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6th International Conference on Intelligent Computing and Control Systems, ICICCS 2022

作者： Ajay, P. Sharma, Avinash Dankan Gowda, V. Sharma, Anil Kumaraswamy, S. Arun, M.R. Anna University Department of Electronics and Communication Engineering Tamilnadu Chennai India Maharishi Markandeshwar Engineering College Department of Computer Science Engineering Haryana India Bms Institute of Technology and Management Department of Electronics and Communication Engineering Karnataka Bangalore India Guru Gobind Singh Indraprastha University University School of Information Communication & Technology Delhi India Global Academy of Technology Department of Computer Science and Engineering Karanataka Bengaluru India Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Department of Electronics and Communication Engineering Tamilnadu Chennai India

ISBN: (纸本)9781665410359

The Internet of Things (IoT) is a technology that extends the reach of the Internet to items in the real world, encompassing both living and non-living objects. The Internet serves as a platform for linking people and computers. Things are real-world items such as automobiles, schools, animals, heart rate monitors, and other household equipment, amongst many more examples. Since the previous several decades, scientists have been working on developing devices, networks, and protocols that may be used to monitor, control, and track real-world objects and events. Sensors, actuators, and Radio Frequency Identification Devices (RFID) are the devices that are employed for these reasons, and they are collectively referred to as IoT devices in this thesis. Wireless sensor and actuator networks (WSAN), machine-to-machine networks, and other networks established with the help of these devices are examples of networks built with the help of these devices. communication between machines (M2M), SCADA, and RFID tracking system, among other things. The collaborative load balancing across fog nodes is proposed in this work, and the load balancing approach is used to disperse the load. © 2022 IEEE.

关键词： Middleware

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Analysis and Assessment of Wind Energy Potential of Socotra Archipelago in Yemen

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computers, Materials & Continua 2022年第1期70卷 1177-1193页

作者： Murad A.Almekhlafi Fahd N.Al-Wesabi Imran Khan Nadhem Nemri Khalid Mahmood Hany Mahgoub Noha Negm Amin M.El-Kustaban Ammar Zahary Department of Electrical Engineering–Communication Engineering Sana’a UniversityYemen Department of Computer Science King Khalid UniversityMuhayel AseerKingdom of Saudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen Department of Electrical Engineering University of Engineering and TechnologyPeshawarP.O.B 814Pakistan Department of Information Systems King Khalid UniversityMayahel AseerKSA Computer Science Department King Khaled UniversityKSA&Faculty of Computers and InformationComputer Science DepartmentMenoufia UniversityEgypt Computer Science Department King Khaled UniversityKSA&Faculty of ScienceDepartment of Mathematics and Computer ScienceMenoufia UniversityEgypt Electronics Department Faculty of EngineeringUSTSana’aYemen Faculty of Computer and IT Sana’a UniversityYemen

The increasing use of fossil fuels has a significant impact on the environment and ecosystem,which increases the rate of *** the high potential of renewable energy sources inYemen and the absence of similar studies in the region,this study aims to examine the potential of wind energy in Socotra *** was done by analyzing and evaluating wind properties,determining available energy density,calculating wind energy extracted at different altitudes,and then computing the capacity factor for a number of wind turbines and determining the *** average wind speed in Socotra Island was obtained from the Civil Aviation and Meteorology Authority data,only for the five-year data currently *** results showed high wind speeds from June to September(9.85-14.88 m/s)while the wind speed decreased for the rest of the *** average wind speed in the five years was 7.95 m/*** average annual wind speed,wind energy density,and annual energy density were calculated at different altitudes(10,30,and 50 m).According to the International Wind Energy Rating criteria,the region of Socotra Island falls under Category 7 and is classified as‘Superb’for most of the *** study provides useful information for developing wind energy and an efficient wind approach.

关键词： Energy potential wind characteristics Weibull distribution wind power density Socotra island

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Multi objective Ant Colony Optimization Technique for Task Scheduling in Cloud Computing 3

Multi objective Ant Colony Optimization Technique for Task S...

