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International Conference on Data Analytics and management, ICDAM 2023

作者： Panda, Parnani Banerjee, Sushovan Mishra, Sushruta Shashidhar, Chitra de Albuquerque, Victor Hugo C. Reis, Marcello Singh, Pooja Kalinga Institute of Industrial Technology Deemed to Be University Bhubaneswar India Department of Commerce and Management Seshadripuram College Bengaluru560020 India Graduate Program in Telecommunication Engineering Federal Institute of Education Science and Technology of Ceará Fortaleza Brazil Federal University of Ceará Ceará Brazil Fort Lauderdale United States Lead of the Biomedical Data Analytics Research Group Bengaluru India Federal Institute of Ceará Ceará Brazil Meteora Consultoria Fortaleza Brazil Galgotias University Uttar Pradesh Greater Noida India

ISBN: (纸本)9789819965465

The aim of our study is to evaluate the quality of water using machine learning methods. Potability is a subjective word that quantifies water quality. In this research, a variety of metrics were used to measure general potability of the water. The prescribed elements are applied like variable matrix to denote water quality. The article used three different classification methods, with success rates ranging from 84.27 to 93.16%, to predict the water quality class including ensemble approach like Random Forest (RFC), SVM for classification (SVC), as well as XGBoost. The Gradient Boosting approach, out of all the ones used, received the greatest accuracy (93.16%), precision (96.3%), recall (92.76%) and F-score (94.54%). Also, it achieved the least computational delay with a mean latency of 1.34 s. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Water quality

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Combining magnet-assisted soil washing and soil amendment with zero-valent iron to restore safe rice cultivation in real cadmium-contaminated paddy fields

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Chemosphere 2023年 340卷 139816页

作者： Khum-in, Vinita Suk-in, Jirapon In-ai, Papop Piaowan, Kitsanateen Praimeesub, Yarnnapat Rintachai, Kusuma Supanpaiboon, Wisa Phenrat, Tanapon Department of Civil Engineering Faculty of Engineering Rajamangala University of Technology Thanyaburi Pathumthani 12110 Thailand Department of Civil Engineering Faculty of Engineering Naresuan University Phitsanulok65000 Thailand Faculty of Engineering Naresuan University Phitsanulok65000 Thailand Information and Research Center for Mae Tao Watershed Development Tak Province Mae Sot Thailand Naresuan University Faculty of Medical Science Phitsanulok65000 Thailand Research Program of Toxic Substance Management in the Mining Industry Center of Excellence on Hazardous Substance Management Chulalongkorn University Bangkok10330 Thailand

Local villagers in Mae Sot District, Tak Province, Thailand are at risk of diseases related to cadmium (Cd) due to excessive consumption of rice contaminated with Cd due to zinc mining. This study verifies the hypothesis that to achieve safe rice cultivation, magnet-assisted soil washing followed by soil amendment using zero-valent iron (ZVI) is required not only for rapid remediation of the existing Cd contamination but also for the prevention of Cd recontamination caused by contaminated run-off from an upgradient contaminated paddy. Accordingly, this study conducted a pilot-scale demonstration of the combined technique to restore a real Cd-contaminated paddy (41.02 ± 5.47 mg/kg−1) and compared it with remediation using only soil amendment with ZVI or only magnet-assisted soil washing. The Cd concentration in rice grains from the contaminated rice field without treatment was 0.86 ± 0.01 mg/kg−1, and thus higher than the acceptable level of 0.4 mg/kg−1. Even though the use of magnet-assisted soil washing without amendment initially removed all the bioavailable Cd from the soil, it failed to reduce Cd uptake by the rice plants. This failure was caused by heavy off-season rain, which flooded and re-contaminated the experimental fields with Cd-contaminated run-off from an upgradient contaminated field, leading to a Cd concentration in rice grains of 1.21 ± 0.01 mg/kg−1. Similarly, the use of ZVI as a soil amendment without magnet-assisted soil washing could not ensure safe rice cultivation during the off-season flood, as Cd concentration in the rice grains was still 0.60 mg/kg−1. However, magnet-assisted soil washing followed by soil amendment using ZVI successfully removed Cd from soil and sequestered Cd from Cd-contaminated run-off, resulting in protection against Cd re-contamination in soil and the reduction of Cd content in rice grains to 0.33 mg/kg−1, representing a 60% removal efficacy. Also, this combined technique remained positive for rice growth compared to n

关键词： Food safety

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Energy consumption of high-rise double skin façade buildings, a machine learning analysis

