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Smart Power Control and Renewable Energy (ICSPCRE), IEEE International Conference on

作者： D Jaya Narayana Reddy Krishna Priya R J. Arun Kumar P. Dharani Prasad Mustafa Nawaz Nookala Venu G Pullaiah College of Engineering and Technology Research and Consultancy Department University of Technology and Applied Sciences Governorate of Musandam Sultanate of Oman Department of ECE Vel Tech Rangarajan Sagunthala R&D Institute of Science and Technology Dept of Pharmacology Mohan Babu University MB School of Pharmaceutical sciences (Erstwhile Sree Vidyaniketan College of Pharmacy) Tirupati Department of Computer Science and Engineering Sri Sairam Institute of Technology Centre for IoT Madhav Institute of Technology & Science (MITS) (A Govt. Aided UGC Autonomous Institute) Gwalior Madhya Pradesh India

ISBN: (数字)9798350377002

ISBN: (纸本)9798350377019

In the dynamic landscape of agriculture, the convergence of technological advancements and sustainable practices has become imperative. The emergence of soilless farming, driven by hydroponics and aeroponics, presents a promising solution to address food security challenges while mitigating environmental concerns. Central to the success of soilless farming is efficient plant phenotyping, which traditionally relies on labour-intensive methodologies. However, this paradigm is shifting with the integration of Artificial Intelligence (AI) and Deep Learning techniques. This research endeavours to pioneer an innovative approach to plant phenotyping in soilless farming by harnessing the power of AI. Leveraging a unique dataset meticulously curated from controlled hydroponic and aeroponic environments, our study aims to redefine the boundaries of agricultural research and practice. By employing state-of-the-art Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), we dissect complex phenotypic traits encompassing leaf morphology, biomass accumulation, and physiological responses. Through iterative model refinement and validation, we strive to develop a robust framework capable of real-time phenotypic assessment across diverse plant species and growth stages. By synthesizing diverse environmental conditions and perturbations, we augment the original dataset, enhancing model generalization and adaptability. Moreover, through transfer learning techniques, Furthermore, the scalability and accessibility of AI technologies pave the way for democratizing agricultural innovation, fostering inclusive growth and resilience in the face of global challenges.

关键词： Deep learning Technological innovation Recurrent neural networks Plants (biology) Biological system modeling Scalability Real-time systems

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Effects of Code Cloning in Mobile Applications 3

Effects of Code Cloning in Mobile Applications

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3rd International Conference on Computing, Mathematics and engineering Technologies, iCoMET 2020

作者： Azeem, Muhammad Zubair Imran, Azhar Akhtar, Faheem Wajahat, Ahsan Latif, Jahanzaib Memon, Suhail Ahmed University of Lahore Department of Computer Science Sargodha Pakistan Beijing University of Technology School of Software Engineering Beijing China Department of Computer Science Sukkur IBA University Sukkur Pakistan LARMIS Board of Revenue Govt. of Sindh Matiari70150 Pakistan

ISBN: (纸本)9781728149707

Developers usually copy and paste code during software development that results in similar patches of code spread in different files. Such type of code clones cause difficulty in making changes and result in bugs. In this study, we want to analyze the extent of the use of code cloning in the development of mobile applications and their effect on post-release bugs. This information should help developers and designers to develop and design better applications and software that present their results to the best advantage. © 2020 IEEE.

关键词： Cloning

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Performance evaluation of threshold-based and k-means clustering algorithms using iris dataset

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Recent Patents on engineering 2019年第2期13卷 131-135页

作者： Mittal, Mamta Sharma, Rajendra Kumar Singh, Varinder Pal Department of Computer Science & Engineering G. B. Pant Govt. Engineering College Okhla New Delhi India Department of Computer Science & Engineering Thapar University PatialaPunjab India

