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2024 International Conference on Information Technology Systems and Innovation, ICITSI 2024

作者： Wijaya, Andri Stiawan, Deris Abdiansah Suprapto, Bhakti Yudho Saputra, Iwan Pahendra Anto Rini, Dian Palupi Sayfudin Idris, Mohd.Yazid Budiarto, Rahmat Universitas Katolik Musi Charitas Faculty of Engineering Universitas Sriwijaya Department of Information System Indonesia Universitas Sriwijaya Faculty of Computer Science Indonesia Sriwijaya University Faculty of Engineering Electrical Engineering Dept. Palembang Indonesia Sriwijaya University Faculty of Comp.Science Informatic Engineering Dept. Palembang Indonesia Universitas Muhammadiyah Palembang Indonesia Universiti Teknologi Malaysia School of Computing Faculty of Computing Johor81310 Malaysia Al-Baha University College of Computing and Information Al Aqiq Saudi Arabia

ISBN: (纸本)9798331511470

The latest approach in cyber threat intelligence (CTI) is becoming increasingly crucial in detecting evolving cyber threats, including malware on Android devices. This problem is getting deeper when the number of Android users in Indonesia is increasing compared to other platforms. Therefore, it is necessary to develop a new method that integrates the CTI framework with the use of machine learning to improve the accuracy and speed in detecting Android malware. By utilizing intelligence data from structured threat reports, this method aims to identify suspicious patterns and abnormal behavior that may not be detected by conventional security systems so that with this updated security system it is proactive towards the development of new types of malware threats, with the hope of being able to make a significant contribution to strengthening especially mobile devices with the Android platform and being able to provide more effective solutions in reducing the risk of malware attacks on Android. © 2024 IEEE.

关键词： Cyber attacks

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Smart Energy Management System Using Machine Learning

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Computers, Materials & Continua 2024年第1期78卷 959-973页

作者： Ali Sheraz Akram Sagheer Abbas Muhammad Adnan Khan Atifa Athar Taher M.Ghazal Hussam Al Hamadi School of Computer Science National College of Business Administration&EconomicsLahore54000Pakistan Riphah School of Computing&Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Pattern Recognition and Machine Learning Lab Department of SoftwareGachon UniversitySeongnamGyeonggido13120Korea Department of Computer Science COMSATS University IslamabadLahore CampusLahore54000Pakistan School of Information Technology Skyline University CollegeSharjah1797United Arab Emirates Network and Communication Technology Lab Center for Cyber SecurityFaculty of Information Science and TechnologyUniversiti Kebangsaan MalaysiaBangiSelangor43600Malaysia College of Engineering and IT University of DubaiDubaiUnited Arab Emirates

Energy management is an inspiring domain in developing of renewable energy ***,the growth of decentralized energy production is revealing an increased complexity for power grid managers,inferring more quality and reliability to regulate electricity flows and less imbalance between electricity production and *** major objective of an energy management system is to achieve optimum energy procurement and utilization throughout the organization,minimize energy costs without affecting production,and minimize environmental *** energy management is an essential and complex subject because of the excessive consumption in residential buildings,which necessitates energy optimization and increased user *** address the issue of energy management,many researchers have developed various frameworks;while the objective of each framework was to sustain a balance between user comfort and energy consumption,this problem hasn’t been fully solved because of how difficult it is to solve *** inclusive and Intelligent Energy Management System(IEMS)aims to provide overall energy efficiency regarding increased power generation,increase flexibility,increase renewable generation systems,improve energy consumption,reduce carbon dioxide emissions,improve stability,and reduce energy *** Learning(ML)is an emerging approach that may be beneficial to predict energy efficiency in a better way with the assistance of the Internet of Energy(IoE)*** IoE network is playing a vital role in the energy sector for collecting effective data and usage,resulting in smart resource *** this research work,an IEMS is proposed for Smart Cities(SC)using the ML technique to better resolve the energy management *** proposed system minimized the energy consumption with its intelligent nature and provided better outcomes than the previous approaches in terms of 92.11% accuracy,and 7.89% miss-rate.

关键词： Intelligent energy management system smart cities machine learning

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Cutting-Edge Image Recognition Leveraging Deep Learning and Machine Learning for Enhanced Accuracy

Cutting-Edge Image Recognition Leveraging Deep Learning and ...

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Artificial Intelligence and Quantum Computation-Based Sensor Application (ICAIQSA), International Conference on

作者： Abhishek Shrivastava Vinesh Kumar Jay Prakash Maurya School of Mechanical Engineering VIT Bhopal University Sehore India School of Computing Science Engineering and Artificial Intelligence VIT Bhopal University Sehore India School of Computing Science & Engineering VIT Bhopal University Sehore India

