Research Problem/Questions – Information extracted from the point cloud is used for robotic vision, mobility, navigation of unmanned vehicles, security, inspection, planning and many more. Three-dimensional modelling is performed by collecting very
{"title":"Akıllı Şehirlerde 3B Nokta Bulutu ile Digital Çözümler","authors":"Cihan Altuntaş","doi":"10.36287/ijmsit.6.2.208","DOIUrl":"https://doi.org/10.36287/ijmsit.6.2.208","url":null,"abstract":"Research Problem/Questions – Information extracted from the point cloud is used for robotic vision, mobility, navigation of unmanned vehicles, security, inspection, planning and many more. Three-dimensional modelling is performed by collecting very","PeriodicalId":166049,"journal":{"name":"International Journal of Multidisciplinary Studies and Innovative Technologies","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129813307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
– Industrial systems have experienced four major revolutions from the past to the present. In light of these revolutions, mechanical systems have replaced human power for the first time. Over time, starting from the steam in mechanical systems, a mass production system has been started, which has reached the present day with electrical energy. Automatic studies have been carried out using electronic relays and control units in systems that have emerged as the concept of automation. Today, controllers have begun to collect the data they receive from the system and need to enable the system to run a process without the need for a human. Thanks to these developments, the importance of collecting and processing data in production facilities are increasing day by day. In line with these collected data, many improvements and reports can be made in production with the support of artificial intelligence. Within the scope of this study, it is aimed to transfer the data obtained from the vulcanization presses in the facility or on the site to the ERP (Enterprise Resource Planning) system. It is aimed to provide faster and ubiquitous access to the requested data by selecting cloud ERP, not physical ERP, as the source of the ERP system. The data are processed primarily in PLCs (Programmable Logic Controller) located over the presses. The processed data is recorded by connecting to a database through the KEPServerEX program based on the OPC (Open Communication Platform). The Node-RED development tool is used for the connection of the database and cloud ERP system, as well as for urgent field maintenance and process preparation stages. Thanks to this program, it is easy to connect multiple applications that are different from each other. Thanks to a node located in the system, the data determined can be sent to authorized persons via e-mail or SMS notification. In this way, the user is notified quickly to prepare the production line for the anomalies that occur or for the different product types in the queue. In line with the collected data, failures that may occur in the future can be prevented, maintenance periods can be deducted with predictive maintenance and other problems that may occur can be prevented. Out of this, production capacity can be determined, the working performances of the working operators can be deduced and planning works can be carried out healthily.
——工业体系从古至今经历了四次大变革。鉴于这些革命，机械系统第一次取代了人力。随着时间的推移，从机械系统中的蒸汽开始，一个大规模的生产系统已经开始，它已经发展到今天的电能。自动化研究已在系统中使用电子继电器和控制单元进行，这些系统已作为自动化概念出现。今天，控制器已经开始收集他们从系统接收到的数据，并且需要使系统能够在不需要人工的情况下运行一个过程。由于这些发展，在生产设施中收集和处理数据的重要性日益增加。根据这些收集到的数据，在人工智能的支持下，可以在生产中进行许多改进和报告。在这项研究的范围内，其目的是将从设施或现场的硫化压力机获得的数据转移到ERP(企业资源规划)系统。它的目的是通过选择云ERP而不是物理ERP作为ERP系统的来源，提供对所请求数据的更快和无处不在的访问。数据主要在位于压力机上的plc(可编程逻辑控制器)中处理。处理后的数据通过基于OPC (Open Communication Platform)的KEPServerEX程序连接到数据库进行记录。Node-RED开发工具用于数据库与云ERP系统的连接，以及紧急现场维护和流程准备阶段。由于这个程序，它很容易连接多个应用程序，彼此不同。由于位于系统中的节点，确定的数据可以通过电子邮件或短信通知发送给授权人员。通过这种方式，可以快速通知用户，以便为发生的异常或队列中的不同产品类型准备生产线。根据收集到的数据，可以预防未来可能发生的故障，预测性维护可以减少维护周期，可以预防可能发生的其他问题。由此可以确定生产能力，推断作业人员的工作性能，健康地进行规划工作。
