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7th International Conference on Signal Processing and Machine Learning, SPML 2024

作者： Liu, Huanjing Valderrama, Camilo Zhang, Xingying Liu, Qian The Department of Applied Computer Science The University of Winnipeg Canada The Department of Mechanical Engineering The University of Manitoba Canada

ISBN: (纸本)9798400717192

Polysomnography (PSG)-based sleep staging is vital for assessing sleep quality. As a state-of-the-art deep learning model structure, Transformer has been increasingly utilized to enhance sleep stage classification efficiency. However, the default self-attention mechanism in Transformer encoder often struggles with long-term dependencies in time sequences. To overcome this limitation, we introduce a novel method that integrates the Matrix Profile, a time series data mining technique, with the Transformer's self-attention mechanism to better capture global data abnormalities and temporal dynamics. Our approach preprocesses PSG data from multiple channels using Matrix Profiles to highlight significant patterns. These profiles, combined with time-frequency representations, are fed into a Transformer encoder to fuse multi-channel features, and enhance the understanding of temporal interdependencies. The enhanced features are classified via two fully connected layers, yielding substantial improvements in sleep stage classification accuracy and efficiency on multichannel data as compared to the baseline models. This work not only underscores the efficacy of Matrix Profile in sleep classification but also proposes a new paradigm for processing complex temporal data in deep learning models. The complete code for this model is available at https://***/EliteriaLYU/MPSleepNet. © 2024 ACM.

关键词： Sleep research

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Design of Neural Network Based Wind Speed Prediction Model Using GWO

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computer Systems science & engineering 2022年第2期40卷 593-606页

作者： R.Kingsy Grace R.Manimegalai Department of Computer Science and Engineering Sri Ramakrishna Engineering CollegeCoimbatore641022India Department of Computer Science and Engineering PSG Institute of Technology and Applied ResearchCoimbatore641062India

The prediction of wind speed is imperative nowadays due to the increased and effective generation of wind *** power is the clean,free and conservative renewable *** is necessary to predict the wind speed,to implement wind power *** paper proposes a new model,named WT-GWO-BPNN,by integrating Wavelet Transform(WT),Back Propagation Neural Network(BPNN)and GreyWolf Optimization(GWO).The wavelet transform is adopted to decompose the original time series data(wind speed)into approximation and detailed ***-BPNN is applied to predict the wind *** is used to optimize the parameters of back propagation neural network and to improve the convergence *** work uses wind power data of six months with 25,086 data points to test and verify the performance of the proposed *** proposed work,WT-GWO-BPNN,predicts the wind speed using a three-step procedure and provides better *** Absolute Error(MAE),Mean Squared Error(MSE),Mean absolute percentage error(MAPE)and Root mean squared error(RMSE)are calculated to validate the performance of the proposed *** results demonstrate that the proposed model has better performance when compared to other methods in the literature.

关键词： Wind speed wavelet transform back propagation neural network grey wolf optimization time series

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A Novel Approach to Bat Protection IoT-Based Ultrasound System of Smart Farming

Lecture Notes on Data Engineering and Communications Technol...

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Lecture Notes on Data engineering and Communications Technologies 2023年 180卷 178-186页

作者： Rahman, Md. Hafizur Noman, S.M. Salehin, Imrus Akhund, Tajim Md. Niamat Ullah Department of Digital Anti-Aging Healthcare Inje University Gimhae Korea Republic of Faculty of Computer Science and Engineering Frankfurt University of Applied Sciences Frankfurt Germany Department of Computer Engineering Dongseo University Busan Korea Republic of Department of Computer Science and Engineering Daffodil International University Dhaka Bangladesh

In past decades, scientific research has explored various bat detection systems methods, a common trend to identify heterogeneous species of bats. In this article, we represented an ultrasonic bat detection and protection method by interfacing an IoT automated device for the first time in agriculture development to introduce steady security in a preventive way. The automated bat banisher system is an effectual model for farmers to protect their land at a very affordable cost from nuisance bats. Moreover, the highest-quality fruits are the ones that bats choose to eat when they attack. This prevents the farmer from getting the best possible yield, Farmers have tried everything from handcrafted sound systems and medication to nets and traps to get rid of the bats, but they have yet to be effective. We created an Internet of Things-based automated bat banisher to combat bats invading farms. In this research, our High-Frequency Ultrasound (IoT automated) System has the potential to save farmers money, time, and effort. Farmers may increase agricultural output to provide the highest suitable fruit supply. Therefore, an ultrasonic IoT-based bat Banisher device is the most straightforward and functional means of dealing with nuisance bats. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Fruits

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An Adaptive on Demand Modified Ant Colony Optimization Routing for VANETs 23th

An Adaptive on Demand Modified Ant Colony Optimization Routi...