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3rd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2024

作者： Hemanth, S.V. Kirubha, D. Reddy, Sheri Ramchandra Chelladurai, T. Soundari, A. Gnana Amirthayogam, G. Hyderabad Institute of Technology and Management Department of Computer Science and Engineering Telangana Hyderabad501401 India Rajarajeswari College of Engineering Department of Computer Science and Engineering Karnataka Bangalore560074 India Telangana Hyderabad501401 India Psna College of Engineering and Technology Department of Electronics and Communication Engineering Tamil Nadu Dindigul624622 India Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Thandalam600124 India Department of Information Technology Tamilnadu Chennai603103 India

ISBN: (纸本)9798350375190

Cloud Computing (CC) is a powerful paradigm for accessing IT services over the internet, allowing multiple consumers to share resources. Therefore, it requires task scheduling, allocating, and gradually releasing resources. Hence, efficient Task Scheduling (TS) and Resource Allocation (RA) in cloud systems is crucial to optimize resource usage and ensure timely completion. Assigning computing tasks in a cloud environment is a multifaceted process affected by numerous factors, including network bandwidth availability, completion time, and cost considerations. Traditional scheduling models based on heuristic algorithms have limitations in complex in cloud environments. To tackle these issues, we introduce Multi objective Ant Colony Optimization (MACO) and Adaptive Sequence Dynamic Allocation (ASDA) techniques for TS and RA in the cloud environment. Initially, the tasks submitted globally are divided into long and short queues. After that, the MACO algorithm schedules the task based on queues. Subsequently, the proposed ASDA algorithm efficiently allocates the most appropriate Virtual Machine (VM). If a VM is already occupied, the proposed method promptly chooses the next available VM based on the progress of the work completion process. According to the experimental results, the proposed algorithm achieves significant cost savings compared to other algorithms. © 2024 IEEE.

关键词： Virtual machine

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Mental Illness Disorder Diagnosis Using Emotion Variation Detection from Continuous English Speech

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computers, Materials & Continua 2021年第12期69卷 3217-3238页

作者： S.Lalitha Deepa Gupta Mohammed Zakariah Yousef Ajami Alotaibi Department of Electronics&Communication Engineering Amrita School of EngineeringAmrita Vishwa VidyapeethamBengaluruIndia Department of Computer Science&Engineering Amrita School of EngineeringAmrita Vishwa VidyapeethamBengaluruIndia Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversitySaudi Arabia

Automatic recognition of human emotions in a continuous dialog model remains challenging where a speaker’s utterance includes several sentences that may not always carry a single *** work with standalone speech emotion recognition(SER)systems proposed for continuous speech only has been *** the recent decade,various effective SER systems have been proposed for discrete speech,i.e.,short speech *** would be more helpful if these systems could also recognize emotions from continuous ***,if these systems are applied directly to test emotions from continuous speech,emotion recognition performance would not be similar to that achieved for discrete speech due to the mismatch between training data(from training speech)and testing data(from continuous speech).The problem may possibly be resolved if an existing SER system for discrete speech is ***,in this work the author’s existing effective SER system for multilingual and mixed-lingual discrete speech is enhanced by enriching the cepstral speech feature set with bi-spectral speech features and a unique functional set of Mel frequency cepstral coefficient features derived from a sine filter *** augmentation is applied to combat skewness of the SER system toward certain *** using random forest is *** enhanced SER system is used to predict emotions from continuous speech with a uniform segmentation *** to data scarcity,several audio samples of discrete speech from the SAVEE database that has recordings in a universal language,i.e.,English,are concatenated resulting in multi-emotional speech ***,fear,sad,and neutral emotions,which are vital during the initial investigation of mentally disordered individuals,are selected to build six categories of multi-emotional *** results demonstrate the suitability of the proposed method for recognizing emotions from continuous speech as well as from discrete speech.

关键词： Continuous speech cepstral bi-spectral multi-emotional discrete emotion filter bank mental illness

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Automatic Query Quality Prediction Using Feed Forward Neural Network 4

Automatic Query Quality Prediction Using Feed Forward Neural...

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4th IEEE Annual Flagship India Council International Subsections Conference, INDISCON 2023

作者： Swathi, B.P. Geetha, M. Suhas, M.V. Manipal Institute of Technology Manipal Academy of Higher Education Department of Information & Communication Technology Manipal India Manipal Institute of Technology Manipal Academy of Higher Education Department of Computer Science and Engineering Manipal India Manipal Institute of Technology Manipal Academy of Higher Education Department of Electronics and Communication Engineering Manipal India

ISBN: (纸本)9798350333558

Text retrieval activity involves retrieving the source code which software developers conduct on a daily basis. Current methods for retrieving source code rely on regular expressions and assume that the developers searching the code base are well-versed in the source code. Software developers ought to possess freedom to formulate queries on the codebase using natural language sentences as opposed to a search being a keyword or pattern-based, which are difficult to remember. When a bug is raised, developers who are new to the source code base may issue an NLQ to the code base to obtain the code where they must provide a fix. Nevertheless, the performance of a text search is highly dependent on query quality, and it succeeds when the textual query is of good quality. Predicting query quality in advance on a source code retrieval system can alert developers when a query is unlikely to succeed, thereby saving them time and effort from going through a long list of results. In this paper, the quality of the query is predicted using a back-propagation approach to train a feed-forward neural network (multi-layer perceptron). The model is trained and evaluated on a dataset that is created from the source code documentation. Natural language processing pre-retrieval metrics are exploited to study the significance of training the model. The model proves to be a good predictor of query quality with 85.75% accuracy. © 2023 IEEE.

