Applied Computer Science最新文献_第2页

NEW APPROACH FOR BREAST CANCER DETECTION- BASED MACHINE LEARNING TECHNIQUE 基于机器学习技术的乳腺癌检测新方法

Applied Computer Science Pub Date : 2024-03-30 DOI: 10.35784/acs-2024-01

Malek M. Al-Nawashi, Obaida M. Al-hazaimeh, M. Khazaaleh

引用次数: 0

EMOTION RECOGNITION FROM HEART RATE VARIABILITY WITH A HYBRID SYSTEM COMBINED HIDDEN MARKOV MODEL AND POINCARE PLOT 利用混合系统结合隐马尔可夫模型和波因卡雷图，从心率变异性识别情绪

Applied Computer Science Pub Date : 2024-03-30 DOI: 10.35784/acs-2024-07

Sahar ZAMANI KHANGHAH, K. Maghooli

{"title":"EMOTION RECOGNITION FROM HEART RATE VARIABILITY WITH A HYBRID SYSTEM COMBINED HIDDEN MARKOV MODEL AND POINCARE PLOT","authors":"Sahar ZAMANI KHANGHAH, K. Maghooli","doi":"10.35784/acs-2024-07","DOIUrl":"https://doi.org/10.35784/acs-2024-07","url":null,"abstract":"The best emotion recognition system based on physiological signals with a simple operatory should have higher accuracy and fast response speed. This paper aims to develop an emotion recognition system using a novel hybrid system based on Hidden Markov Model and Poincare plot. For this purpose, an electrocardiogram from the MAHNOB-HCI database was used. A novel feature extraction from a hybrid system combining Hidden Markov Model and Poincare plot was presented. The authors extracted time and frequency domain features from heart rate variability, and used two central hybrid systems, the Support Vector Machine/ Hidden Markov Model and the Hidden Markov Model/ Poincare Plot. Finally, the support vector machine was used as a classifier to classify emotions into positive and negative. The proposed method showed a classification accuracy of 95.02 ± 1.97 % overall. Also, the computing time of the method is around 163 milliseconds. The key of this paper is in the use of hybrid machines to improve accuracy without high computation time. This method can be used as a real-time system due to the low computation time and can be developed in many fields, such as medical examination and security systems.","PeriodicalId":36379,"journal":{"name":"Applied Computer Science","volume":"27 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140364618","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}

引用次数: 0

IMPLICATIONS OF NEURAL NETWORK AS A DECISION-MAKING TOOL IN MANAGING KAZAKHSTAN’S AGRICULTURAL ECONOMY 神经网络作为哈萨克斯坦农业经济管理决策工具的影响

Applied Computer Science Pub Date : 2024-01-05 DOI: 10.35784/acs-2023-39

M. Kulisz, A. Duisenbekova, J. Kujawska, Danira Kaldybayeva, B. Issayeva, Piotr Lichograj, W. Cel

{"title":"IMPLICATIONS OF NEURAL NETWORK AS A DECISION-MAKING TOOL IN MANAGING KAZAKHSTAN’S AGRICULTURAL ECONOMY","authors":"M. Kulisz, A. Duisenbekova, J. Kujawska, Danira Kaldybayeva, B. Issayeva, Piotr Lichograj, W. Cel","doi":"10.35784/acs-2023-39","DOIUrl":"https://doi.org/10.35784/acs-2023-39","url":null,"abstract":"This study investigates the application of Artificial Neural Networks (ANN) in forecasting agricultural yields in Kazakhstan, highlighting its implications for economic management and policy-making. Utilizing data from the Bureau of National Statistics of the Republic of Kazakhstan (2000-2023), the research develops two ANN models using the Neural Net Fitting library in MATLAB. The first model predicts the total gross yield of main agricultural crops, while the second forecasts the share of individual crops, including cereals, oilseeds, potatoes, vegetables, melons, and sugar beets. The models demonstrate high accuracy, with the total gross yield model achieving an R-squared value of 0.98 and the individual crop model showing an R value of 0.99375. These results indicate a strong predictive capability, essential for practical agricultural and economic planning. The study extends previous research by incorporating a comprehensive range of climatic and agrochemical data, enhancing the precision of yield predictions. The findings have significant implications for Kazakhstan's economy. Accurate yield predictions can optimize agricultural planning, contribute to food security, and inform policy decisions. The successful application of ANN models showcases the potential of AI and machine learning in agriculture, suggesting a pathway towards more efficient, sustainable farming practices and improved quality management systems.","PeriodicalId":36379,"journal":{"name":"Applied Computer Science","volume":"48 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139384267","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}

引用次数: 0

IMPACT OF FRICTION COEFFICIENT VARIATION ON TEMPERATURE FIELD IN ROTARY FRICTION WELDING OF METALS – FEM STUDY 金属旋转摩擦焊中摩擦系数变化对温度场影响的有限元研究

