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Spatio-Temporal Variation of Particulate Matter (PM10) During High Particulate Event (HPE) in Malaysia 1

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3rd international conference on Green Environmental Engineering and technology (IConGEET) / 7th international conference on Green Design and Manufacture (IConGDM)

作者： Ridzuan, Nursyaida Amila Mohammad Noor, Norazian Mohamed Rahim, Nur Alis Addiena A. Jafri, Izzati Amani Mohd Gyeorgy, Deak Univ Malaysia Perlis Fac Civil Engn Technol Arau 02600 Perlis Malaysia Univ Malaysia Perlis Ctr Excellence Geopolymer & Green Technol Sustainable Environm Res Grp SERG Arau 02600 Perlis Malaysia Natl Inst Res & Dev Environm Protect Bucharest IN 294 Splaiul Independentei St6th Dist Bucharest 060031 Romania

ISBN: (数字)9789811679209

ISBN: (纸本)9789811679209;9789811679193

Particulate matter (PM10) is the key indicator of air quality index in Malaysia and Southeast Asia's main haze-related pollutant. PM10 emanation is believed to cause the strongest harm to public health and the environment. therefore, it is very important to study the temporal and spatial characteristics of PM10 and the weather parameters, hence the relationship between them can be identified. A database with hourly PM10 concentration and weather parameters were obtained from Department of Environment (DOE) Malaysia from the period of 2012-2016 at two study areas that are located in Klang Valley, namely, Petaling Jaya and Shah Alam. the temporal analysis for PM10 concentration was observed by using descriptive statistics, boxplot and time series plot whereas the spatial analysis was conducted using windrose diagram. the finding shows that the highest average concentration of PM10 at Petaling Jaya and Shah Alam in 2015 exceeded the Malaysia Ambient Air Quality Standard, which were 60.13 mu g/m(3) and 66.22 mu g/m(3) respectively. It was due to high particulate event (HPE) that had affected Malaysia during the period of Southwest Monsoon, where the massive land and forest fires came from Sumatra and Kalimantan, Indonesia. According to the wind rose rose diagram, the wind mostly blew from northeast in January until February as Malaysia experienced northeast monsoon where rainfall happened. Shah Alam received stronger wind compared to the Petaling Jaya because the topography of city.

关键词： Air quality Air quality modeling Haze Particulate matter

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Research on the Process-based Generation Method of Scenarios database for Maritime Autonomous Surface Ship Test

Research on the Process-based Generation Method of Scenarios...

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ICETIS 2022;7th international conference on Electronic technology and Information Science

作者： Xinyu Wang Yihang Wang ilin Ma Hui Bian Xuan Zhao Yaoyao Lan

In recent years, Maritime Autonomous Surface Ship (MASS) has been developed rapidly and has demonstrated many new capabilities, which poses a challenge to the testing methods of autonomous ships. Currently, traditional test methods is no longer sufficient to support comprehensive testing and verification. For virtual testing, there is still a lack of a reliable virtual test scenario generation process. therefore, this paper proposes a method for generating virtual test scenarios for autonomous ships. It is based on the scenario generation frame of the intelligent car and comprehensively considers the feature of the operating environment of the MASS. this process develops an element database by deconstructing the real scenes. For generating, it reconstructs and assigns the elements according to the test task (functional scenario) and the logical relationship between the elements (logical scenario) to reconstruct the new scenario. the new scenarios obtained in this way are optimized and supplemented to be the test scenarios database. In addition, a prototype following this frame was designed and loaded with the "automatic pathfinding task of the Wuhan section of the Yangtze River under good navigation conditions" for testing. the experiment generated 48 different scenarios, proving that this generator can output a comprehensive test scenario database to meet test requirements.