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23rd International Conference on Intelligent Systems Design and Applications, ISDA 2023

作者： Kumari, J. Jesy Janet Thangam, S. Raja, A. Saleem Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India Department of Computer Science and Engineering University of Technology and Applied Science-Shinas Shinas Oman

ISBN: (纸本)9783031648496

Around the world, vehicle accidents claim many priceless lives. To tackle this problem, the Vehicular ad hoc networks (VANETs) are the most effective solution. Effective communication between vehicular nodes in VANETs is extremely important because of the rapid mobility of vehicles and different network topology. Currently, VANET mostly serves the public security, stability, information for voyageurs, and traffic Management, control of congestion, guidance, etc. Chaos on roadways can occur at any moment, anyplace. It is a situation in which the flow of traffic regulations might cease to function. Collisions, maintaining roads, violation of legal rules, etc., so to evade the congestion in the surrounding region. VANETs represent a dynamic and challenging communication environment characterized by high mobility, intermittent connectivity, and rapid changes in network topology. Efficient and reliable routing is crucial for enabling diverse applications such as traffic management, safety communication, and infotainment services in VANETs. In this research, propose a multi-faceted approach to improve routing performance in VANETs. An adaptive routing algorithm that considers vehicle mobility patterns and dynamically adjusts communication routes based on the anticipated movement of neighboring vehicles such as Modified Ant Colony Optimization (MACO) technique. This adaptability enhances the robustness of the network against frequent topology changes and improves the overall packet delivery ratio, end-to-end delay, and network reliability compared to traditional routing protocols. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Vehicular ad hoc networks

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An Adaptive Framework for Classification and Detection of Android Malware

International Journal of Interactive Mobile Technologies

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International Journal of Interactive Mobile Technologies 2024年第21期18卷 59-73页

作者： Al Sharah, Ashraf Alrub, Yousef Abu Owida, Hamza Abu Elsoud, Esraa Abu Alshdaifat, Nawaf Khtatnaha, Hamzah Department of Electrical Engineering College of Engineering Technology Al-Balqa Applied University Amman Jordan Department of Computer Information Systems Faculty of Prince Al-Hussein Bin Abdallah II for Information Technology The Hashemite University Zarqa Jordan Department of Medical Engineering Faculty of Engineering Al-Ahliyya Amman University Amman Jordan Department of Computer Science Faculty of Information Technology Zarqa University Zarqa Jordan Faculty of Information Technology Applied Science Private University Amman Jordan

The hardware and software of a computer are controlled by its operating system (OS), which performs essential tasks such as input and output processing, file and memory management, and the management of peripheral devices such as disk drives and printers. Application software refers to programs designed for specific purposes, these applications, often freely available and open source, contribute to the rising number of downloads. In the third quarter of 2022, combined downloads from the Apple App Store and Google Play Reached an estimated 35.3 billion. However, the prevalence of insecurity in these applications and technologies heightens the potential for cybercrimes. Protection against unauthorized intruders is crucial in identifying malicious applications. Machine learning (ML) serves as a promising avenue for detecting malware attacks, offering potential solutions to bolster cybersecurity measures. We propose a novel approach utilizing ML to enhance malware detection accuracy by segmenting datasets into distinct groups. Our research employs supervised ML techniques on the CICMaldroid2020 dataset, which includes comprehensive information such as intent actions, permissions, and sensitive APIs. The dataset was partitioned into four groups, each containing 150 features, and analyzed across four experiments to distinguish between attack and benign classes. Our proposed model demonstrated exceptional performance, with the random forest algorithm achieving an accuracy of 98.6% and a precision of 98.75%. These results highlight the effectiveness of our segmentation approach and its significant contribution to advancing malware detection in Android applications, offering a promising direction for future cybersecurity solutions. © 2024 by the authors of this article.