Applied Computer Science Pub Date : 2023-10-02 DOI: 10.35784/acs-2023-22

Andrzej ŁUKASZEWICZ, Jerzy JÓZWIK, Kamil CYBUL

引用次数: 0

FUZZY MULTIPLE CRITERIA GROUP DECISION-MAKING IN PERFORMANCE EVALUATION OF MANUFACTURING COMPANIES 制造企业绩效评价中的模糊多准则群体决策

Applied Computer Science Pub Date : 2023-09-30 DOI: 10.35784/acs-2023-23

Sara SALEHI

{"title":"FUZZY MULTIPLE CRITERIA GROUP DECISION-MAKING IN PERFORMANCE EVALUATION OF MANUFACTURING COMPANIES","authors":"Sara SALEHI","doi":"10.35784/acs-2023-23","DOIUrl":"https://doi.org/10.35784/acs-2023-23","url":null,"abstract":"Today's market competition requires constant improvement of manufacturing companies. The primary key to sustainable improvement is evaluating the efficiency of manufacturing processes, which inevitably demands access to thorough and comprehensive information. However, due to the multiple numbers of effective factors that are varied in nature and value, it is impossible to identify certain factors that ensure the efficiency of a manufacturing procedure. As a solution, this paper proposes a novel approach that applies fuzzy TOPSIS. This approach provides the flexibility of evaluating multiple and varied factors of different weights in scrutinizing the efficiency of a manufacturer. The proposed approach has been applied to three different manufacturers (i.e., alternatives) in three steps. In the first step, with reference to the related literature and comments of manufacturing experts, the valuable factors (i.e., the criteria) have been selected to which experts specified linguistic terms. Linguistic terms were then converted to fuzzy numbers. Fuzzy TOPSIS was applied to analyze the efficiency performance of manufacturers. In the last step, to determine the impact of criteria weights on the decision-making process, sensitivity analysis was carried out. The findings confirm the implacability of the proposed approach to manufacturing performances in a consolidated manner. The approach can be employed by marketing managers, senior administrators, and other authorities in the manufacturing and business sectors.","PeriodicalId":36379,"journal":{"name":"Applied Computer Science","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135084107","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}

引用次数: 0

DATA ENGINEERING IN CRISP-DM PROCESS PRODUCTION DATA – CASE STUDY crisp-dm工艺生产数据中的数据工程-案例研究

Applied Computer Science Pub Date : 2023-09-30 DOI: 10.35784/acs-2023-26

Jolanta BRZOZOWSKA, Jakub PIZOŃ, Gulzhan BAYTIKENOVA, Arkadiusz GOLA, Alfiya ZAKIMOVA, Katarzyna PIOTROWSKA

引用次数: 0

ADAPTIVE SECURE AND EFFICIENT ROUTING PROTOCOL FOR ENHANCE THE PERFORMANCE OF MOBILE AD HOC NETWORK 自适应安全高效路由协议，提高移动AD hoc网络的性能

Applied Computer Science Pub Date : 2023-09-30 DOI: 10.35784/acs-2023-29

Md. Torikur RAHMAN, Mohammad ALAUDDIN, Uttam Kumar DEY, Dr. A.H.M. Saifullah SADI

{"title":"ADAPTIVE SECURE AND EFFICIENT ROUTING PROTOCOL FOR ENHANCE THE PERFORMANCE OF MOBILE AD HOC NETWORK","authors":"Md. Torikur RAHMAN, Mohammad ALAUDDIN, Uttam Kumar DEY, Dr. A.H.M. Saifullah SADI","doi":"10.35784/acs-2023-29","DOIUrl":"https://doi.org/10.35784/acs-2023-29","url":null,"abstract":"Nowadays Mobile Ad Hoc Network (MANET) is an emerging area of research to provide various communication services to end users. Mobile Ad Hoc Networks (MANETs) are self-organizing wireless networks where nodes communicate with each other without a fixed infrastructure. Due to their unique characteristics, such as mobility, autonomy, and ad hoc connectivity, MANETs have become increasingly popular in various applications, including military, emergency response, and disaster management. However, the lack of infrastructure and dynamic topology of MANETs pose significant challenges to designing a secure and efficient routing protocol. This paper proposes an adaptive, secure, and efficient routing protocol that can enhance the performance of MANET. The proposed protocol incorporates various security mechanisms, including authentication, encryption, key management, and intrusion detection, to ensure secure routing. Additionally, the protocol considers energy consumption, network load, packet delivery fraction, route acquisition latency, packets dropped and Quality of Service (QoS) requirements of the applications to optimize network performance. Overall, the secure routing protocol for MANET should provide a reliable and secure communication environment that can adapt to the dynamic nature of the network. The protocol should ensure that messages are delivered securely and efficiently to the intended destination, while minimizing the risk of attacks and preserving the network resources Simulation results demonstrate that the proposed protocol outperforms existing routing protocols in terms of network performance and security. The proposed protocol can facilitate the deployment of various applications in MANET while maintaining security and efficiency.","PeriodicalId":36379,"journal":{"name":"Applied Computer Science","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135126780","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}

引用次数: 0

PERFORMANCE EVALUATION OF STOCK PREDICTION MODELS USING EMAGRU 基于emagru的股票预测模型的性能评价

Applied Computer Science Pub Date : 2023-09-30 DOI: 10.35784/acs-2023-30

Erizal ERIZAL, Mohammad DIQI

引用次数: 0

NUMERICAL CALCULATIONS OF WATER DROP USING A FIREFIGHTING AIRCRAFT 用灭火飞机对水滴进行数值计算

Applied Computer Science Pub Date : 2023-09-30 DOI: 10.35784/acs-2023-24

Zbigniew CZYŻ, Paweł KARPIŃSKI, Krzysztof SKIBA, Szymon BARTKOWSKI

引用次数: 0

A LATIN AMERICAN MARKET ASSET VOLATILITY ANALYSIS: A COMPARISON OF GARCH MODEL, ARTIFICIAL NEURAL NETWORKS AND SUPPORT VECTOR REGRESSION 拉丁美洲市场资产波动分析:garch模型、人工神经网络与支持向量回归的比较

Applied Computer Science Pub Date : 2023-09-30 DOI: 10.35784/acs-2023-21

Victor CHUNG, Jenny ESPINOZA

引用次数: 0