检索结果-内蒙古大学图书馆

Improvement Suggestion Performance of Blowing Machine Line 4 with Total Productive Maintenance (TPM) Method at PT. Coca-Cola Amatil Indonesia MedanUnit 1

Improvement Suggestion Performance of Blowing Machine Line 4...

引用

1st International Conference of SNIKOM 2018, ICoSNIKOM 2018

作者： Irwansyah, Defi Harahap, M.R.F. Erliana, Cut Ita Abdullah, Dahlan Sari, Ayuesteka Siregar, Nurintanasyiah Achmaddaengs, G.S. Indahingwati, Asmara Sumartono, Eko Wilujeng, Sri Nurmawati Subekti, Purwo Kurniasih, Nuning Rosalina, Febrianti Hartono, H. Departement of Industrial Engineering Universitas Malikussaleh Aceh Indonesia Departement of Informatics Universitas Malikussaleh Aceh Indonesia Department of Management STIE Sakti AlamKerinci Jambi Indonesia Department of Management STIE Labuhanbatu Sumatera Utara Indonesia Department of Management Universitas 45 Surabaya Indonesia Department of Management School of Economics Indonesia STIESIA Surabaya Indonesia Faculty of Agriculture Universitas Bengkulu Bengkulu Indonesia Department of Management Faculty of Economy Universitas Kanjuruhan Malang Indonesia Program Study of Industrial Engineering University of 45 Surabaya Indonesia Mechanical Engineering Pasir Pengaraian University Riau Indonesia Faculty of Communication Sciences Library and Information Science Program Universitas Padjadjaran Bandung Indonesia Department of Agrotechnology Universitas Muhammadiyah Sorong Sorong Indonesia Department of Computer Science STMIK IBBI Medan Indonesia

Maintenance is an activity to maintain facilities or equipment of the factory and make repairs or adjustments to the necessary replacement to satisfactory condition of production operations in accordance with what is planned. Companies often experience damage to the Blowing machine so that interconnected machines cannot be operated. The purpose of this study was to improve the performance of Blowing line 4 engines with the Total Productive Maintenance (TPM) method at PT. Coca-Cola Amatil Indonesia Medan Unit, also to determine the level of Blowing machine performance based on the analysis of overall equipment effectiveness (OEE) at PT. Coca-Cola Amatil Indonesia Medan Unit. The method used in this study is the overall equipment effectiveness (OEE) method to measure Ishikawa's treatments and diagrams to compare and propose low engine performance. The results of data processing shows machine maintenance has not comply the OEE standards in July 81.48%, August 81.48%, September 78.07%, October 81.22%, November 78.08%, and those that fill the standards in June amount to 86.48%, with losses that most affect the effectiveness of equipment in line 4 blowroom machine is Equipment Failure Losses of 11.42% based on the results of the study, the proposed improvement in engine performance is to provide training to employees, and increase operator awareness. against engine damage, thus the production process will run smoothly. © Published under licence by IOP Publishing Ltd.

关键词： Data handling

来源：评论

学校读者我要写书评

暂无评论

Extraction of corn seed image texture using machine learning method

引用

AIP Conference Proceedings 2024年第1期2987卷

作者： Yampi R. Kaesmetan Fuzy Yustika Manik Wisard Kalengkongan Informatics Techniques Study Program STIKOM Uyelindo Kupang Kupang Indonesia Faculty of Computer Sciences and Information Technology Universitas Sumatera Utara Medan Indonesia Information System Study Program Universitas Sam Ratulangi Manado Manado Indonesia

