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Implementation of Various Artificial Intelligence Approach for Prediction and Recommendation of Personality Disorder Patient

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Journal of Physics: Conference Series 2021年第1期1751卷

作者： H Sulistiani K Muludi A Syarif Doctoral Program of Mathematics and Natural Sciences Faculty University of Lampung Jl. Sumantri Brojonegoro No. 1 Bandar Lampung Indonesia. Faculty of Engineering and Computer Science Universitas Teknokrat Indonesia Jl. ZA. Pagaralam No. 9-11 Bandar Lampung Indonesia. Department of Computer Science Faculty of Mathematics and Science University of Lampung Jl. Sumantri Brojonegoro No. 1 Bandar Lampung Indonesia.

Personality disorder is known as chronic psychological disorders. It is a serious problem of the individual character and behavior that affect work, family and social life of a person. In many cases, the possibility of people do not realize that they have a personality disorder as a way of thinking and behaving seems natural to the patient, and the patient may blame others. To diagnose a personality disorder early, it is necessary to develop a system that is able to predict personality disorders and recommendation type of therapy patients should undergo. Artificial Intelligence is a technique that is very popular today. Various kinds of approaches and algorithms can be applied in the world of health, such as expert systems, neural networks and fuzzy logic. The aim of this study is to assess the artificial intelligence approach in predicting and recommending the type of therapy for patients with personality disorders.

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The next cryptocurrency price movement prediction application uses patterned datasets

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AIP Conference Proceedings 2024年第1期3116卷

作者： Rizky Parlika Mustafid Basuki Rahmat Diponegoro University Information Systems Doctoral Study Program Graduate School 50241 Jl. Imam Bardjo SH Pleburan Semarang Indonesia University of Pembangunan Nasional “Veteran” Jawa Timur Department of Informaton Technology Faculty of Computer Science 60294 Rungkut Madya Gunung Anyar Surabaya Indonesia

Researchers and experts have developed various techniques, models, and methods to predict the price movements of cryptocurrencies, especially Bitcoin. However, among the many techniques studied in the literature, there is still a lack of focus on mining, creating, and developing datasets with specific patterns for predicting the next cryptocurrency price movement. This is an exciting reason to conduct further research. A web-based Patterned Dataset Application and a Telegram bot were constructed to address this issue. These tools read the price position of each cryptocurrency and predict the next price direction based on the last position indicated by the Patterned Dataset Application. The experiment’s results show that when the Patterned Dataset Application shows a diamond crash position, it is time to make a purchase; conversely, when it shows a diamond moon position, it is time to make a sale. It is hoped that by utilizing the Patterned Dataset Application, potential losses can be minimized, and there is more potential for profit in cryptocurrency trading. Even though the initial data source comes from Indonesia’s most prominent digital cryptocurrency trading market, according to coinmarketcap, namely Indodax, the results of this patterned dataset application can often describe the same cryptocurrency conditions globally. The novelty of this research is to produce a new way of predicting the next cryptocurrency price movement using patterned datasets. At the end of this paper, it will be proven that hypothesis 1 and hypothesis 2 on the results of the patterned dataset are true.

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Modelling and reducing fuel flow pulsation of a fuel-metering system during pump mode switching in a turbofan engine

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IOP Conference Series: Earth and Environmental science 2019年第5期240卷

作者： S Masuda F Shimizu M Fuchiwaki K Tanaka Control Systems Engineering Department Research & Engineering Division Aero Engines Space & Defense Business Area IHI Corporation 229 Tonogaya Mizuho-machi Nishitama-gun Tokyo 190-1297 Japan Department of Computer Science and Systems Engineering Doctoral Program Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology 680-4 kawazu Iizuka-shi Fukuoka 820-8502 Japan Department of Mechanical Information Science and Technology School of Computer Science and Systems Engineering Kyushu Institute of Technology 680-4 kawazu Iizuka-shi Fukuoka 820-8502 Japan

In this research, the transient characteristics of a new type fuel metering system for aircraft turbofan engines using two types of pumps, a gear pump and a centrifugal pump, were studied by modelling and simulation. This new fuel metering system is capable of hydraulically unloading the operating state of each pump by the pump mode switching mechanism within the permissible range of the pump rotation speed and the fuel flow rate and it is possible to reduce the fuel temperature rise due to the pressure loss in the circuit in the operation region of the entire fuel system. In addition to this, by using a small centrifugal pump that can realize high discharge flow rate, it is possible to reduce weight compared to the conventional fuel system. However, when the pump mode is switched, unexpected fluctuation in the fuel flow rate can occur when a large change in the inlet pressure of the system occurs, the pressure control unit cannot follow the change, and the transient phenomenon cannot be suppressed. At this time, the pressure waveform generated at the time of changing the pump mode includes a high frequency component such that the pressure control unit, which plays a role of keeping the metering valve differential pressure constant, cannot follow up. Therefore, in this paper, we focused on the frequency of the pressure change waveform when the pump mode was changed and studied the model of the fuel system inlet pressure in the gear pump mode. Based on that model, we propose a method to reduce the frequency characteristics of the pressure change occurring at the time of pump mode change.