关键词： information retrieval

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User-Centric Drink Customization with Cloud-Powered Collaborative Filtering with Raspberry Pi Integration 11

User-Centric Drink Customization with Cloud-Powered Collabor...

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11th International Conference on Reliability, Infocom Technologies and Optimization, ICRITO 2024

作者： Gowriswari, S. Fathima, S Shafla Joseph Rajan, D. Antony Mohankumar, N. Sasirekha, V. Rajmohan, M. Sri Sairam Engineering College Department of Instrumentation and Communication Engineering Tamil Nadu Chennai India B.S. Abdur Rahman Crescent Institute of Science and Technology Department of Information Technology Tamil Nadu Chennai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Tamil Nadu Chennai India B.V. Raju Institute of Technology Department of Electronics and Communication Engineering Telangana India Srm Institute of Science and Technology Faculty of Management Studies Tamil Nadu Chennai India Hindustan Institute of Technology and Science Department of Electronics and Communication Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350350357

This paper proposes an approach for user-centric drink customization by combining Raspberry Pi technology with cloud-powered collaborative filtering. By using collaborative filtering algorithms housed in cloud architecture, the proposed solution seeks to improve the beverage customization experience. A specialized Raspberry Pi interface allows users to input their preferences and comments, which are automatically included in the collaborative filtering mechanism. With the help of this cloud-based system, user data can be processed and analyzed in real time, enabling personalized drink suggestions. Adding Raspberry Pi devices to a system makes it more responsive and makes data processing more localized, which is great for users. The combination of Raspberry Pi with cloud-powered collaborative filtering shows that it can provide a highly customized and adaptable drink experience. This study adds to the growing body of knowledge in cloud-based collaborative filtering and Internet of Things (IoT) applications, and it provides a potential way to improve customer happiness in the beverage business. © 2024 IEEE.

关键词： Collaborative filtering

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DESIGN OF TWO CORE PHOTONIC CRYSTAL FIBER(TC-PCF) WITH CIRCULAR-ELLIPTICAL LATTICE STRUCTURE BASED TEMPERATURE SENSOR 8

DESIGN OF TWO CORE PHOTONIC CRYSTAL FIBER(TC-PCF) WITH CIRCU...

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8th International Conference on Computing in engineering and Technology, ICCET 2023

作者： Pravesh, Ram Kumar, Dharmendra Pandey, Bramha P. Chaudhary, Vijay Shanker Kumar, Santosh Department of Electronics and Communication Engineering Madan Mohan Malaviya University of Technology UP Gorakhpur273010 India Department of Computer Science Engineering Galgotias College of Engineering and Technology UP Greater Noida201310 India Shandong Key Laboratory of Optical Communication Science and Technology School of Physics Science and Information Technology Liaocheng University Liaocheng252059 China

ISBN: (纸本)9781839539237

This paper proposes a unique two-core photonic crystal fibre-based temperature sensor that combines circular and elliptical air hole lattice structures. Version 5.6 of the commercially available COMSOL Multiphysics software is based on the finite element method (FEM) used to develop and explore the impact of different effects of the sensor's basic geometric characteristics on its sensing capabilities. Two solid cores that are separated by vertical elliptical air holes create two independent waveguides. Because the background material's refractive index varies with temperature, Temperature has an interference with the TC-PCF transmission spectrum. The proposed TC-PCF temperature sensor can detect temperature in the range of 0 °C to 600 °C with fiber length 16 cm long and calculated sensitivity is 20 pm/°C. As a result of mode coupling between two waveguides, light is transported between one core and another core along the fibre when one core of a two-core PCF receives optical light from the input side. At 600 °C the maximum coupling length is observed 2.801 mm with operating wavelength 1.54 urn for proposed PCF. © The Institution of engineering & Technology 2023.