ISBN: (数字)9798331517953

ISBN: (纸本)9798331517960

This paper investigates advanced techniques in image recognition and classification by integrating deep learning and machine learning approaches to achieve higher accuracy. Through the implementation of sophisticated training algorithms, the study demonstrates enhanced performance in recognizing and categorizing images across various data models. A major turning point in the development of image identification technology came in 2012 when deep neural networks were introduced. These networks surpassed earlier cutting-edge algorithms and completely changed the computer vision industry. This progress has brought us closer to achieving human-level accuracy in tasks such as identity verification. The role of large datasets like ImageNet is crucial, as they provide the foundation for the success of deep learning. With continuous research pushing the limits of picture identification and producing major advances in human knowledge, deep learning has a huge influence on business, society, and technology. Additional research in this area might lead to creative uses that revolutionize our relationship with our surroundings. Key topics discussed include data pre-processing, post-processing, model optimization, and accuracy enhancement. The findings highlight the potential of cutting-edge technologies to advance image classification and recognition in various sectors, such as medical imaging and visual analysis. The approach emphasizes scalability and adaptability, ensuring that models can be effectively applied to real-world scenarios. Future research will focus on refining these models to handle even more complex image datasets, further enhancing their practical utility and reliability.

关键词： Deep learning Training Adaptation models Visualization Image recognition Accuracy Computational modeling Visual systems Data models Reliability

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Execution of Convolution Coding Method for FPGA in Industrial Automation using VERILOG HDL 7

Execution of Convolution Coding Method for FPGA in Industria...

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7th International Conference on computing Methodologies and Communication, ICCMC 2023

作者： Venusamy, Kanagaraj Kannadhasan, S. Vimalesh, A. Chandramohan, P. Shanmugam, M. Priyadarsini, K. Department of Mechatronics Engineering Rajalakshmi Engineering College Chennai India Department of Electronics and Communication Engineering Study World College of Engineering Coimbatore Chennai India Department of Data Science and Business Systems School of Computing SRM Institute of Science & Technology Kattankulathur Chennai India

ISBN: (纸本)9781665464086

In this paper, the performance study of the FPGA-based encoder is delivered and received with little errors given the large number of applications that employ digital communication to store and retrieve data recently. Forward Error Correction units a wireless communication system region that is essential. Several types of encryption methods have been measured, and the error is completely different. Convolution code writing approach, an honest technique used to rectify mistakes during the data transfer. Convolutional encoder area unit compelled to provide the output in the kind of register style with specified positions in the register. The areas in which the region is entirely arranged are likewise shown as arrows. The position of the registers provides probable state transitions wherein example, L is the register's length. Using these facts, the best way to execute of data transmission in digital communication channels is to correct errors in codes. FPGA device utilized in convolutional encoder's hardware implementation. Vivado and XILINX ISE are usedfor performance analysis. © 2023 IEEE.

关键词： Convolution

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Performance Evaluation of Optical Wireless Communication System in Fog Weather Conditions 2

Performance Evaluation of Optical Wireless Communication Sys...

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2nd International Conference on Electronics and Renewable Systems, ICEARS 2023

作者： Venusamy, Kanagaraj Kannadhasan, S. Prakash, E. Priyadarsini, K. Study World College of Engineering Department of Electronics and Communication Engineering Chennai Coimbatore India Rajalakshmi Engineering College Department of Mechatronics Engineering Chennai India School of Computing Srm Institute of Science & Technology Department of Data Science and Business Systems Chennai Kattankulathur India

ISBN: (纸本)9798350346640

Free space optical communication being an emerging technology, has Fog as a primary challenge on its way which makes fog modelling necessary to manage wireless networks. In this paper, an analytical study was made on the performance of five mathematical fog models employing the NRZ-OOK modulation scheme for transmission and a Si PIN photodiode as the photo receptor. This article focuses on numerous performance specifications including Signal to noise ratio [SNR], Bit error rate [BER] and channel capacity all against visibility under fog for propagations wavelengths of 850 nm and 1550 nm and simulations were carried out in MATLAB. The results indicate that the wavelength of 1550nm as more advantageous option over the others for FSO wireless links and an investigation on different models and their characteristics define their suitability for implementation. © 2023 IEEE.

关键词： Visibility

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Facial Expression Recognition (FER) System Using Deep Learning 1

Facial Expression Recognition (FER) System Using Deep Learni...

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1st IEEE Karachi Section Humanitarian Technology Conference, Khi-HTC 2024

作者： Yan, Ooi Juin Ashraf, Humaira Ihsan, Uswa Jhanjhi, Nz Ray, Sayan Kumar Kavita Taylor's University Masters of Applied Computing Selangor Malaysia Taylor's University School of Computer Science SCS Malaysia International Islamic University Department of Computer Science Islamabad Pakistan Uttaranchal University Department of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350373042

Sentiment analysis of both text and images have been widely implemented machine learning application. Facial expression recognition (FER) is a widely known application of sentiment analysis of image data. This application has already been implemented in various industry, but challenges such as the complexities of facial features and different image angle still remain. This project aims to develop a FER system capable of classifying human expressions through facial images using deep learning techniques. A CNN-based architecture was proposed and training using the FER2013 dataset, which is a commonly used facial expression dataset. Overall, the trained model achieved an accuracy of 63.97% through the dataset. The trained CNN model was then employed to develop a web-based prototype of a FER system through Python Flask. © 2024 IEEE.

关键词： Sentiment analysis

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Automatic Generation of Smart Contracts from Real-World Contracts in Natural Language 9

Automatic Generation of Smart Contracts from Real-World Cont...