关键词： Android malware

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AVirtual Cloud Storage Architecture for Enhanced Data Security

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computer Systems science & engineering 2023年第2期44卷 1735-1747页

作者： M.Antony Joans Kumar C.Christopher Columbus E.Ben George T.Ajith Bosco Raj Department of Information Technology St.Xavier’s Catholic College of EngineeringNagercoil629003Tamil NaduIndia Department of Computer Science Engineering PSN College of Engineering and TechnologyTirunelveli627152India Department of Computer Science Engineering University of Technology and Applied SciencesMuscat112Oman Department of Electronics and Communications Engineering PSN College of Engineering and TechnologyTirunelveli627152India

The sensitive data stored in the public cloud by privileged users,such as corporate companies and government agencies are highly vulnerable in the hands of cloud providers and *** proposed Virtual Cloud Storage Archi-tecture is primarily concerned with data integrity and conﬁdentiality,as well as *** provide conﬁdentiality and availability,theﬁle to be stored in cloud storage should be encrypted using an auto-generated key and then encoded into distinct *** the encoded chunks ensured theﬁle integrity,and a newly proposed Circular Shift Chunk Allocation technique was used to determine the order of chunk ***ﬁle could be retrieved by performing the opera-tions in *** the regenerating code,the model could regenerate the missing and corrupted chunks from the *** proposed architecture adds an extra layer of security while maintaining a reasonable response time and sto-rage *** results analysis show that the proposed model has been tested with storage space and response time for storage and *** VCSA model consumes 1.5x(150%)storage *** was found that total storage required for the VCSA model is very low when compared with 2x Replication and completely satisﬁes the CIA *** response time VCSA model was tested with different sizedﬁles starting from 2 to 16 *** response time for storing and retrieving a 2 MBﬁle is 4.96 and 3.77 s respectively,and for a 16 MBﬁle,the response times are 11.06 s for storage and 5.6 s for retrieval.

关键词： Erasure code regenerating code cryptography virtual cloud storage architecture circular shift chunk allocation algorithm

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Enhanced Water Quality Control Based on Predictive Optimization for Smart Fish Farming

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computers, Materials & Continua 2023年第6期75卷 5471-5499页

作者： Azimbek Khudoyberdiev Mohammed Abdul Jaleel Israr Ullah DoHyeun Kim Department of Applied Informatics Kimyo International University in TashkentTashkent100121Uzbekistan Department of Computer Science Virtual University of PakistanLahore54000Pakistan Department of Computer Engineering Jeju National UniversityJeju63243Korea

The requirement for high-quality seafood is a global challenge in today’s world due to climate change and natural resource *** of Things(IoT)based Modern fish farming systems can significantly optimize seafood production by minimizing resource utilization and improving healthy fish *** objective requires intensive monitoring,prediction,and control by optimizing leading factors that impact fish growth,including temperature,the potential of hydrogen(pH),water level,and feeding *** paper proposes the IoT based predictive optimization approach for efficient control and energy utilization in smart fish *** proposed fish farm control mechanism has a predictive optimization to deal with water quality control and efficient energy consumption *** farm indoor and outdoor values are applied to predict the water quality parameters,whereas a novel objective function is proposed to achieve an optimal fish growth environment based on predicted *** logic control is utilized to calculate control parameters for IoT actuators based on predictive optimal water quality parameters by minimizing energy *** evaluate the efficiency of the proposed system,the overall approach has been deployed to the fish tank as a case study,and a number of experiments have been carried *** results show that the predictive optimization module allowed the water quality parameters to be maintained at the optimal level with nearly 30%of energy efficiency at the maximum actuator control rate compared with other control levels.

关键词： Smart fish farming internet of things(IoT) predictive optimization objective function fuzzy logic control(FLC)

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Blockchain-based secure and transparent election and vote counting mechanism using secret sharing scheme

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Journal of Ambient Intelligence and Humanized Computing 2023年第10期14卷 14009-14027页

作者： Chouhan, Vikas Arora, Anshul Department of Computer Science and Engineering Indian Institute of Technology Roorkee Roorkee India Department of Applied Mathematics Delhi Technological University Delhi India

