(cHAp)to fabricate a PEEK-cHAp biocomposite,using the fused deposition modeling(FDM)method and a surface treatment strategy to create microporous architectures onto the filaments of PEEK lattice ***,nanostructure and morphological tests of the PEEK-cHAp biocomposite were modeled and analyzed on the FDM-printed PEEK-cHAp biocomposite sample to evaluate its mechanical and thermal strengths as well as in vitro cytotoxicity via a scanning electron microscope(SEM).A technique was used innovatively to create and investigate the porous nanostructure of the PEEK with controlled pore size and distribution to promote cell penetration and biological integration of the PEEK-cHAp into the *** vivo tests demonstrated that the surface-treated micropores facilitated the adhesion of newly regenerated soft tissues to form tight implant-tissue interfacial bonding between the cHAp and *** results of the cell culture depicted that PEEK-cHAp exhibited better cell proliferation attachment spreading and higher alkaline phosphatase activity than PEEK *** islands formed on the PEEK-cHAp composite after immersion in simulated body fluid of Dulbecco’s modified Eagle medium(DMEM)for 14 days and grew continuously with more or extended *** microstructure treatment of the crystallinity of PEEK was comparatively and significantly different from the PEEK-cHAp sample,indicating a better treatment of *** in vitro results obtained from the PEEK-cHAp biocomposite material showed its biodegradability and performance suitability for bone *** study has potential applications in the field of biomedical engineering to strengthen the conceptual kn

关键词： 3D printing PEEK-cHAp biocomposite Nanostructure Bone implant Composite morphing

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Blockchain Based Verification of Educational and Professional Certificates

Blockchain Based Verification of Educational and Professiona...

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International Conference on Computational Systems and Communications (ICCSC)

作者： Anjali Singh SPS Chauhan Amit Kumar Goel Master of Technology in Computer Science and Engineering School of Computing Science and Engineering Galgotias University Greater Noida India School of Computing Science and Engineering Galgotias University Greater Noida India

Educational Documents and Certificates are a proof of professional achievements for anyone. Without these documents, it is not possible to start your career and hence play a very important role in everyone's professional life. Till date, Colleges, Universities and various educational institutes issue paper based degrees and certificates which are prone to get damaged or may be lost. The other drawback is that this process of issuing of degrees and manual process of verification of those documents by third parties is a time taking and cumbersome process. The employers take a lot of time for verifying these paper based degrees and certificates before they give the job offer. Forgery of paper based documents is also easier and has led to many educational scams. This paper aims to give the solution to the problems mentioned above through Blockchain Implementation. Block chain technology is not only limited to crypto currencies but is also of great applications in various fields like health, supply chain management, finance, etc. It has disrupted the traditional education system. This paper highlights as to how the educational certificates can be verified using the Ethereum platform and smart contracts. The traditional paper certificates would be converted to digital certificates on student's request, their hash value would be calculated using cryptographic hash functions and stored on Blockchain. A unique certificate ID and transaction hash value would be generated which would then be used to verify the certificates through a common platform.

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An Effective Analysis of Proficient Two Level Security Contraptions for Loading Data in Cloud 1

An Effective Analysis of Proficient Two Level Security Contr...

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1st IEEE International Conference on Innovations in High Speed Communication and Signal Processing, IHCSP 2023

作者： Arulkumaran, G. Jayagopalan, Santhosh Thanga Mariappan, L. Balamurugan, P. School of Computing and Information Technology REVA University Bengaluru India British Applied College Department of Computing Umm Al Quwain United Arab Emirates School of Information Technology and Engineering Vellore Institute of Technology Vellore Department of Smart Computing Vellore Dist Tamil Nadu India School of Computing SRM Institute of Science and Technology Department of Networking and Communications Chengalpattu Dist Tamil Nadu Kattankulathur India

ISBN: (纸本)9798350345957

One of the cornerstones of the future generation of computing is cloud computing, a form of internet-based computing. It allows for the instantaneous allocation of Internet-accessible resources whenever they are needed. Services such as software as a service (SaaS), platform as a service (PaaS), and infrastructure as a service (IaaS) are made available to people and businesses through cloud computing. By giving customers a low-cost, scalable, and financially-independent place to store their data, cloud storage services have seen rapid revenue growth in recent years. An interoperable cloud computing system is built on open architectures and interfaces that support both private and public cloud services. Many businesses today are making the switch to the cloud because of the numerous advantages it offers in terms of data storage, retrieval, management, and availability. While cloud computing is receiving a lot of attention, it is imperative that security problems be addressed first. This study proposes a crypto-stegno mechanism in the cloud as a solution to cloud security problems. This study proposes a practical method for ensuring data privacy and security in cloud storage. In order to obtain their own public and private key, users must first register their information in the cloud and come up with a unique username and password. Cryptography, a means of concealing information and sending information in an unreadable format, is employed in the next level of security. Secure data transmission and storage on the web, electronic commerce, digital media privacy, and ATM transfer are all dependent on cryptography to some degree. Repudiation, integrity, authenticity, and confidentiality are all possible using today's cryptographic methods. Signcryption is a lightweight cryptographic system that combines encryption and signatures in a logical way to achieve higher security with less computing time. © 2023 IEEE.

