Journal of Intelligent Systems with Applications最新文献_第2页

Big Data in Health and the Importance of Data Visualization Tools 健康中的大数据和数据可视化工具的重要性

Journal of Intelligent Systems with Applications Pub Date : 2022-05-02 DOI: 10.54856/jiswa.202205198

Fehmi Skender, I. Ali

{"title":"Big Data in Health and the Importance of Data Visualization Tools","authors":"Fehmi Skender, I. Ali","doi":"10.54856/jiswa.202205198","DOIUrl":"https://doi.org/10.54856/jiswa.202205198","url":null,"abstract":"Big data concepts are increasing with their spatial speed, from personal information to extensive volume data. Since the human brain perceives visual data faster, the data must be processed and displayed appropriately. As in all areas of life, the size of the data obtained in the health sector has increased rapidly. Data storage and security have gained importance with the excessive increase in data. Big data, data mining, and visualization tools have become increasingly important to process and use data for valuation purposes. Therefore, the visualization of data and the use of analysis tools play a significant role in data processing and decision-making in the development of the health sector. The importance of data visualization tools in the health sector will become increasingly indispensable. There are many software tools developed for these purposes. This study's literature review explained the basic concepts of big data and data visualization. Research in the health sector around the world was summarized. In addition to this literature review, analyses with comparison and deduction research methods were also carried out. As a result, suggestions were made by making predictions for future studies in the health sector.","PeriodicalId":112412,"journal":{"name":"Journal of Intelligent Systems with Applications","volume":"36 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132335333","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

In House Development of Contact Microphone Based Wearable Device for Knee Joint Health Assessment Using Vibroarthrography 基于接触式麦克风的关节振动成像可穿戴设备的研制

Journal of Intelligent Systems with Applications Pub Date : 2022-05-02 DOI: 10.54856/jiswa.202205209

D. Verma, Mirsaidin Hussain, P. Kumari, S. Kanagaraj

{"title":"In House Development of Contact Microphone Based Wearable Device for Knee Joint Health Assessment Using Vibroarthrography","authors":"D. Verma, Mirsaidin Hussain, P. Kumari, S. Kanagaraj","doi":"10.54856/jiswa.202205209","DOIUrl":"https://doi.org/10.54856/jiswa.202205209","url":null,"abstract":"Nowadays, bone joint disorders are very common in humans. The knee joint abnormality often comes with the increasing age of people. Cartilage degradation and rubbing action of the femoral condyle to the tibial condyle generates the knee joint sounds and this stage turns into osteoarthritis. There are pre-existing diagnosis methods available like X-ray, MRI, etc. but they have their limitations. Some treatment methods are invasive and some are semi-invasive. Early diagnosis of osteoarthritis is possible using vibroarthrography which is a purely non-invasive method and sensor signal output can be featured as an informative tool for next-level treatment. In this study, a contact microphone-based wearable device has been fabricated for knee joint health monitoring and joint angle-based sensor voltage output is characterized. The result of fast Fourier transformation from healthy subjects is observed to be from 0 Hz-100 Hz and short-term Fourier transformation is performed for the obtained decibel value from 40-45 dB. The result of a pathological knee is studied in spectral density analysis and observed a continuous emission of joint sound and signal power distribution is observed over the frequency range of 0 Hz - 500 Hz.","PeriodicalId":112412,"journal":{"name":"Journal of Intelligent Systems with Applications","volume":"147 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116369648","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

Classification of Sleep Stages via Machine Learning Algorithms 通过机器学习算法对睡眠阶段进行分类

Journal of Intelligent Systems with Applications Pub Date : 2022-05-02 DOI: 10.54856/jiswa.202205210

