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International Conference on Advanced Information and Communication Technologies (AICT)

作者： Oleh Pisnyi Ivan Kit Khrystyna Lipianina-Honcharenko Jürgen Sieck Anatoliy Sachenko Maciej Dobrowolski Grygoriy Sapozhnyk Master's degree in Computer Science West Ukrainian National University Ternopil Ukraine Department for Information-Computing Systems and Control West Ukrainian National University Ternopil Ukraine Hochschule für Technik und Wirtschaft Berlin Berlin Germany Research Institute for Intelligent Computer Systems West Ukrainian National University Ternopil Ukraine Department of Informatics and Teleinformatics Kazimierz Pulaski University of Technology and Humanities in Radom Radom Poland

In a world of rapid technological changes and growing interest in cultural heritage, the development of innovative tools for travelers and history enthusiasts becomes incredibly important. Even in the digital age, interactive ways of exploring historical landmarks remain relevant and attractive. In this research, an AR Intelligent Real-time Method for Cultural Heritage Object Recognition has been developed. The method is implemented through a chatbot, which, when using a smartphone's camera, recognizes objects of cultural heritage and provides descriptions of these objects. The chatbot opens up new possibilities for travelers, allowing them to enjoy history and cultural heritage using intelligent tools and augmented reality.

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An Experiment to Develop an Enhanced Medical Image Security by using Deep Learning Assisted Crypto Policy

An Experiment to Develop an Enhanced Medical Image Security ...

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Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication Engineering (RMKMATE), International Conference on

作者： Ramkumar G V Sujatha B Raja M. TamilSelvi A. Balaji ATA Kishore Kumar Department of ECE Saveetha School of Engineering SIMATS Chennai India Department of Master of Computer Applications S.A. Engineering College Chennai India Department of ECE Dr. M.G.R. Educational and Research Institute Chennai India Department of ECE SRM Institute of Science and Technology Chennai India Department of ECE Rajalakshmi Institute of Technology Chennai India Department of ECE School of Engineering Mohan Babu University (Erstwhile Sree Vidyanikethan Engineering College) Tirupati Andra Pradesh India

Ensuring a high level of safety and security is imperative when transmitting medical images via open access channels. Medical images hold immense importance in various applications, particularly in real-time contexts like telemedicine. Due to the unique characteristics of medical imaging data, determining the appropriate techniques for safeguarding confidential images against unauthorized access becomes challenging. Existing encryption methods primarily cater to textual data, leaving a gap in effectively securing multimedia data such as images. Using DNN leaves these systems open to attack from adversarial samples, which are pictures with slight changes that can trick the model into producing inaccurate predictions. Utilizing the MNIST database, this research demonstrates that Deep Learning algorithms may be used to encrypted data without compromising accuracy. This finding holds significance as it offers a potential solution for preserving data security while benefiting from advanced machine learning capabilities. In addition, the research goes farther by training a model using encrypted information to categories X-ray coronary angiography images, making it a more difficult scenario. The suggested DNN model's remarkable accuracy score of 0.983 highlights its ability to make predictions with an exceptional level of correctness.

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Step-by-Step Image Encryption Using UACI and PixAdapt 2nd

Step-by-Step Image Encryption Using UACI and PixAdapt

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2nd International Conference on Cyber Warfare, Security and Space Computing, SpacSec 2024

作者： Balamurugan, J. Yadav, Mali Madhavi, Jetti Reddy, A. Basi Selvan, R. Senthamil Department of Master of Business Administration St. Joseph’s College of Engineering OMR Tamilnadu Chennai India Department of Physical Education Lovely Professional University Punjab India Department of Mathematics Malla Reddy Engineering College Medchal Hyderabad India Department of Computer Science and Engineering School of Computing Mohan Babu University Andhra Pradesh Tirupati India Department of Electronics and Communication Engineering Annamacharaya Institute of Technology and Sciences Andhra Pradesh Tirupati India

ISBN: (纸本)9783031734939

A new cutting-edge method recently garnered interest is image encryption utilizing a genetic approach. Currently, most genetically based picture encryption algorithms use fixed parameters to encrypt images, ignoring any image-representative properties. This research led to PixAdapt, a novel adaptive picture encryption technique. It is being re-engineered such that the fitness of the encrypted picture can be determined using UACI, and the relevant parameters may be adjusted using hereditary hill climb or pretend annealing. Pseudorandom numbers have been generated using a variety of chaos-based maps, including the Logistic, Rossler, Henon, and Tent maps, as well as the linear feedback shift register. The PixAdapt algorithm uses the theory of confusion and diffusion to further ensure that the plaintext and ciphertext images are completely dissimilar. This is the first instance of optimizing picture encryption settings using metaheuristic search algorithms. Finding the best possible UACI value, the hereditary hill climb algorithm encrypts all of the photos. Fitness enhancement, limit evolution, arithmetical analysis, and encryption quality testing have all been conducted on the method. When it comes to effectively encrypting images, PixAdapt is one of a kind and has shown that the UACI encryption parameter is a good match. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Shift registers