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Implementation of Fuzzy-based Model for Prediction of Thalassemia Diseases

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Journal of Physics: Conference Series 2021年第1期1751卷

作者： E. R. Susanto A. Syarif K Muludi R. R. W. Perdani A. Wantoro Doctoral Program of Mathematics and Science Faculty Lampung University. Jl. Sumantri Brojonegoro No 1 Bandar Lampung Indonesia. Faculty of Engineering and Computer Science Universitas Teknokrat Indonesia. Jl. ZA. Pagaralam No.9-11 Bandar Lampung Indonesia. Department of Computer Science Faculty of Mathematics and Science University of Lampung. Jl. Sumantri Brojonegoro No 1 Bandar Lampung Indonesia. Faculty of Medical Science Lampung University. Jl. Sumantri Brojonegoro No 1 Bandar Lampung Indonesia

Thalassemia is known as one of the blood disorder diseases that is inherited by parents. There are several types of Thalassemia, namely as Thalassemia major, minor, and intermedia. Among them, Thalassemia major is the most dangerous and needs more attention. Generally, it can be detected since the child is one year old. Late detection of this disease can have adverse consequences and various complications. This study aims to develop a new model for the prediction of thalassemia for children. The model adopts a fuzzy-based rule. The novelty in this article is that our model has 4 outputs, namely thalassemia major, intermedia, minor and not thalassemia. In the previous article it only had 3 outputs. In this study, we intend to implement a model that we developed using a fuzzy-based approach to classify thalassemia diseases based on CBC data. This article describes how to build a model and implement it in software. We compare the test results with the opinion of pediatricians regarding thalassemia. The final results of testing 4 CBC data show that our proposed model has successfully identified the type of thalassemia.

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Implementation of Certainty Factor Method for Diagnoses of Photocopy Machine Damage

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Journal of Physics: Conference Series 2019年第1期1255卷

作者： Aditiya Pakpahan Jijon Raphita Sagala Rolly Yesputra Adyanata Lubis Herman Saputra Husain Hengki Tamando Sihotang Teknik Informatika STMIK Pelita Nusantara Medan Sumatera Utara Indonesia Sistem Komputer STMIK Royal Kisaran Sumatera Utara-Indonesia STKIP Rokania Pasir Pengaraian Riau Teknik Informatika STMIK Bumigora Mataram Doctoral Program Faculty of Computer Science and Information Technology Universitas Sumatera Utara Sumatera Utara Indonesia

Photocopying machines are machines that make paper copies of documents and other visual images quickly and cheaply. PT. TRITANU has a copy machine product, such as the Fotocpy Sharp machine Type B201D. The rapid development of photocopying technology at this time can be seen that adult photocopying machines are now not only operating copier but can scan, print, and even fax. The rapid development of photocopying technology does not necessarily provide complete convenience to users. This can be seen from the high cost of consultation in the event of damage to the photocopy machine, requiring time to check the damaged machine, and not to mention other procedures in the repair that exist at PT. TRANANU. So from to provide solutions to these problems, the researchers made an Expert System for Handling Print Results Problems on Sharp Photocopying Machines Type B201D Using the Certainty Factor Method. System testing shows that the system is able to diagnose damage to the B201D copy machine based on the symptoms in the printout, even though these symptoms contain uncertainty. The results of the diagnosis are accompanied by Certainty Factor values that indicate the level of truth, accuracy of possible damage to the B201D copy machine.

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Self-Awareness for Autonomous Systems

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PROCEEDINGS OF THE IEEE 2020年第7期108卷 971-975页

