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Design of sustainable green supply chain management using house of risk

AIP Conference Proceedings 2024年第1期2952卷

作者： Lolyka Dewi Indrasari Ana Komari Afiff Yudha Tripariyanto Heribertus Budi Santosa Eko Siswanto Pamadya Vitasmoro Johan Alfian Pradana Venus Khatta Salsabilah Industrial Engineering Study Program Faculty Engineering Universitas Kadiri Kediri Indonesia

The continued role of the green management supply chain has become a parameter of the company’s sustainability. The role that is realized is to provide effectiveness in terms of reducing risks arising from the supply chain. Risks that arise deserve to be identified by the achievement of reducing supply chain risks that occur. The purpose of this study is to model the risks of green supply chain management using the house of risk method. This method as an integration of FMEA-QFD. The product used as a case is snail chips from PT. QRP. Due to the ineffective supply chain, various risks arise where this risk in addition to harming the company also harms the snail material supply vendors. Identification of risks by occurrence and risk agents totaling 22 types. The findings serve as a basis for constructing potential risks modeled with a causal diagram. It was found that the highest case parameter was that there was poor communication with long responses, one of which was. As a result of this case, the prevention action indicator can be clearly known with consideration of 6M (man, machine, material, measurement, method and mother nature). That the preventive action relationship with 6M can create a green supply chain design according to existing conditions. The virtues of the design formed are considering 6M supported by the role of ISO.

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Android-Based Lecturer Workload Simulation Application 2

Android-Based Lecturer Workload Simulation Application

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2nd International Conference on Computer Science and engineering Technology, ICCSET 2019

作者： Triyanto, Wiwit Agus Study Program of Information System Engineering Faculty Muria Kudus University Indonesia

In carrying out their duties, lecturers must conduct Tri dharma education activities which include teaching, research and service according to their respective fields of science. Every tri dharma activity carried out must be reported once every semester in the form of a lecturer workload *** number of activities contained in the rubric makes many lecturers experience confusion to calculate how the credit performance in the Tridharma activities carried out. Therefore, it is necessary to have a simulation application that helps the calculation of credit performance of Tridharma activities in accordance with the BKD rubric. The lecturer workload simulation application can help lecturers to calculate credits for the Tridharma activities that have been carried out. The lecturer workload simulation application can also provide information on what physical evidence needs to be prepared by the lecturer. © Published under licence by IOP Publishing Ltd.

关键词： Android (operating system)

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An Efficient Three-Factor Authenticated Key Agreement Technique Using FCM Under HC-IoT Architectures

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Computers, Materials & Continua 2022年第7期72卷 1373-1389页

作者： Chandrashekhar Meshram Agbotiname Lucky Imoize Sajjad Shaukat Jamal Parkash Tambare Adel R.Alharbi Iqtadar Hussain Department of Post Graduate Studies and Research in Mathematics Jayawanti Haksar Government Post-Graduation CollegeCollege of Chhindwara UniversityBetul460001M.P.India Department of Electrical and Electronics Engineering Faculty of EngineeringUniversity of LagosAkokaLagos100213Nigeria Department of Electrical Engineering and Information Technology Institute of Digital CommunicationRuhr University44801BochumGermany Department of Mathematics College of ScienceKing Khalid UniversityAbhaSaudi Arabia Water Resources&Applied Mathematics Research Lab Nagpur440027India College of Computing and Information Technology University of TabukTabuk71491Saudi Arabia Mathematics Program Department of MathematicsStatistics and PhysicsCollege of Arts and SciencesQatar University2713DohaQatar

The Human-Centered Internet of Things(HC-IoT)is fast becoming a hotbed of security and privacy *** users can establish a common session key through a trusted server over an open communication channel using a three-party authenticated key *** of the early authenticated key agreement systems relied on pairing,hashing,or modular exponentiation processes that are computationally intensive and *** order to address this problem,this paper offers a new three-party authenticated key agreement technique based on fractional chaotic *** new scheme uses fractional chaotic maps and supports the dynamic sensing of HC-IoT devices in the network architecture without a password *** projected security scheme utilized a hash function,which works well for the resource-limited HC-IoT *** results show that our new technique is resistant to password guessing attacks since it does not use a ***,our approach provides users with comprehensive privacy protection,ensuring that a user forgery attack causes no ***,our new technique offers better security features than the techniques currently available in the literature.

关键词： Three-party authenticated key agreement anonymity fractional chaotic maps Chebyshev polynomial password table human-centered internet of things(HC-IoT)

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Review Paper on Bluetooth Based Home Automation Using Android Phone

Review Paper on Bluetooth Based Home Automation Using Androi...