Background: Clustering is one of the data mining tools which classify the raw data reasonably into disjoint clusters. Researchers have developed many algorithms to cluster large data sets based on specific parameters. Objective: This study is centered around the popular partitioning-based technique, i.e., k-means. It requires the number of clusters to be generated as an input parameter;it does not provide a global solution of the problem;and it is sensitive to outliers and initial seed selection. Methods: In this paper, authors have discussed threshold-based clustering method, single pass method, which overcomes the above limitations but it requires a threshold value as an input parameter. Other re-searchers’ work related to k-means published in patent form is noteworthy and paving path for the researchers. Results: To assess the quality of clustering, numerous validity measures and indices have been assessed on the Iris dataset for both k-means and threshold-based clustering algorithms. It has been observed from the experiments that threshold-based method generates more separated and compact clusters, in addition, there is significant improvement in the validity indices. Conclusion: Threshold-based clustering generates the clusters automatically which are not sensitive to initial seeds selection and outlier;it is more scalable. It will inevitably be an efficient approach of partitioning based clustering whenever one will select the threshold value carefully or will propose new functions for deciding the value of threshold. © 2019 Bentham Science Publishers.

关键词： K-means clustering

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Exploring the application domains of ML-based facial emotion recognition systems: Framework, techniques and challenges

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AIP Conference Proceedings 2024年第1期2919卷

作者： Sita Rani Pankaj Bhambri Jaskiran Kaur Yashwant Singh Sangwan Department of Computer Science & Engineering Guru Nanak Dev Engineering College Ludhiana-141006 Punjab INDIA Department of Information Technology Guru Nanak Dev Engineering College Ludhiana-141006 Punjab INDIA Department of Computer Science Govt. College Hisar-125001 Haryana INDIA

Human facial expressions are one of the important techniques of non-verbal communication. Facial expressions are the most tender signs for larger communication and are complemented by other gestures like eye contact, hand movement, etc. This is the direct method of communication of human emotions and intent. In this paper, the authors present the Facial Emotion Recognition (FER) framework and a brief survey of various FER techniques. It also presents the various phases of the FER system i.e., face detection, pre-processing, feature extraction, and classification. Various FER databases like JAFFE, YALE, MUG, etc. are also summarized in terms of the number of emotions, number of images, and resolution. The importance of the domain in other related subject areas like medicine, neuroscience, psychology, decision science, gaming, mental research, etc., is also introduced. The authors explored the application areas of FER techniques. The authors also present the various challenges faced in the real-time implementation of FER models. Finally, the paper is concluded by discussing future research directions.

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Real-Time Life Analysis of the Electric Vehicles using IoT - computer-Based Smart Systems

Real-Time Life Analysis of the Electric Vehicles using IoT -...

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Communication, Security and Artificial Intelligence (ICCSAI), International Conference on

作者： Bathala Neeraja Hmingthanpuii Ralte Kirti Jain Samarth Ramchandra Surlekar Dinesh Ashok Arani Romie C. Mabborang EEE Electrical and Electronics Engineering Dept Government Polytechnic Hyderabad Telangana India Govt. Mizoram Law College Affiliated to Mizoram University Mizoram India School of Advanced Computing Sanjeev Agrawal Global Educational University Bhopal Madhya Pradesh India Department of Electrical- High voltage Engineering National Institute of Technology Calicut Kerala India Manglayatan University Aligarh Uttar Pradesh India Mathematics Department Pamantasan ng Lungsod ng Maynila (University of the City of Manila) Manila Philippines

Most significant automobile manufacturers are now interested in developing Electric Vehicles (EVs). The improvements in battery life and low emissions of EVs have sparked a lot of attention in recent years. Similarly, the growth of the Internet of Things (IoT) made it possible for an increasing number of devices to be connected. However, the autonomy and lack of infrastructure in most locations outside of major cities are one of the consumer concerns regarding adopting EVs. This study's primary objective is to explore how IoT-based systems may be used to analyze real-world usage data for EVs. The systematic literature review was the methodology utilized in this research. This study found that IoT technology has enormous potential for use in advancing and developing the Smart Grid. EVs are a type of dynamic electrical energy storage system that is pretty common due to their excellent electrical properties and flexibility. Still, their mass adoption significantly impacts the grid and poses a risk of damaging their batteries in the event of overcharging or deep discharging. EV batteries require a particular state of charge prediction to reduce the risk of damage, allowing them to have a longer lifespan and protect the devices they power. With the aid of a real-time Battery Monitoring System (BMS) that uses the coulomb counting method for State of Charge (SoC) estimate, a comparison between three techniques-Node-Red, Message Queuing Telemetry Transport (MQTT), and Arduino approach-is studied in this study based on their ease of implementation and overall lack of complexity.