作者： Dutt, Nikil Regazzoni, Carlo S. Rinner, Bernhard Yao, Xin Nikil Dutt (Fellow IEEE) received the Ph.D. degree from the University of Illinois at Urbana–Champaign Champaign IL USA in 1989.""He is currently a Distinguished Professor of computer science (CS) cognitive sciences and electrical engineering and computer sciences (EECS) with the University of California at Irvine Irvine CA USA. He is a coauthor of seven books. His research interests include embedded systems electronic design automation (EDA) computer architecture distributed systems healthcare Internet of Things (IoT) and brain-inspired architectures and computing.""Dr. Dutt is a Fellow of ACM. He was a recipient of the IFIP Silver Core Award. He has received numerous best paper awards. He serves as the Steering Committee Chair of the IEEE/ACM Embedded Systems Week (ESWEEK). He is also on the steering organizing and program committees of several premier EDA and embedded system design conferences and workshops. He has served on the Editorial Boards for the IEEE Transactions on Very Large Scale Integration (VLSI) Systems and the ACM Transactions on Embedded Computing Systems and also previously served as the Editor-in-Chief (EiC) for the ACM Transactions on Design Automation of Electronic Systems. He served on the Advisory Boards of the IEEE Embedded Systems Letters the ACM Special Interest Group on Embedded Systems the ACM Special Interest Group on Design Automationt and the ACM Transactions on Embedded Computing Systems. Carlo S. Regazzoni (Senior Member IEEE) received the M.S. and Ph.D. degrees in electronic and telecommunications engineering from the University of Genoa Genoa Italy in 1987 and 1992 respectively.""He is currently a Full Professor of cognitive telecommunications systems with the Department of Electrical Electronics and Telecommunication Engineering and Naval Architecture (DITEN) University of Genoa and a Co-Ordinator of the Joint Doctorate on Interactive and Cognitive Environments (JDICE) international Ph.D. course started initially as EU Erasmus Mundus Project and

Autonomous systems are able to make decisions and potentially take actions without direct human intervention, which requires some knowledge about the system and its environment as well as goal-oriented reasoning. In computer systems, one can derive such behavior from the concept of a rational agent with autonomy (“control over its own actions”), reactivity (“react to events from the environment”), proactivity (“act on its own initiative”), and sociality (“interact with other agents”) as fundamental properties \n[1]\n. Autonomous systems will undoubtedly pervade into our everyday lives, and we will find them in a variety of domains and applications including robotics, transportation, health care, communications, and entertainment to name a few. \nThe articles in this month’s special issue cover concepts and fundamentals, architectures and techniques, and applications and case studies in the exciting area of self-awareness in autonomous systems.

关键词： Special issues and sections Autonomous systems Self-aware Robot sensing systems Computational modeling

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The rain water management model on an appropriate hilly area to fulfil the needs of cocoa farm during dry season

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IOP Conference Series: Earth and Environmental science 2018年第1期157卷

作者： M Hasbi R Darma M Yamin M Nurdin M Rizal Department of Computer Science Mathematics Hasanuddin University Jalan Perintis Kemerdekaan KM 10 Makassar 90245 Indonesia. Doctoral Program Department of Agricultural Hasanuddin University Jalan Perintis Kemerdekaan KM 10 Makassar 90245 Indonesia. Department of Agicultural Socio-economics Hasanuddin University Jalan Perintis Kemerdekaan KM 10 Makassar 90245 Indonesia.

Cocoa is an important commodity because 90% farmers involved, easily marketed, and potentially harvested along the year. However, cocoa productivity tended to decrease by an average of only 300 kg hectare-1 year-1 or away from the potential productivity of two tons. Water management was an alternative method to increase its productivity by harvesting rainwater on the hilly cocoa farm area and distributing the water based on the gravity law. The research objective was to describes how to manage rainwater at the hilly cocoa farm area, so that the water needs of cocoa farm were met during the dry season. The important implication of the management was the water availability that supports the cocoa cultivation during the year. This research used qualitative method with descriptive approach to explain the appropriate technical specification of infrastructure to support the rainwater management. This research generated several mathematical formulas to support rainwater management infrastructure. The implementation of an appropriate rainwater utilization management for cocoa farm will ensuring the availability of water during dry season, so the cocoa farm allowed to produce cacao fruit during the year.

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Life cycle assessment and leather production

Collagen and Leather

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Collagen and Leather 2021年第1期 39-51页

作者： Diego Navarro Jianhui Wu Wei Lin Pere Fullana-i-Palmer Rita Puig Environmental Engineering doctoral program Universitat Politècnica de Catalunya (UPC) Curtidos Badia SAU Department of Biomass and Leather Engineering Key Laboratory of Leather Chemistry and Engineering of Ministry of EducationSichuan University UNESCO Chair in Life Cycle and Climate Change ESCI-UPF Pompeu Fabra University Department of Computer Science and Industrial Engineering Universitat de Lleida (UdL)

Leather industry is facing new trends on production and consumption patterns due to society *** economy is proposing a transition from the current economic model to a more sustainable one,in which waste is designed out and resources will be reused and recycled as long as *** this transition,Life Cycle Assessment(LCA) is an important tool to help *** the present review,39 English-written peer-reviewed papers related to LCA and leather have been found,30 of which were published in the last 6 years,meaning LCA is nowadays an important *** are presented within 4 types,focused on:1) the whole leather production process,2) a single step in the production process(e.g,new technologies for unhairing),3) waste treatment and recycling,and 4) life cycle thinking with ideas on long-term strategies for leather *** discussed in the literature review,leather industry has important challenges to address:increasing sustainability and transparency on the supply chain,and strengthening the beauty of *** up these challenges from a life cycle perspective will help leather industry flourish in the coming future.