关键词： Cryptography

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Decentralized Vehicle Legitimacy Verification for Toll Gate Using Blockchain

Decentralized Vehicle Legitimacy Verification for Toll Gate ...

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Next Generation Communication & Information Processing (INCIP), International Conference on

作者： D.R. Deekshith Prabhava Vishwananda Murthy Pulipaka Sai Praneeth Yadav Madda G. Loka Raghavendra P. Gouthaman Department of Networking and Communications School of Computing College of Engineering and Technology SRM Institute of Science and Technology Kattankulathur India Department of Networking and Communications Faculty of Engineering and Technology School of Computing SRM Institute of Science and Technology India

ISBN: (数字)9798331528140

ISBN: (纸本)9798331528157

As we know Vehicle registration number plate plays a key role in verifying the identity of a vehicle, it is mandatory and crucial for every Automobile. On the other hand, the existing toll system does not verify the legitimacy of a car whether the number plate is original or a duplicate one. So, this paper aims to propose an innovative solution for this problem that deals with inspecting a number plate while a vehicle passes through the toll gate. We use blockchain technology which stores the transaction of a vehicle after it is proven as the legal one. Our approach follows that while registering the vehicle at the office we provide a unique code and store that unique along with the owner details and we integrate that code in the number plate as RFID, we only do this once while registering afterward it can't be tampered with. When a vehicle passes through toll we scan and retrieve the unique code and verify whether it exists in our database. If it exists, the Vehicle is legitimate. If we can't extract the unique code from the number plate, then it is a duplicate one. If it is legal the transaction will be processed as usual, and the block of transaction will be added to the existing blockchain network. To summarise this paper demonstrates a solution that is reliable, and secure and reduces fraud activities that lead to scandal.

关键词： Hands Codes Information processing Logic gates Blockchains Automobiles Security Reliability License plate recognition Radiofrequency identification

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Research challenges of Blockchain in 6G Network

Research challenges of Blockchain in 6G Network

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2022 IEEE Delhi Section Conference, DELCON 2022

作者： Sharma, Tripti Prasad, Sanjeev Kumar Sharma, Vedangi Inderprastha Engineering College Department of Computer Science-Data Science Ghaziabad India Galgotias University School of Computer Science and Engineering Greater Noida India Galgotias University School of Computing Science and Engineering U.P. Greater Noida India

ISBN: (纸本)9781665458832

Nowadays, video calling is very much on demand, and it is working well in 4G and 5G networks. It is a time for 3D calling, virtual reality live streaming and holographic communication;Accessing this type of data requires ultrahigh data rates and traffic volumes, so there is a need to speed up the network and increase bandwidth. On the other hand, a system has to maintain reliability, security, availability and flexibility in a wireless network. The network should be extended to the needs of human life such as entertainment, healthcare, smart cities, and transportation expected to enhance service quality with a high-end user experience. To establish this network, the telecommunications infrastructure must upgrade its unmatched service level requirements. The two major disruptive emerging components in this modern Internet-enabled era of technology are both the blockchain and the Internet of Things (IoT). In research and industry, IoT has experienced exponential growth, although it suffers from several limitations, such as poor interoperability, decentralization, privacy, and security vulnerabilities. 6G applications can be based on telecommunications networks and IoT, therefore, the network must ensure strong connectivity between nodes and also ensure the privacy and security of user data. Blockchain is the appropriate solution for these issues. Blockchain is a distributed ledger technology and it enables many industries to exchange data over the Internet between trusted parties without using a central server. The blockchain facilitates verifiable, transparent and secure digital asset transactions with proof of right and ownership. There is a need to identify the role of blockchain in 6G networks. This paper explores the challenges and opportunities related to blockchain for 6G networks, future application possibilities and upcoming research directions. © 2022 IEEE.