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Safe Transportation System using IoT based Alcohol Detection

Safe Transportation System using IoT based Alcohol Detection

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International Conference on ent Computing and Control Systems (ICICCS)

作者： G Pradeepkumar P Vijayakumar N Chandrasekaran C Rohith Bhat C Senthilkumar Neelam Sanjeev Kumar Department of Electronics and Communication Engineering KPR Institute of Engineering and Technology Coimbatore India Department of Master of Computer Applications Kongu Engineering College Perundurai Tamil Nadu Department of Electrical and Electronics Engineering PSNA College of Engineering and Technology Dindigul Department of Computer Science and Engineering Saveetha School of Engineering SIM ATS Chennai India Department of Electronics and Communication Engineering Saveetha School of Engineering SIMATS University Chennai India Department of Biomedical Engineering Saveetha School of Engineering SIMATS Chennai India

Every year, drunk driving injures and sometimes kills a number of people. It is critical to investigate an IoT-based alcohol detection system for safe mobility. Because it uses sensors and a microprocessor to monitor the driver’s BAC and cuts off the car’s ignition if it suspects that the driver has been drinking while driving, this system can detect and prevent drunk driving. The proposed system will use IoT to remotely monitor and analyze the driver’s Blood Alcohol Level (BAC). A communication module, a microprocessor, and an alcohol sensor comprise the system. The communication component sends real-time data to a BAC server for monitoring and analysis. The proposed strategy reduces the likelihood of accidents, improves driver and passenger safety, and lowers the likelihood of transportation companies having to pay for injuries or damages. IoT-based technologies that detect alcohol can aid in the prevention of drunk driving. By monitoring drivers’ BACs in real time and discouraging drunk driving, this device has the potential to significantly reduce traffic-related injuries and fatalities.

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APPLICATION OF THE DIGITAL ANNEALER UNIT IN OPTIMIZING CHEMICAL REACTION CONDITIONS FOR ENHANCED PRODUCTION YIELDS

arXiv

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arXiv 2024年

作者： Li, Shih-Cheng Wang, Pei-Hwa Su, Jheng-Wei Chiang, Wei-Yin Huang, Shih-Hsien Lin, Yen-Chu Ou, Chia-Ho Chen, Chih-Yu Insilico Medicine Taiwan Ltd. Taipei City110208 Taiwan Department of Chemical Engineering Massachusetts Institute of Technology CambridgeMA02139 United States Quantum Information Center Chung Yuan Christian University Taoyuan City320314 Taiwan Master Program in Intelligent Computing and Big Data Chung Yuan Christian University Taoyuan City320314 Taiwan Department of Computer Science and Information Engineering National Pingtung University Pingtung City900392 Taiwan

Finding appropriate reaction conditions that yield high product rates in chemical synthesis is crucial for the chemical and pharmaceutical industries. However, due to the vast chemical space, conducting experiments for each possible reaction condition is impractical. Consequently, models such as QSAR (Quantitative Structure-Activity Relationship) or ML (Machine Learning) have been developed to predict the outcomes of reactions and illustrate how reaction conditions affect product yield. Despite these advancements, inferring all possible combinations remains computationally prohibitive when using a conventional CPU. In this work, we explore using a Digital Annealing Unit (DAU) to tackle these large-scale optimization problems more efficiently by solving Quadratic Unconstrained Binary Optimization (QUBO). Two types of QUBO models are constructed in this work: one using quantum annealing and the other using ML. Both models are built and tested on four high-throughput experimentation (HTE) datasets and selected Reaxys datasets. Our results suggest that the performance of models is comparable to classical ML methods (i.e., Random Forest and Multilayer Perceptron (MLP)), while the inference time of our models requires only seconds with a DAU. Additionally, in campaigns involving active learning and autonomous design of reaction conditions to achieve higher reaction yield, our model demonstrates significant improvements by adding new data, showing promise of adopting our method in the iterative nature of such problem settings. Our method can also accelerate the screening of billions of reaction conditions, achieving speeds millions of times faster than traditional computing units in identifying superior conditions. Therefore, leveraging the DAU with our developed QUBO models has the potential to be a valuable tool for innovative chemical synthesis. Copyright © 2024, The Authors. All rights reserved.

