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Occurrence of cadmium in groundwater in China: a review

Arabian Journal of Geosciences 2022年第17期15卷 1-13页

作者： Hoareau, Carol Emilly Hadibarata, Tony Yılmaz, Murat Environmental Engineering Program Faculty of Engineering and Science Curtin University Malaysia Miri Malaysia Department of Chemical Engineering Faculty of Engineering Osmaniye Korkut Ata University Osmaniye Türkiye

China has one of the world’s fastest-growing economies due to its increase in various industrial activities. A side effect of economic growth is severe environmental problems such as heavy metal contamination of soil and groundwater. Anthropogenic activities are the main sources of cadmium which is highly mobile and toxic with the potential to bioaccumulate in the ecosystem. It can contaminate ground and river water consequently negatively impacting agriculture and water sources. Anthropogenic source of Cd concentrations in China is 0.002 mg/L in drinking water, 0.102 mg/kg in soil, and 0.23–0.96 mg/kg in paddy soil. Geological trends and health implications of cadmium contamination in Human, southern China were analyzed. Source, transportation, and various conventional remediation processes exist today and can be categorized as biological, physical, and chemical. Using nanoparticle technology, it has been found that adsorption capacities can be 3 to 4 times higher compared to using powdered activated carbon. From the experiment carried out, a maximum adsorption capacity of 10.86 mg/g for cadmium was obtained. Cadmium intake in south China populations occurred at an alarming rate and most children were at greater risk of being affected. Therefore, cadmium contamination should be taken seriously by the responsible authorities.

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Effect of High-Flow Nasal Cannula on Capnogram Waveform for studying Non-Invasive Human Ventilation

Effect of High-Flow Nasal Cannula on Capnogram Waveform for ...

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Biomedical engineering Conference (NBEC), IEEE National

作者： Tjokorda Gde Tirta Nindhia Nursyasa Aqila Mohammed Julia Jais Jamaludin Pagupathi Devandran Nabiel Rafa Angel Bhaswara Thalitakum Hutajulu M.B. Malarvili Study Program of Mechanical Engineering Engineering Faculty Udayana University Jimbaran Bali Indonesia School of Biomedical and Health Science Engineering Universiti Teknologi Malaysia Johor Malaysia

This study is conducted to compare three different cannulas; all purpose nasal cannula with 2 prongs, nasal pressure cannula with 2 prongs and single port nasal cannula which are commonly used for capnography device. These cannulas or sometimes called as nasal prong is connected to the device via nose of subjects studied. This procedure is a part of respiratory study to monitor lungs condition and breathing pattern. This study involves 47 subject where the exhaled breath was recorded to make comparison and choose the most suitable and effective for capnography waveform analysis. Utilizing Statistical Package for the Social Sciences (SPSS) to find the normality of all the nasal cannula data based on capnogram waveform. The result from the analysis shows that the frequency distribution for type 1 nasal cannula which is also known as all-purpose nasal cannula had the feature values closer to the standard value. Our study proofs that all purpose nasal cannula sampling is the most suitable to capture exhaled breath for monitoring respiratory conditions.

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Analysis of marine debris at Alue Naga and Ulee Lheue beaches in Banda Aceh City using the transect method

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Materials Today: Proceedings 2022年 63卷 S339-S345页

作者： Windari, Wulan Saiful, Saiful Gani, Asri Mahidin Master of Environment Management Postgraduate Program Syiah Kuala University Banda Aceh Indonesia Chemistry Department Faculty of Mathematics and Natural Science Syiah Kuala University Banda Aceh Indonesia Chemical Engineering Faculty of Engineering Syiah Kuala University Banda Aceh Indonesia Research Center for Environmental and Natural Resources Universitas Syiah Kuala Darussalam Banda Aceh 23111 Indonesia