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Journal of Building engineering 2024年 89卷

作者： Rezaie, Maedeh Kariminia, Shahab Band, Shahab S. Ameri, Rasoul Farokhi, Maryam Pai, Hao-Ting Gocer, Ozgur Rismanchi, Behzad Shooshtarian, Salman Department of Architecture Advancement in Architecture and Urban Planning Research Center Najafabad Branch Islamic Azad University Najafabad Iran Future Technology Research Center National Yunlin University of Science and Technology Douliu Taiwan Department of Information Management International Graduate School of Artificial Intelligence National Yunlin University of Science and Technology Taiwan Department of Information Management National Yunlin University of Science and Technology Taiwan Bachelor Program of Big Data Applications in Business National Pingtung University Pingtung Taiwan School of Architecture Design and Planning The University of Sydney SydneyNSW Australia Renewable Energy and Energy Efficiency Group Department of Infrastructure Engineering Faculty of Engineering and Information Technology The University of Melbourne Australia School of Property Construction and Project Management RMIT University Melbourne Australia

Most energy exchanges take place through the building skin. The skin characteristics play a decisive role in the extent of these exchanges, but they are somewhat more varied in the double skin façade (DSF). Among these characteristics, cavity segmentation has a noticeable effect on the implementation of the DSF in different directions during the hot and cold seasons. The aim of this study was to investigate the role of DSF segmentation in energy consumption and natural ventilation of high-rise buildings in hot and dry climates. This study used DesignBuilder software to study sixty-four segmentation component scenarios in an eight-story residential building in Isfahan, Iran. Moreover, a proposed hybrid model utilizing the hybridization of the Hunger Game Search and Gradient Boosting (HGS-GB) algorithm was employed to estimate energy consumption in various scenarios involving lighting, heating, cooling, and total scenarios. The available outcomes revealed that the HGS-GB model had a better performance in comparison with other individual models, such as Gradient Boosting (GB), Random Forest (RF), and K-nearest neighbors (KNN). The R2 values for lighting, heating, cooling, and total energy estimation were 0.9993, 0.9958, 0.9991, and 0.9922, respectively. The findings of this study suggest the significance of DSF segmentation in energy consumption and natural ventilation in high-rise buildings in hot and dry climates. © 2024 Elsevier Ltd

关键词： Forestry

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Any Bluetooth device can be hacked. Know how?

Cyber Security and Applications

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Cyber Security and Applications 2024年 2卷

作者： Muraleedhara, Prathibha Christo, Mary Subaja J, Jaya Yuvasini  D College of Technology – Information Security and Program Management University of Houston 77204 TX United States Department of Networking and Communication School of Computing SRM Institute of Science and Technology Kantankulathur Chennai India Department of Electronics and Communication Engineering Hindustan College of Engineering and Technology India Assistant Professor Department of Computer Science and Business Systems Thiagarajar College of Engineering Madurai 625015 India

In today's world, Bluetooth technology is integrated into almost every device we use, from wireless headsets, mice, and keyboards to cars and smart home devices. But with the convenience of this technology comes the risk of privacy and security breaches. Each Bluetooth device has potential vulnerabilities that cybercriminals can exploit and take advantage of. It is important to create awareness about various Bluetooth vulnerabilities, exploits, and ways to prevent them. This article examines the dark side of Bluetooth technology by explaining how hackers can find ways to bypass the advanced security features of laptops, phones, cars, or smart home devices to compromise the devices and steal personal sensitive data. Whether it is a casual user of Bluetooth technology or a business owner with multiple devices, understanding these risks is crucial to protecting yourself and your information. This article begins by explaining the basics of Bluetooth technology and how it works. Followed by a list of security risks involved while using Bluetooth and finally, it highlights the best practices to protect the devices and the data they contain. © 2024

关键词： Ad hoc networks and security risk Bluetooth Exploit Threat Vulnerability

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Deep Learning-Based Automated Segmentation of Fiber Breaks in Advanced Composites 38

Deep Learning-Based Automated Segmentation of Fiber Breaks i...