关键词： Machine learning

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BINARY SEARCH AND FIRST ORDER GRADIENT BASED METHOD FOR STOCHASTIC OPTIMIZATION

arXiv

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arXiv 2020年

作者： Pandey, Vijay Completed master’s degree in Computer Science and Engineering Indian Institute of Technology Kharagpur India

In this paper, we present a novel stochastic optimization method, which uses the binary search technique with first order gradient based optimization method, called Binary Search Gradient Optimization (BSG) or BiGrad. In this optimization setup, a non-convex surface is treated as a set of convex surfaces. In BSG, at first, a region is defined, assuming region is convex. If region is not convex, then the algorithm leaves the region very fast and defines a new one, otherwise, it tries to converge at the optimal point of the region. In BSG, core purpose of binary search is to decide, whether region is convex or not in logarithmic time, whereas, first order gradient based method is primarily applied, to define a new region. In this paper, Adam is used as a first order gradient based method, nevertheless, other methods of this class may also be considered. In deep neural network setup, it handles the problem of vanishing and exploding gradient efficiently. We evaluate BSG on the MNIST handwritten digit, IMDB, and CIFAR10 data set, using logistic regression and deep neural networks. We produce more promising results as compared to other first order gradient based optimization methods. Furthermore, proposed algorithm generalizes significantly better on unseen data as compared to other methods. Copyright © 2020, The Authors. All rights reserved.

关键词： Deep neural networks

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Development of Lightweight and Cheaper 5G Mobile Communication System to Analyze the Performance of Espresso Ciphers and Grain Family 2nd

Development of Lightweight and Cheaper 5G Mobile Communicati...

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2nd International Conference on Cyber Warfare, Security and Space Computing, SpacSec 2024

作者： Kamalanathan, C. Balamurugan, J. Sharma, Neelam Reddy, A. Basi Selvan, R. Senthamil Department of Electrical Electronics and Communication Engineering GITAM Deemed to Be University Bengaluru Campus Karnataka Bengaluru India Department of Master of Business Administration St.Joseph’s College of Engineering OMR Tamilnadu Chennai India Department of Physical Education Lovely Professional University Punjab India Department of Computer Science and Engineering School of Computing Mohan Babu University Andhra Pradesh Tirupati India Department of Electronics and Communication Engineering Annamacharaya Institute of Technology and Sciences Andhra Pradesh Tirupati India

ISBN: (纸本)9783031734939

A significant difficulty in a resource-constrained setting is keeping an optimal sense of balance among safety and other presentation parameters such as memorial need, energy requirement and throughput. In its most recent study on lightweight cryptography, the National institute of Standards and technology (NIST) recommended symmetric cyphers for devices with little resources. This work presents statistical security studies of six modern stream ciphers: Espresso, Grain v1, Sprout, Fruit, Plantlet, and Lizard. The analyses were conducted using the following tests: avalanche, randomness, structure, and autocorrelation. After porting the improved code to a microcontroller in low-cost, that is the ATmega 328P, they have also conducted a thorough performance study of these ciphers. A device’s suitability for use in an IoT-based network is a deciding factor in its selection. According to statistical security, performance measurements, and comparative analysis, the chosen ciphers are good choices for situations with limited resources. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： 5G mobile communication systems

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The by-product of oil palm dosage application on Turnera subulata growth supports water supply

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AIP Conference Proceedings 2024年第1期3026卷

作者： Pauliz Budi Hastuti Gilang Tri Anggara Wiwin Dyah Ully Parwati Teddy Suparyanto Digdo Sudigyo Bens Pardamean Faculty of Agriculture STIPER Institute of Agriculture Yogyakarta Indonesia 55281 Faculty of Agricultural Technology STIPER Institute of Agriculture Yogyakarta Indonesia 55281 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

Plant growth with complex organic matter content can be enhanced by using oil palm by-products. These organic materials can maintain the water supply in the plant body. Therefore, in oil palm plantations with significant groundwater consumption, organic matter’s the ability to sustain water availability. Caterpillars that devour palm leaves are among the numerous pests that threaten oil palm plantations. Predators of leaf-eating caterpillars use the holly rose flower (Turnera subulata) in oil palm farms as a habitat. Therefore, the effect of the type and dose treatment of oil palm by-products on the growth of Turnera subulata was observed to support sustainable water management in oil palm plantations. The research was carried out using a factorial design arranged in a Completely Randomized Design (CRD) consisting of two components: the type of palm oil mill by-product (boiler ash, empty bunches, and solid) and the dose of a by-product (% volume) consisting of four dosages (0, 25, 33, and 50% volume). The research data were analyzed using variance at the 5% test level. A DMRT test at the 5% test level was conducted on the treatment that had a significant effect. The growth of Turnera subulata was most positively impacted by a solid application dose of 50% volume. Turnera subulata plants responded the least favorably to the application of empty bunches in any dose treatment.