Alue Naga Beach and Ulee Lheue Beach are beaches located in Banda Aceh City, Aceh Province, these two beaches have a fairly large role in the fields of fisheries, transportation, and tourism. During the last few years, the population growth rate of Banda Aceh City has increased by 2% per year, this causes the volume of waste generated to be even greater, unfortunately, the municipal waste management office cannot manage it fully. Most of the untreated waste enters water bodies and has the potential to pollute the marine and coastal environment. So it is necessary to do research to provide an overview of the level of marine debris pollution on the two beaches. This study uses the transect method, the waste obtained is grouped according to size and type. The results showed that marine debris on Ulee Lheue beach was found to be more numerous and varied than marine debris on Alue Naga beach. Overall, macro waste with a size range of 2.5−1 m was the most commonly found and plastic was the waste with the highest yield with a density value of 65.8 g/m2, an abundance of 6.56 items/m2, and a percentage of 75%. © 2022

关键词： Beaches

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Classification Of Ornamental Fish Types Using CNN Method With VGG-16 And U-NET Architecture

Classification Of Ornamental Fish Types Using CNN Method Wit...

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Consumer Technology (ICCT-Pacific), International Conference on

作者： Ni Luh Wiwik Sri Rahayu Ginantra Christina Purnama Yati I Gusti Ayu Agung Diatri Indradewi I Komang Agus Yudiawan Technology and Informatics Informatics Engineering Institut Bisnis dan Teknologi Indonesia (INSTIKI) Denpasar Indonesia Department of Informatics Engineering Information Systems Study Program Faculty of Engineering and Vocational Studies Universitas Pendidikan Ganesha (UNDIKSHA) Denpasar Indonesia

ISBN: (数字)9798331504120

ISBN: (纸本)9798331504137

Ornamental fish are a type of fish that live in freshwater or seawater habitats and are typically maintained for aesthetic purposes, often in ornamental ponds or as household pets. The diversity of colors, shapes, and patterns observed in ornamental fish presents a challenge in their classification. Therefore, a method capable of accurately recognizing the visual characteristics of these fish is required. The objective of this study is to evaluate the performance of two Convolutional Neural Network (CNN) architectures, specifically VGG-16 and U-Net, using five distinct types of ornamental fish, namely Angel Fish, Betta Fish, Clown Fish, Gold Fish, and Guppy Fish. The dataset comprises 3.240 images that have been processed using TensorFlow and Keras on Google Collaboratory. The results demonstrated that U-Net demonstrated superior performance in segmentation, with an Average Intersection over Union (IoU) of 58.91 % and an Average Dice Coefficient of 73.72%. In contrast, VGG-16 exhibited signs of overfitting, as evidenced by lower evaluation metrics. To enhance the efficacy of the transfer learning model, further optimization is recommended.

关键词： Measurement Image segmentation Visualization Shape Transfer learning Fish Internet Convolutional neural networks Optimization Overfitting

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Evaluating factors influencing community readiness for post-mining environmental development strategies

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Journal of environmental Management 2024年 366卷 121823页

作者： Sutrisno, Agung Dwi Lee, Chun-Hung Suhardono, Sapta Suryawan, I Wayan Koko Department of Mining Engineering Institut Teknologi Nasional Jl. Babarsari Caturtunggal Depok Sleman Yogyakarta55281 Indonesia Department of Natural Resources and Environmental Studies College of Environmental Studies and Oceanography National Dong Hwa University Hualien97401 Taiwan Environmental Sciences Study Program Faculty of Mathematics and Natural Sciences Universitas Sebelas Maret Surakarta57126 Indonesia Department of Environmental Engineering Faculty of Infrastructure Planning Universitas Pertamina Jalan Sinabung II Terusan Simprug Jakarta12220 Indonesia

