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Grammatical Evolution of Synthesizable Finite State Machine-Based Behavioural Level Hardware Description Language Codes 16th

Grammatical Evolution of Synthesizable Finite State Machine-...

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16th International Joint Conference on Computational Intelligence, IJCCI 2024

作者： Majeed, Bilal McEllin, Jack Sarma, Rajkumar Youssef, Ayman Mota Dias, Douglas Ryan, Conor BDS Labs Dept. of CSIS University of Limerick Limerick Ireland Dept. of Computers and Systems Electronics Research Institute Cairo Egypt Department of Computer Science & Applied Physics Atlantic Technological University Galway Ireland

ISBN: (纸本)9789897587214

The importance of designing efficient and accurate digital circuits has grown due to the widespread use of wearable, ready-made, and custom electronic products. These digital circuits are typically sequential and designed using synthesizable Hardware Description Languages (HDLs) that can be translated into hardware. A large part of this exercise comprises designing synthesizable HDLs for sequential circuits, which are challenging to design and test, thus requiring much time for the engineers to construct them. This paper proposes using Grammatical Evolution (GE) to evolve the synthesizable HDL codes for sequential circuits on the behavioural or algorithmic level in SystemVerilog. The codes evolved in this work are of JK-Flip Flop (JK-FF), 3-bit UpDown Counter (UDC), and 8-Floor Elevator (8FE), all from the perspective of Finite State Machines (FSMs). Circuits such as 3-bit UDC and JK-FF are the basic blocks in many circuits in the industry, while 8FE is a real-life example mimicking 3-bit UDC but with a few practical exceptions. All circuits are evolved using two types of grammars. The G1 Type Grammar evolves parts of the code, while the more powerful and generic G2 Type Grammar evolves the full HDL codes for these sequential circuits. The GE-based evolution of these synthesizable design codes using both types of grammar achieves a success rate of over 86% for all circuits. Moreover, all the solution circuits evolved with the best achieved success score under the respective hyperparameter settings for G1 and G2 Type Grammar are synthesised, and their synthesis reports are compared against the synthesis reports of Gold (human-designed) circuits. The synthesis is performed using Cadence Genus at Generic Process Design Kit (GPDK) 45, 90, and 180 nm technology libraries. The synthesis results show that machine-generated designs often perform as well as or better than human-designed circuits. © 2024 by SCITEPRESS – science and Technology Publications, Lda.

关键词： Flip flop circuits

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The Integration of 6G and Blockchain into an Efficient AIoT-Based Smart Education Model 6

The Integration of 6G and Blockchain into an Efficient AIoT-...

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6th World Symposium on Communication Engineering, WSCE 2023

作者： Lioupa, Anna Memos, Vasileios A. Stergiou, Christos L. Ishibashi, Yutaka Psannis, Konstantinos E. School of Information Sciences University of Macedonia Dept. of Applied Informatics Thessaloniki Greece Graduate School of Engineering Nagoya Institute of Technology Dept. of Computer Science Nagoya Japan

ISBN: (纸本)9798350339505

The technological advances impact the future classrooms and the whole education system. The evolution of 6G promises faster speeds based on terahertz, wireless communication, the leverage of artificial intelligence (AL), virtually reality (VR) and generally a fully connected world. The use of applications of IoT and AIoT improves the education environment, but the intelligent network services undoubtedly gather, store and analyze big data which are vulnerable to attackers. As a solution we may consider the technology of blockchain. The trust and security of next generation intelligent networks are essential part of their design. In this article we suggest a data security system based on blockchain for AL applications in 6G networks. First, we present two Al-enabled applications, indoor positioning and mobile payment within the framework of 6G in the university area. We present the efficiency of blockchain in data security for Al-enabled systems using two case studies of indoor positioning system and mobile payment. The 6G system which is fully supported by Al and the integration of this in technology of blockchain, is ensured the security in future wireless communication. © 2023 IEEE.