Ali Bulut, Galip Ozturk, Ibrahim Kaya

{"title":"Classification of Sleep Stages via Machine Learning Algorithms","authors":"Ali Bulut, Galip Ozturk, Ibrahim Kaya","doi":"10.54856/jiswa.202205210","DOIUrl":"https://doi.org/10.54856/jiswa.202205210","url":null,"abstract":"Sleep is a natural form of rest for humans. People need sleep to perform their daily functions. Insufficient or unstable sleep may adversely affect the function of many systems in human body. Sleep disorders can be seen common and cause serious health problems that affect quality of life. From past to present, it has become imperative to classify sleep stages in order to accurately analyze and diagnose these disorders. This classification is made by people who are experts in the field of sleep. However, this process is a very laborious task that requires high attention, and since it is done by a human, it is quite normal to make wrong classifications. As a solution to this, it is possible to make these classifications with machine learning techniques to obtain more accurate results. In this study, we compared different classification methods with each other and examined the channel-based accuracy of the method that gives the highest accuracy based on channels. The accuracy of the Fine Gaussian SVM Method was 98.9% and the F1-score was 98.95, the accuracy of the Weighted KNN Method was 97.9% and the F1-score was 97.89, the accuracy of the Wide Neural Network Method was 97.4% and the F1-score was 97.09, the accuracy of the Cubic SVM Method was 96.2% and the F1-score was 96.36. When we examine the Fine Gaussian SVM Method with the highest accuracy based on channels, we found accuracy of only Fpz-CZ channel is 98.1%, accuracy of only Pz-Oz channel is 94.5%.","PeriodicalId":112412,"journal":{"name":"Journal of Intelligent Systems with Applications","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126218251","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: 2

Motor Imaginary Task Classification using Statistically Significant Time Domain and Frequency Domain EEG features 基于统计显著时域和频域脑电特征的运动想象任务分类

Journal of Intelligent Systems with Applications Pub Date : 2022-05-02 DOI: 10.54856/jiswa.202205203

Murside Degirmenci, Yilmaz Kemal Yuce, Y. Isler

{"title":"Motor Imaginary Task Classification using Statistically Significant Time Domain and Frequency Domain EEG features","authors":"Murside Degirmenci, Yilmaz Kemal Yuce, Y. Isler","doi":"10.54856/jiswa.202205203","DOIUrl":"https://doi.org/10.54856/jiswa.202205203","url":null,"abstract":"Motor Imaginary (MI) electroencephalography (EEG) signals are obtained when a subject imagines a task without essentially applying it. The accurate decoding of MI EEG signals plays an important role in the design of brain-computer interface (BCI) systems due to the use of these signals in the rehabilitation process of paralyzed patients in recent studies. In this study, two different MI tasks were tried to be differentiated by extracting time-domain and frequency-domain features from 22 channel EEG signals and determining best combination of important and distinctive features based on statistical significance. MI EEG signals were supplied from BCI Competition IV Dataset-IIa. These features were differentiated using 25 different classification algorithms and 5-fold cross-validation method. The repeatability of the results was examined testing each algorithm 10 times. As a result, the highest average accuracy rate of 60.69% was calculated in the Quadratic Support Vector Machine (SVM) using all features and 62.52% in the Ensemble Subspace Discriminant (ESD) algorithm using only the selected features by the independent t-test. The results showed that the independent t-test based feature selection increased the performance in 20 classifiers, and decreased the performance in 5 classifiers. Also, the effectiveness of the feature selection method examined using the paired-sample t-test which is known as repeated measures t-test. The significance value, p-value was found as 0.04. Therefore, the independent t-test based feature selection method is an effective feature selection method and is providing the significant improvement in classifier performance.","PeriodicalId":112412,"journal":{"name":"Journal of Intelligent Systems with Applications","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126898202","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: 2

Detecting Tagged People in Camera Images 检测标记的人在相机图像

Journal of Intelligent Systems with Applications Pub Date : 2022-05-02 DOI: 10.54856/jiswa.202205197

Muhammed Telceken, Y. Kutlu

{"title":"Detecting Tagged People in Camera Images","authors":"Muhammed Telceken, Y. Kutlu","doi":"10.54856/jiswa.202205197","DOIUrl":"https://doi.org/10.54856/jiswa.202205197","url":null,"abstract":"With the development of technology, cameras are used more widely. It is possible to evaluate the widespread use of cameras in various subjects in daily life. Especially face recognition systems are one of the most important areas of use of cameras. Facial recognition systems can be used in many areas such as cyber security, entertainment, security applications of daily used devices, and faster and easier transactions in financial areas. Although a lot of progress has been made in this regard, face recognition systems are still used widely enough because it is thought that they have weaknesses in terms of security. Many scientists are working on facial recognition. In this study, it is aimed to detect the faces of people determined from videos or live camera images in the best and safest way. Yolov4 object detection algorithm, a ready-made algorithm, was used for the detection of human faces on images. The faces of the people in the images were detected by training the data set we created in the Yolov4 algorithm. An accuracy of 99.1 has been achieved for detecting people's faces on images. The data set we created with pictures of certain people is trained in the CNN algorithm. The faces of the people detected on the images were classified on the model trained with the CNN algorithm for the identification of the people, and the accuracy value was examined for the detection of the identified people on the video recordings or live images from the cameras.","PeriodicalId":112412,"journal":{"name":"Journal of Intelligent Systems with Applications","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130739494","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