Indonesia is the largest corn exporter in the world. Corn (Zea mays I.) Problems in determining the selection of corn seed to replant, especially corn in East Nusa Tenggara, are still a critical issue. The things that affect the quality of corn are found: the seeds are damaged, the seeds are dull, the seeds are dirty, the beans are broken due to the drying process, and the shell of the corn. The determination of the quality of corn grains usually is done manually with visual observation. The manual system requires a long time and produces good quality products that are not consistent due to the limitation of visual fatigue and differences in the perception of each observer. This research uses image texture extraction comparison with statistical methods I orde (color moment) and orde statistics II (GLCM) to select the corn seed. Orde statistics I (color moment) shows the emergence of the value of the degree of gray probability pixels in an image, while orde statistics II (GLCM) shows the relationship between two probability pixels forming a concurrence matrix from the image data. This research is expected to help the process of classification in determining the corn seed. The algorithm k of the nearest neighbor (K-NN) who used to research the classification of the object of the image that will be examined. The results of this study successfully performed using k-Nearest neighbor (k-NN) with a distance of euclidean distance and k=1 with the extraction of the color moment got the highest accuracy is 88%, and the extraction GLCM to characterize the homogeneity of 75.5%, correlation of 78.67%, a contrast of 65.75% and energy of 63.82% with an average accuracy of 70.93%.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Empowering Biomedical Discovery with AI Agents

arXiv

引用

arXiv 2024年

作者： Gao, Shanghua Fang, Ada Huang, Yepeng Giunchiglia, Valentina Noori, Ayush Schwarz, Jonathan Richard Ektefaie, Yasha Kondic, Jovana Zitnik, Marinka Department of Biomedical Informatics Harvard Medical School BostonMA United States Department of Chemistry and Chemical Biology Harvard University CambridgeMA United States Program in Biological and Biomedical Sciences Harvard Medical School BostonMA United States Department of Brain Sciences Imperial College London London United Kingdom Harvard College CambridgeMA United States Program in Biomedical Informatics Harvard Medical School BostonMA United States Department of Electrical Engineering and Computer Science MIT CambridgeMA United States Kempner Institute for the Study of Natural and Artificial Intelligence Harvard University MA United States Broad Institute of MIT and Harvard CambridgeMA United States Harvard Data Science Initiative CambridgeMA United States

We envision "AI scientists" as systems capable of skeptical learning and reasoning that empower biomedical research through collaborative agents that integrate AI models and biomedical tools with experimental platforms. Rather than taking humans out of the discovery process, biomedical AI agents combine human creativity and expertise with AI’s ability to analyze large datasets, navigate hypothesis spaces, and execute repetitive tasks. AI agents are poised to be proficient in various tasks, planning discovery workflows and performing self-assessment to identify and mitigate gaps in their knowledge. These agents use large language models and generative models to feature structured memory for continual learning and use machine learning tools to incorporate scientific knowledge, biological principles, and theories. AI agents can impact areas ranging from virtual cell simulation, programmable control of phenotypes, and the design of cellular circuits to developing new therapies. © 2024, CC BY.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

E-precision agriculture for small scale cash crops in Tobasa regency

引用

IOP Conference Series: Materials Science and Engineering 2017年第1期237卷

作者： Panca Putra Simanjuntak Pangeran Tiurniari Napitupulu Soni Pratama Silalahi Kisno Norlina Pasaribu Libuše Valešová Institut Teknologi Del Faculty of Informatics and Electrical Engineering Computer Network Management Study Program Toba Samosir 22381. Institut Teknologi Del Faculty of Informatics and Electrical Engineering Informatics Engineering Study Program Jl. Sisingamangaraja Sitoluama Toba Samosir Sumatera Utara 22381 Indonesia Czech University of Life Sciences Prague Department of Economics and Development Kamýcká 129 Prague 6 CZ 16521 Czech Republic

Cash crop is a promising sector in Tobasa regency; however, the trend showed a negative change of the cash crop production in. This research aims to develop an application which is based on Arduino for watering and fertilizing corn land. The result of using e-precision agriculture based on embedded system is 100% higher than the conventional one and the risk of harvesting failure using the embedded system decreased to 50%. Embedded system in this study acquired critical environment measurements which at last affected the yield raising and risk reduction. As the result, the use of e-precision agriculture provided a framework to be used by different stakeholders to implement e-agriculture platform that supports marketing of agricultural production since the system is proven to save the material and time which finally reduces the risk of harvesting failure and increases the yield. In other words, the system is able to economize the use of water and fertilizer on a small corn land. The system will be developed for more efficiency in material loss and the mobile-based application development to reach sustainable rural development particularly for cash-crop farmers.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Increasing accuracy of classification physical activity based on smartphone using ensemble logistic regression with boosting method