{"title":"TRANSFERRING VULCANIZING PRESS DATA TO THE ERP SYSTEM ON THE CLOUD","authors":"Elif Demir, B. Arifoğlu","doi":"10.36287/ijmsit.6.2.244","DOIUrl":"https://doi.org/10.36287/ijmsit.6.2.244","url":null,"abstract":"– Industrial systems have experienced four major revolutions from the past to the present. In light of these revolutions, mechanical systems have replaced human power for the first time. Over time, starting from the steam in mechanical systems, a mass production system has been started, which has reached the present day with electrical energy. Automatic studies have been carried out using electronic relays and control units in systems that have emerged as the concept of automation. Today, controllers have begun to collect the data they receive from the system and need to enable the system to run a process without the need for a human. Thanks to these developments, the importance of collecting and processing data in production facilities are increasing day by day. In line with these collected data, many improvements and reports can be made in production with the support of artificial intelligence. Within the scope of this study, it is aimed to transfer the data obtained from the vulcanization presses in the facility or on the site to the ERP (Enterprise Resource Planning) system. It is aimed to provide faster and ubiquitous access to the requested data by selecting cloud ERP, not physical ERP, as the source of the ERP system. The data are processed primarily in PLCs (Programmable Logic Controller) located over the presses. The processed data is recorded by connecting to a database through the KEPServerEX program based on the OPC (Open Communication Platform). The Node-RED development tool is used for the connection of the database and cloud ERP system, as well as for urgent field maintenance and process preparation stages. Thanks to this program, it is easy to connect multiple applications that are different from each other. Thanks to a node located in the system, the data determined can be sent to authorized persons via e-mail or SMS notification. In this way, the user is notified quickly to prepare the production line for the anomalies that occur or for the different product types in the queue. In line with the collected data, failures that may occur in the future can be prevented, maintenance periods can be deducted with predictive maintenance and other problems that may occur can be prevented. Out of this, production capacity can be determined, the working performances of the working operators can be deduced and planning works can be carried out healthily.","PeriodicalId":166049,"journal":{"name":"International Journal of Multidisciplinary Studies and Innovative Technologies","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128891065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Hava Lidar ve fotoğraflardan kentsel alanların digital ikizinin oluşturulması ve karşılaştırılması","authors":"Cihan Altuntaş","doi":"10.36287/ijmsit.7.1.15","DOIUrl":"https://doi.org/10.36287/ijmsit.7.1.15","url":null,"abstract":"","PeriodicalId":166049,"journal":{"name":"International Journal of Multidisciplinary Studies and Innovative Technologies","volume":"792 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117053059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
– Flooding is one of the most dangerous natural causes that inflict harm to both life and property on a yearly basis. Therefore, building a flood model for predicting the immersion zone in a watershed is critical for decision-makers. Floods are a perilous tragedy that annually threatens Iraq and the Middle East region, impacting millions of people. In this context, having suitable flood forecasting algorithms may help people by reducing property damage and saving lives by warning communities of potentially severe flooding events ahead of time. Data mining techniques such as artificial neural network (ANN) approaches have recently been applied to model floods. The purpose of this study is to develop a model that extrapolates the past into the future using existing statistical models and recurrent neural networks and is powered by rainfall forecasting data. We investigate a number of time series forecasting approaches, including Long Short-Term Memory (LSTM) Networks. The forecasting methods investigated are tested and implemented using rainfall data from the Mosul region of Iraq. In addition, in flood occurrences and conducting experiments to study the relationship between rainfall and floods.