关键词： Internet of things

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A Federated Learning Network Intrusion Detection System for Multiple Imbalances

A Federated Learning Network Intrusion Detection System for ...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Zeng, Yifan Zheng Li, Jian School of Computer Science and Engineering Sun Yat-sen University Guangzhou China Yunnan Key Laboratory of Service Computing Yunnan University of Finance and Economics Kunming China Jinan China

ISBN: (纸本)9798350368741

Centralized training of deep learning-based network intrusion detection systems (DLNIDS) raises privacy concerns and incurs huge overhead. Federated learning (FL), while preserving privacy, confronts challenges including size imbalance, heterogeneous and global imbalance. To address these issues, this paper proposes a Self-Balancing Federated learning Network Intrusion Detection System (SBFedNIDS) for accurate and efficient network intrusion detection while preserving privacy and tackling negative impact caused by multiple imbalances resulting from FL. SBFedNIDS can efficiently mitigate model bias cause by multiple imbalances and addresses imbalances at data-level via federated cost sensitive learning (FCSL) and client synthetic minority over-sampling technique (CSMOTE), without requiring additional training resources, unlike generative models. Extensive experiments on a benchmark dataset show that SBFedNIDS outperforms baselines in multiple unbalanced scenarios and even surpasses centralized training in several settings. © 2025 IEEE.

关键词： Data Imbalance Deep Learning Federated Learning Network Intrusion Detection

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Artificial Intelligence in System and Software engineering for Auto Code Generation

Artificial Intelligence in System and Software Engineering f...

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2024 International Conference on Electrical, Electronics and computing Technologies, ICEECT 2024

作者： Ghai, Anupriya Sharma Rawat, Vandna Gupta, Vishan Kumar Ghai, Kapil Graphic Era Hill University School of Computing Dehradun India Graphic Era Deemed to be University Science Engineering Department of Computer Dehradun India Amity University. Punjab School of Engineering and Technology Mohali India Graphic Era Hill University Department of Chemistry Dehradun India

ISBN: (纸本)9798350378092

Artificial Intelligence has profoundly impacted system and software engineering by facilitating the automation of complicated tasks, reducing errors, and accelerating the development process. AI-driven tools help enhance efficiency, improve code quality, and promote the generation of more adaptive and innovative software solutions. The present research uses AI-generated tools to explore how AI transforms code synthesis. The study will include a comparative analysis of the performance of manual coding and other automated methods to explore how AI can accelerate code synthesis and make modern web development more competent or effective. It is suggested in the research that with algorithmic and contextual consideration, the quality of code developed by the AI would be higher in most cases than by people due to lower error rates and shorter synthesis. Overall, the central conclusion of the research is that AI plays a crucial role in transforming systems and software engineering. The paper also includes information on ethical dilemmas, robust validation mechanisms, conservative modes, and current research. © 2024 IEEE.

关键词： Software quality

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AI-Driven Assessment and Evaluation: Enhancing Sustainability in Educational Practices 3

AI-Driven Assessment and Evaluation: Enhancing Sustainabilit...

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3rd International Conference on Automation, computing and Renewable Systems, ICACRS 2024

作者： Chinnasamy, P. Pushpalatha, M. Nirmala, V. Vidhya, V. Ayyasamy, Ramesh Kumar Priya, Divya Department of Computer Science and Engineering School of Computing Kalasalingam Academy of Research and Education Tamilnadu India Department of Computer Science and Technology Karpagam College of Engineering Coimbatore India Department of MCA Annamacharya PG College of Computer Studies Rajampet Kadapa India India Kampar Perak Malaysia Department of Computer Science and Engineering MLR Institute of Technology Hyderabad India

ISBN: (纸本)9798331532420

AI-powered educational technologies are emerging as transformative forces in the quickly changing field of education, where innovation is essential to keeping ahead of the competition. Assessments are one area that is undergoing revolutionary transformation. Artificial Intelligence (AI) is redefining the way we evaluate learning outcomes as traditional evaluation approaches struggle to keep up with the demands of the digital age. The field of artificial intelligence-powered learning assessments has a lot of promising future developments ahead of it. This research proposes novel technique in assessment and evaluation based on online education system using Artificial intelligence in machine learning techniques. Here, the input has been analysed as student performance data based on online education and processed for removing of missing values with noise removal. Then this data has been analysed using spatio LSTM convolutional fuzzy neural network for classification of evaluation and assessment model. the experimental analysis has been carried out for various student performance analysis dataset in terms of training accuracy, average precision, specificity, F-measure and recall. Proposed method training accuracy 97%, Average precision 94%, F-measure 90%, RECALL 93%, SPECIFICITY 96%. © 2024 IEEE.

关键词： Adversarial machine learning

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