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Implementation of an Early Warning System using Internet of Things and Rainfall Threshold

Implementation of an Early Warning System using Internet of ...

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International conference of Electronics, Communication and Aerospace Technology (ICECA)

作者： Veera Sivakumar Chinamuttevi KDV Prasad Dankan Gowda V A.Yasmine Begum Rama Chaithanya Tanguturi Bashir Ahmed Department of Engineering Univeristy of Technology and Applied Sciences-IBRI Sultanate of Oman Symbiosis Institute of Business Management Hyderabad Telangana India Department of Electronics and Communication Engineering BMS Institute of Technology and Management Bangalore Kamataka India Department of EIE Sree Vidyanikethan Engineering College A.rangampet Andhra Pradesh Department of Computer Science and Engineering Pace Institute of Technology and Sciences Ongole Andhra Pradesh Department of Physics Govt. Degree College Banihal Banihal Ramban Jammu and Kashmir

ISBN: (纸本)9781665482721

Landslide hazard guideline serves as one among the various elements within a built-in processing and preparation investigation. The landslide hazard zonation studies are the critical task in the landslide risk assessment process. Also to minimize the death toll due to landslides, landslide early warning is one of the important considerations. The attempts on landslide hazard zonation have been carried out in India for the past few decades. However, the systematic landslide hazard zonation studies started in the early 1980's. The major challenge of efficiently communicating with the hardware (Pi processor) through internet or satellite connectivity depends on the availability of the resources. The major difference between this proposed architecture and the already available predicting systems is that, this is a low cost and user-friendly app interface which can communicate information with the users in a matter of seconds. A test was performed by making a model in the lab-scale (using sensor network) and artificially triggering soil slide by sprinkling water (artificial rain). To perform early warning to authorities, an android based mobile application has been created using the Internet of Things. The present application alerts the people while rainfall in the identified slope area exceeds the threshold limits.

关键词： Wireless sensor networks Systematics Alarm systems Soil Terrain factors Hazards Risk management

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Evaluation of mechanical and tribological properties of hybrid AA6061 Al matrix composite

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Materials Today: Proceedings 2020年 27卷 2918-2924页

作者： M. Karthikraja K. Ramanathan S. Selvaraj S. Sargunanathan Mechanical Engineering Department Alagappa Chettiar Govt. College of Engg and Tech Karaikudi 630003 India Mechanical Engineering Department Annamalai Polytechnic College Chettinad 630102 India

Aluminium matrix composite is that the effective and qualified material among the commercial domain. In this work, a trial has been created to make Aluminium Alloy 6061 metal bolstered with SiC and Al2O3 particles. The matrix metal aluminium has several distinctive properties like high strength, less weight and easy machinability . Silicon carbide has splendid hardness and wear resistance and aluminium oxide provides good compressive strength and wear resistance. Hence, they were chosen as the matrix and reinforcements. Four Samples are prepared by varying weight percentages of reinforcements. The reinforcements are taken equally for hybridization of each sample and varied as 2.5%, 5% and 7.5% and a monolithic aluminium sample also prepared for the comparison purposes. By using squeeze casting technique, the needful quantities of reinforcements mixed in the stirred molten stage of aluminium are solidified under high pressure. The purpose of the study is to judge the mechanical properties like hardness and compressive strength and tribological behaviour of the on top of invented AMC.

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PV based Isolated Irrigation System with its Smart IoT Control in Remote Indian Area

PV based Isolated Irrigation System with its Smart IoT Contr...

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International Conference on computer, Electrical & Communication engineering (ICCECE)

作者： Arunava Chatterjee Soumyajit Ghosh Department of Electrical Engineering Jadavpur University Kolkata India Department of Electrical Engineering Raghunathpur Govt. Polytechnic Kolkata India

ISBN: (数字)9781728144764

ISBN: (纸本)9781728144771

This paper presents an automated pumped irrigation system implementation for a remote onshore Indian area. The system is powered using a PV based module. In this study, the parameters such as irradiation, moisture content of soil, availability of load, etc. has been extensively taken into account. The irrigation system also has a storage battery for storing and retrieving the energy available for the PV module and for supplying loads. The system is entirely controlled using a microcontroller. The system is remotely monitored using an Internet of Things (IoT) based smart controller. An economic analysis for the scaled-up system is also performed to study practical setup of such a system in Indian conditions. Appropriate simulations and experimental studies on a laboratory-based model validate the proposed study.

