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Medical Image Analysis Using Deep Learning Technnique 5

Medical Image Analysis Using Deep Learning Technnique

引用

5th international conference on Information Management and Machine Intelligence, ICIMMI 2023

作者： Saxena, Surabhi Parveen, Nikhat Agarwal, Devendra Department of Artificial Intelligence and Data Science Poornima Institute of Engineering & Technology Rajasthan Jaipur India Department of Computer Science and Engineering Konneru Lakshmaiah Education Foundation Vijayawada Guntur India Goel Institute of Technology and Management Uttar Pradesh Lucknow India

ISBN: (纸本)9798400709418

Clinical picture classification, pattern recognition, and quantification have seen significant advancements with the help of artificial intelligence, particularly through deep learning techniques. Deep learning has rapidly emerged as the most rapidly evolving field within AI, and its applications have been successfully demonstrated across various domains, including medicine. this review briefly examines recent applied research in several medical fields, such as neurology, brain imaging, retinal analysis, pneumonias, computerized pathology, breast imaging, cardiovascular studies, musculoskeletal imaging, and gastrointestinal imaging. Deep learning networks prove to be highly effective when dealing with large scale medical datasets, enabling information discovery, knowledge dissemination, and knowledge-based prediction. this research aims to present both foundational knowledge and state-of-the-art deep learning techniques to facilitate the interpretation and analysis of medical images. the primary objectives of this work are to explore advancements in medical image processing research and implement the identified and addressed key criteria in practical applications. © 2023 ACM.

关键词： Deep learning

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Design and Development of an Interactive Chess Board for Quarto 9

Design and Development of an Interactive Chess Board for Qua...

引用

9th international conference on Applied System Innovation, ICASI 2023

作者： Chou, Yu-Wei Liao, Chen-Wei Shih, Jin-Ruei Kuo, Jui-Huan Wong, Kai-Yi Chung Yuan Christian University Department of Intelligent Computing and Big Data No. 200 Zhongbei Rd. Zhongli Dist Taoyuan City Taiwan Chung Yuan Christian University Department of Electrical Engineering No. 200 Zhongbei Rd. Zhongli Dist Taoyuan City Taiwan Chung Yuan Christian University Department of Information Management No. 200 Zhongbei Rd. Zhongli Dist Taoyuan City Taiwan

ISBN: (纸本)9798350398380

this research designed and developed an interactive chess board capable of playing Quarto game against humans. the designed interactive chess board utilizes CoreXY mechanism to manipulate the electromagnet to achieve two-dimensional movement under the chess board. Furthermore, the designed interactive chess board employs a depth camera with the YOLOv5 algorithm to identify the features and position of each chess piece. Finally, the game strategy mechanics of the Quarto game are combined to the system for the chess board. © 2023 IEEE.

关键词： CoreXY Frame Interactive Chess Board Quarto YOLOv5

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Pixel-level land cover change detection in the Loess Plateau based on different data 5

Pixel-level land cover change detection in the Loess Plateau...

引用

5th international conference on Geoscience and Remote Sensing Mapping, ICGRSM 2023

作者： Zhang, Xinyang Wu, Qiaoli Jiang, Jie Pei, Yujie School of Geomatics and Urban Spatial Information Beijing University of Civil Engineering and Architecture Beijing102616 China

ISBN: (纸本)9781510672789

the implementation of ecological engineering such as afforestation and reforestation in the Loess Plateau over the past two decades has brought significant changes to its land use and land cover (LULC). However, the differing spatial resolutions of land use data from various sources hinder an objective analysis of the effects of national ecological projects on vegetation growth in the Loess Plateau. Based on the commonly used MODIS LULC data and the latest CLCD LULC dataset from Wuhan University, the land use transition matrix calculation and change pixel detection were conducted for the period between 2001 and 2019 in the Loess Plateau. the analysis of the CLCD LULC data revealed that grass, cropland, and forest dominate the land use types in the Loess Plateau. Over the past two decades, approximately 15% (around 97000 km2) of the Loess Plateau experienced land use changes. During this period, the forest and grass areas increased by 14025 km2 and 7262 km2, respectively. these increases were mainly due to the conversion from cropland and shrub, which saw decreases in area by -18843 km2 and -1671 km2, respectively. the patterns of land use changes were consistent across the seven provinces and regions within the Loess Plateau, with notable afforestation effects observed in Shanxi and Shaanxi provinces, where forest increased by 6303 km2 and 4143 km2, respectively. Inner Mongolia primarily witnessed grassland restoration, resulting in a substantial growth of 5879 km2 in grass. However, the results obtained from MODIS LULC data were contradictory. According to these results, the cropland area in the Loess Plateau increased by 20688 km2, while the grass area decreased by 26635 km2 between 2001 and 2019, constituting 32.4% and 41.7% of the total changed area, respectively. the study outcomes provide valuable insights for scientifically analyzing the ecological benefits of afforestation and reforestation projects in the Loess Plateau, serving as a reference for improving