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Perceptron Partition Model to Minimize Input Matrix

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IOP Conference Series: Materials science and Engineering 2019年第1期536卷

作者： Zulfian Azmi Mahyuddin K.M. Nasution Muhammad. Zarlis Herman Mawengkang Syahril Efendi Postgraduate Doctoral of Computer Science Universitas Sumatera Utara Padang Bulan USU Medan 20155 Indonesia. Information Technology Department Universitas Sumatera Utara Padang Bulan USU Medan 20155 Indonesia. Program Pasca Sarjana Doktoral Ilmu Komputer Universitas Sumatera Utara Indonesia. Department of Mathematics Universitas Sumatera Utara Padang BulanUSU Medan20155 Indonesia.

Implementation of Neuron Network model using Perceptron has not given optimal result in real time learning. The large number of inputs expressed in matrix form makes the process slower in pattern recognition. So, it takes characteristic to represent all the input matrices by using the partition method. By partitioning each input and with the best weight and using the activation function will produce an output value. And learning is valid in recognizing patterns only 1 iteration only. Further validation is done on the water mill control module with dissolved oxygen input, water pH, salinity and water temperature. With Perceptron Partition learning algorithm more real-time than perceptron model. Testing on the waterwheel input whether rotating or stopping by Matrix Laboratory software simulation.

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Treatment Algorithm for the Resorption of Calcific Tendinitis Using Extracorporeal Shockwave Therapy: A Data Mining Study

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Orthopaedic Journal of Sports Medicine 2024年第3期12卷 23259671241231609页

作者： Chou, Wen-Yi Cheng, Jai-Hong Lien, Yu-Jui Huang, Tian-Hsiang Ho, Wen-Hsien Chou, Paul Pei-Hsi Doctoral Degree Program in Biomedical Engineering College of Medicine Kaohsiung Medical University Kaohsiung Taiwan Department of Orthopedic Surgery Kaohsiung Chang Gung Memorial Hospital Chang Gung University College of Medicine Kaohsiung Taiwan Department of Leisure and Sport Management Cheng Shiu University Kaohsiung Taiwan Center for Shockwave Medicine and Tissue Engineering Department of Medical Research Kaohsiung Chang Gung Memorial Hospital Chang Gung University College of Medicine Kaohsiung Taiwan Department of Healthcare Administration and Medical Informatics Kaohsiung Medical University Kaohsiung Taiwan Department of Computer Science and Information Engineering National Penghu University of Science and Technology Penghu Taiwan College of Professional Studies National Pingtung University of Science and Technology Pingtung Taiwan Department of Sports Medicine College of Medicine Kaohsiung Medical University Kaohsiung Taiwan Division of Sports Medicine Department of Orthopaedic Surgery Kaohsiung Medical University Hospital Kaohsiung Taiwan Department of Orthopaedics School of Medicine College of Medicine Kaohsiung Medical University Kaohsiung Taiwan Department of Orthopaedic Surgery Kaohsiung Municipal Hsiao-Kang Hospital Kaohsiung Taiwan

Background: Although evidence indicates that extracorporeal shockwave therapy (ESWT) is effective in treating calcifying shoulder tendinitis, incomplete resorption and dissatisfactory results are still reported in many cases. Data mining techniques have been applied in health care in the past decade to predict outcomes of disease and treatment. Purpose: To identify the ideal data mining technique for the prediction of ESWT-induced shoulder calcification resorption and the most accurate algorithm for use in the clinical setting. Study Design: Case-control study. Methods: Patients with painful calcified shoulder tendinitis treated by ESWT were enrolled. Seven clinical factors related to shoulder calcification were adopted as the input attributes: sex, age, side affected, symptom duration, pretreatment Constant-Murley score, and calcification size and type. The 5 data mining techniques assessed were multilayer perceptron (neural network), naïve Bayes, sequential minimal optimization, logistic regression, and the J48 decision tree classifier. Results: A total of 248 patients with calcified shoulder tendinitis were enrolled in this study. Shorter symptom duration yielded the highest gain ratio (0.374), followed by smaller calcification size (0.336) and calcification type (0.253). With the J48 decision tree method, the accuracy of 3 input attributes was 89.5% by 10-fold cross-validation, indicating satisfactory accuracy. A treatment algorithm using the J48 decision tree indicated that a symptom duration of ≤10 months was the most positive indicator of calcification resorption, followed by a calcification size of ≤10.82 mm. Conclusion: The J48 decision tree method demonstrated the highest precision and accuracy in the prediction of shoulder calcification resorption by ESWT. A symptom duration of ≤10 months or calcification size of ≤10.82 mm represented the clinical scenarios most likely to show resorption after ESWT. © The Author(s) 2024.

关键词： calcific tendinitis data mining extracorporeal shockwave therapy J48 decision tree shoulder

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