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Plant Disease Classification Using VGG-19 Based Faster-RCNN 7th

Plant Disease Classification Using VGG-19 Based Faster-RCNN

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Proceedings of the 7th international conference on Advances in Computing and Data Sciences, ICACDS 2023

作者： Nawaz, Marriam Nazir, Tahira Khan, Muhammad Attique Rajinikanth, Venkatesan Kadry, Seifedine Department of Software Engineering University of Engineering and Technology Taxila Taxila47050 Pakistan Faculty of Computing Department of Computer Science Riphah International University Gulberg Green Campus Islamabad Pakistan Department of Computer Science HITEC University Taxila Pakistan Department of Computer Science and Engineering Division of Research and Innovation Saveetha School of Engineering SIMATS Chennai602105 India Department of Applied Data Science Noroff University College Kristiansand4612 Norway Ajman University Ajman346 United Arab Emirates Department of Electrical and Computer Engineering Lebanese American University Byblos Lebanon

ISBN: (纸本)9783031379390

Early plant disease diagnosis can help farmers avoid spending money on costly crop pesticides and aid them to boost food production. Scientists have put a lot of effort to classify plant diseases, but it is difficult to quickly locate and identify different crop abnormalities due to the high degree of resemblance between the normal and damaged parts of plant leaves. Additionally, the procedure of detecting plant diseases has been made more challenging due to the extensive color, size, shape, and intensity variations in the background and foreground of the plant images. To address the existing difficulties, we have introduced an effective deep learning (DL) based system called Faster-RCNN o recognize and classify various types of plant diseases. the suggested method consists of 3 basic steps. In order to identify the area of interest in investigated samples, we first create annotations for them which are later used for Faster-RCNN training. the Faster-RCNN model employs the VGG-19 network to extract the relevant keypoints from the given images which are later passed to the regressor and classification units to identify and categorize the various crop diseases using the estimated features. We evaluated our method on a widely used standard plant sample repository called the PlantVillage database, and the findings show that our approach is reliable for classifying plant diseases under a variety of image-capturing scenarios. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Crops

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Research on Security Mechanism and Forensics of SQLite database 7th

Research on Security Mechanism and Forensics of SQLite Datab...

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7th international conference on Artificial Intelligence and Security, ICAIS 2021

作者： Zhang, Chengdu Yin, Jie Jiangsu Police Institute Nanjing201101 China

ISBN: (纸本)9783030786175

With the rapid development of information technology and wireless communication technology, SQLite database has been widely used in various occasions in peacetime. SQLite database, as a relatively common database in the Android operating system, usually contains a series of key information such as call records and short messages. Research on SQLite database has a certain positive effect on public security electronic evidence collection. this article hopes to study the security mechanism and cracking method of SQLite database, the encryption and decryption mechanism and operation method of open source software such as SQL Cipher, and the actual forensic operation of WeChat as an example to conduct the research of SQLite database forensic analysis. © 2021, Springer Nature Switzerland AG.

关键词： database systems

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ORGANIZING SMART CITY DATA BASED ON 3D POINT CLOUD IN UNSTRUCTURED database - AN OVERVIEW 7

ORGANIZING SMART CITY DATA BASED ON 3D POINT CLOUD IN UNSTRU...

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7th international conference on Smart City Applications, SCA 2022

作者： Mohd Ariff, S.A. Azri, S. Ujang, U. Choon, T.L. 3D Gis Research Group Geoinformation Faculty of Built Environment and Surveying Universiti Teknologi Malaysia Johor Johor Bahru81310 Malaysia Faculty of Built Environment and Surveying Universiti Teknologi Malaysia Johor Johor Bahru81310 Malaysia

the concept of the 3D smart city is an integration of smart cities and information technology. One of the data sources of a smart city is point cloud data that are produced from various data acquisition tools such as LiDAR, Terrestrial Laser Scanning, and Unmanned Aerial Vehicle. Due to the large size of point cloud data input, traditional databases could not handle the data efficiently. Alternatively, unstructured databases have become an option. Furthermore, data for smart city applications are considered being complex and large. Storing data in the unstructured database can easily be retrieved from various front ends such as web and mobile devices. However, unstructured databases do not have fixed schema and data types that often limit the uses of 3D point cloud data in relational databases. there are four categories of the data model in the unstructured database: document store, key-value, column store, and graph store. Each of the categories has different characteristics and approaches to handling data. thus, this paper aims to summarise an overview of each category and determine the most suitable data organisation and environment for a 3D point cloud of a smart city. the overview will aid the developer or user select and comparing available data models in the unstructured database to handle 3D point clouds. © 2022 international Society for Photogrammetry and Remote Sensing. All rights reserved.