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Sustainable Emerging Innovations in engineering and Technology (ICSEIET), International Conference on

作者： Priyanka Bhardwaj Manidipa Roy Shilpa Srivastava Sanjay Kumar Singh Vidushi Gupta Mega Novita Muhammad Amirudin Imadudin Harjanto ABES Engineering College Ghaziabad U.P India Postgraduate Program of Science Education Universitas PGRI Semarang Semarang Central Java Indonesia Department of Electrical Engineering Faculty of Engineering and Informatics Universitas PGRI Semarang Semarang Central Java Indonesia

Electronic devices and appliances have become quintessential part of households with the recent development and integration of a home automation system with numerous client modules, including a remote mobile host controller, as in offices, home appliances etc.. Through Bluetooth, the client modules communicate with the host controller such as an Android smart phone. This paper presents a prototype can be implemented in practice with maximum efficiency keeping the security feature in mind.

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TinyML for Safe Driving: The Use of Embedded Machine Learning for Detecting Driver Distraction

TinyML for Safe Driving: The Use of Embedded Machine Learnin...

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Metrology for Automotive (MetroAutomotive), IEEE International Workshop on

作者： Thommas Flores Marianne Silva Mariana Azevedo Thais Medeiros Morsinaldo Medeiros Ivanovitch Silva Max Mauro Dias Santos Daniel G. Costa Postgraduate Program in Electrical and Computer Engineering (PPgEEC) Federal University of Rio Grande do Norte Natal Brazil INEGI Faculty of Engineering University of Porto Porto Portugal Federal University of Technology Ponta Grossa Brazil

Among the main causes of road accidents, one of the most significant is related to driver distraction while driving, which is responsible for 18% of car accidents worldwide. This situation has demanded the development of mechanisms to automatically detect this dangerous behavior while driving. One of the computational solutions that has been considered viable to detect situations like this is the use of Convolutional Neural Networks (CNN), but some complex issues arise when deploying CNN models in microcontroller-based embedded devices with constrained processing and memory capabilities. In this context, this paper proposes a driver distraction detection system that achieves high accuracy (99.3%) and low latency (72ms) while requiring minimal computational resources (Peak- RAM of 164 KB and Flash of 52.7 KB). This solution exploiting Tiny Machine Learning (TinyML) algorithms was developed with the support of the Edge Impulse platform, used to perform the entire ML pipeline, from data pre-processing and ML model creation to deployment into an Arduino Portenta H7 board. By designing a driver assistance system that can be integrated into vehicles, it is expected that an affordable solution based on embedded machine learning is provided, tackling a real-world problem by potentially reducing accidents caused by driver distractions.

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The Impact Perceived Desirability, Propensity to Act, and Perceived Feasibility Towards Technoprenurial Commitment Based on a Entreprenurial Event Theory

The Impact Perceived Desirability, Propensity to Act, and Pe...

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International Conference on Cybernetics and Intelligent System (ICORIS)

作者： Stefanus Rumangkit Aloysius Bagas Pradipta Irianto Antonius Satria Hadi Management Department BINUS Business School Doctor of Research in Management Bina Nusantara University Jakarta Indonesia Information System Department Faculty of Engineering Atma Jaya University Yogyakarta Indonesia Study Program of Entrepreneurship Faculty of Economy University of Widya Mataram Yogyakarta Indonesia

ISBN: (数字)9798331539603

ISBN: (纸本)9798331539610

Technopreneurship represent a form of entrepreneurship that emphasizes entrepreneurial skills and technology. Studies on technopreneurship have been conducted, but research investigating antecedents of technopreneurship based on the entrepreneurial event model (EEM), is still limited. Most research on technopreneurship is dominated by the use of the theory of planned behavior (TPB). Therefore, this study aims to investigate the driving factors in EEM, namely perceived desirability, propensity to act, and perceived feasibility to technopreneurship intention. In addition, another purpose of this study is to explore technopreneurship intention towards technopreneurship commitment. To achieve this goal, the study used quantitative research design, primary data sources, and data collection methods using questionnaires. The sample in this study amounted to 240, with the sampling method using purposive sampling. Reliability, validity, and hypothesis testing using Smart-PLS software version 3. The results showed that perceived desirability affects technoprenurial intention, propensity to act affects technoprenurial intention, perceived feasibility affects technoprenurial intention, and technoprenurial intention affects technopreneurial commitment.

关键词： Industries Soft sensors Education Entrepreneurship Predictive models Data collection Sampling methods Software reliability Intelligent systems Testing

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Villages Status Classification Analysis Involving K-Means Algorithm to Support Kementerian Desa Pembangunan Daerah Tertinggal dan Transmigrasi Work programs 1

Villages Status Classification Analysis Involving K-Means Al...

