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Air Particulate Matters Auto-Rule-Based Labeling to Support Long-Distance Run Environment Data Classification 13

Air Particulate Matters Auto-Rule-Based Labeling to Support ...

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13th IEEE Symposium on computer Applications and Industrial Electronics, ISCAIE 2023

作者： Wandy, Wandy Adi, Kusworo Ayu, Media Anugerah Diponegoro University Doctoral Program of Information Systems School of Postgraduate Studies Semarang Indonesia Diponegoro University Faculty of Science and Mathematics Department of Physics Semarang Indonesia Sampoerna University Faculty of Engineering and Technology Department of Computer Science South Jakarta Indonesia

ISBN: (纸本)9798350347319

Sports science is an interdisciplinary and multidisciplinary science that strives to increase athletic performance and endurance. Sport science recognizes and prevents injuries. Sensors and statistics formalize Sports science. Runners need coaches and teams to support them before, during, and after the run race. Coaches generate running training plans to boost performance. Running race performances may be impacted by air pollution exposure while training, so coaches should consider limiting air pollution exposure when training. One of the external factors is Particulate Matter (PM2.5 and PM10). Sensors connecting to the Internet can record external factors and produce csv data. The foundation of supervised machine learning is the labeling process. Labeling a set of data is one of the laborious and time-consuming phases in every machine-learning application because it requires verifying the accuracy of the labels and making any necessary revisions. This research aimed to find a solution to automatically label numerous air particulate matter raw data using a rule based on parameters to reduce manual work, human errors and faster processes. This labeled data will later be used for supervised machine learning classification to support the coach in generating training programs for the runners in a Sports information System. Based on Indonesia Air Quality index rule-based approach, labeled text data in csv has been generated and tested with PM2.5 and PM10 parameters in three scenarios with a 100% success rate. It was possible to automate the labeling process, and it explained how automation results in fast and accurate results. © 2023 IEEE.

关键词： Classification (of information)

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Dental Disease Detection based on CNN for Panoramic Dental Radiographs 11

Dental Disease Detection based on CNN for Panoramic Dental R...

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11th IEEE International Conference on Intelligent Computing and information systems, ICICIS 2023

作者： El Bagoury, Manar Al-Shetairy, Mirna Ahmed, Omar Mehanny, Samah S Hamdy, Tassneem Omar, Gihan Akram, Marwan Mohamed, Rana Amr, Hebatullah Gad, Walaa Ain Shams University Faculty of Computer and Information Sciences Bioinformatics Program Cairo Egypt Ain Shams University Faculty of Computer and Information Sciences Computer Science Department Cairo Egypt Faculty of Dentistry Cairo and Galala Universities Oral Biology Department Cairo Egypt Cairo University Faculty of Dentistry Oral and Maxillofacial Radiology Department Cairo Egypt Future University in Egypt Faculty of Oral and Dental Medicine Oral Radiology Department Cairo Egypt Ain Shams University Faculty of Computer and Information Sciences Information Systems Department Cairo Egypt

ISBN: (纸本)9798350322101

Panoramic dental radiography is one of the examination tools frequently performed in dental clinics and hospitals as it captures a wide range of the dental region and its surroundings, but due to the complex structure of the dental area and lack of time, dentists focus on tiny parts of the images. With the help of Machine Learning, dentists can detect dental defects and anomalies faster and more accurately. In this study, a data set of 733 panoramic radiographs of adult patients was collected from the faculty of Oral and Dental Medicine, Future University, Egypt. Using a combination of pre-trained CNN architecture and a finetuned network, the collected panoramic radiographs were used to determine the optimal architecture. The purpose of this research was to develop a computer-aided detection system based on a finetuned CNN algorithm, and to evaluate the accuracy and usefulness of this system for the detection of proximal and occlusal caries, interdental and inter radicular alveolar bone loss, periapical lesions, and impacted teeth in panoramic radiographs. Different object detection models were tested to detect selected dental diseases that were found in the panoramic radiographs, and after a few experiments, the YOLOv5 architecture was proved to be the most optimal after achieving 0.61 mAP@0.5 and 0.28 mAP@ [0.5-0.95] for the total six classes. This is the best-achieved results to our knowledge. © 2023 IEEE.

关键词： Object detection

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Convolutional Neural Network Analysis on Handwriting Patterns and Its Relationship to Personality: A Systematical Review

Convolutional Neural Network Analysis on Handwriting Pattern...