关键词： Blockchain

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Exploring OSINT for Modern Day Reconnaissance

Exploring OSINT for Modern Day Reconnaissance

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2023 Annual International Conference on Emerging Research Areas: International Conference on Intelligent Systems, AICERA/ICIS 2023

作者： Ram, Ajay S. Thalakkat, Arya Udayan, Devika Khader, Aiby A. Hari, K. George, Vipin Government Engineering College Dept. of Computer Science and Engg. Thrissur India School of Technology and Applied Science Dept. of Cyber Forensics Kottayam India Kerala Police Academy Dept. of Computer Application Thrissur India Kerala Police Academy Police Computer Lab Thrissur India Kerala Police Academy Thrissur India

ISBN: (纸本)9798350303452

The Internet's growth has connected users globally, forming a vast network of data. As new social media platforms with diverse features emerge, individuals are drawn to sharing their personal data online. This inclination stems from a desire to display social status. However, this openness poses risks, as personal data uploaded to the internet can easily unveil one's online identity. Extracting such data is a straightforward process, as a simple correlation of evidence with an online profile can summarize a user's identity. By combining various sources of information linked to a specific individual, a comprehensive profile can be created. As the digital landscape expands, Open Source Intelligence (OSINT) has become an invaluable tool for gathering information. OSINT involves searching and accessing publicly available data to extract relevant information, analyze patterns, and draw conclusions. It encompasses activities like web scraping, data mining, social media monitoring, and online research. OSINT is crucial for understanding public sentiment, identifying potential threats, conducting background checks, investigating crimes, and performing competitive analysis. This paper investigates the impact of OSINT as a modern day reconnaissance tool. Through case studies and real-world examples, the research demonstrates the effectiveness of OSINT in enhancing situational awareness, supporting decision-making for law enforcement agencies, and using OSINT as a modern-day reconnaissance tool. © 2023 IEEE.

关键词： Data mining

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Impact of Learning Style based Teaching on Students Performance in a Formal Methods Course for computer Scientists 11

Impact of Learning Style based Teaching on Students Performa...

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11th IEEE International Conference on Teaching, Assessment and Learning for Engineering, TALE 2022

作者： Schorr, Ruth Frankfurt University of Applied Sciences Dept. of Computer Science and Engineering Frankfurt Germany

ISBN: (纸本)9781665491174

Teaching a formal methods course can be challenging. Students perceive formal methods as difficult, too mathematical and practical irrelevant. Students show low motivation for the subject, they just want to pass the course with minimal effort. Grades in mandatory formal methods courses are typically below average. In order to address the problems, we analyzed the learning styles of our students. In this work-inprogress paper, we present the changes made to our teaching framework and their impact on student performance. This paper is an experience report on improving performance of master students in formal methods at Frankfurt University of applied sciences. © 2022 IEEE.

关键词： Formal methods

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Modeling Hot Rolling Process Forces Using Bio-Inspired Metaheuristic Search Algorithm 2

Modeling Hot Rolling Process Forces Using Bio-Inspired Metah...

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2nd International Conference of Intelligent Methods, Systems and Applications, IMSA 2024

作者： Sheta, Alaa Braik, Malik Oznergiz, Ertan Elashmawi, Walaa H. Rausch, Peter Othman, Emad S. Southern Connecticut State University Department of Computer Science New HavenCT United States Al-Balqa Applied University Computer Science Department Salt Jordan Istanbul Technical University Mechanical Engineering Faculty Istanbul Turkey Misr International University Dept of Computer Science Cairo Egypt George Simon Ohm Univ. of Applied Sciences Computer Science Department Nuremberg Germany AL-Shorouk Academy Management Information System Dept. Cairo Egypt