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9th IEEE Smart World Congress, SWC 2023

作者： Fan, Yuqing Chen, E. Zhu, Yan He, Xiao Yau, Stephen S. Pandya, Krutik University of Science and Technology Beijing School of Computer and Communication Engineering Beijing10083 China Arizona State University School of Computing and Augmented Intelligence TempeAZ85281 United States

ISBN: (纸本)9798350319804

Real-world contract texts are in natural languages, and normally suffer from lack of accuracy and are subject to interpretations. Hence, it is difficult to automatically generate smart contracts from real-world contracts for monitoring and enforcement of the execution of real-world contracts. Smart contracts can be viewed as a digital twin of real-world contracts because smart contracts in the digital world have the same objective as their corresponding real-world contracts in natural languages. In this paper, an approach to automatic generation of smart contracts from real-world contracts in a natural language is presented. In this approach, a language, called the Contract Text Markup Language (CTML), is used to facilitate automatic abstraction of the details of the real-world contract and convert them to a marked-up contract, which can be automatically compiled to generate the corresponding smart contract executable code for monitoring and enforcing the execution of the real-world contract. A legal contract in English is used to illustrate this approach. In addition, an online smart contract library is presented to facilitate the applications of this approach. © 2023 IEEE.

关键词： and Contract Text Markup Language automatic generation blockchain digital twin real-world contracts smart contracts

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Feedback-Regulated Information Fusion Approach for Optimizing Multiple Spread Control in complex Network

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Procedia Computer science 2024年 233卷 822-831页

作者： Jo Cheriyan Jyothisha J Nair Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Amritapuri Kerala 690546 India

The information spread uses a social media platform, where one user intends to share information with others intentionally or non-intentionally. The rapid spread of information on social media platforms is a complex phenomenon influenced by many factors. However, the factors influencing this rapid spread in the online space still need to be discovered. Individuals utilize social media platforms to share their experiences regarding various events related to products or services. Given the intricate and multilayered nature of social media networks, the feedback received from each layer essentially mirrors the collective perceptions of the world. This process involves fusing information from each node within the network to arrive at a decision specific to the corresponding layer. And regulate the multiple spreads through the social networks. The system is verified by using a diffusion model to ensure correctness. The verification and validation show the suitability of the proposed system in controlling multiple spreading.

关键词： Complex networks Social media Information fusion Feedback Epidemic model

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A Novel Approach for Song Recommendation System Using Deep Neural Networks

A Novel Approach for Song Recommendation System Using Deep N...

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2023 IEEE World Conference on Applied Intelligence and computing, AIC 2023

作者： Eliyajer, Gunde Natarajan, B. Bhuvaneswari, R. Elakkiya, R. Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Chennai India Department of Computer Science Birla Institute of Technology and Science Pilani Dubai Campus Dubai United Arab Emirates

ISBN: (纸本)9798350310061

The song recommendation model is a powerful tool for improving user experience and engagement with streaming music services. Depending on user emotion recognition, the proposed Song suggester Convolutional Neural Network (CNN). The proposed model uses facial expressions to recognize the user's emotions, which are then used to recommend songs that match their mood. The model is trained on a large dataset of facial expressions and songs with emotional labels. The facial expression images are pre-processed using various image augmentation techniques and then fed into the CNN model for feature extraction. The extracted features are then used to predict the user's emotions, which are mapped to the corresponding emotional labels of songs. The recommended songs are then presented to the user, who can choose to add them to their playlist. The proposed model outperforms existing emotion-based song recommendation models and has the potential to enhance user experience in music streaming services with an accuracy of 93%. © 2023 IEEE.

关键词： Emotion Recognition

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Cooperative differential games guidance laws for multiple attackers against an active defense target

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Chinese Journal of Aeronautics 2022年第5期35卷 374-389页

作者： Fei LIU Xiwang DONG Qingdong LI Zhang REN School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control LaboratoryBeihang UniversityBeijing 100083China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang UniversityBeijing 100083China Key Laboratory of Dependable Service Computing in Cyber Physical Society Ministry of Education of ChinaChongqing UniversityChongqing 400044China

This paper is concerned with a scenario of multiple attackers trying to intercept a target with active *** types of agents are considered in the guidance:The multiple attackers,the target and the defender,where the attackers aim to pursuit the target from different directions and evade from the defender *** guidance engagement is formulated in the framework of a zero-sum two-person differential game between the two opposing teams,such that the measurements on the maneuver of the target or estimations on the defending strategy of the defender can be *** of the attackers resides in two aspects:redundant interception under the threat of the defender and the relative intercept geometry with the *** miss distances,the relative intercept angle errors and the costs of the agents are combined into a single performance index of the *** formulation enables a unitary approach to the design of guidance laws for the *** minimize the control efforts and miss distances for the attackers,an optimization method is proposed to find the best anticipated miss distances to the defender under the constraint that the defender is endowed with a capture *** simulations with two cases are conducted to illustrate the effectiveness of the proposed cooperative guidance law.

关键词： Active defense Cooperative guidance Differential games Minimum effort optimization Relative intercept angle

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