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Electrical, computer, Communications and Mechatronics engineering (ICECCME), International Conference on

作者： Luka Kaučić Ivana Kovačević Ivan Aleksi Tomislav Keser Josip Zidar Snježana Rimac-Drlje Department of Computer Engineering and Automation Faculty of Electrical Engineering Computer Science and Information Technology Osijek Osijek Croatia Department of Communications Faculty of Electrical Engineering Computer Science and Information Technology Osijek Osijek Croatia

Monitoring sugar concentration during fermentation is crucial for producing high-quality alcoholic beverages. Traditional methods for measuring sugar concentration can be costly and time-consuming, especially for small-scale producers. In this study, we developed a low-cost buoyant force measurement device for monitoring sugar concentration in water solutions. The device consists of a buoyant object fully submerged in the solution and connected to a load-cell sensor. As the sugar concentration in the liquid increases, the buoyant force on the object increases, and the load-cell measures this force. Proposed device is calibrated using solutions of known sugar concentrations and its high accuracy and precision is presented. The device is tested in controlled environment to ensure accurate tracking changes in sugar concentration over time. Proposed device can be a valuable tool for small-scale producers looking to optimize their fermentation processes while minimizing costs.

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Optimization of Expert Solutions for Events Forecasting 4

Optimization of Expert Solutions for Events Forecasting

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4th International Conference on control, Artificial Intelligence, Robotics and Optimization, ICCAIRO 2023

作者： Pkhovelishvili, Merab Archvadze, Natela Shetsiruli, Lia Georgian Technical University Faculty of Informatics and Control Systems Tbilisi Georgia Ivane Javakhishvili Tbilisi State University Department of Computer Science Tbilisi Georgia School of Business and Management Grigor Robakidze University Batumi Georgia

ISBN: (纸本)9798350300918

Expertise is a universal method for solving managerial decision problems and is used in cases where there are no (or not found) criteria that allow solving the problem optimally or rationally. At its core, the examination is based on the use of human experience and is carried out with the involvement of experts. Recently, expert evaluations have been intensively used in various fields, especially in the prediction of tectonic natural disasters, because statistical data in this field are very few or difficult to obtain and analyze. Our article discusses the initial and subsequent criteria for determining the competence of experts, what influence the competence of an expert has in calculating his rank, and how these ranks are used for the conclusion of a group of experts, if this or that event will occur or what is the percentage of the event's occurrence. © 2023 IEEE.

关键词： Disasters

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Enhancement of Dielectric Characteristics of Contaminated Transformer Oil Using TiO2Nanoparticles 23

Enhancement of Dielectric Characteristics of Contaminated Tr...

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23rd International Middle East Power systems Conference, MEPCON 2022

作者： Negm, Tarek S. Mansour, Diaa-Eldin A. Hossam-Eldin, Ahmed A. Alexandria University Faculty of Engineering Department of Electrical Engineering Alexandria Egypt School of Electronics Communications and Computer Engineering Egypt-Japan University of Science and Technology Electrical Power Engineering Department Alexandria Egypt Tanta University Faculty of Engineering Electrical Power and Machines Engineering Department Tanta Egypt

ISBN: (纸本)9781665463638

The electrical and physical characteristics of insulation systems of transformers are an essential factor in its continuity, maintainability and safety. The main contaminant inside transformer oil is cellulose particles that lead to deterioration and sometimes complete failure of its dielectric. This study investigates the effect of adding nanoparticles at different concentrations at room temperature to contaminated mineral oil, aiming to enhance the dielectric behaviors of these oils. Three different contamination levels are considered;0.02, 0.04 and 0.06 g/L of base oil. Titanium dioxide TiO2 is used as nanofillers with two different concentrations;0.02 and 0.04 g/L. Impulse voltage breakdown with both positive and negative polarity was measured for the contaminated oil and nanofluids. Using nanofluids positively influenced the contaminated oil by increasing its impulse breakdown voltage. The maximum enhancement percentage reached is 62.1% for positive polarity and 64.5% for negative polarity when adding 0.02g/L of TiO2. © 2022 IEEE.