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Sustainable and Green IoT Solutions for Environmental Monitoring

Sustainable and Green IoT Solutions for Environmental Monito...

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International Conference on science technology Engineering and Management (ICONSTEM)

作者： E. Afreen Banu N. Venkateswaran P.S. Latha Mageshwari Elangovan M Rakesh Kumar Pandey Department of Computer Science Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences (SIMATS) Thandalam Chennai Tamil Nadu India Department of Master of Business Administration Panimalar Engineering College Chennai Tamil Nadu India Department of Physics (S&H) R.M.K. Engineering College Kavaraipettai Tamil Nadu India Department of Aerospace Engineering SNS College of Technology Coimbatore Tamil Nadu India Department of Civil Engineering MATS University Raipur Chhattisgarh India

ISBN: (数字)9798350365092

ISBN: (纸本)9798350365108

In response to growing environmental enterprises, this exploration paper investigates the development and perpetuation of sustainable and green Internet of Effects (IoT) results for environmental monitoring. With the rapidfire expansion of IoT technologies, an occasion arises to work on these advancements for the benefit of environmental conservation and sustainability sweats. This study explores the design and deployment of IoT-grounded detector networks able to cover colorful environmental parameters, such as air quality, water quality, and biodiversity, in a manner that minimizes energy consumption and environmental impact. By employing energy-effective detector bumps, renewable energy sources, and eco-friendlyaccouterments, the proposed results aim to achieve a balance between technological invention and environmental responsibility. Through case studies and performance evaluations, the efficacity and feasibility of these sustainable IoT results are examined, pressing their eventuality to grease data-driven decisions- timber and promote sustainable practices in environmental operation. The findings of this exploration contribute to the ongoing conversation on sustainable development and emphasise the role of IoT in fostering a greener and more flexible future.

关键词： Performance evaluation Technological innovation Renewable energy sources Green products Detectors Water quality Pressing

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Maximum Energy Productivity for Concurrent Wireless Data and Power Shifting-Enabled IoT Network with Energy Coordination

Maximum Energy Productivity for Concurrent Wireless Data and...

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Artificial Intelligence and Knowledge Discovery in Concurrent Engineering (ICECONF), International Conference on

作者： Sneha Joseph Sankar R Angelina Royappa Anandakumar D Gururaj D K.V. Karthikeyan Department of Electronics and Communication Engineering R.M.K. Engineering College Chennai Department of Master of Computer Application S.A Engineering College Chennai Department of Electronics and Communication Engineering Velammal Engineering College Chennai Department of Electronics and Communication Engineering Nandha Engineering College Erode Department of Electronics and Communication Engineering Rajalakshmi Engineering College Chennai Department of Electronics and Communication Engineering Sathyabama Institute of Science and Technology Chennai

The online phase may be successfully extended by simultaneous wireless data, internet of things (IoT) components, and sophisticated technologies. The development support base station is developed to accomplish the exchange of renewable electricity to manage the volatility of power generation by the hybrid access points. In this research, we jointly investigate the cooperative SWIPT-enabled IoT systems. While maximizing the program's energy consumption, we must also adhere to maximize the transmission limits, thermoelectric generator restrictions, and customer quality of service (QoS) requirements. We collaborate to find solutions to the challenges of power-sharing, period shifting, and ecological collaboration. The incessant algorithm is employed to address the load distribution and duration swapping problems, the matching algorithm is employed to fix the cooperation agreement issue, and since this trouble is a nonlinear optimization issue, it is challenging to address directly. Instead, we are using the interchanging differential technique. The outcomes of the simulations demonstrate that the suggested algorithm performs with a considerable advantage in terms of energy conservation compared to the comparative method. Also, it has been shown that using energy collaboration technologies can reduce the amount of power a system uses and make it run better.

关键词： Wireless communication Productivity Renewable energy sources Collaboration Quality of service Knowledge discovery Internet of Things

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