Modification of posterior probability variable with frequency factor according to Bayes Theorem 根据贝叶斯定理，用频率因子修饰后验概率变量

Journal of Intelligent Systems with Applications Pub Date : 2022-05-02 DOI: 10.54856/jiswa.202205195

Mehmet Sait Vural, Muhammed Telceken

{"title":"Modification of posterior probability variable with frequency factor according to Bayes Theorem","authors":"Mehmet Sait Vural, Muhammed Telceken","doi":"10.54856/jiswa.202205195","DOIUrl":"https://doi.org/10.54856/jiswa.202205195","url":null,"abstract":"Probability theory is a branch of science that statistically analyzes random events. Thanks to this branch of science, machine learning techniques are used inferences for the prediction or recommendation system. One of the statistical methods at the forefront of these techniques is Bayesian theory. Bayes is a simple mathematical formula used to calculate conditional probabilities and obtain the best estimates. The two most important parts of the formula are the concepts of a priori probability and posterior/conditional probability. In a priori probability, the most rational assessment of the probability of an outcome is made based on the available data, while in posterior probability, the probability of the event occurring is calculated after considering all evidence or data. In this study, a new mathematical model is presented to calculate the posterior probability variable of Bayesian theory more precisely. According to this new mathematical model, equal priority probabilities of some variables should be recalculated according to frequency. Calculations are applied to two nodes. The first of these two nodes is the node consisting of the existing data, and the second is the queried node. The positive frequency value will be applied when the variables consisting of existing data and having the same a priori probabilities are found at the questioned node, and negative frequency value will be applied for the other variables. Thus, while calculating a standard probability value according to Bayesian Theory, frequency-based values are taken into account with the help of the newly created mathematical model. With the help of these frequencies, the modification of the system reveals more precise results according to these two basic principles. The results obtained were tested with the cross validation method and high accuracy rates were determined.","PeriodicalId":112412,"journal":{"name":"Journal of Intelligent Systems with Applications","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131739229","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: 1

Recognition of Turkish Command to Play Chess Game Using CNN 利用CNN识别土耳其语下棋指令

Journal of Intelligent Systems with Applications Pub Date : 2022-05-02 DOI: 10.54856/jiswa.202205211

Y. Kutlu, Gizem Karaca

{"title":"Recognition of Turkish Command to Play Chess Game Using CNN","authors":"Y. Kutlu, Gizem Karaca","doi":"10.54856/jiswa.202205211","DOIUrl":"https://doi.org/10.54856/jiswa.202205211","url":null,"abstract":"A platform has been created that allows playing chess with Turkish voice commands. The aim of this study is to enable individuals with limited movement abilities as a result of congenital reasons or a certain disease or accident to play chess and perform a social activity without the help of another person, and to be rehabilitated at the same time. It consists of three parts: Chess module, Human-computer interaction module and Artificial Intelligence module. 29 words have been determined to provide movement in the game on the platform. Voice recordings from 151 people, 86 men and 65 women, were used. Feature selection was made on 43790 voice recordings by using mel frequency cepstral coefficients (MFCC) and gammatone cepstral coefficients (GTCC) methods. The results obtained were classified using the traditional CNN model. The data obtained after using MFCC and GTCC methods were used as inputs in the CNN model. In addition, the data obtained by the two methods were combined and trained in the model. Depending on the methods used in the created model, 83% to 85.9% results were obtained. It was determined that the results obtained using the MFCC method were more successful.","PeriodicalId":112412,"journal":{"name":"Journal of Intelligent Systems with Applications","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131702096","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: 1