关键词： Photonic crystal fibers

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On Road Vehicle Detection and Tracking in Various Weather Conditions

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Journal of The Institution of Engineers (India): Series B 2022年 1-10页

作者： Anandhalli, Mallikarjun Baligar, Pavana Baligar, Vishwanath P. Hiremath, Prakash S. Department of Electronics and Communication Engineering KLS Gogte Institute of Technology Belagavi Belagavi India Department of Information Science and Engineering Smt. Kamala and Sri Venkappa M. Agadi College of Engineering and Technology Laxmeshwar India Department of Computer Science and Engineering KLE Technological University Hubballi India Department of Master of Computer Application KLE Technological University Hubballi India

The paper aims in presenting distinctive pattern in identification of vehicles using basic and sequential algorithms. Vehicle detection and classification are crucial in traffic control and management decision-making. Vehicle characteristics are critical elements for identifying vehicles. For vehicle detection, the programmer additionally employs thresholds and corner detection techniques. This technique shall be used in order to extract the interest points from an image, while background subtraction method can remove unwanted points. Within a region of object, many corner points will be compacted, which is regarded an initial prerequisite. Thickly surrounded ends are clustered;which provides clue of points related to each vehicle, which is an important part in vehicle identification. The non-vehicle region is separated when the grouping is completed. The corner points are traced using the LK algorithm to ensure that they remain stable. A 93.95% success rate is achieved. © 2022, The Institution of Engineers (India).

关键词： Decision making

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An Analysis of Web Security Measures for Protecting Wireless Networks from Malicious Attack 3

An Analysis of Web Security Measures for Protecting Wireless...

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3rd International Conference on Smart Generation Computing, communication and Networking, SMART GENCON 2023

作者： Balaji, N.V. Senthamilselvan, K. Dhabliya, Dharmesh Mishra, Dinesh Saxena, Manish Akhtar, Md. Amir Khusru Karpagam Academy of Higher Education Department of Computer Science Coimbatore641021 India Prince Shri Venkateshwara Padmavathy Engineering College Department of Electronics and Communication Engineering Chennai India Vishwakarma Institute of Information Technology Department of Information Technology Maharashtra Pune India Mangalayatan University Department of Computer Science Jabalpur India Himalayan University Department of Computer Science Itanagar India Usha Martin University Department of Coputing & Information Technology Ranchi India

ISBN: (纸本)9798350319125

This technical abstract is an analysis of internet security features for shielding Wi-Fi networks from malicious assaults. The main objective of this evaluation is to perceive the best security features for defensive a wireless community, and to determine which of the net protection alternatives are the best and within your means. The evaluation makes use of each quantitative and qualitative studies methods to degree different factors which includes cost, inconvenience, implementation complexity, and safety warranty. After an extensive assessment of the present net protection alternatives, its miles concluded that a combination of encryption, authentication, firewalls, access control lists, and antivirus/anti-malware software is the maximum efficient approach for preserving a wireless community secure from malicious assaults. Furthermore, the most excellent security features depend upon the size, complexity, and price range of the corporation, and ought to be tailor-made to fulfill the precise needs of the employer. © 2023 IEEE.

关键词： community corporation determine evaluation maximum

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IIDS: Design of Intelligent Intrusion Detection System for Internet-of-Things Applications 7

IIDS: Design of Intelligent Intrusion Detection System for I...

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7th IEEE Conference on information and communication Technology, CICT 2023

作者： Narayan, K.G. Raghavendra Mookherji, Srijanee Odelu, Vanga Prasath, Rajendra Turlapaty, Anish Chand Das, Ashok Kumar Computer Science and Engineering Indian Institute of Information Technology Sri City Sri City Chittoor517646 India Electronics and Communication Engineering Indian Institute of Information Technology Sri City Sri City Chittoor517646 India Center for Security Theory and Algorithmic Research International Institute of Information Technology Hyderabad Hyderabad500 032 India

ISBN: (纸本)9798350305173

With rapid technological growth, security attacks are drastically increasing. In many crucial Internet-of-Things (IoT) applications such as healthcare and defense, the early detection of security attacks plays a significant role in protecting huge resources. An intrusion detection system is used to address this problem. The signature-based approaches fail to detect zero-day attacks. So anomaly-based detection particularly AI tools, are becoming popular. In addition, the imbalanced dataset leads to biased results. In Machine Learning (ML) models, the F1 score is an important metric to measure the accuracy of class-level correct predictions. The model may fail to detect the target samples if the F1 is considerably low. It will lead to unrecoverable consequences in sensitive applications such as healthcare and defense. So, any improvement in the F1 score has a significant impact on the resource protection. In this paper, we present a framework for an ML-based intrusion detection system for an imbalanced dataset. In this study, the most recent dataset, namely CICIoT2023 is considered. The random forest (RF) algorithm is used in the proposed framework. The proposed approach improves 3.72%, 3.75% and 4.69% in precision, recall and F1 score, respectively, with the existing method. Additionally, for unsaturated classes (i.e., classes with F1 score 1 score improved significantly by 7.9%. As a result, the proposed approach is more suitable for IoT security applications for efficient detection of intrusion and is useful in further studies. © 2023 IEEE.

关键词： Internet of things

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