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38th Technical Conference of the American Society for Composites, ASC 2023

作者： Jain, Sudhir Li, Carina Xiaochen Vuong, Daniel McGllick, Matthew Saifaee, Saeed Furtado, Carolina Kopp, Reed Joseph, Joshua Adjodah, Dhaval Rosini, Sebastian Sinclair, Ian Spearing, S. Mark Wardle, Brian L. Integrated Design and Management Program Massachusetts Institute of Technology CambridgeMA02139 United States Department of Aeronautics and Astronautics Massachusetts Institute of Technology CambridgeMA02139 United States Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States MIT Media Lab Massachusetts Institute of Technology CambridgeMA02139 United States Department of Mechanical Engineering University of Southampton SouthamptonSO17 1BJ United Kingdom Departments of Aeronautics and Astronautics and Mechanical Engineering Massachusetts Institute of Technology CambridgeMA02139 United States

ISBN: (纸本)9781605956916

The heterogeneity of the microstructure and the anisotropy of the mechanical properties of carbon fiber reinforced polymer composites (CFRP) are associated with complex damage mechanisms that make failure prediction highly challenging. Typical damage mechanisms for CFRP include: (i) interlaminar cracking (delamination), (ii) matrix cracking, and (iii) fiber breakage. X-ray computed tomography (CT) has been utilized recently to identify the complex damage in progressive failure of CFRP in 3D and 4D (3D spatial and 1D temporal). However, these scans contain a large amount of data (≈10 GB/mm3), which makes it challenging to extract mechanistic insights in a reasonable time frame. In previous work, we presented the first deep learning (DL) convolutional neural network (CNN) segmentation of multiclass microscale matrix damage in CFRP. The trained CNN segments complex and sparse composite matrix damage mechanism to ≈ 99.99% agreement, with nearly 100% of human time eliminated, providing higher accuracy compared to human segmentation. In this work, we developed CNN-based method for the automated segmentation of fiber breaks using synchrotron radiation-based CT (SRCT) scans that have been human-labeled. The model employed a U-Net full CNN as the high-level encoder (feature extraction)-decoder (feature localization) structure, and VGG16 as the deep CNN backbone via the publicly available Segmentation Models GitHub repository. An unbiased evaluation was performed comparing the machine vs. the human-labeled ground truth. Finally, active learning was presented for the machine-assisted relabeling of datasets containing fiber breaks. The deep learning-based automated segmentation method demonstrated accurate identification (> 90%) of fiber breakage for CFRP. © 2023 by DEStech Publications, Inc. and American Society for Composites. All rights reserved.

关键词： Complex networks

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The impact of copper oxide nanoparticles reinforced nanocellulose acetate membrane on antibacterial and dye removal Potency

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Results in engineering 2024年 23卷

作者： Yanuhar, Uun Suryanto, Heru Amin, Muhamad Maulana, Jibril Mohamad Lal, Mohammad Tamrin Caesar, Nico Rahman Study Program of Aquatic Resources Management Faculty of Fisheries and Marine Sciences Universitas Brawijaya East Java Indonesia Department of Mechanical and Industrial Engineering Faculty of Engineering Universitas Negeri Malang Jl. Semarang 5 Malang65145 Indonesia Department of Aquaculture Faculty of Fisheries and Marine Universitas Airlangga Jl. Dharmahusada Permai Surabaya60115 Indonesia Borneo Marine Research Institute Universiti Malaysia Sabah Jalan UMS Sabah Kota Kinabalu88400 Malaysia Doctoral Program of Environment Science Post Graduate Program Universitas Brawijaya Jalan Veteran East Java Malang65145 Indonesia

With the rapid growth of the textile, leather, cosmetics, and pharmaceutical industries, concerns about pollutants in these sectors, especially dye pollutants, are increasing. This research characterizes bacterial nanocellulose acetate membranes made from Sargassum extract reinforced with copper oxide nanoparticles and tests their antibacterial properties and dye removal in water. Sargassum sp. extract was fermented using Acetobacter xylinum for 10 days, producing bacterial nanocellulose, which was then esterified to create bacterial nanocellulose acetate. Copper oxide nanoparticles were added to the bacterial nanocellulose acetate solution in varying concentrations, cast, and oven-dried. The membrane was analyzed using Fourier-transform infrared spectroscopy, X-ray diffraction, scanning electron microscope, antibacterial activity, and dye removal. Results showed uniform copper oxide nanoparticles distribution on the membrane surface. Structure analysis revealed diffraction peaks at 35.44° and 38.57°, indicating a reduced crystalline index but improved membrane effectiveness. Antibacterial tests showed a zone of inhibition against bacterial growth, increasing with higher copper oxide nanoparticle content. The addition of copper oxide nanoparticles also influenced the dye removal capacity for Metanil Yellow, Congo Red, Eosin Yellow, Methylene Blue, and Malachite Green. The kinetic analysis showed that the adsorption process follows a pseudo-first-order model, with higher correlation coefficients (R2) compared to the pseudo-second-order model. © 2024 The Author(s)