关键词： Smart city

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Intelligent Knowledge Modeling and Distributed database Constructing for Intelligent Radar Countermeasure 7

Intelligent Knowledge Modeling and Distributed Database Cons...

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7th international conference on Computer and Communications, ICCC 2021

作者： Su, Zhaoxiang Qin, Zhen Deng, Bo Li, Yan Beijing Institute of Technology School of Information and Electronics Beijing China Northern Institute of Electronic Equipment Beijing China Beijing Institute of Technology Chongqing Innovation Center Chongqing China

ISBN: (纸本)9781665409506

Intelligent radar countermeasure are the current development trend in the field of radar countermeasure. Knowledge modeling can support the whole process of radar countermeasure. It can not only provide prior knowledge for the countermeasure system but also dynamically update the generated new knowledge. To deal with the rapidly growing mass of knowledge in the knowledge base system, the use of a distributed architecture can ensure the stability of the knowledge base. At present, there are two difficulties in the construction of a knowledge base system in radar countermeasure. First, it is difficult to construct a comprehensive representation for multiple data sources and complex counter-targets. Second, the massive data and knowledge gives huge pressure for storage. To deal with the above problems, we systematically design a hierarchical dynamic knowledge base as well as several sub-databases based on the specific application of intelligent radar countermeasure. Furthermore, the distributed database based on the architecture of Mycat is constructed, which relieves the pressure on storage, reading and writing, as well as the crash risk of a single machine. We have demonstrated the performance of the distributed knowledge base. © 2021 IEEE.

关键词： Knowledge based systems

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the Intersection of AI and Blockchain in Education: A Bibliometric and thematic Analysis

The Intersection of AI and Blockchain in Education: A Biblio...

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international conference on Computing Communication Control and Automation (ICCUBEA)

作者： Natashaa Kaul Amruta Deshpande Amit Mittal Rajesh Raut Symbiosis Center for Management and Human Resource Development Symbiosis International University Pune India Indira School of Business Studies PGDM Pune India Chitkara Business School Chitkara University Punjab India Indira School of Business Studies PGDM Pune

Two cutting-edge technologies that are revolutionizing the education industry are artificial intelligence (AI) and blockchain. the study on AI and blockchain in education is bibliometrically analyzed in this paper, emphasizing topics, frameworks, and potential future research areas. the analysis uses the Scopus database to pinpoint essential works and sketch out the conceptual framework of this field of study. the findings show an increasing interest in applying AI and blockchain technology in various educational settings, from K-12 to higher education, as well as the various research paradigms and methodologies used in this field. Studies emphasize creating knowledge management tools, learning algorithms, and decision support systems to strengthen the educational process and enhance learning results. the study also emphasizes the growing demand for cutting-edge technologies like deep learning and the Internet of things. this paper provides a comprehensive evaluation of research on AI and blockchain in education by highlighting key ideas and frameworks that have been applied in this area. the results offer relevant information on the current level of research in this field and suggest potential directions for advancement.

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Computer-aided system for extending the performance of diabetes analysis and prediction 7

Computer-aided system for extending the performance of diabe...

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7th international conference on Software Engineering and Computer Systems and 4th international conference on Computational Science and Information Management, ICSECS-ICOCSIM 2021

作者： Murad, Saydul Akbar Azmi, Zafril Rizal M Hakami, Zaid Hafiz Prottasha, Nusrat Jahan Kowsher, Md Universiti Malaysia Pahang Faculty of Computing Malaysia Jazan University Faculty of Computer Science and Information Technology Jazan Saudi Arabia Daffodils International University Department of Computer Science and Engineering Bangladesh Noakhali Science and Technology University Department of Applied Mathematics Bangladesh