This research delves into the complex factors that affect how ready a community is to embrace new environmental development strategies, which could significantly change the region's social and economic fabric. Using a structured questionnaire, exploratory factor analysis and logistic regression analysis, the study assesses how corporate practices in resource management, environmental governance, efforts to enhance community capabilities, and various demographic factors influence the community's willingness to adapt to change. Despite its intentions to benefit both the mining operations and the community, corporate resource management appears to have a paradoxical impact on the community's willingness to pursue new environmental paths. This negative impact can be attributed to the dependency it creates. Effective corporate resource management can lead to a community becoming heavily reliant on the stability and benefits provided by the mining company. This dependency fosters a sense of security and satisfaction with the status quo, making community members less inclined to explore or support new and potentially disruptive environmental strategies. The stability provided by the mine's resource management practices may inadvertently anchor the community to existing economic structures, reducing their impetus to seek alternative livelihoods or adapt to new socioeconomic conditions. However, it is essential to consider the limitations of this finding. One limitation is the potential bias in community perceptions, where immediate benefits from corporate resource management overshadow long-term considerations for sustainable development. Additionally, the context-specific nature of this study means that these findings may not be universally applicable to all mining communities. © 2024 Elsevier Ltd

关键词： Mining

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Image Processing Implementation to Classify Coffee Fruit Ripeness Using K-Nearest Neighbor (KNN) Algorithm 8

Image Processing Implementation to Classify Coffee Fruit Rip...

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8th International Conference on Information Management and Technology, ICIMTech 2023

作者： Hussaini Dermawan, M. Farhan Witarsyah, Deden Syamsuar, Dedy Fakhrurroja, Hanif Luthfi, Ahmad Herdiansyah, Muhammad Izman Telkom University Faculty of Industrial Engineering Bandung Indonesia School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia Islamic University of Indonesia Faculty of Industrial Technology Department of Informatics Jogjakarta Indonesia Universitas Bina Darma Informatics Study Program Faculty of Science and Technology Palembang Indonesia

ISBN: (纸本)9798350326093

Coffee is one of the plantation crops that has long been a cultivated plant in Indonesia. The classification of coffee fruit maturity manually still has several weaknesses and requires a long process, has low accuracy and is inconsistent, this is because the determination is made subjectively by coffee farmers. As for the classification of coffee fruit maturity levels automatically, it can be faster with objective determination, therefore the use of image processing is relatively easier, faster, and based on a quantified descriptive assessment to determine coffee maturity. Image Processing is a method used to process or manipulate images in 2-dimensional form. In the classification process, there are many methods used to obtain classification of objects based on training data. One of the algorithms used for the classification process is K-Nearest Neighbor (KNN). KNN is a classification technique for objects based on training data that is the closest or has similar characteristics to the object. KNN includes supervised learning algorithms, where the results of the new query instance are classified based on the majority of the categories in K-Nearest Neighbors (K-NN). The finding indicated that class classification of ripe and unripe were 88,24 % and 100% respectively with 93,33% accuracy level. © 2023 IEEE.

关键词： Classification (of information)

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Transforming disposable masks to sustainable gasoline-like fuel via pyrolysis

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environmental Advances 2024年 15卷

作者： Sari, Mega Mutiara Inoue, Takanobu Salsabilla, Vionna Chantika Septiariva, Iva Yenis Mulyana, Rahmad Prayogo, Wisnu Arifianingsih, Nur Novilina Suhardono, Sapta Suryawan, I. Wayan Koko Department of Environmental Engineering Faculty of Infrastructure Planning Universitas Pertamina Jakarta 12220 Indonesia Department of Architecture and Civil Engineering Toyohashi University of Technology Aichi Toyohashi 441-8580 Japan Civil Engineering Study Program Faculty of Engineering Universitas Sebelas Maret Jl. Ir. Sutami 36A Surakarta 57126 Indonesia Department of Civil Engineering Faculty of Engineering Universitas Negeri Medan North Sumatra Medan Indonesia Department of Environmental Engineering Faculty of Civil and Environmental Engineering Institut Teknologi Bandung Bandung 40116 Indonesia Department of Environmental Science Universitas Sebelas Maret. Central Java Surakarta Indonesia