关键词： Fourier transform infrared spectroscopy

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Quantifying random variability in decision-making in pediatric cardiac surgery

JTCVS Open

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JTCVS Open 2025年 25卷 382-392页

作者： Dlugos, Kayla V. Mazwi, Mjaye Signorile, Marisa Steve Fan, Chun-Po Trbovich, Patricia Honjo, Osami Institute of Medical Science University of Toronto ON Canada Division of Cardiovascular Surgery The Labatt Family Heart Centre The Hospital for Sick Children Toronto ON Canada Department of Surgery University of Toronto ON Canada Division of Cardiac Critical Care Seattle Children's Hospital Seattle Wash United States Ted Rogers Computational Program Ted Rogers Centre for Heart Research Peter Munk Cardiac Centre UHN Toronto ON Canada Institute of Health Policy Management and Evaluation University of Toronto Toronto ON Canada North York General Hospital Toronto ON Canada Institute of Biomedical Engineering University of Toronto Toronto ON Canada

Objective: Random variability in day-to-day decision-making referred to as “noise” is associated with variation that negatively affects both the reproducibility and quality of decision-making. Although well described in other fields, the prevalence and significance of noise in medical decision-making are understudied and largely unknown. The goal of this study was to quantify noise in medical decision-making using a noise audit. Methods: A noise audit was completed by 71 (n = 71) Heart Centre staff at the Hospital for Sick Children and Seattle Children's Hospital and involved a series of cases and questions surrounding decisions commonly encountered in the care for patients with transposition of the great arteries and critical aortic stenosis. Entropy was used to quantify total variation in responses. Because absolute entropy was not immediately comparable across audit questions with a different number of prespecified options, we reported a standardized version of entropy, which was calculated by dividing the absolute entropy by its theoretical maximum for each case. To compare responses in easy to hard questions across years of experience (<10 years and >10 years) and role, we reported aggregate entropy ratios. Aggregate entropy ratios were calculated by first stratifying by group of comparison and then calculating the standardized entropy for each question and taking the average of standardized entropies for easy questions and hard questions. Finally, to determine the ratio (easy to hard), we divided the average standardized entropy of the easy questions by the average standardized entropy of the hard questions. Results: The overall audit aggregate entropy ratio was 0.85 less than 1, indicating lower-complexity questions had less variation than higher-complexity questions. The aggregate entropy ratio for those with more than 10 years of experience was 0.8 and 0.87, respectively, for those with less than 10 years of experience. The aggregate entropy ratios for thos

关键词： congenital heart surgery entropy medical decision-making noise noise audit random variability

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Research on Traffic Sign Detection and Recognition System Using Deep Ensemble Learning

Research on Traffic Sign Detection and Recognition System Us...

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IEEE International Conference on Computer Communication and the Internet (ICCCI)

作者： Lung-Jen Wang Taweelap Suwattanapunkul Jarinya Thalauy Parinya Jansengrat Department of Computer Science and Information Engineering National Pingtung University Pingtung Taiwan International Master Program in Information Technology and Applications International College National Pingtung University Pingtung Taiwan Department of Big Data Management and Analytics Rajamangala University of Technology Thanyaburi Pathum Thani Thailand

ISBN: (数字)9798350351767

ISBN: (纸本)9798350351774

There is a rise in car accidents due to human errors on the road. A critical task of self-driving cars that can reduce accidents on the road is traffic sign detection and recognition (TSDR), which is vital in alerting drivers to the presence of traffic signs in advance. This research will separate the proposed deep ensemble learning algorithm into two methods. First, after the traffic scene process, the algorithm will detect the traffic sign as two categories with the YOLOv5s network. Then, process the traffic sign to recognize the traffic sign into seven classes with the MobileNet network. The detection model was trained with the Taiwan Traffic Sign Detection (TTSD) dataset collected from Taiwan roads. The recognition model was trained with the Taiwan Traffic Sign Recognition (TTSR) dataset. The result of the proposed algorithm showed high performance when experimenting with 95.83% accuracy, 87.34% true prediction, and 191.3 milliseconds (ms) of inference time.

关键词： YOLO Roads Prediction algorithms Inference algorithms Internet Autonomous automobiles Ensemble learning

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Construction Process Quality Control Assisted Mobile Application 8

Construction Process Quality Control Assisted Mobile Applica...