{"title":"Flood Forecasting Using Neural Network: Applying The LSTM Network In The Mosul Region. Iraq","authors":"A. Ibrahim, Ayad Khalaf Jirri Halboosh","doi":"10.36287/ijmsit.6.1.113","DOIUrl":"https://doi.org/10.36287/ijmsit.6.1.113","url":null,"abstract":"– Flooding is one of the most dangerous natural causes that inflict harm to both life and property on a yearly basis. Therefore, building a flood model for predicting the immersion zone in a watershed is critical for decision-makers. Floods are a perilous tragedy that annually threatens Iraq and the Middle East region, impacting millions of people. In this context, having suitable flood forecasting algorithms may help people by reducing property damage and saving lives by warning communities of potentially severe flooding events ahead of time. Data mining techniques such as artificial neural network (ANN) approaches have recently been applied to model floods. The purpose of this study is to develop a model that extrapolates the past into the future using existing statistical models and recurrent neural networks and is powered by rainfall forecasting data. We investigate a number of time series forecasting approaches, including Long Short-Term Memory (LSTM) Networks. The forecasting methods investigated are tested and implemented using rainfall data from the Mosul region of Iraq. In addition, in flood occurrences and conducting experiments to study the relationship between rainfall and floods.","PeriodicalId":166049,"journal":{"name":"International Journal of Multidisciplinary Studies and Innovative Technologies","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131178017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Explaining a simple electronic circuit analysis with a voltage source, a resistor, cables and an ampermeter assembly to the students at a basic level. Today, we withness the fact that students are born into the age of technological devices such as computers, phones and tablets. We are concerned that kids who spend the majority of their daytime hours using these devices are wasting their important time. This study mostly based on using the Roblox platform as a response to the query, what modern and up-to-date tools can we use while teaching students not only for engineering education, but also mathematics, science (positive sciences such as physics, chemistry, biology, geography, geometry e.t.c.) or applied sciences to students. Today, developers can code their own game experiences in Lua language and publish them to the world using the widely known Roblox platform worldwide. Today, it seems possible to develop a game simulation experience with Roblox Studio based on engineering knowledge. In this study, Ohm's law, which is widely known in electricity, is taken as an example. A circuit simulation development study was conducted to perform a simple electrical circuit analysis by developing an exemplary experience (Game Experience) in the Roblox universe. What makes this approach interesting is to show the student that game development can be done with Roblox Studio instead of playing Roblox. This study's objective is to demonstrate the viability of giving the formulas that are frequently used in Engineering education as a game experience on the Roblox platform by using the Lua language. It was thought that the presentation of this study would be appropriate in order to perform three-dimensional simulation in the experience development environment offered by Roblox Studio of approaches in engineering.
{"title":"Roblox Studio İle Mühendislik Eğitimi İçin Deneyim Geliştirme","authors":"Onur Yolal","doi":"10.36287/ijmsit.6.1.51","DOIUrl":"https://doi.org/10.36287/ijmsit.6.1.51","url":null,"abstract":"Explaining a simple electronic circuit analysis with a voltage source, a resistor, cables and an ampermeter assembly to the students at a basic level. Today, we withness the fact that students are born into the age of technological devices such as computers, phones and tablets. We are concerned that kids who spend the majority of their daytime hours using these devices are wasting their important time. This study mostly based on using the Roblox platform as a response to the query, what modern and up-to-date tools can we use while teaching students not only for engineering education, but also mathematics, science (positive sciences such as physics, chemistry, biology, geography, geometry e.t.c.) or applied sciences to students. Today, developers can code their own game experiences in Lua language and publish them to the world using the widely known Roblox platform worldwide. Today, it seems possible to develop a game simulation experience with Roblox Studio based on engineering knowledge. In this study, Ohm's law, which is widely known in electricity, is taken as an example. A circuit simulation development study was conducted to perform a simple electrical circuit analysis by developing an exemplary experience (Game Experience) in the Roblox universe. What makes this approach interesting is to show the student that game development can be done with Roblox Studio instead of playing Roblox. This study's objective is to demonstrate the viability of giving the formulas that are frequently used in Engineering education as a game experience on the Roblox platform by using the Lua language. It was thought that the presentation of this study would be appropriate in order to perform three-dimensional simulation in the experience development environment offered by Roblox Studio of approaches in engineering.","PeriodicalId":166049,"journal":{"name":"International Journal of Multidisciplinary Studies and Innovative Technologies","volume":"272 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123303337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