关键词： Land use

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EASATrack: Infrared Object Tracking Based on Edge Activation and Scale Adaptive Cross-Correlation 5

EASATrack: Infrared Object Tracking Based on Edge Activation...

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5th international conference on Robotics, Intelligent Control and Artificial Intelligence, RICAI 2023

作者： Wang, Boran Yuan, Jing Zhang, Xuebo Wang, Yang Cui, Wenpeng Zheng, Zhe Nankai University Engineering Research Center of Trusted Behavior Intelligence Ministry of Education Tianjin China College of Artificial Intelligence Nankai University Tianjin China Tianjin Municipal Data Management Center Tianjin China Beijing Smartchip Microelectronics Technology Company Limited Beijing China

ISBN: (纸本)9798350357950

the blurring of object edges in infrared images and scale variations among consecutive frames largely affect the precision of existing tracking model. To this end, a model called EASATrack based on edge activation and scale adaptive cross-correlation is designed. First, in this model, an edge activation module is employed to amplify the edge information of the object within infrared images. then, a scale adaptive cross-correlation module is designed to perceive object information across varying scales, thereby accommodating changes in object scale during similarity computations. Finally, to validate the proposed model, plenty experiments are conducted on publicly available datasets PTB-TIP and LSOTB-TIR. the results demonstrate that the proposed model achieves leading performance in terms of precision and success rate on both datasets. © 2023 IEEE.

关键词： Edge Activation Infrared Image Object Tracking Scale Adaptive Cross-Correlation

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Circularly Arranged Six Element Cavity Backed SIW Arc Shape Slot Antenna 5

Circularly Arranged Six Element Cavity Backed SIW Arc Shape ...

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5th international conference on Inventive Research in Computing Applications, ICIRCA 2023

作者： Srivastava, Ashutosh Yadav Ch T, Krishna Teja Venkateswaran, K. Cmr Institute of Technology Dept. of Electronics and Communication Engineering Bengaluru India

ISBN: (纸本)9798350321425

In this research work, cavity backed antenna (CBA) with arc shape slot and circularly arranged six element cavity backed arc shape slot antenna are proposed by incorporating Substrate Integrated Waveguide (SIW) technology. Initially, a single element CBA having arc shaped slot in opposite layer to feedline, is considered. the cavity boundaries are constructed with the technique used under SIW technology. the antenna offered high gain and low cross polarization (X-Pol) behavior in operating frequency bands. the designed cavity backed SIW arc shape antenna offers twin operational band in the operating frequency range of 10.12 GHz to 10.34 GHz (1st band) and 13.58 GHz to 13.96 GHz (2nd band). the found mid operating frequencies are 10.21 GHz, and 13.79 GHz, while at mid operating frequencies achieved antenna gain is 12.01 dBi and 12.50 dBi, respectively in the direction of intended communication. Furthermore, six elements circularly arranged assembly is created such that arc slots are oriented along the transversal direction along with longitudinal orientation to feedline (tapered microstrip line). the design of circularly arranged six element CBA achieves a greater bandwidth, enhanced gain and overall reduced amount of cross polarization value. the designed array of the cavity backed SIW are shape slot antenna also offers twin band outcome in the operating radio frequency (RF) band of 10.26 GHz to 10.61 GHz (1st band) and 13.71 GHz to 14.16 GHz (2nd band), and the achieved mid operating frequencies are 10.41 GHz and 13.96 GHz, respectively. At these frequencies antenna gain is 20.10 dBi and 20.50 dBi, in the direction of communication. the proposed model has achieved an overall antenna efficiency of 93%. © 2023 IEEE.