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8th IEEE International Conference on Industrial engineering and Applications, ICIEA 2021

作者： Kruachottikul, Pravee Cooharojananone, Nagul Phanomchoeng, Gridsada Wongsanao, Keetapat Thabsuwan, Sirada Suwannatrai, Kuptipong Pongsuttisatta, Watcharapong Ganyaporngul, Sirapavee Kovitanggoon, Kittikul Vajarodaya, Napatsapa Graduate School Chulalongkorn University Technopreneurship and Innovation Management Program Bangkok Thailand Chulalongkorn University Faculty of Science Department of Mathematics and Computer Science Bangkok Thailand Chulalongkorn University Faculty of Engineering Department of Mechanical Engineering Bangkok Thailand Chulalongkorn University Faculty of Science Department of Mathematics and Computer Science Bangkok Thailand Solitech Innovations and Technologies Co. Ltd. Bangkok Thailand

ISBN: (纸本)9781665428958

Digital transformation plays a big role in many industries, including construction. One of the obstacles to manage large-scale and complex construction projects is inefficient communication between involving personnel. Most problems are such as misunderstanding contexts, incomplete information, ignorance, missing multimedia files, etc. In Thailand, organizations adopt digital transformation by utilizing a variety of applications and software to complete their projects, such as LINE, G-Suite, Asana, etc. Users have to spend a lot of time to learn each application and software to be able to achieve maximum performance. Construction process quality control assisted application is the new tool developed for uniting all needs and solving communication problems. Requirements are gathered by five interviews with three major organizations, the Thailand Department of Highway, Team Built Co., Ltd., and one major construction company. Requirements were analyzed to extract the most useful features that are beneficial to all users. React Native and the Expo framework were used to develop the frontend part of the application. For the backend part, the application used microservice architecture with various cloud services, like Amazon AWS, Expo Server, and Firebase Cloud Messaging. In the end, the application was put through hand-on tests by 13 on-site personnel. The final results showed the average scores of the user interface, hands-on experience, and benefits for the users were 4, 4.16, and 3.92 (out of 5), respectively, in which the total satisfaction score is 4.03(out of 5). © 2021 IEEE.

关键词： Construction

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Potential of fungal thermostable alpha amylase enzyme isolated from Hot springs of Central Anatolia(Turkey)in wheat bread quality

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Food Bioscience 2022年第1期45卷 214-222页

作者： Arzu Unal Asiye Seis Subasi Semra Malkoc Ijlal Ocak SElif Korcan Elif Yetilmezer Seyhun Yurdugül Hülya Yaman Turgay Sanal Alaettin Keceli Igdır University Faculty of AgricultureDepartment of Agricultural BiotechnologyI˘gdırTurkey Ministry of Agriculture and Forestry Field Crops Central Research Institute Department of Quality and TechnologyAnkaraTurkey Eskisehir Technical University Faculty of EngineeringDepartment of Environmental EngineeringEskisehirTurkey Afyon Kocatepe University Faculty of EducationDepartment of Mathematics and Science EducationDivision of Science EducationAfyonTurkey Usak University Vocational School of Health ServicesMedical Laboratory Techniques ProgramUsakTurkey Ministry of Agriculture and Forestry Field Crops Central Research Institute Department of BiotechnologyAnkaraTurkey Bolu Abant Izzet Baysal University Faculty of Arts and ScienceDepartment of BiologyBoluTurkey Bolu Abant Izzet Baysal University Vocational School of the Technical Sciences of BoluFood Technology ProgramBoluTurkey Pamukkale University School of Applied SciencesDepartment of Organic Farming Business ManagementDenizliTurkey

Many industrial processes may quickly proceed with biotechnological and enzymatic *** and production facilitator properties of enzymes have provided variable advantages for ***,enzyme utilization has become inevitable for industry and supplied financial advantages in case of the high energy requirement *** the study,the amylase enzymes were isolated from thermal spring sources,and the effect on bread quality was ***,fungal amylases were isolated from thermal spring sources(29-98◦C)in various places around *** determining the functional properties of amylase enzymes,the most active enzyme was used in bread production to examine their effect on bread *** maximum alpha-amylase activity(38.6 U/mg)has been detected in Aspergillus niger G 2-1 *** compared with the commercially available one,native alpha-amylase increased the bread volume.A significant difference(p<0.01)was found in the color properties and size of the bread between microbial produced in this study and commercially produced *** ppm alpha-amylase addition showed the optimum bread properties for dough processing.

关键词： Alpha-amylase Thermal spring Quality of bread Commercial enzymes

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