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2024 International Conference on Intelligent and Innovative Practices in engineering and Management, IIPEM 2024

作者： Bennet, Deepthi Tabitha Samantha Bennet, Preethi Anitha Gracy, J. Sharmila, P. Thiagarajar College of Engineering Dept. of Applied Mathematics and Computational Science Madurai India

ISBN: (纸本)9798350390049

The detection and classification of malware pose significant challenges in cybersecurity due to the ever-evolving nature of malicious threats. In this study, we propose a novel approach for classifying malware using deep neural networks (DNNs). Our dataset comprises of 25 distinct classes of malware samples. After developing and testing 4 DNNs, including ResNet50, InceptionResNetV2, VGG16, DenseNet169, a robust and efficient model capable of accurately identifying and categorizing malware instances is built using DenseNet169. The process involves feature extraction from byteplot *** proposed malware detection model uses DenseNet169 as it has shown very high accuracy (95%), precision, recall and F1-score for the *** research contributes to advancing the state-of-the-art in malware classification, providing insights into the efficacy of deep neural networks for combating sophisticated cyber threats in modern computing environments. © 2024 IEEE.

关键词： Cyber attacks

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Revolutionizing Residential EV Charging Through IoT-Enabled Smart Energy Metering for Sustainability 6

Revolutionizing Residential EV Charging Through IoT-Enabled ...

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6th International Conference on Mobile Computing and Sustainable Informatics, ICMCSI 2025

作者： Sivakumar, N. Charles Raja, S. Meenakshi Devi, M. Saraswathi Meena, R. Dept. of EEE Thiagarajar College of Engineering Tamilnadu Madurai India Dept. of Applied Mathematics and Computational Science Thiagarajar College of Engineering Tamilnadu Madurai India

ISBN: (纸本)9798331522667

The rapid growth in Electric Vehicle (EV) adoption poses substantial challenges to residential energy infrastructures, especially in terms of the strain it places on local grids during charging. This paper proposes an IoT-based Smart Energy Meter System (SEM) designed to efficiently manage EV charging in residential environments. The system integrates IoT technology with advanced energy metering features, enabling real-time monitoring and control of charging operations. The system is composed of intelligent energy meters for real-time monitoring, an IoT-enabled hub for data collection and processing, and an intuitive consumers interface for customizing and managing EV charging schedules. By continuously monitoring energy consumption and charging demands, the system optimizes charging schedules to reduce peak loads, lower energy costs, and enhance grid stability. It provides residents with insights into their energy usage and charging patterns, empowering them to make informed decisions to reduce their carbon footprint. Furthermore, the system seamlessly integrates with renewable energy sources and energy storage solutions, promoting clean energy usage for EV charging. Through cloud-based analytics and predictive maintenance, it ensures reliable and uninterrupted charging services. The proposed IoT-based SEM system offers a scalable and sustainable solution for managing EV charging in residential settings, supporting electric mobility while improving energy efficiency and promoting environmental sustainability. © 2025 IEEE.

关键词： Predictive maintenance

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Content Based Classification of Short Messages using Recurrent Neural Networks in NLP

Content Based Classification of Short Messages using Recurre...

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2024 International Conference on Artificial Intelligence, Computer, Data sciences, and Applications, ACDSA 2024

作者： Bennet, Deepthi Tabitha Bennet, Preethi Samantha Thiagarajan, Priya Sundarakantham, K. Thiagarajar College of Engineering Dept. of Applied Mathematics and Computational Science Madurai India Thiagarajar College of Engineering Dept. of Computer Science and Business Systems Madurai India Thiagarajar College of Engineering Dept. of Computer Science and Engineering Madurai India

ISBN: (纸本)9798350394528

Short message spam poses a significant threat for all mobile phone users, as it can act as an efficient tool for cyberattacks including spreading malware and phishing. Traditional anti-spam measures are only minimally effective against modern spammers. Intelligent analysis of the content to categorise the messages as Spam (unwanted and unsolicited) or Ham (useful messages) is therefore essential to safeguard the user from such attacks. Various artificial intelligence (AI) techniques are proving to be useful in the analysis of the content of such short messages to classify and filter spam. We have trained, validated and tested seven such AI techniques on the SMS spam collection dataset to identify the best model for designing and developing a content based classification system. Recurrent Neural Networks (RNN) have shown the highest performance metrics (Test Accuracy: 99.28%) and hence our proposed system includes a RNN model for classification. A web app of this system has also been deployed where a single SMS can be input and the designed system can classify it as Spam or Ham. The designed system is compared against existing systems and is found to be significantly better. © 2024 IEEE.