– The article aims to develop a methodology for quantitative assessment and forecasting of the quality of decision-making in organizational and technical systems under the conditions of uncertainty of control agents. A stochastic model for predicting the reliability of control results and decision-making risks under the uncertainty of model agents was developed. The paper proposes a method for aggregating system structural uncertainties of the control and measurement process on the example of robust multi-aspect. The proposed mathematical application implements a multi-agent approach to solving the general problem of evaluating the robustness of control according to the criteria of «producer risk» and «consumer risk». For the purposes of modeling, such branches of mathematics and methods as probability theory and mathematical statistics, regression and correlation analysis, expert evaluation methods, simulation and structural-functional modeling, and agent-based approach are used. A probabilistic model has been developed to assess and predict the reliability of control and decision-making risks under the uncertainty of system agents. The novelty of the proposed model consists in taking into account the statistical nature of normative values. The proposed mathematical application implements a dual method for solving the general problem of assessing the quality of the control process by the magnitude of risks in the decision-making system. In the first case, the problem of quantitative risk assessment is solved for given statistical characteristics of control agents, and in the second case, the necessary measurement accuracy is determined for given uncertainties and risk levels in the control system
{"title":"STOCHASTIC PROGRAMMABLE PARADIGM OF QUALITY CONTROL MANAGEMENT IN MULTI-AGENT SYSTEMS","authors":"K. Alibekkyzy","doi":"10.36287/ijmsit.6.2.157","DOIUrl":"https://doi.org/10.36287/ijmsit.6.2.157","url":null,"abstract":"– The article aims to develop a methodology for quantitative assessment and forecasting of the quality of decision-making in organizational and technical systems under the conditions of uncertainty of control agents. A stochastic model for predicting the reliability of control results and decision-making risks under the uncertainty of model agents was developed. The paper proposes a method for aggregating system structural uncertainties of the control and measurement process on the example of robust multi-aspect. The proposed mathematical application implements a multi-agent approach to solving the general problem of evaluating the robustness of control according to the criteria of «producer risk» and «consumer risk». For the purposes of modeling, such branches of mathematics and methods as probability theory and mathematical statistics, regression and correlation analysis, expert evaluation methods, simulation and structural-functional modeling, and agent-based approach are used. A probabilistic model has been developed to assess and predict the reliability of control and decision-making risks under the uncertainty of system agents. The novelty of the proposed model consists in taking into account the statistical nature of normative values. The proposed mathematical application implements a dual method for solving the general problem of assessing the quality of the control process by the magnitude of risks in the decision-making system. In the first case, the problem of quantitative risk assessment is solved for given statistical characteristics of control agents, and in the second case, the necessary measurement accuracy is determined for given uncertainties and risk levels in the control system","PeriodicalId":166049,"journal":{"name":"International Journal of Multidisciplinary Studies and Innovative Technologies","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121173185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
– Sign language is one of the ways of communication that is used by people who are unable to speak or hear (deaf and mute), so not all people are able to understand this language. Therefore, to facilitate communication between normal people and deaf and mute people, many systems have been invented that translate gestures and signs within sign language into words to be understandable. The aim behind this research is to train a model to be able to detect and recognize hand gestures and signs and then translate them into letters, numbers and words using You Only Look One (YOLO) method through pictures or videos, even in real time. YOLO is one of the methods used in detecting and recognizing things that depend in their work on convolutional neural networks (CNN), which are characterized by accuracy and speed in work. In this research, we have created a data set consisting of 8000 images divided into 40 classes, for each class, 200 images were taken with different backgrounds and under lighting conditions, which allows the model to be able to differentiate the signal regardless of the intensity of the lighting or the clarity of the image. And after training the model on the dataset many times, in the experiment using image data we got a very good results in terms of MAP = 98.01% as an accuracy and current average loss=1.3 and recall=0.96 and F1=0.96, and for video results it has the same accuracy and 28.9 frame per second (fps).