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1st International Conference on Advanced Information Scientific Development, ICAISD 2020

作者： Hasugian, Paska Marto Hutahaean, Harvei Desmon Sinaga, Bosker Sriadhi Silaban, Saranom Informatics Engineering Study Program STMIK Pelita Nusantara Computer Science and Informatics Education Study Program Faculty of Engineering Universitas Negeri Medan Medan20221 Indonesia

Data mining is a technique of extracting information that has not been known before in a collection of data in the database. Data mining has been applied in various fields that require extracting information, some of the work that can be generated with data mining is classification, prediction, and data grouping. In this study, an analysis of village data collection was carried out to explore the potential or knowledge of the data that has been presented with the main objective of producing a grouping of village status. To support clustering or grouping activities the K-means algorithm used with the general process is to carry out the modeling process without supervision and is one of the methods for grouping data with a system partition, with the principle of allocating each data to the centroid or the closest average, work steps conducted in support of this research is to collect data related to the analysis of data grouping and proceed with the calculation process in accordance with the work steps of the K-means algorithm, the amount of data used as a test of 303 villages scattered in the old Padang regency. The results of calculations by displaying a new group of Cluster 0 is occupied by 120 villages, cluster 1 with a total data of 123 villages, Cluster 2 with a total of 6 villages, cluster 3 with a total of 33 villages while cluster 4 with a total of 21. © 2020 Published under licence by IOP Publishing Ltd.

关键词： K-means clustering

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Classifying Tweet Sentiment Analysis on Airlines using Random Forest Classifier, Naïve Bayes Classifier and K-Nearest Neighbors Classifier Algorithm

Classifying Tweet Sentiment Analysis on Airlines using Rando...

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Artificial Intelligence Robotics, Signal and Image Processing (AIRoSIP), International Conference on

作者： Ivan Alexander Yaya Heryadi Lukas Wayan Suparta Ilvico Sonata Computer Science Departement Binus Graduate Program Computer Science Bina Nusantara University Jakarta Indonesia Cognitive Engineering Research Group Faculty of Engineering Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Yogyakarta Indonesia

ISBN: (数字)9798350327472

ISBN: (纸本)9798350327489

Opinion has always affected businesses and individuals especially from the Public. People react through social media and spread it incompletely. The situation was then accepted as public opinion. There are three categories of opinion i.e., positive, negative, and neutral. To investigate public opinion on a particular issue of interest, sentiment analysis might be employed. By offering a solution to the text classification challenge, this experiment focuses on the perception of airline tweets among the American public. We offer a method to classify tweets as positive, negative, or neutral using three machine learning classifiers: Random Forest Classifier, Naive Bayes Classifier, and K-Nearest Neighbors Classifier. We examined the performance of three machine learning classifiers in terms of accuracy, average precision, average recall, and average f-1 score. The results demonstrate that the Random Forest Classifier, which produces 82% accuracy, 80% average precision, 82% average recall, and 80% average f1-score, performs the best among the machine learning classifiers.

关键词： Training Sentiment analysis Accuracy Social networking (online) Text categorization Nearest neighbor methods Naive Bayes methods Random forests Robots Airline industry

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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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Assessment of road traffic performance of the Tsunami evacuation road in Padang Municipality area based on the traffic volume simulation approach 4

Assessment of road traffic performance of the Tsunami evacua...

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4th International Conference on Earthquake engineering and Disaster Mitigation, ICEEDM 2019

作者： Yossyafra, Yossyafra Fitri, Nurhuda Sidhi, Rahmat Punama Yosritzal, Yosritzal Mazni, Deni Irda Civil Engineering Department Faculty of Engineering Universitas Andalas Indonesia Civil Engineering Study Program Universitas Dharma Andalas Indonesia

There are many cities on the west coast of the Sumatra, which are at high risk of the Tsunami disaster. Regional Regulations on Regional Spatial Planning for each City/Regency have compiled disaster mitigation by constructing several evacuation roads. This study wants to illustrate: what are the volume of traffic generation and road performance, if there is a Tsunami disaster. The simulation is developed by predicting traffic volume based on parameters, population density, vehicle ownership, land use, and activities in the area around the road. The assessment was carried out on two tsunami evacuation roads in the city of Padang, West Sumatra Province. The results show that the highest traffic volume occurred in the period from 06.30 a.m until 3:00 p.m., during school activities. One of the roads will not be able to accommodate the volume of traffic during a disaster, due to significant traffic congestion. This study shows that: (1) the period of activity and land use are two main parameters, which must be considered in designing tsunami evacuation roads, (2) The degree of saturation ratio and the ratio between the capacity of sections of Tsunami evacuation routes can be proposed as a parameter for assessing the performance of Tsunami evacuation roads in urban areas. © 2020 The Authors, published by EDP Sciences.

关键词： Tsunamis

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