引用

Journal of Physics: Conference Series 2019年第4期1341卷

作者： A Lawi F Aziz S L Wungo Department of Computer Science Universitas Hasanuddin Makassar Indonesia. 90245 Faculty of Mathematics and Natural Sciences Universitas Pancasakti Makassar Indonesia. 90132 Program Study Informatics Engineering STMIK Kreatindo Monokwari Indonesia. 98300

At present, the smartphone is equipped with several sensors such as Accelerometer, Gravity sensor, and Gyroscope which can be used to recognize human physical activities such as walking upstair and walking downstairs etc. Machine learning is needed to group data and get information. Statistical methods have poor performance in classifying because procedures must be met. To overcome this, an ensemble technique was used. This study proposes the application of the gradientboost ensemble method to classify walking upstair and walking downstairs. The *** system is designed for data retrieval using a smartphone. Then, the dataset will be partitioned into 70% training data and 30% test data. The results show that the performance of the ensemble boosting method produces 81.82% accuracy, 86.11% sensitivity and 77.50% specificity.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Graph Artificial Intelligence in Medicine

引用

Biomedical Data Science 1000年第1期7卷 345-368页

作者： Ruth Johnson Michelle M. Li Ayush Noori Owen Queen Marinka Zitnik 1Department of Biomedical Informatics Harvard Medical School Boston Massachusetts USA email: marinka@hms.harvard.edu 2Berkowitz Family Living Laboratory Harvard Medical School Boston Massachusetts USA 3Bioinformatics and Integrative Genomics Program Harvard Medical School Boston Massachusetts USA 4Department of Computer Science Harvard John A. Paulson School of Engineering and Applied Sciences Allston Massachusetts USA 5Broad Institute of MIT and Harvard Cambridge Massachusetts USA 7Kempner Institute for the Study of Natural and Artificial Intelligence Harvard University Allston Massachusetts USA 6Harvard Data Science Initiative Cambridge Massachusetts USA

In clinical artificial intelligence (AI), graph representation learning, mainly through graph neural networks and graph transformer architectures, stands out for its capability to capture intricate relationships and structures within clinical datasets. With diverse data—from patient records to imaging—graph AI models process data holistically by viewing modalities and entities within them as nodes interconnected by their relationships. Graph AI facilitates model transfer across clinical tasks, enabling models to generalize across patient populations without additional parameters and with minimal to no retraining. However, the importance of human-centered design and model interpretability in clinical decision-making cannot be overstated. Since graph AI models capture information through localized neural transformations defined on relational datasets, they offer both an opportunity and a challenge in elucidating model rationale. Knowledge graphs can enhance interpretability by aligning model-driven insights with medical knowledge. Emerging graph AI models integrate diverse data modalities through pretraining, facilitate interactive feedback loops, and foster human–AI collaboration, paving the way toward clinically meaningful predictions.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Mineral water production for health therapy based on nanomaterial filters

引用

AIP Conference Proceedings 2023年第1期2748卷

作者： Mohamad Amin Dewi Nawang Arum Ihya Fakhrurizal Amin Ahya Zhilalikbar Amin Ekowati Retnaningtyas Department of Biology Faculty of Mathematics and Natural Sciences Universitas Negeri Malang Jl. Semarang No. 5 Malang 65145 Indonesia Poltekkes Kemenkes Malang Malang Indonesia Faculty of Medicine Universitas Indonesia Jakarta Indonesia Study Program of Informatics Engineering Faculty of Computer Sciences Universitas Brawijaya Malang Indonesia