关键词： Substrate integrated waveguides

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big data Security: Detect and Prevent the data from Attacks with Digital Forensic Tools

Big Data Security: Detect and Prevent the Data from Attacks ...

引用

international conference on Smart Systems and Inventive technology (ICSSIT)

作者： Sayyad Jilani Namburi Nanda Kishore Nelakuditi Nikhil Chand RudraRaju Dinesh Varma G. Raja P. Venkateswara Rao Department of Computer Science & Engineering (Honors) Koneru Lakshmaiah Educational Foundation Vaddeswaram AndhraPradesh

the main objective of this research is to defend big data against various cyberattacks. Today, it is commonplace to use big data security to safeguard data and analytical processes against malicious activity. Cybercriminals are increasingly using fraudulent calls and texts and other techniques to steal users' private information. Nowadays, these attacks are increasingly frequently online. this study has found various security technologies and strategies that are being utilized to make big data more secure from our prior research references. this study has also learnt about digital forensics tools that may be used to identify who, where, and how an attack was conducted. the fields of data science and cybersecurity are combined in this study. Detecting attacks on big data and ensuring and mitigating data security using cybersecurity and digital forensics techniques are the key goals of this study.

关键词： data security Digital forensics big data data science Computer crime

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7th international conference on Sustainable Energy engineering, ICSEE 2023

7th International Conference on Sustainable Energy Engineeri...

引用

7th international conference on Sustainable Energy engineering, ICSEE 2023

ISBN: (纸本)9783031339059

the proceedings contain 25 papers. the special focus in this conference is on international conference on Sustainable Energy engineering. the topics include: Impact of Urban Morphology on Urban Heat Island Intensity in a Mediterranean City: Global Sensitivity and Uncertainty Analysis;self-Adaptive Ageing Models for Optimal Management and Planning of Assets in Microgrids;study on Fast Charging Using Phase Change Materials for Electric Vehicle Applications;impact of Smart Hydronic System with Heat Pump on Electricity Load of a Typical Queensland Household;comparison of Decomposition Techniques in Forecasting the Quarterly Numbers of Pole-Mounted Transformer Failures;research on Energy-Saving Optimization of Variable Flow Air Conditioning Chilled Water System;Parametric Analysis and Comparative Study of the Transcritical CO2 Cycle and the Organic Rankine Cycle for Low-Temperature Geothermal Sources;structural Optimization of Liquid-Cooled Battery Modules with Different Flow Configurations;a Study on Heat Generation of Lithium-Ion Battery Used in Electric Vehicles by Simulation and Experiment;Design and Implementation of an Automated Hybrid Sustainable Energy Generation from Earth-Battery and Solar PV System;prediction of Fuel Consumption of Heavy Commercial Vehicles Based on Random Forest;highway Traffic Carbon Emission Estimation Based on big data of Electronic Toll Collection: A Case Study from Guangzhou, China;Carbon Capture and Storage (CCS) for India: Bottlenecks and their Role in Adoption;Quantitative Assessment of Low-Carbon Transition Pathways of Power Generation Company Considering CCS technology;measuring the Financial Impact of Typhoon Due to Climate Change;the Literature Intellectual Structure of System Dynamics on Waste;internet of things-Based Smart Building for Energy Efficiency.

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Requirements Elicitation from Two Preliminary Design-thinking-Computational thinking Surveys 5

Requirements Elicitation from Two Preliminary Design-Thinkin...

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5th international conference on Modern Management based on big data, MMBD 2024

作者： Lee, Chien-Sing Chuap, Kusselin Yuthasax Prak Neo, Marcus Sau-Hoong School of Engineering and Technology Sunway University Malaysia