Histopathological Evaluation of Tissue Specific Responses of Subacute Clothianidin Administration in Oncorhynchus mykiss 亚急性给药氯噻虫胺对褐蝽组织特异性反应的组织病理学评价

Journal of Intelligent Systems with Applications Pub Date : 2021-12-27 DOI: 10.54856/jiswa.202112173

G. Nur, Demet Dogan, H. Deveci

引用次数: 0

Evaluation of Wigner-Ville Distribution Features to Estimate Steady-State Visual Evoked Potentials' Stimulation Frequency 评价Wigner-Ville分布特征估计稳态视觉诱发电位刺激频率

Journal of Intelligent Systems with Applications Pub Date : 2021-12-27 DOI: 10.54856/jiswa.202112178

Murside Degirmenci, Ebru Sayilgan, Y. Isler

{"title":"Evaluation of Wigner-Ville Distribution Features to Estimate Steady-State Visual Evoked Potentials' Stimulation Frequency","authors":"Murside Degirmenci, Ebru Sayilgan, Y. Isler","doi":"10.54856/jiswa.202112178","DOIUrl":"https://doi.org/10.54856/jiswa.202112178","url":null,"abstract":"Brain Computer Interface (BCI) is a system that enables people to communicate with the outside world and control various electronic devices by interpreting only brain activity (motor movement imagination, emotional state, any focused visual or auditory stimulus, etc.). The visual stimulation based recording is one of the most popular methods among various electroencephalography (EEG) recording methods. Steady-state visual-evoked potentials (SSVEPs) where visual objects are blinking at a fixed frequency play an important role due to their high signal-to-noise ratio and higher information transfer rate in BCI applications. However, the design of multiple (more than 3) commands systems in SSVEPs based BCI systems is limited. The different approaches are recommended to overcome these problems. In this study, an approach based on machine learning is proposed to determine stimulating frequency in SSVEP signals. The data set (AVI SSVEP Dataset) is obtained through open access from the internet for simulations. The dataset includes EEG signals that was recorded when subjects looked at a flickering frequency at seven different frequencies (6-6.5-7-7.5-8.2-9.3-10Hz). In the machine learning-based approach Wigner-Ville Distribution (WVD) is used and features are extracted using Time-Frequency (TF) representations of EEG signals. These features are classified by Decision Tree, Linear Discriminant Analysis (LDA), k-Nearest Neighbor (k-NN), Support Vector Machine (SVM), Naive Bayes, Ensemble Learning classifiers. Simulation results demonstrate that the proposed approach achieved promising accuracy rates for 7 command SSVEP systems. As a consequence, the maximum accuracy is achieved in the Ensemble Learning classifier with 47.60%.","PeriodicalId":112412,"journal":{"name":"Journal of Intelligent Systems with Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125777900","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: 8

Artificial Intelligence Applications in Nutrition and Dietetics 人工智能在营养营养学中的应用

Journal of Intelligent Systems with Applications Pub Date : 2021-12-27 DOI: 10.54856/jiswa.202112175

I. Ulker, F. Ayyıldız

{"title":"Artificial Intelligence Applications in Nutrition and Dietetics","authors":"I. Ulker, F. Ayyıldız","doi":"10.54856/jiswa.202112175","DOIUrl":"https://doi.org/10.54856/jiswa.202112175","url":null,"abstract":"Artificial intelligence (AI) is a branch of computer science whose purpose is to imitate thought processes, learning abilities, and knowledge management. The increasing number of applications in experimental and clinical medicine is striking. An artificial intelligence application in the field of nutrition and dietetics is a fairly new and important field. Different apps related to nutrition are offered to the use of individuals. The importance of individual nutrition has also triggered the increase in artificial intelligence apps. It is thought that different apps such as food preferences and dietary intake can play an important role in health promotion. Researchers may have some difficulties such as remembering the frequency or amount of intake in assessment of dietary intake. Some applications used in the assessment of food consumption contribute to overcoming these difficulties. Besides, these apps facilitate the work of researchers and provide more reliable results than traditional methods. The apps to be used in the field of nutrition and dietetics should be developed by considering the disadvantages. It is thought that artificial intelligence applications will contribute to both the improvement of health and the assessment and monitoring of nutritional status.","PeriodicalId":112412,"journal":{"name":"Journal of Intelligent Systems with Applications","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131419792","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