Privacy and transparency in vote counting are the most prevalent concerns these days due to the involvement of untrusted authorities in the counting process. As a result, the counting process faces significant privacy, trust, and transparency hurdles. Hence, there is a need for an efficient and trusted mechanism to resolve such problems. Blockchain technology has the potential to bring transparency and trust in several applications. Therefore, in this work, we explore blockchain technology in conjunction with a secure partitioning scheme to promote transparency, trust, and privacy between users and participating authorities in a decentralized platform. This paper presents a chaincode-based implementation of our proposed secure and verifiable vote counting mechanism that enables trust and fairness over a decentralized platform. Multiple authorities participate in the vote counting process in a trusted manner to cooperate and coordinate in a decision process over a decentralized platform. Our research exhibits that blockchain technology can eliminate the trust gaps and increase transparency and fairness in the election and vote counting procedure. We register user votes in the blockchain platform based on the secret sharing mechanism to enable fairness and openness between counting authorities. Each vote is recorded into the distributed ledger to support openness and verifiability in our mechanism. The ledger is accessible to every registered user as per the permissioned blockchain policy. We created many authorities in the blockchain network and deployed multiple smart contracts on the Hyperledger platform to analyze the feasibility of our strategy. The performance results are obtained and reported using the Hyperledger Caliper benchmark tool. The results demonstrate that the proposed chaincode-based solution achieves the highest throughput at 200–400 tps for fetching and removing contracts. We achieve the optimal latency of 18.09 s for the vote distribution contract

关键词： Smart contract

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Secured Data Storage Using OAuth and Encryption of Data Using AES with Patterns and Hidden Layer

Secured Data Storage Using OAuth and Encryption of Data Usin...

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2024 International Conference on Smart Systems for Electrical, Electronics, Communication and computer engineering, ICSSEEC 2024

作者： Vilasini, V. Hariharan, K. Chezhian, Nethra Kaviyarasu, D. PSG Institute of Technology and Applied Research Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350378177

In today's digital era, the use of data is becoming more day by day. Data is serving as a main source for all the applications we rely on. As the volume of data rapidly increases, the need for security also increases in the same phase. This brings the need for securing the data in a more effective manner. The need to protect sensitive data is underscored by the increasing intricacy of cyberattacks and the expansion of virtual commerce. It is imperative to rely on several legal and regulatory requirements for the need for data security. The failure to do so may result in severe penalties. In order to maintain trust in digital interactions, data security during transmission and storage is becoming more important as the world gets smaller. If the data is not secured in an effective manner, the growth of the companies and several other technologies may collapse and result in higher threats to the world. Both firms and governments are required to preserve intellectual property and information related to national security. The availability, confidentiality, and integrity of data are critical for sustaining innovation, trust, and business continuity. This project focusses on the two-level authentication of the system where the users are allowed to store the sensitive data. The first level authentication is provided using OAuth where it is a single sign on mechanism which is advantageous to the users to access it easily. The second level authentication is provided using the encryption technique where the Advanced Encryption Standard is used along with the creative usage of user-generated patterns as a hidden layer in the encryption process. Here a symmetric key is used for the encryption to make it more secure. The two-level authentication brings high level security for the stored data. © 2024 IEEE.

关键词： Data integrity

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Intelligent Systems for Data Driven Agriculture: Enhancing Farmer Productivity Through Automation and Artificial Intelligence

Intelligent Systems for Data Driven Agriculture: Enhancing F...

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2024 International Conference on Smart Systems for Electrical, Electronics, Communication and computer engineering, ICSSEEC 2024

作者： Lokesh, S. Madhavan, Arvind Ramanathan, R.M. Prakash Anand, Krteen PSG Institute of Technology and Applied Research Department of Computer Science and Engineering Tamilnadu India

ISBN: (纸本)9798350378177

Numerous obstacles endanger the livelihoods of smallholder farmers and global food security. Crop output losses due to plant diseases alone are estimated to be between 15% to 25% every year. However, farmers' capacity to recognize and treat illnesses in a timely manner is hampered by things like a lack of agronomic expertise, limited access to actionable insights, and information gaps. The work proposes a comprehensive end-to-end web application that uses machine learning models to help farmers with configurable expert advice, smart farm management, and automatic disease detection. Thus, enabling farmers to identify the infection using their smart phones and obtain crop - fertilizer recommendations for the crops to be treated in the farmer's area based on historical data analysis of yield-influencing elements such as geography, weather, and soil. The proposed system will employ Generative Artificial Intelligence, such as ChatGPT's natural language processing and generation capabilities, to engage in conversational interactions with farmers. The work achieves close to 95% accuracy after utilizing 30 epochs in the area of disease detection and 97% accurate models are achieved for fertilizer outputs. These features along with it's high accuracy can assist farmers in making informed decisions, utilising the data obtained to reduce crop output losses. © 2024 IEEE.

关键词： Smart agriculture

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