ISBN: (纸本)9781643685281

big data (BD) innovations have become the key differentiators in any competitive analyses, and has become/is, a lifestyle. Building on the Diffusion of Innovation theory, technology Acceptance Models 1, 2, 3, and the international Requirements engineering Boards’ (IREB) Requirements engineering framework, this study aims to identify perceptions towards BD innovations, to design agile feature-based and rule-based intelligent systems, adaptable to progressive changes over time in the future. To reduce variable bias, random sampling of two overlapping demographics is carried out, over two time periods. the first case study, involves perceptions towards BD Innovations, blockchain, Augmented Reality/Virtual Reality/Mixed Reality. the second case study relates to perceptions towards intelligent assistants, e.g. Alexa. For the first case study, by triangulating correlation analyses, linear regression analyses, k-means and hierarchical agglomerative clustering (HAC) results, findings reveal different degrees of acceptance/caution among age groups and gender, and the influence of job prospects on perceptions. Furthermore, HAC’s profile means is more explanatory in terms of distribution and number of clusters, while k-means’ profile means is more positive than HAC’s. For the second case study, findings indicate that personality/dispositions, technology Acceptance Model’s (TAM) adjustment and anchor, as well as interaction styles, may influence perceptions, more than gender or ability. Together, the two case studies provide age-progressive requirements analyses, and an opportunity tree. the fuzzy characterizations can be used in computational thinking design and matrix factorization in (fuzzy) rule-based design for seniors. However, sample size is small and thus, not generalizable. © 2024 the authors and IOS Press.

关键词： Matrix factorization

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Challenges and Strategies for Smart technology Adoption in BIM-Based Construction Projects 5th

Challenges and Strategies for Smart Technology Adoption in B...

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5th international conference on Structural engineering and Construction Management

作者： Afrizal, Azlin Khudzari, Fakhira Rahman, Rahimi A. Alias, Ahmad Rizal Naganathan, Hariharan Univ Malaysia Pahang Al Sultan Abdullah Fac Civil Engn Technol Kuantan 25200 Malaysia Daffodil Int Univ Fac Grad Studies Dhaka 1341 Bangladesh Wentworth Inst Technol Sch Management Boston MA USA

ISBN: (纸本)9783031704338;9783031704314;9783031704307

the adoption of smart technology in Building Information Modelling (BIM)-based construction projects faces significant challenges and opportunities. Concerns about job displacement and privacy invasion contrast with the potential for enhanced environmental and societal benefits. this study aims to identify the relationship between the key challenges and critical strategies associated with adopting smart technology specifically in the domain of BIM-based construction projects. To achieve that aim, the objectives are (1) to identify the key challenges that arise when11sxw integrating smart technology into the BIM framework, (2) identify critical strategies for successful adoption within BIM projects and (3) analyse the interrelationship between these key challenges and strategies. the research methodology involves a systematic literature review tailored to the BIM-based construction context, leading to a list of challenges and strategies. Questionnaire survey data were collected from construction professionals experienced in BIM projects. Valid responses undergo analysis using normalization mean score ranking and correlation analysis. Anticipated findings include tailored key adoption challenges for BIM-based smart technology, critical strategies, and insights into their interplay. the key challenges identified are organizational and process changes, the need for skilled specialists, and interconnectivity issues. the critical strategies include staff training and development, establishing standards, and promoting knowledge management for smart technologies. this paper is part of a series analyzing smart technology adoption in BIM-based construction projects, providing guidance for decision-makers in developing effective smart technology integration strategies.

关键词： Smart technology adoption BIM Construction projects Challenges Strategies

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Weather Prediction Analysis using Classifiers and Regressors in Machine Learning 5

Weather Prediction Analysis using Classifiers and Regressors...

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5th international conference on Smart Systems and Inventive technology, ICSSIT 2023

作者： Chiranjeevi, B.S. Shreegagana, Beluvigi Bhavana, H.S. Karanth, Inchara Rani, K.P. Asha Gowrishankar, S. Dr. Ambedkar Institute of Technology Department of Computer Science and Engineering Karnataka Bengaluru India

ISBN: (纸本)9781665474672

Weather predictions are essential because they protect both property and human lives. Forecasts based on temperature and precipitation are critical for agriculture for merchants in the commodities markets. Humans are also closely related to weather forecast like from daily traveling to daily commuting. Utility firms use temperature projections to predict demand in the upcoming days. Machine learning is a technique that can be used to forecast many different weather patterns, including storms, hurricanes, temperature changes, cyclones, and floods. this study has compared the performance of different deep learning methods for predicting the weather and temperature, including decision tree classifier and SVR, which are rarely used for this purpose. the key variables that affect weather forecasting include air temperature, air pressure, humidity, cloud cover type, solar radiation, precipitation amount and type, and wind speed and direction. Our work focuses on implementing five different machine learning models on a classification dataset and four machine learning models on a regression dataset. Based on our experiments, the regression dataset contributes more towards accurate weather prediction using Decision Tree Regressor, which yields a regression score of 95.70%. © 2023 IEEE.

关键词： Storms

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