ISBN: (纸本)9781665414074

Every year, diabetes causes health difficulties for hundreds of millions of individuals throughout the world. Patients' medical records may be utilized to quantify symptoms, physical characteristics, and clinical laboratory test data, which may then be utilized to undertake biostatistics analysis to uncover patterns or characteristics that are now undetected. In this work, we have used six machine learning algorithms to give the prediction of diabetes patients and the reason for diabetes are illustrated in percentage using pie charts. the machine learning algorithms used to predict the risks of Type 2 diabetes. User can self-assess their diabetes risk once the model has been trained. Based on the experimental results in AdaBoost Classifier's, the accuracy achieved is almost 98 percent. © 2021 IEEE.

关键词： Forecasting

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database Querying Optimization via Genetic Algorithm for Biomedical Research 22

Database Querying Optimization via Genetic Algorithm for Bio...

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Proceedings of the 2022 7th international conference on Systems, Control and Communications

作者： Nguyen thanh Huong Le Minh Hoang School of Electrical and Electronic Engineering Hanoi University of Science and Technology Vietnam and International Research Institute MICA Hanoi University of Science and Technology Vietnam

ISBN: (纸本)9781450397247

thanks to the skyscraping development of hardware and software technologies, the data solutions have become an urgent trend to deal with vast amount of data, especially in biomedical research, human genome and healthcare systems. the healthcare research has always demanded close association with biomedical data to produce personalized medicine and deliver suitable cure and treatments. Nevertheless, coping with huge amount of information from biomedical data requires bulky solutions. In the light of data science, the solution for this issue can change from a theoretical approach to a data-driven approach. database stores a huge amount of information and particular sets of data can be accessed via queries which are written in specific interface language. In order to manage this amount of data, database optimization is implemented to maximize the speed and efficiency with data retrieval or reduce database system response time. Query optimization is one of the major functionalities in database management systems. the purpose of the query optimization is to determine the most efficient and effective way to execute a particular query by considering several query plans. In this article, genetic algorithm (GA) strategy is utilized for biomedical database systems to execute the query plan. Genetic algorithms are extensively using to solve constrained and unconstrained optimization problems. Based on three main types of rules of GA such as selection, crossover and mutation, the querying can be optimized for solving database problem.

关键词： database querying genetic algorithm biomedical research optimization

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Accelerating Sustainability through Leveraging Machine Learning to Analyze CSR Spending in the Indian Automobile Industry

Accelerating Sustainability through Leveraging Machine Learn...

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international conference on Circuit, Power and Computing Technologies (ICCPCT)

作者： Kottala Sri Yogi Dankan Gowda V Anwesha Pati Ved Srinivas Santosh Aghav Ibrahim Abdullah Department of Operations Symbiosis Institute of Business Management Hyderabad Symbiosis International University Pune India Department of Electronics and Communication Engineering BMS Institute of Technology and Management Bangalore Karnataka Symbiosis Institute of Business Management Hyderabad India Department of Human Resources Thiagarajar School of Management Madurai Tamil Nadu India Symbiosis Law School Hyderabad Symbiosis International (Deemed University) Pune India Department of Computer Science Al-Turath University College Baghdad Iraq

ISBN: (数字)9798350372816

ISBN: (纸本)9798350372823

this paper uses machine learning to assess Corporate Social Responsibility spending trends on the Indian automobile sector between 2016 and 2021. Simply put, the aim of the research is to recognize trends and patterns in sustainability expenditures. More specifically, the study examines how businesses allocate money across the three important aspects of the sustainability report: People, Planet, and Profit Purcell, 2020. the research is based on a largely industry-based database obtained from public companies’ records. the use of advanced statistical techniques, such as machine learning and random forest modeling, enables one to examine the impact of financial allocations on sustainability achievements. Increments in CSR spending are related to enhanced company sustainability performance in terms of correlation outcomes. the paper also recognizes areas where cost cuts have the best returns, as well as shortfalls in the existing CSR approach, offering a strategy for possible development’s.

关键词： Profitability Companies Market research Automobiles Synchronization Resource management Sustainable development

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