The past COVID-19 pandemic has led to a surge in the use of disposable masks, posing a significant environmental challenge due to the swift accumulation of waste. This study explores the potential of pyrolysis to transform this waste into valuable pyrolysis oil with characteristics akin to gasoline, addressing both waste management and energy derivation concerns. Pyrolysis, a thermal decomposition process, was applied to mask materials, producing an oil with a high calorific value of 45.93 MJ/kg. The chemical makeup of this pyrolytic oil was meticulously characterized using Pyrolysis-Gas Chromatography-Mass Spectrometry (PY-GC/MS) and Fourier-transform Infrared Spectroscopy (FTIR), confirming the presence of hydrocarbons similar to those found in gasoline. Achieving an efficiency of 41.865 %, the pyrolytic approach demonstrated a promising potential for not only managing mask waste but also creating an alternative energy carrier. However, the study advises that before considering this pyrolytic oil for engine use, a thorough evaluation of its combustion quality, engine compatibility, and environmental impact is essential. This investigation advances the discussion on sustainable waste management, offering insights into the generation of alternative fuels from daily waste streams, while also highlighting the necessity for comprehensive analyses to ensure the practicality and efficiency of such novel energy solutions. © 2023 The Author(s)

关键词： Alternative fuel sources Disposable masks Energy recovery techniques Medical waste valorization Thermochemical conversion

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Machine Learning Stroke Prediction in Smart Healthcare:Integrating Fuzzy K-Nearest Neighbor and Artificial Neural Networks with Feature Selection Techniques

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Computers, Materials & Continua 2025年第3期82卷 5115-5134页

作者： Abdul Ahad Ira Puspitasari Jiangbin Zheng Shamsher Ullah Farhan Ullah Sheikh Tahir Bakhsh Ivan Miguel Pires Department Information System Study Program Faculty of Science and TechnologyUniversitas AirlanggaSurabaya60286Indonesia School of Software Northwestern Polytechnical UniversityXi’an710072China Research Center for Quantum Engineering Design Faculty of Science and TechnologyUniversitas AirlanggaSurabaya60286Indonesia School of Computer Science and Software Engineering Shenzhen UniversityShenzhen518061China Cybersecurity Center Prince Mohammad Bin Fahd University617Al JawharahKhobarDhahran34754Saudi Arabia Cardiff School of Technologies Cardiff Metropolitan UniversityWestern AvenueCardiffCF52YBUK Instituto de Telecomunicacoes Escola Superior de Tecnologia e Gestao de AguedaUniversidade de Aveiroágueda3750-127Portugal

This research explores the use of Fuzzy K-Nearest Neighbor(F-KNN)and Artificial Neural Networks(ANN)for predicting heart stroke incidents,focusing on the impact of feature selection methods,specifically Chi-Square and Best First Search(BFS).The study demonstrates that BFS significantly enhances the performance of both *** BFS preprocessing,the ANN model achieved an impressive accuracy of 97.5%,precision and recall of 97.5%,and an Receiver Operating Characteristics(ROC)area of 97.9%,outperforming the Chi-Square-based ANN,which recorded an accuracy of 91.4%.Similarly,the F-KNN model with BFS achieved an accuracy of 96.3%,precision and recall of 96.3%,and a Receiver Operating Characteristics(ROC)area of 96.2%,surpassing the performance of the Chi-Square F-KNN model,which showed an accuracy of 95%.These results highlight that BFS improves the ability to select the most relevant features,contributing to more reliable and accurate stroke *** findings underscore the importance of using advanced feature selection methods like BFS to enhance the performance of machine learning models in healthcare applications,leading to better stroke risk management and improved patient outcomes.