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Systematic Literature Review on Agile, Cloud, and Devops Integration: Challenges, Benefits

SSRN

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SSRN 2024年

作者： El Aouni, Fatiha Moumane, Karima Idri, Ali Najib, Mehdi Jan, Saeed Ullah Software Project Management Research Team National School of Computer Science and Systems Analysis Mohammed V University in Rabat Rabat10112 Morocco MSDA University Mohamed VI Polytechnic Ben Guerir Morocco TICLab College of Engineering and Architecture International University of Rabat Sala Al Jadida Morocco Higher Education Department Govt Degree College Wari Dir Upper 18200 Pakistan

Context : In today’s fast-paced digital landscape, integrating DevOps, cloud, and agile methodologies is crucial for meeting software demands. However, this integration remains *** : This study explores the integration of Agile, Cloud, and DevOps in today’s software development landscape. It aims to analyze the challenges and benefits associated with merging these three approaches, focusing on its impact on software testing and the role of mindset in successful implementation and identifying the most suitable Agile *** : This investigation utilizes a Systematic Literature Review(SLR) to enrich comprehension of these integrations in current software development *** : The analysis of 31 articles highlights benefits such as improved collaboration and accelerated development, despite challenges with tool proliferation. Platforms like Jenkins, GitLab, Kubernetes, and Docker show promise in addressing these complexities. Our study examines the advantages and challenges of this integration, focusing on its impact on software testing and the role of mindset in successful implementation and identifyingthe most suitable Agile *** : The integration of Agile, DevOps, and Cloud signifies a vital move towards collaborative, scalable, and automated methods, crucial for swift delivery, enhanced quality, and ongoing competitiveness. This unified approach is fundamental for organizational advancement and innovation in the ever-evolving software development realm. Further research should tackle challenges in merging these methods and delve into their interactions with emerging technologies to refine practices for increased efficiency. © 2024, The Authors. All rights reserved.

关键词： Integration

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Exploring the impact of cloud and edge computing in education: Addressing challenges and unveiling opportunities

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AIP Conference Proceedings 2024年第1期3149卷

作者： K. Arun Kumar H. Varun Chand Neethu Maria John Sruthy Emmanuel Sarojarani Polamarasetty Seema Sabharwal Department of Computer Science & Engineering Mohan Babu Uniiversity Tirupati Andhra Pradesh India Department of Computer Science & Engineering College of Engineering Perumon Kerala India Department of Computer Science & Engineering Mangalam College of Engineering Ettumanoor Kerala India Department of Computer Science & Engineering Godavari Institute of Engineering and Technology Rajahmundry Andhra Pradesh India Department of Computer Science Govt. P. G. College for Women Panchkula Haryana India

In this study, the effect, difficulties, and possible benefits of cloud and edge computing on the landscape of education are examined. The specific focus of the study is on how bettering educational procedures and results may be accomplished by integrating cloud and edge computing technologies. This essay’s first focus is on the issue of resource scalability and optimization in educational settings. Utilizing cloud computing allows educational institutions to effectively manage and distribute resources, improving operational performance and cost-effectiveness. To provide uninterrupted access to educational resources even in low-bandwidth situations, edge computing is also looked at as a potential solution to connection and latency problems. The difficulty of data security and privacy in cloud-based educational systems is also highlighted by this research. It examines the significance of sound data management techniques and looks into ways to safeguard private student data. The results highlight the need of putting in place strict security controls to protect student privacy while reaping the rewards of cloud and edge computing technologies. The last section of this essay discusses the outcomes of merging cloud and edge computing in educational contexts. It demonstrates how cloud-based LMSs improve accessibility, collaboration, and customized learning experiences. The study also shows how real-time data processing on the edge might support adaptive learning strategies and intelligent educational apps.

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