关键词： Insulating oil

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Medical Diagnoses: Heart Disease Prediction 2

Medical Diagnoses: Heart Disease Prediction

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2nd International Conference on Business Analytics for Technology and Security, ICBATS 2023

作者： Mahfuri, Mahmoud Ghazal, Taher M. Mudassar, Muhammad Siddiqui, Shahan Yamin Farooq, Sajid Kanwal, Nayab Ahmad, Munir International University for Science and Technolgy Computer and Information Technolgy Department Faculty of Engineering Syria Center for Cyber Security Faculty of Information Science and Technology Selangor Bangi43600 Malaysia Skyline University College School of Information Technology University City Sharjah 1797 United Arab Emirates The University of Lahore Lahore Pakistan Minhaj University Department of Computer Science Lahore Pakistan School of Computer Science National College of Business Administration & Economics Lahore Pakistan NCBA&E School of Computer Science Lahore Pakistan Applied Science Private University Applied Science Research Center Amman11937 Jordan

ISBN: (纸本)9798350335644

The successful and continuously increasing applications of machine learning (ML) and data mining (DM) in the wide range of fields such as e-businesses, public or private sectors, marketing and retails has led the ML and DM applications in other industries and health sectors. In the health sector the data is information wise too rich but not knowledge rich. It can be due to the lack of effective tools and research study in this era. In this research work, an efficient model is proposed based on the machine learning and data mining tools to predict a particular medical disease that is the heart disease. The solution for the problem which is addressed that data is not knowledge-rich, is presented in this paper. Waikato Environment and Python is used for to analyze the data, so that an automation system can be formed. Several experiments are to be implemented to compare the performance through Supervised Learning and Unsupervised Learning. Bayesian learning (Naïve Bayes), Tree's algorithm (Decision Tree), and Neural Networks (MLPNN) are applied on the same dataset. Comparatively, Decision Tree gives best accuracy when compared with Naïve Bayes, ANN performs more effective when compared with others two Bayesian algorithms (Naïve Bayes) and Tree's algorithm (Decision tree). © 2023 IEEE.

关键词： Decision trees

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Design and Implementation of Single to Multi-cloud Securities in Network 8th

Design and Implementation of Single to Multi-cloud Securitie...

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8th International Conference on Emerging Research in Computing, Information, Communication and Applications, ERCICA 2023

作者： Ramesh Naidu, P. Kawale, Sheetalrani R. Dankan Gowda, V. Hussain, Naziya Samal, Ansuman Department of Computer Science and Engineering Nitte Meenakshi Institute of Technology and Management Karnataka Bangalore India Department of Computer Science Karnataka State Akkamahadevi Women’s University Karnataka Vijayapura India Department of Electronics and Communication Engineering BMS Institute of Technology and Mangement Karnataka Bangalore India School of Computers IPS Academy Madhya Pradesh Indore India Faculty of Hospitality and Tourism Management Siksha O Anusandhan Deemed to be University Odisha Bhubaneswar India

ISBN: (纸本)9789819976218

The adoption of cloud computing has skyrocketed in a lot of companies. One of the biggest selling points of cloud computing is how cheap it is and how easily you can access your data. Since users routinely save sensitive data with cloud storage providers despite the fact that they may not be reliable, cloud computing security is a vital concern in the cloud computing ecosystem. Due to concerns around current service failure and damaging entrants in the single-cloud, consumers are predicted to shift away from engaging with "single cloud" suppliers. Multiple clouds, or "inter-clouds" as they are sometimes called, are becoming increasingly popular. In this study, we investigate the problem of securing multiple cloud environments and discuss some potential approaches to the problem. Researchers have paid less effort to studying how to use several cloud providers while keeping data secure than they have to studying individual clouds. Multi-clouds can reduce vulnerability to some types of attacks, hence this initiative aims to increase their adoption. However, there are still major worries about the security and trustworthiness of cloud-based data storage. We present DEPSKY, a system that encrypts, encodes, and replicates data over numerous clouds to increase availability, integrity, and confidentially stored in the cloud. Our infrastructure, together with Planet Lab, has been deployed to four commercial clouds, where users from all around the world can use the service. Our protocols improved perceived availability and, for most cases, access latency when compared to those of individual cloud providers. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Cloud computing Multi-cloud Network and DEPSKY Security

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Self-Configured Workflow Platform for MapReduce Job Execution in Cloud Environment

Self-Configured Workflow Platform for MapReduce Job Executio...