ISBN: (纸本)9798350362633

This research introduces the application of an innovative bio-inspired metaheuristic technique, termed the Crow Search Algorithm (CSA), to model a crucial industrial process - hot rolling manufacturing. Inspired by the foraging patterns of crows, the CSA algorithm has demonstrated its prowess in solving diverse optimization challenges. In the context of this study, the CSA algorithm is harnessed to fine-tune the parameters of a simulation model focused on predicting the force exerted during a hot rolling procedure. The proposed model takes into consideration a range of influential factors, including the initial temperature (Ti), width (Ws), carbon equivalent (Ce), gauge (hi), draft (i), and roll diameter (R). The findings underscore the CSA's capability to deliver an exceptional modeling performance characterized by swift convergence and high solution quality. By getting along very well with the proposed model with the CSA algorithm, a robust and efficient avenue to optimize the hot rolling process emerges, with the potential for expansion into other manufacturing domains. The computational and simulation results demonstrated that the proposed approach-based CSA outperformed different meta-heuristic search algorithms, such as the Salp Swarm Algorithm (SSA), Dandelion Optimizer (DO), Particle Swarm Optimization (PSO), Gray Wolf Optimizer (GWO), and Moth-Flame Optimization (MFO), in all test cases. The CSA has achieved the highest coefficient of determination (R2), equal to 0.97244, and the lowest mean squared error (MSE), equal to 1904.97, compared to its opponent algorithms. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

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Ontology population using CNN model: Application to COVID-19 diagnosis 6

Ontology population using CNN model: Application to COVID-19...

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6th International Conference on Pattern Analysis and Intelligent Systems, PAIS 2024

作者： Mellal, Nacima Saighi, Asma Institute of Applied Science & Technology University of Oum Research Laboratory of Artificial Intelligence And Autonomous Objects Dept. Networks And Telecommunication El Bouaghi Algeria University of Oum Research Laboratory of Artificial Intelligence And Autonomous Objects Dept. Computer Science El Bouaghi Algeria

ISBN: (纸本)9798350350265

AI models and especially deep learning models have found applications across various medical domains. While many studies focus on using electronic health records (EHRs) data to train AI models, implementing the reverse process poses several challenges. Also, the heterogeneous nature of the used data in EHRs, such as diagnoses, clinical reports, test results, prescriptions, and medical images, makes their interpretation difficult for the practitioners which require a unified understanding. Medical ontologies are useful to improve data interpretability and semantics. In this paper, we aim to create a synergy between ontologies and deep learning techniques to enhance efficiency, data understanding, and provide healthcare quality. We propose a system in which our developed ontology is populated automatically using the predictions of an AI model. We have developed and trained a CNN model to aid in the COVID-19 diagnosis. The initial obtained results are promising with an accuracy of 98%. © 2024 IEEE.

关键词： COVID-19

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A technical Concept for enhancing the Student Experience in Hybrid Lecture Scenarios 26

A technical Concept for enhancing the Student Experience in ...

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26th International Symposium on Multimedia, ISM 2024

作者： Schimanke, Florian Mertens, Robert Prankel, Felix Hsw University of Applied Sciences Dept. of Computer Science and Engineering Hameln Germany Sennheiser Electronic Se and Co. Kg Vocational Training Kg Wedemark Germany

ISBN: (纸本)9798331511111

During the COVID-19 pandemic, learning had to be shifted from in-person settings to entirely online or hybrid teaching scenarios. Schools and universities in Germany were forced to quickly deploy solutions which often provided lackluster quality. This shift was also implemented indiscriminately across subjects so that screen intensive courses (such as programming) were impacted in the same way as practical courses like hardware engineering. In many cases, this left a negative impression of such hybrid scenarios on participants. However, with steady improvements in technology, hybrid meetings have established themselves in corporate environments and steadily gained popularity in parts of higher education programs. Especially in the case of dual programs, this is also applicable to lectures and seminars. This paper explores using products from Sennheiser electronic SE & Co. KG with microphone arrays and audio-over-IP technology in combination with network cameras as an example, this concept aims to create an environment for seamlessly integrated hybrid lectures with about 30 participants in presence. © 2024 IEEE.

关键词： Curricula

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Increase the Degree of Accuracy by Employing A More Accurate Classification Approach 2

Increase the Degree of Accuracy by Employing A More Accurate...