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International Conference on Informatics, Multimedia, Cyber and information System (ICIMCIS)

作者： Zaid Romegar Mair Widya Cholil Evi Yulianti Dona Marcelina Theresiawati Ika Nurlaili Isnainiyah Informatics Study Program Computer and Natural Science Faculty Indo Global Mandiri University Indonesia Informatics Study Program Computer Science Faculty Universitas Pembangunan Nasional Jakarta Indonesia Information System Study Program Computer and Natural Science Faculty Indo Global Mandiri University Indonesia

It can be argued that the Convolutional Neural Network (CNN) used in this research is an efficient algorithm for classifying images based on the end prediction of the path taken. In every plot that is made, there is a similar process for achieving a prediction of the final result. The implementation for each of these procedures follows the steps that are summarized into a flow of analysis stages that can help to develop the application of an algorithm. The initial stage is to take the handwriting from the user which is then pre-processed the image, to eliminate existing noise, and sharpen the contrast, so that the image can be seen clearly. Images will be processed and analyzed using the Convolutional Neural Network model, training will be carried out, with an average training of a dataset of 100 epochs or about 7 to 10 minutes, and labeling on the trained dataset. The accuracy of the training reached 98.89%, as a proportion of the different characteristics of the handwriting sample.

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The Analysis of Online Order Mobile Application Using User Experience Questionnaire (A Case study Approach) 7

The Analysis of Online Order Mobile Application Using User E...

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7th International Conference on information Management and Technology, ICIMTech 2022

作者： Hartono, Sugiarto Shahudin, Faizah Widagdo, Hermawan Honggo Hendrawan, Tommy School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia School of Economics and Management Xiamen University Malaysia Selangor Malaysia Faculty of Science & Technology Information System Study Program Universitas Nasional Karangturi Semarang50227 Indonesia PT. Elgibor Solusi Digital Semarang50167 Indonesia

ISBN: (数字)9781665450904

ISBN: (纸本)9781665450904

ABC Application is owned by ABC Company which already has branches of more than 100 stores in 7 countries where Indonesia is one of the branches with 79 stores spread across several cities, especially Jabodetabek area. ABC has launched an application that has been operating for more than a year;because the ABC application is new to the food and beverage sector, the application has received several positive and negative responses from its users especially on its user experience. Based on this background, this research will more focus on user experience of ABC Application. ABC Application can find out the assessment of user experience and improve the results of any negative responses in the form of criticism or suggestions from users. The method used in this research is the User Experience Questionnaire (UEQ). From the research results that have been carried out, the novelty scale is the scale with the lowest attachment of all respondents. Therefore, improving and developing the ABC application through this scale is necessary. © 2022 IEEE.

关键词： Surveys

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Rapid modeling and analysis with QGENIE

Rapid modeling and analysis with QGENIE

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International Multiconference on computer science and information Technology, IMCSIT '09

作者： Druzdzel, Marek J. Decision Systems Laboratory School of Information Sciences and Intelligent Systems Program University of Pittsburgh Pittsburgh PA 15260 United States Faculty of Computer Science Bialystok Technical University Wiejska 45A 15-351 Bialystok Poland

ISBN: (纸本)9781424453146

QGENIE is a specialized interface to GENIE, a decision modeling environment developed by the Decision systems Laboratory, University of Pittsburgh. QGENIE allows for rapid construction of graphical models in which all variables are propositional, almost no numerical probabilities are displayed at the user interface, and degrees of truth of propositions are displayed by means of node colors. All numerical parameters, such as prior probability distributions over variables and strengths of influences between variables, are entered by means of graphical sliders. While the underlying computations are all numerical and based on Bayesian updating, QGENIE makes the impression of a qualitative, "order of magnitude" type system that aids rapid model building and an approximate analysis of systems. © 2009 IEEE.

关键词： Probability distributions

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An empirical evaluation of costs and benefits of simplifying Bayesian networks by removing weak arcs 27

An empirical evaluation of costs and benefits of simplifying...

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27th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2014

作者： Ratnapinda, Parot Druzdzel, Marek J. Decision Systems Laboratory School of Information Sciences and Intelligent Systems Program University of Pittsburgh PittsburghPA15260 United States Faculty of Computer Science Bialystok University of Technology Wiejska 45A Bialystok15-351 Poland

We report the results of an empirical evaluation of structural simplification of Bayesian networks by removing weak arcs. We conduct a series of experiments on six networks built from real data sets selected from the UC Irvine Machine Learning Repository. We systematically remove arcs from the weakest to the strongest, relying on four measures of arc strength, and measure the classification accuracy of the resulting simplified models. Our results show that removing up to roughly 20 percent of the weakest arcs in a network has minimal effect on its classification accuracy. At the same time, structural simplification of networks leads to significant reduction of both the amount of memory taken by the clique tree and the amount of computation needed to perform inference. Copyright © 2014, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Bayesian networks

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Insensitivity of constraint-based causal discovery algorithms to violations of the assumption of multivariate normality

Insensitivity of constraint-based causal discovery algorithm...

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21th International Florida Artificial Intelligence Research Society Conference, FLAIRS-21

作者： Voortman, Mark Druzdzel, Marek J. Decision Systems Laboratory School of Information Sciences and Intelligent Systems Program University of Pittsburgh Pittsburgh PA 15260 United States Faculty of Computer Science Bialystok Technical University Wiejska 45A 15-351 Bialystok Poland

ISBN: (纸本)9781577353652

Constraint-based causal discovery algorithms, such as the PC algorithm, rely on conditional independence tests and are otherwise independent of the actual distribution of the data. In case of continuous variables, the most popular conditional independence test used in practice is the partial correlation test, applicable to variables that are multivariate Normal. Many researchers assume multivariate Normal distributions when dealing with continuous variables, based on a common wisdom that minor departures from multivariate Normality do not have a too strong effect on the reliability of partial correlation tests. We subject this common wisdom to a test in the context of causal discovery and show that partial correlation tests are indeed quite insensitive to departures from multivariate Normality. They, therefore, provide conditional independence tests that are applicable to a wide range of multivariate continuous distributions. Copyright © 2008, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Normal distribution

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Does query-based diagnostics work?