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2022 Applied Informatics International Conference, AiIC 2022

作者： Saadoon, Muntadher Admodisastro, Novia University of Malaya Faculty of Computer Science and Information Technology Department of Software Engineering Kuala Lumpur50603 Malaysia Universiti Putra Malaysia Faculty of Computer Science and Information Technology Selangor Serdang43400 Malaysia

ISBN: (数字)9781728184289

ISBN: (纸本)9781728184289

Hadoop MapReduce becomes the essential framework to store, process and analyse big data in large-scale computing environments. The framework provides numerous opportunities to handle data-intensive applications like web crawling and indexing, data mining, anomaly prediction and machine learning. However, manual configurations of the framework parameters expose to human errors and lead to performance overhead and resource consumption penalties. Existing deployment automation solutions intended to mitigate the limitations by only facilitating the application execution workflow without considering crucial conditions that violates the overall performance after setting up the infrastructure parameters. This paper proposes a self-configured workflow platform with a user-friendly collaborating environment that provides automated setups of the framework paraments to obtain ideal performance compared to the native deployment of Hadoop MapReduce. The self-configured workflow platform has been evaluated in experiments on a real Hadoop cloud-based cluster and the results shows that the execution times are comparable to the native application. © 2022 IEEE.

关键词： MapReduce

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Leveraging Large Language Models for Automatic Smart Contract Generation

Leveraging Large Language Models for Automatic Smart Contrac...

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IEEE Annual International computer Software and Applications Conference (COMPSAC)

作者： Emanuele Antonio Napoli Fadi Barbàra Valentina Gatteschi Claudio Schifanella Department of Control and Computer Engineering Politecnico di Torino Turin ITALY Department of Computer Science University of Turin Turin ITALY

ISBN: (数字)9798350376968

ISBN: (纸本)9798350376975

In the rapidly evolving landscape of blockchain technology, smart contracts stand as pivotal instrument for automating and enforcing digital agreements. However, their creation often necessitates specialized programming skills, hindering broader adoption and accessibility. This paper proposes a pipeline that leverages the capabilities of Large Language Models (LLMs) to automate the generation of smart contracts. By harnessing the natural language understanding and generation capabilities of LLMs, our approach aims to make accessible smart contract development to people that are not familiar with this task. The proposed pipeline employs the CO-STAR methodology to optimize prompt creation for high-quality outputs. Moreover, in order to assess the correctness and reliability of the generated smart contracts, we leverage on Slither, one of the most cutting-edge vulnerability detection tools. Furthermore, we propose a benchmarking suite based on metrics such as compilability, vulnerabilities, and presence of comments, among the others, in order to evaluate the effectiveness of the pipeline in terms of consistency of generated smart contracts, LLM's temperature effect, and prompt selection. The results show that our pipeline is able to produce 98.1% of compilable smart contracts, the temperature value has negligible effect on the generated smart contracts, and the CO-STAR methodology produces valuable and consistent outputs with low-impact vulnerabilities.

关键词： Measurement Large language models Instruments Smart contracts Pipelines Programming Software

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Segmentation of butterflies from complex agro-ecological images using quantum mechanics and spatial refinement

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Digital Signal Processing: A Review Journal 2023年 135卷

作者： Filali, Idir Achour, Brahim Ramdani, Mohamed LARI laboratory Department of Computer Science Faculty of Electronic Engineering and Computer Science Mouloud Mammeri University Tizi-Ouzou15000 Algeria

The presence of butterflies is an important indicator of environmental health and stability. Its pollination ability increases agricultural yields. However, some butterflies may also cause crop degradation. Butterfly segmentation in complex agro-ecological environments is therefore a preliminary step whose accuracy affects species recognition. We propose in this paper a segmentation method composed of a sequence of three steps. First, we combine background connectivity with local distinctiveness measures to locate roughly butterfly areas. Second, we deploy an adaptation of the Schrödinger equation on a graph propagation process that checks regional similarities to those areas. Finally, we perform a spatial refinement that optimizes the butterfly detection. Both objective and subjective comparative experiments suggest that our method performs well against image artifacts. Obtained results outperform those of some state-of-the-art methods that reach high performance. © 2023 Elsevier Inc.