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2nd International Conference on Business Analytics for Technology and Security, ICBATS 2023

作者： Khan, Muhammad Farhan Sajid Farooq, Muhammad Joghee, Shanmugan University of Health Sciences Dept. of Forensic Sciences Lahore Pakistan Lahore Garrison University Dept. of Computer Science Lahore Pakistan Applied Science Research Center Applied Science Private University Amman11937 Jordan Skyline University School of Business Sharjah United Arab Emirates

ISBN: (纸本)9798350335644

Traditional artificial neural networks and machine learning have traditionally been used to classify images;however, these approaches have not only struggled to keep up with the processing demands of such datasets but have also performed inefficiently and with poor classification accuracy due to the processing demands of enormous image datasets during feature extraction and model training. Large photo collections make it challenging for machine learning and traditional artificial neural networks to keep up with their processing demands. Deep learning significantly surpasses other, more traditional techniques for photo classification. Another difficulty was that when dealing with really large pictures, standard artificial neural networks were forced to exceed their data storage limits. As a direct result of their research, the authors of the study developed a deep-learning model for image tagging. This model was developed as a tool to aid in the identification and categorization of pictures on a large scale. Following a brief explanation of neural network theory, the study's focus shifted to an examination of the various convolutional neural network types and the general strategy for employing such networks for picture categorization. The present model of a convolutional neural network was utilized to minimize noise and alter the parameters used in the feature extraction operation. This was supposed to improve the results' dependability. An upgraded convolutional neural network was used to develop the model's architecture. The resulting deep learning model improved operational effectiveness and data categorization accuracy significantly. To achieve this purpose, the structure must be modified so that it can work as effectively as possible. Experiments were carried out to evaluate if the number of times an image classification network model is put through its training process influences the level of accuracy obtained by the model. This was done to see how effectively

关键词： Image classification

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AAF-SCM: An Authenticated Framework for Supply Chain Management

AAF-SCM: An Authenticated Framework for Supply Chain Managem...

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Intelligent Systems and Advanced Applications (ICISAA), International Conference on

作者： Prince Roy Rajneesh Kumar Md Neaz Morshed Dept. of Applied Computer Science Fairleigh Dickinson University Dept. of Computer Science & Engineering Maharishi Markandeshwar (Deemed to be University)

ISBN: (数字)9798331539948

ISBN: (纸本)9798331539955

The process of a supply chain involves a series of activities that distribute, assemble, and manage products, transferring them from the supplier to the end consumer. It operates as a complex, interconnected network regulated by supply and demand. Security in supply chain management is a crucial aspect of its overall security measures, focusing primarily on maintaining essential end-to-end protection. Without this, several attacks can be used to manipulate data and valuable information from the entire chain of networks. This paper explains how encrypted intermediates can secure the entire SCM by validating each intermediate using public-private key encryption. We also demonstrate and assess how the proposed AAF-SCM model can aid in tracing security breaches or unauthorized data tampering. We also validate this model against nefarious attacks like Fabrication, Assertion, Deletion, and Modification. Finally, we propose opportunities to develop innovative systems that enhance security through intermediary steps.

关键词： Fabrication Supply chain management Supply and demand Supply chains Focusing Data models Encryption Protection Intelligent systems

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Learning Individualized Automatic Content Magnification in Gaze-based Interaction

Learning Individualized Automatic Content Magnification in G...

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2023 IEEE International Symposium on Multimedia, ISM 2023

作者： Eggenkemper, Florian Kolker, Lars Valente, Mike Rothkopf, Constantin A. Mertens, Robert Technical University of Darmstadt Centre for Cognitive Science Institute of Psychology Germany Hsw University of Applied Sciences Dept. of Computer Science and Engineering Hamelin Germany Bhh University of Applied Sciences Hamburg Germany

ISBN: (纸本)9798350395761

The precision of modern commercial off-the-shelf eye trackers has reached a level sufficient for developing gaze-based applications. In many but not all applications, accuracy even allows for replacing a computer mouse with gaze-bazed pointing. The Multi-Modal Interaction Concept for Efficient input (M2ice) tackles accuracy problems with an on-demand hybrid fisheye magnifier. This paper introduces an image-analysis-based approach that identifies areas on the screen where to automatically activate magnification for improved interaction. It combines the separate actions magnifying and clicking into one seamless action. The approach works by combining OpenCV filters for detection of clickable elements on the screen with a local machine learning algorithm predicting whether magnification is needed based on size and position of screen elements. A user study (n = 28) showed a significant speed increase of 18.50 percent (t(27)=-3.95, p=.0002 at α = .05) with automatic magnification compared to separate shortcuts for clicking and magnification. © 2023 IEEE.

关键词： Eye tracking

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