关键词： Recurrent neural networks

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Assessing Student Comprehension and Implementation of Design Thinking in Mechanical engineering Education

Assessing Student Comprehension and Implementation of Design...

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2024 International Conference on Decision Aid sciences and Applications, DASA 2024

作者： Naji, Malak I. Abdelhameed, Wael Awawdeh, Safa Applied Science University Dept. of Electrical and Mechanical Engineering Bahrain Applied Science University Dept. of Civil and Architectural Engineering Bahrain

ISBN: (纸本)9798350369106

This paper investigates how the integration of fundamental principles of mechanical engineering within students' learning in the context of drawing, manufacturing process, and fabrication methods influences the understanding and practical application of design thinking principles among first-year students. The program interlinks theoretical education with work in laboratories on issues dealing with orthographic and isometric projections, metal forming, casting, machining, and welding. The students' improvement is evaluated by Pre-Intervention, Mid-Intervention, and Post-Intervention Surveys. These surveys also monitored shifts in student knowledge, technical skills, and design thinking. The results have indicated a significant gain over the course of the intervention in the student's ability to navigate the idea-to-product continuum, in the students' skill with AutoCAD, and in the competencies associated with manufacturing and fabrication processes. Such research exemplifies how a structured curriculum effectively incorporates theoretical teaching with hands-on experience for improved engineering education to equip students better for the challenges faced in the industry. © 2024 IEEE.

关键词： Students

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EVALUATION OF HYDROELASTIC RESPONSE AND STRUCTURAL FAILURE OF PONTOON TYPE FLOATING OFFSHORE WIND TURBINES SUBJECTED TO WIND AND OCEAN WAVES

Journal of Structural and Construction Engineering

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Journal of Structural and Construction engineering 2024年第816期89卷 235-246页

作者： Fujita, Ken-Ichi Yashiro, Harumi Dept. of Engineering Faculty of Engineering Nagasaki Institute of Applied Science Japan School of Systems Engineering National Defense Academy of Japan Japan

An evaluation method of hydroelastic response and structural failure of pontoon type floating offshore wind turbines for wind and ocean waves is presented. The response to the mean wind speed is analyzed statically and to both variable wind speed and waves are analyzed by using a stationary random vibration theory. The failure is evaluated by using a first order reliability method. A boundary and finite element hybrid model is used to the hydroelastic analysis of the structures. Moreover, variations of the response and the failure probability of the structures for different wind speed and direction are discussed. © 2024 Architectural Institute of Japan. All rights reserved.

关键词： Wind

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THE EFFECT OF FREEZING ON THE PHYSICO-CHEMICAL PROPERTIES OF TOMATO FRUITS (SOLANUM LYCOPERSICUM L.)

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UPB Scientific Bulletin, Series B: Chemistry and Materials science 2024年第1期86卷 165-172页

作者： Marcu, Iuliana Radu, Gabriel Lucian Dept. of Applied Chemistry and Materials Science The National University of Science and Technology POLITEHNICA Bucharest Faculty of Chemical Engineering and Biotechnologies Romania

The modifications of the physico-chemical properties of tomatoes were investigated in case of freezing, applied on two varieties of cherry tomatoes (Flaviola and Ema) cultivated in Buzău, Romania. Preserving by freezing is a common method of keeping the physico-chemical properties for the tomato fruits at home. Fresh fruits and vegetables, when harvested, keep on undergoing chemical modifications likely to bring forth product alteration and damaging. That is the reason why such products must be frozen as soon as possible after harvesting and upon their maximum degree of ripening. The outcomes achieved as a result of the research regarding the content of macroelements (Ca, K, Mg, Na), microelements (Fe, Mn, Ba, Cu, Ni) and also the one in carotenoids (lycopene and β-carotene) after freezing, show that this procedure considerably affected both tomato content as compared to the sample in its fresh condition, which means that there was a certain nutritional value loss. More specifically, in case of the Ema tomato, the content of potassium (K) increased from 141.2 mg L-1 to 186.1 mg L-1 and for Flaviola from 154.6 mg L-1 to 165.53 mg L-1, content of iron (Fe) decreased from 181.37µg L-1 to 126.70 µg L-1 and the content of copper (Cu) increased for both tomatoes, in case of the Flaviola from 30.1 µg L-1 to 35.0 µg L-1 and for Ema sample from 31.55 µg L-1 to 76.13 µg L-1. © 2024, Politechnica University of Bucharest. All rights reserved.