关键词： Quantum theory

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The Impact of the Digital Transformation of Education on Literacy

The Impact of the Digital Transformation of Education on Lit...

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International IEEE Conference and Workshop: Óbuda on Electrical and Power engineering (CANDO-EPE)

作者： Imre Farkas Attila Kovari Mónika Rajcsanyi-Molnar Department of Computer Systems and Control Technology Institute of Computer Engineering University of Dunaujvaros Dunaujvaros Hungary Institute of Digital Technology Faculty of Computer Science Eszterházy Károly Catholic University Eger Hungary Institute of Electronics and Communication Systems Kandó Kálmán Faculty of Electrical Engineering Obuda University Budapest Hungary GAMF Faculty of Engineering and Computer Science John Von Neumann University Kecskemét Hungary Department of Economics and Management Institute of Social Sciences University of Dunaujvaros Dunaujvaros Hungary

ISBN: (数字)9798331531119

ISBN: (纸本)9798331531126

During the COVID19 epidemic, people of all ages from all walks of life around the world have become inevitably familiar with and almost dependent on the digital tools of the age and the opportunities they offer. A change had to take place very quickly that was unprecedented. This process has also affected education. During the time of the reading lock-in, there was a proliferation of digital curricular content. The second time around, online education came to the fore, thanks to less or well-functioning online platforms, and has since become part of everyday teaching. What is the effectiveness and usefulness of sharing knowledge in this way? Is literacy still needed at all? Can online and hybrid (a controlled mix of face-to-face and online) education replace the well-established contact and face-to-face education? The study show that the respondents believe that online education has had an impact on literacy and that it is perceived to have a positive impact. The results indicate that online education has a positive impact on the literacy levels of students, as it facilitates knowledge acquisition and enhances digital literacy skills.

关键词： Power engineering Epidemics Navigation Knowledge acquisition Digital transformation Education Information age Digital intelligence Cultural differences Problem-solving

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Effective Anatomy Learning Using Markerless Augmented Reality Interface for Medical Education

Effective Anatomy Learning Using Markerless Augmented Realit...

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Advances in Data engineering and Intelligent Computing systems (ADICS), International Conference on

作者： S. Athinarayanan M. Masthan Saravanan Chandrasekaran V. Ashwin Ram Mahesh T R Vivek V Department of CSE School of Computing Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and Technology (Deemed to be University) Avadi Chennai India Arffy Technologies Private Limited Bengaluru Karnataka India Department of Computer Science and Engineering SRM Institute of Science and Technology Ramapuram Chennai Tamil Nadu Department of Computer Science and Engineering (AIML) SRM Institute of Science and Technology Ramapuram Chennai India Department of Computer Science & Engineering Faculty of Engineering and Technology JAIN (Deemed-to-be University) Bengaluru Department of Computer Science & Engineering Faculty of Engineering and Technology JAIN (Deemed-to-be University) Bengaluru India

ISBN: (数字)9798350364828

ISBN: (纸本)9798350364835

Anatomy is a branch of biology dealing with the identification and explanation of living things body systems. Human anatomy is a significant chapter in every Biology class for secondary and post-secondary students. Traditional approaches and tools for studying human body anatomy include manuals with illustrations and images, as well as artificial anatomy mannequins. It isn't sufficient but and its miles tough to assist medical students to recognize it with actual and correct information and images approximately the anatomy of our human body. This is due to students' inability to visualize the actual configuration of human anatomy body parts and their lack of familiarity with 2D representations in textbooks. Furthermore, some students have difficulty interpreting 2D representations in textbooks, making it impossible for them to comprehend and gain information as quickly as possible in studying the layout of human anatomy body parts. Using Google AR Core and Unity3D, we proposed a system that builds a human anatomy learning android application that assists the medical students to visualize and analyze the Human Anatomy subject in an interactive way by using the Augmented Reality (AR) technique. The markerless AR approach is being used to create this scheme which uses the novel method to use the mobile computing platform as an alternative learning tool for studying the intricate structures of human body anatomy more practically and engagingly.

关键词： Human anatomy Image recognition Operating systems Layout Manuals Biology Internet

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