Clean water is one of the most important needs, including for daily drinking, because 70-80% of the human body is water. There are many benefits of consuming adequate drinking water for health. Consuming clean and healthy water is one of the keys to getting a healthy body, because water also plays a role in oxygen transportation throughout the body. To produce clean and healthy water, technological innovations are needed, one of which is to use a nano filter-based device which can reduce solutes, colour, hardness and high metal ions by up to 70%. The purpose of this research is to produce drinking water that is healthy and can be useful in health therapy with nano material-based filters. The resulting water product is drinking water with a pH of 8+. This nano material-based tool has been tested using 3 water samples, namely well water, PDAM water and river water. The results showed that well water with a pH of 8.71, TDS (total dissolved solid) 282 and a test of 4 heavy metals (Pb, Cu, Zn and Cr) were below the threshold and the results after filtering were the most ideal among other water samples and recommended for consumption that can afford for health therapy.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Application of factor analysis method to support the users acceptance model of ERP systems implementation

引用

Journal of Physics: Conference Series 2021年第1期1836卷

作者： W Sardjono J Sudirwan W Priatna G R Putra Information Systems Management Department BINUS Graduate Program -Master of Information Systems Management Bina Nusantara University Jakarta Indonesia – 11480 School of Information Systems Department BINUS Undergraduate Program Bina Nusantara University Jakarta Indonesia 11480 Informatics Engineering Engineering Bhayangkara University Jakarta Raya Indonesia Computer Science Study Program Faculty of Mathematics & Natural Sciences Pakuan University Bogor Indonesia

An e-Commerce company has been using an Enterprise Resource Planning (ERP) system for several years, but is still constrained in its implementation, this is reflected in the number of issue/change request tickets submitted by users who have not been able to reach ideal conditions. To overcome this problem, we need an appropriate reference model, the ERP system user acceptance model in companies. The study conducted factors that influence the level of acceptance of SAP ERP users in the XYZ group to then determine a model that is able to explain practically the level of ERP system user acceptance, which in turn can produce concrete proposals to increase ERP system user acceptance. Research is quantitative descriptive using factor analysis and regression analysis methods. The research method uses a questionnaire with a total of 107 valid respondents coming from 8 company names under the XYZ group in 6 Southeast Asian countries. The conclusion of the study is that there are 24 indicators and 4 factors that influence user acceptance of the SAP ERP system. These four factors are the low contribution of the ERP system, the quality of ERP systems and data, the development of ERP systems, and also the low quality of ERP system supporters. It is hoped that by optimizing the value of the 4 factors, the XYZ group can increase user acceptance of the SAP ERP system so that the system can provide benefits expected by the company to be competitive advantage.

关键词：

来源：评论

学校读者我要写书评

暂无评论

In silico analysis of tetrahydroxycurcumin compound in tumeric (Curcuma longa) as inhibitor of SARS-CoV-2 virus replication

引用

AIP Conference Proceedings 2023年第1期2748卷

作者： Mohamad Amin Nanda Hilda Khikmawati Suryadi Suryadi Rifcha Fachrunnisa Ihya Fakhrurizal Amin Dina Maulina Ahya Zhilalikbar Amin Nik Ahmad Nizam Nik Malek Restu Fitriani Department of Biology Faculty of Mathematics and Natural Sciences Universitas Negeri Malang Jl. Semarang No.5 Malang 65145 Indonesia Special Education Department Faculty of Education Universitas Negeri Malang Jl. Semarang No.5 Malang 65145 Indonesia Faculty of Medicine Universitas Indonesia Jakarta Indonesia Biology Education Study Program Faculty of Teacher Training and Education Universitas Lampung Lampung Indonesia Department of Biosciences Faculty of Science Universiti Teknologi Malaysia Johor Malaysia Study Program of Informatics Engineering Faculty of Computer Sciencies Universitas Brawijaya Malang Indonesia Biotechnology Program Faculty of Mathematics and Natural Sciences Universitas Negeri Malang Jl. Semarang No.5 Malang 65145 Indonesia