关键词： Freezing

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Firefly Algorithm Approach for Recovering the Mathematical Structure of One-Dimensional Chaotic Maps from Time Series Data 3

Firefly Algorithm Approach for Recovering the Mathematical S...

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3rd International Conference on Computer Technologies, ICCTech 2024

作者： Galvez, Akemi Fister, Iztok Fister, Iztok Iglesias, Andres University of Cantabria Dept. of Applied Mathematics & Computational Sciences Santander Spain University of Maribor Faculty of Electrical Engineering & Computer Science Maribor Slovenia

ISBN: (纸本)9798350395419

Uncovering the mathematical structure of unknown chaotic systems from limited time series data poses a significant challenge in the field of dynamical systems, with broad applications across various domains. In this paper, we propose a swarm intelligence approach to tackle this issue, specifically focusing on one-dimensional discrete maps. Our approach leverages the firefly algorithm, a popular nature-inspired metaheuristic, known for its optimization capabilities. We assess the performance of the method by applying it to two illustrative examples of time series derived from one-dimensional maps: the Hénon map and the Burger map. The results show that this approach is promising for recovering the equations of motion of one-dimensional chaotic maps, even in situations where no additional information is available beyond the provided data points. © 2024 IEEE.

关键词： Time series

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Mechanistic evaluation of segregation in HMA mixtures

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International Journal of Transportation science and Technology 2024年第3期15卷 198-210页

作者： Ibrahim Asi Aya Al-Asi Civil Engineering Dept. Al Ahliyya Amman UniversityAmman 19328Jordan Civil Engineering Dept. Applied Science Private UniversityP.O.Box 166Amman 11931Jordan

Segregation in hot mix asphalt(HMA)mixtures is defined as the separation of the coarse aggregate particles in the mixtures from the rest of the *** can be a result of aggregate stockpiling and handling,production,storage,truck loading practices,con-struction practices,and equipment *** is usually evaluated visually,which is considered as a subjective method with no definite limits and depends on the evaluator’s *** study uses two mechanistic surface texture indicators,i.e.,mean texture dept.(MTD)that is measured using sand patch method and mean profile dept.(MPD)using laser texture profilometer to evaluate if a road section is segregated or *** sand patch method is standardized in ASTM E965-15(2019)"for Measuring Pavement Macrotexture dept. Using Volumetric Technique".MPD is covered by the inter-national standards ASTM E1845-15"Standard Practice for Calculating Pavement Macrotexture Mean Profile dept.".Using both measured MTD values at grid point crossings,and average MPD values at 25 m intervals in the wheel paths,in addition to the use of statistical analysis of the obtained data,assuming that the obtained data are normally distributed and finding the 95%probability limits of the MTD and MPD values,it is possible to prove the closeness of the obtained texture dept. indicator data,homogeneity of the road section,and that the segregation is only present at very limited localized locations.

关键词： Segregation Pavement Hot mix asphalt(HMA) Aggregate Asphalt Mean texture dept.

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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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2024 IEEE International Conference on Intelligent Systems and Advanced Applications, ICISAA 2024

作者： Roy, Prince Kumar, Rajneesh Morshed, Md Neaz Fairleigh Dickinson University Dept. of Applied Computer Science United States Dept. of Computer Science & Engineering India

ISBN: (纸本)9798331539948

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. © 2024 IEEE.

关键词： Supply chain management

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EVALUATION OF SEAQUAKE RESPONSE AND STRUCTURAL FAILURE OF PONTOON-TYPE FLOATING OFFSHORE WIND TURBINES

Journal of Structural and Construction Engineering

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Journal of Structural and Construction engineering 2024年第826期89卷 1471-1482页

作者： Fujita, Ken-Ichi Yashiro, Harumi Dept. of Engineering Faculty of Engineering Nagasaki Institute of Applied Science Graduate School of Engineering Nagasaki University Japan School of Systems Engineering National Defense Academy of Japan Japan

An evaluation method of seaquake response of pontoon-type offshore wind turbines using stationary random vibration theory is presented. Seabed motion in the vertical direction due to an earthquake is modeled as a stationary random process. A BE-FE hybrid model is used for the response analysis. The excitation surface on the seabed is discretized by boundary elements. The response results are used to structural failure probability and the probability is analyzed using a first-order reliability method. Numerical examples show the variety of the responses and the failure probability of structures for class of soil, seismic acceleration and epicentral distance. © 2024 Architectural Institute of Japan. All rights reserved.

关键词： Offshore wind turbines

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