关键词： Fuzzy K-nearest neighbor artificial neural network accuracy precision recall F-measure Chi-Square best search first heart stroke

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The Design of VBee Diary Writing Application 9

The Design of VBee Diary Writing Application

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9th International Conference on Education and Technology, ICET 2023

作者： Sidupa, Christiana Nugroho, Hermawan Perdani, Yella Dezas Faculty of Humanities Bina Nusantara University Digital Language Learning Center Interior Design Department Jakarta Indonesia Faculty of Information Technology Satya Wacana Christian University Informatics Engineering Study Program Salatiga Indonesia Faculty of Humanities Bina Nusantara University Digital Language Learning Center Interior Design Department Bandung Indonesia

ISBN: (纸本)9798350358292

The development of critical thinking, creativity, and communication abilities is facilitated by the acquisition of writing skills, which are significant for students. Nevertheless, a considerable number of students presently encounter difficulties in locating the impetus and enthusiasm required for engagement in writing endeavors. The focus of the present paper is application design. The VBee application is a web-based application that facilitates the expression of user creativity and fosters a deeper appreciation for the art of writing. The application boasts a highly intuitive interface that effortlessly enables users to document their thoughts and experiences. It offers a plethora of features that not only facilitate writing but also foster self-expression, including customizable emoticons and the option to provide feedback. By designing the application, it could help support vocational school students in improving the quality of skill-focused education, particularly their English creative writing skill in enjoyment. Besides, the teachers are assisted to guide their students with technologically advanced and entertaining learning tools. © 2023 IEEE.

关键词： Students

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Review of mayflies (Insecta Ephemeroptera) as a bioindicator of heavy metals and microplastics in freshwater

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Science of the Total Environment 2025年 958卷 178057页

作者： Benhadji, Nadhira Kurniawan, Setyo Budi Imron, Muhammad Fauzul Institute of Technology and Life Sciences—National Research Institute Falenty Hrabska Avenue 3 Raszyn05-090 Poland Department of Chemical and Process Engineering Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia Selangor UKM Bangi43600 Malaysia Study Program of Environmental Engineering Department of Biology Faculty of Science and Technology Universitas Airlangga Campus C UNAIR Jalan Mulyorejo Surabaya60115 Indonesia Department of Water Management Faculty of Civil Engineering and Geosciences Delft University of Technology Stevinweg 1 CN Delft2628 Netherlands

Heavy metal and microplastic pollutions are prevalent in freshwater ecosystems, with many freshwater bodies being contaminated by one or both of these pollutants. Recent studies reported extreme detections of Cd, Pb and Zn, high concentrations of Cr, Pb and Cu and microplastics acting as vectors of pollutants, including heavy metals. Mayflies can serve as bioindicators of heavy metal contamination in freshwater ecosystems because changes in their community structure, physiology, and behaviour can reflect and help predict the concentrations of metals in these environments. This review discusses the ecological alterations induced by tissue metal concentration in mayflies and other macroinvertebrates. As sensitive taxa to heavy metal contamination, mayflies can reflect the impacts of this pollution through their ethology and relationship to the substrate, highlighting issues such as eutrophication, alterations in community structure, inhibitory effects and sediment toxicity. Mayflies are also highly affected by microplastic exposure, which leads to ingestion, bioaccumulation, biomagnification, habitat and community alteration, behavioural changes, physiology alteration and toxicity. Mayflies bioindication metrics for assessing the impact of heavy metals and microplastics include the examination of community alteration, functional feeding behaviour, molecular structure, dietary and toxicity impacts, bioaccumulation and biomagnification and biomarkers. Current challenges for the utilization of mayflies as bioindicators include temporal variations in sensitivity, lack of universally recognised protocols and need for standardised protocols for microplastic analysis. Additionally, the applicability of mayflies as bioindicators may vary across different ecosystems, emphasising the need for selecting suitable indicators that align with the unique characteristics of the ecosystem. © 2024 The Authors

关键词： Macroinvertebrates

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