There are many uses of natural ingredients to find out their potential in overcoming Coronavirus Disease 2019. One of the plants that is often used to treat various diseases, including SARS-Cov2 infection is turmeric. Turmeric contains Tetrahydroxycurcumin compounds. The aim of this research was to study the potential of Tetrahydroxycurcumin in preventing infection with the SARS-CoV-2 virus. The results showed that Tetrahydroxicurcumin has the potential to inhibit Tyrosine protein kinase ABL1, which is a protein that plays a role in the preparation of the cytoskeleton during viral infection. The binding affinity of Tetrahydroxycurcumin for this protein is -8.4 kcal/mol.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Mapping geographical inequalities in childhood diarrhoeal morbidity and mortality in low-income and middle-income countries, 2000-17: analysis for the Global Burden of Disease study 2017 (vol 395, pg 1779, 2020)

引用

LANCET 2020年第10239期395卷 1762-1762页

作者： Reiner, R. C., Jr. Hay, S., I Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Global Health School of Medicine University of Washington Seattle WA United States Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States College of Health and Medical Sciences Haramaya University Harar Ethiopia Department of Epidemiology and Biostatistics Haramaya University Harar Ethiopia Department of Medical Laboratory Sciences Haramaya University Harar Ethiopia School of Nursing and Midwifery Haramaya University Harar Ethiopia School of Pharmacy Haramaya University Harar Ethiopia School of Public Health Haramaya University Harar Ethiopia Haramaya University Harar Ethiopia Advanced Diagnostic and Interventional Radiology Research Center Tehran University of Medical Sciences Tehran Iran Cancer Biology Research Center Tehran University of Medical Sciences Tehran Iran Cancer Research Institute Tehran University of Medical Sciences Tehran Iran Department of Economics and Management Sciences for Health Tehran University of Medical Sciences Tehran Iran Department of Environmental Health Engineering Tehran University of Medical Sciences Tehran Iran Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran Department of Health Management and Economics Tehran University of Medical Sciences Tehran Iran Department of Microbiology Tehran University of Medical Sciences Tehran Iran Department of Pharmacology Tehran University of Medical Sciences Tehran Iran Digestive Diseases Research Institute Tehran University of Medical Sciences Tehran Iran Endocrinology and Metabolism Research Center Tehran University of Medical Sciences Tehran Iran Hematology-Oncology and Stem Cell Transplantation Research Center Tehran University of Medical Sciences Tehran Iran Iran National Institute of Health Research Tehran University of Medical Sciences Tehran Iran Metabolomics and

Summary Background Across low-income and middle-income countries (LMICs), one in ten deaths in children younger than 5 years is attributable to diarrhoea. The substantial between-country variation in both diarrhoea incidence and mortality is attributable to interventions that protect children, prevent infection, and treat disease. Identifying subnational regions with the highest burden and mapping associated risk factors can aid in reducing preventable childhood *** We used Bayesian model-based geostatistics and a geolocated dataset comprising 15 072 746 children younger than 5 years from 466 surveys in 94 LMICs, in combination with findings of the Global Burden of Diseases, Injuries, and Risk Factors study (GBD) 2017, to estimate posterior distributions of diarrhoea prevalence, incidence, and mortality from 2000 to 2017. From these data, we estimated the burden of diarrhoea at varying subnational levels (termed units) by spatially aggregating draws, and we investigated the drivers of subnational patterns by creating aggregated risk factor *** The greatest declines in diarrhoeal mortality were seen in south and southeast Asia and South America, where 54·0% (95% uncertainty interval [UI] 38·1-65·8), 17·4% (7·7-28·4), and 59·5% (34·2-86·9) of units, respectively, recorded decreases in deaths from diarrhoea greater than 10%. Although children in much of Africa remain at high risk of death due to diarrhoea, regions with the most deaths were outside Africa, with the highest mortality units located in Pakistan. Indonesia showed the greatest within-country geographical inequality; some regions had mortality rates nearly four times the average country rate. Reductions in mortality were correlated to improvements in water, sanitation, and hygiene (WASH) or reductions in child growth failure (CGF). Similarly, most high-risk areas had poor WASH, high CGF, or low oral rehydration therapy *** By co-analysing geospatial trends in d

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：