Does query-based diagnostics work?

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8th Bayesian Modeling ApplicationsWorkshop, BMAW 2011

作者： Ratnapinda, Parot Druzdzel, Marek J. Decision Systems Laboratory School of Information Sciences and Intelligent Systems Program University of Pittsburgh Pittsburgh PA 15260 United States Faculty of Computer Science Bialystok University of Technology Wiejska 45A 15-351 Bialystok Poland

Query-based diagnostics (Agosta, Gardos, & Druzdzel, 2008) offers passive, incremental construction of diagnostic models that rest on the interaction between a diagnostician and a computer-based diagnostic system. Effectively, this approach minimizes knowledge engineering, the main bottleneck in practical application of Bayesian networks. While this idea is appealing, it has undergone only limited testing in practice. We describe a series of experiments that subject a prototype implementing passive, incremental model construction to a rigorous practical test. We show that the prototype's diagnostic accuracy reaches reasonable levels after merely tens of cases and continues to increase with the number of cases, comparing favorably to state of the art approaches based on learning.

关键词： Bayesian networks

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Mobile Application Implementation as Agriculture 4.0 Strategy for Sugarcane Yield Prediction 9

Mobile Application Implementation as Agriculture 4.0 Strateg...

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9th International HCI and UX Conference in Indonesia, CHIuXiD 2023

作者： Mawandha, Hangger Gahara Rahutomo, Reza Suparyanto, Teddy Pardamean, Bens Institut Pertanian Stiper Faculty of Agricultural Technology Yogyakarta55282 Indonesia Bina Nusantara University School of Information Systems Information Systems Department Jakarta 11480 Indonesia Bina Nusantara University Bioinformatics and Data Science Research Center Jakarta 11480 Indonesia Bina Nusantara University Binus Graduate Program - Master of Computer Science Computer Science Department Jakarta 11480 Indonesia

ISBN: (纸本)9798350304084

information engineering strategies play a significant and transformative role in shaping the landscape of digital agriculture. It drives innovation and efficiency in modern farming practices, with a specific focus on enhancing the value of agricultural commodities, such as sugarcane. The application of mobile technology plays a crucial part in achieving increased sugarcane productivity. Mobile applications, equipped with advanced developer features, offer rapid and user-friendly access to vital information. Traditional methods of estimating sugarcane production relied on manual data recording on paper, followed by data transfer to computer systems, typically managed by sugar factory junior plant officers. This conventional approach presents several inherent weaknesses, including time and effort intensiveness during data recording and entry. Additionally, the potential for errors in calculation and data input is a concern. The storage capacity for paper-based documents is finite, and farmers are often unable to autonomously assess their production potential. The objective of this research is to confront these obstacles by creating a sugarcane production application for Android. This application functions as an information engineering approach focused on forecasting sugarcane yields for plantation owners and their assistants. The development procedure adhered to the systematic waterfall method, following the principles of the Software Development Life Cycle (SDLC) model. Data collection was carried out through observations, while interviews with junior plant officers provided valuable insights into sugarcane estimation techniques. Analysis involved the synthesis of observational and interview data to inform the design of the application's interface and algorithmic system. The resulting application significantly simplifies the process of estimating production potential for farmers, enabling them to access sugarcane productivity data during harvest. Consequently, sugar

关键词： Forecasting

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Procedural Low-Poly Buildings using L-System for Turn-based Tactic Game ***

Procedural Low-Poly Buildings using L-System for Turn-based ...

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International Seminar on Application for Technology of information and Communication (ISemantic)

作者： Augusta Steven Benedict Umi Rosyidah Ardiawan Bagus Harisa Hanny Haryanto Study Program in Information Engineering Faculty of Computer Science Universitas Dian Nuswantoro Semarang Indonesia

ISBN: (数字)9798350366648

ISBN: (纸本)9798350366655

One of the critical visual components in video game creation is 3D asset prototypes, which also require significant effort. A procedural model using the L-system method for making low-poly buildings can address this issue. This model produces low-poly buildings based on simple parameters input by the user. The model receives input in the form of axioms, which are then processed according to predetermined L-system rules. After the building is formed, it is saved as a prefab in Unity so that it can be reused and modified by the user. The proposed method is implemented to our turn-based tactic *** and provided as a Unity package (add-on). Experimental results show that the buildings generated by the model have a minimalistic yet functional benefits.

关键词： Seminars Visualization Video games Three-dimensional displays Shape Buildings Prototypes Games Rendering (computer graphics) Generators

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