手语是不能说话或听不见(聋哑人)的人使用的一种交流方式，所以不是所有的人都能理解这种语言。因此，为了方便正常人和聋哑人之间的交流，人们发明了许多系统，将手语中的手势和符号翻译成易于理解的文字。这项研究的目的是训练一个能够检测和识别手势和手势的模型，然后通过图片或视频，甚至是实时地，使用You Only Look One (YOLO)方法将它们翻译成字母、数字和单词。YOLO是用于检测和识别事物的方法之一，其工作依赖于卷积神经网络(CNN)，其特点是工作的准确性和速度。在本研究中，我们创建了一个由8000张图像组成的数据集，分为40类，每类中有200张图像是在不同背景和光照条件下拍摄的，这使得模型能够在光照强度和图像清晰度的情况下区分信号。在数据集上对模型进行多次训练后，在使用图像数据的实验中，我们获得了MAP = 98.01%作为准确率，当前平均损失=1.3，召回率=0.96,F1=0.96的非常好的结果，对于视频结果，它具有相同的准确率和28.9帧/秒(fps)。
{"title":"American Sign Language Recognition using YOLOv4 Method","authors":"Ali Al-Shaheen, Mesut Cevik, Alzubair Alqaraghuli","doi":"10.36287/ijmsit.6.1.61","DOIUrl":"https://doi.org/10.36287/ijmsit.6.1.61","url":null,"abstract":"– Sign language is one of the ways of communication that is used by people who are unable to speak or hear (deaf and mute), so not all people are able to understand this language. Therefore, to facilitate communication between normal people and deaf and mute people, many systems have been invented that translate gestures and signs within sign language into words to be understandable. The aim behind this research is to train a model to be able to detect and recognize hand gestures and signs and then translate them into letters, numbers and words using You Only Look One (YOLO) method through pictures or videos, even in real time. YOLO is one of the methods used in detecting and recognizing things that depend in their work on convolutional neural networks (CNN), which are characterized by accuracy and speed in work. In this research, we have created a data set consisting of 8000 images divided into 40 classes, for each class, 200 images were taken with different backgrounds and under lighting conditions, which allows the model to be able to differentiate the signal regardless of the intensity of the lighting or the clarity of the image. And after training the model on the dataset many times, in the experiment using image data we got a very good results in terms of MAP = 98.01% as an accuracy and current average loss=1.3 and recall=0.96 and F1=0.96, and for video results it has the same accuracy and 28.9 frame per second (fps).","PeriodicalId":166049,"journal":{"name":"International Journal of Multidisciplinary Studies and Innovative Technologies","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122624940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
– Artificial Intelligence (AI) is a universal field for developing artificial methods that mimic human thinking. Computer games are electronic games consisting of hardware and software that involve human interaction with a user interface to generate visual feedback. Nowadays, it is seen that AI technology is increasingly used in computer games to simulate human-like intelligence and create intelligent behaviors. Especially in newly developed computer games, it is seen that AI is integrated into digital games as “Game Artificial Intelligence”. Behind this situation, there is essentially the simulation of game setup and opponent player behavior in digital games by providing decision making, perception and prediction skills with AI. In this research, it is aimed to develop an AI-based computer game (AI-DIGPOKGAME) and accuracy analysis in C# programming language with the open source Unity 3D Game simulator and "Jetbrains Rider" compiler, which allows users to develop their own digital game models. Within the scope of the study, 13 (thirteen) experiments were carried out. In the aforementioned experiments, it has been verified that within the framework of the game setup where the player fights against AI, AI successfully fulfills the basic principles of the game in order to increase competition and keep the fight at the highest level. It is considered that this research will contribute to the field of AI study in terms of revealing the simulation of rival player behavior in games by AI by providing decision making, perception and prediction skills with AI in digital games and developing new computer game models based on AI in the future.
{"title":"UNITY 3D Simülatöründe Geliştirilen Yapay Zekâ (YZ) Tabanlı Dijital Oyunun Karar Verme Yeteneğinin Doğruluk Analizi","authors":"Mert Sezer Ardal, H. Aydın, Yüksel Bal","doi":"10.36287/ijmsit.6.2.169","DOIUrl":"https://doi.org/10.36287/ijmsit.6.2.169","url":null,"abstract":"– Artificial Intelligence (AI) is a universal field for developing artificial methods that mimic human thinking. Computer games are electronic games consisting of hardware and software that involve human interaction with a user interface to generate visual feedback. Nowadays, it is seen that AI technology is increasingly used in computer games to simulate human-like intelligence and create intelligent behaviors. Especially in newly developed computer games, it is seen that AI is integrated into digital games as “Game Artificial Intelligence”. Behind this situation, there is essentially the simulation of game setup and opponent player behavior in digital games by providing decision making, perception and prediction skills with AI. In this research, it is aimed to develop an AI-based computer game (AI-DIGPOKGAME) and accuracy analysis in C# programming language with the open source Unity 3D Game simulator and \"Jetbrains Rider\" compiler, which allows users to develop their own digital game models. Within the scope of the study, 13 (thirteen) experiments were carried out. In the aforementioned experiments, it has been verified that within the framework of the game setup where the player fights against AI, AI successfully fulfills the basic principles of the game in order to increase competition and keep the fight at the highest level. It is considered that this research will contribute to the field of AI study in terms of revealing the simulation of rival player behavior in games by AI by providing decision making, perception and prediction skills with AI in digital games and developing new computer game models based on AI in the future.","PeriodicalId":166049,"journal":{"name":"International Journal of Multidisciplinary Studies and Innovative Technologies","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122329125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yasin Karabiber, Hüseyin Yağlı, Ceyhun Baydar, İ̇lker Mert
Extended Abstract Todays’ where energy is extremely important, every type of energy that countries can produce using their existing facilities is of great importance especially for countries that are dependent on abroad in term of energy sources. In this respect, another method, which is as important as using renewable energy sources, is to make use of idle energy. The energy that can be generated in natural gas pressure reduction stations can be given as an example of this situation. Existing natural gas pressure reducing and measuring stations reduce the pressure of natural gas by using an expansion valve. In this study, the power generation potential that can be produced by using an expansion turbine instead of an expansion valve for the pressure reduction process of natural gas was investigated. For this, power generation potential was investigated by using one-year data taken from an A-Type pressure reduction and measurement station (RMS-A) in our country. The pressure and temperature values of the natural gas at the station entrance and the inlet flow rate to the station were used as the basic input parameters of the study. The amount of power that can be obtained was calculated by simulating these parameters in a computer software. As a result, it was evaluated that a significant level of power generation can be produced while reducing the pressure of natural gas at pressure reduction and measuring stations.
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– Author identification is one of the application areas of text mining. It deals with the automatic prediction of the potential author of an electronic text among predefined author candidates by using author specific writing styles. In this study, we conducted an experiment for the identification of the author of a Turkish language text by using classical machine learning methods including Support Vector Machines (SVM), Gaussian Naive Bayes (GaussianNB), Multi Layer Perceptron (MLP), Logistic Regression (LR), Stochastic Gradient Descent (SGD) and ensemble learning methods including Extremely Randomized Trees (ExtraTrees), and eXtreme Gradient Boosting (XGBoost). The proposed method was applied on three different sizes of author groups including 10, 15 and 20 authors obtained from a new dataset of newspaper articles. Term frequency-inverse document frequency (TF-IDF) vectors were created by using 1-gram and 2-gram word tokens. Our results show that the most successful method is the SGD with a classification performance accuracy of 0.976% by using word unigrams and most successful method is the LR with a classification performance accuracy of 0.935% by using word bigrams.
{"title":"Author Identification with Machine Learning Algorithms","authors":"İbrahim Yülüce, Feriştah Dalkılıç","doi":"10.36287/ijmsit.6.1.45","DOIUrl":"https://doi.org/10.36287/ijmsit.6.1.45","url":null,"abstract":"– Author identification is one of the application areas of text mining. It deals with the automatic prediction of the potential author of an electronic text among predefined author candidates by using author specific writing styles. In this study, we conducted an experiment for the identification of the author of a Turkish language text by using classical machine learning methods including Support Vector Machines (SVM), Gaussian Naive Bayes (GaussianNB), Multi Layer Perceptron (MLP), Logistic Regression (LR), Stochastic Gradient Descent (SGD) and ensemble learning methods including Extremely Randomized Trees (ExtraTrees), and eXtreme Gradient Boosting (XGBoost). The proposed method was applied on three different sizes of author groups including 10, 15 and 20 authors obtained from a new dataset of newspaper articles. Term frequency-inverse document frequency (TF-IDF) vectors were created by using 1-gram and 2-gram word tokens. Our results show that the most successful method is the SGD with a classification performance accuracy of 0.976% by using word unigrams and most successful method is the LR with a classification performance accuracy of 0.935% by using word bigrams.","PeriodicalId":166049,"journal":{"name":"International Journal of Multidisciplinary Studies and Innovative Technologies","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132493037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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