Proceedings of the International Conference on New Trends in Applied Sciences最新文献

Calculation of Mutual Inductance between Two Planar Coils with Custom Specifications and Positions Using a Machine Learning Approach 利用机器学习方法计算定制规格和位置的两个平面线圈之间的互感

Proceedings of the International Conference on New Trends in Applied Sciences Pub Date : 2023-12-01 DOI: 10.58190/icontas.2023.50

Mahdi Asadi, Ali x Ali Rezaei, A. Abazari

{"title":"Calculation of Mutual Inductance between Two Planar Coils with Custom Specifications and Positions Using a Machine Learning Approach","authors":"Mahdi Asadi, Ali x Ali Rezaei, A. Abazari","doi":"10.58190/icontas.2023.50","DOIUrl":"https://doi.org/10.58190/icontas.2023.50","url":null,"abstract":"Wireless power transmission systems enable the transfer of electricity between grids without the use of physical wires. Different methods are employed for wireless power transfer, each suited to different distances. Inductive coupling, the subject of this study, is typically used for shorter distances. The effectiveness of inductive coupling systems is evaluated using a parameter called mutual inductance. In the present study, an attempt is made to provide a model for calculating mutual inductance in wireless power transfer systems using a machine learning approach. To achieve this goal, finite element simulations are employed, and 64 datasets are generated from mutual inductance calculations in various scenarios. These datasets are used to train machine learning regression algorithms, including linear regression, support vector regression, decision tree regression, and artificial neural networks. The evaluation results, using performance metrics such as R-squared, mean absolute error, and root mean square error, confirm that among these four algorithms, the artificial neural network exhibits higher computational accuracy with an R-squared value of 0.950 for predicting test data.","PeriodicalId":509439,"journal":{"name":"Proceedings of the International Conference on New Trends in Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139193856","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

A PARAMETER ADJUSTMENT LAW FOR MULTIVARIABLE PID CONTROL SYSTEMS WITH DISTURBANCE ATTENUATION PERFORMANCE 具有干扰衰减性能的多变量 pid 控制系统的参数调整规律

Proceedings of the International Conference on New Trends in Applied Sciences Pub Date : 2023-12-01 DOI: 10.58190/icontas.2023.58

Naokix NaokiKANEKO, Takuya Nakagawa, Daiki Asada, H. Oya

引用次数: 0

AN EFFICIENT FEATURE ANALYSIS METHOD OF BIOLOGICAL DATA FOR IMPROVING CATTLE CONCEPTION RATE 提高牛受孕率的高效生物数据特征分析方法

Proceedings of the International Conference on New Trends in Applied Sciences Pub Date : 2023-12-01 DOI: 10.58190/icontas.2023.56

Tatsuya Komatsu, Hiroto Noma, Takumi Asaoka, H. Oya, R. Miura, Koji Yoshioka

引用次数: 0

Exploring the Molecularity of the Odor and Taste Perceptions of “Brown”: A Computational Approach 探索 "棕色 "气味和味道感知的分子性：计算方法

Proceedings of the International Conference on New Trends in Applied Sciences Pub Date : 2023-12-01 DOI: 10.58190/icontas.2023.61

Hirva Bhayani, Roshan Thilakarathne, Neranjan Perera, Chiquito Crasto

{"title":"Exploring the Molecularity of the Odor and Taste Perceptions of “Brown”: A Computational Approach","authors":"Hirva Bhayani, Roshan Thilakarathne, Neranjan Perera, Chiquito Crasto","doi":"10.58190/icontas.2023.61","DOIUrl":"https://doi.org/10.58190/icontas.2023.61","url":null,"abstract":"We have developed a methodology that seeks to associate the molecularity of compounds with the perceptions of specific odor or taste. This methodology goes beyond gross structural features for a molecule: aromatic or aliphatic rings, lengths of the aliphatic straight chains, or the nature and variation in the functional groups. We target specific atom pairs–bonded or remote–within the smell and taste molecule that have structural-electronic features that are reproducible across molecules that elicit similar smell and taste responses. We represent the “structure” of the atom pair by its interatomic distance. The “electronic” aspects are represented by Nuclear Magnetic Resonance (NMR) chemical shifts that uniquely define the electronic environments of the atoms. We used quantum chemistry calculations and the density functional theory (DFT) to determine the chemical shifts and interatomic distances (through the Z-matrix). We used this methodology to process 19 molecules that elicited the smell of “brown,” and 18 molecules that elicited the taste of “brown.” These molecules were accessed through odor and taste indices from the GoodScentsCompany resource (https://www.thegoodscentscompany.com/). These “brown” odorants and tastants elicited other associated smells and tastes. We identified and illustrated specific bond pairs that elicited different smells and tastes. While smell and taste are intrinsically related, our studies also show atom pairs that are likely responsible exclusively for smell and taste, as well as pairs that elicit both. This work will be impactful in the domain of drug design in the pharmaceutical industry, in addition to enhancing our understanding of how a chemical catalyzes the process that results in chemosensory perception.","PeriodicalId":509439,"journal":{"name":"Proceedings of the International Conference on New Trends in Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139194308","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

A RECOGNITION METHOD OF R-PEAKS ON ELECTROCARDIOGRAMS BASED ON WAVELET TRANSFORM WITH PSEUDO-DIFFERENTIAL OPERATORS 基于带伪微分算子的小波变换的心电图 r 峰识别方法

Proceedings of the International Conference on New Trends in Applied Sciences Pub Date : 2023-12-01 DOI: 10.58190/icontas.2023.55

Yuta Yoshikawa, Takayuki Okai, H. Oya, Minoru Yoshida, Md.Masudur Rahman

{"title":"A RECOGNITION METHOD OF R-PEAKS ON ELECTROCARDIOGRAMS BASED ON WAVELET TRANSFORM WITH PSEUDO-DIFFERENTIAL OPERATORS","authors":"Yuta Yoshikawa, Takayuki Okai, H. Oya, Minoru Yoshida, Md.Masudur Rahman","doi":"10.58190/icontas.2023.55","DOIUrl":"https://doi.org/10.58190/icontas.2023.55","url":null,"abstract":"In this paper, we propose a recognition method of R-peaks on electrocardiograms (ECGs) based on wavelet transform with pseudo-differential operators. It is well known that the accurate recognition of R-peaks is highly importance for diagnosis of cardiac diseases and autonomic ataxia. However, the existing results for detection of R-peaks are not always accurate and can have missed peaks or false. Difficulties in accurate R-peaks detection is caused by presence of various noises in ECGs and the physiological variability of the QRS complex. From the above, we propose a more flexible and adaptive recognition method of R-peaks. In order to develop the proposed detection method, noises, artifacts, and baseline variation in ECGs are firstly suppressed by using the low-pass/high-pass filters, moving average, and MaMeMi filter. Next, the time-frequency domain's energy distribution is computed by using wavelet transform with pseudo-differential operators. Furthermore, we introduce a time-series index, -Normalized Spectrum Index ( f^p-NSI) obtained by scalograms based on the wavelet transform with pseudo-differential operators. Finally, R-peaks are recognized by taking the threshold toward the results of f^p-NSI. In this paper, we present the proposed recognition method of R-peaks on ECGs, and the effectiveness (accuracy) of the proposed method is evaluated.","PeriodicalId":509439,"journal":{"name":"Proceedings of the International Conference on New Trends in Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139195650","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

SEISMIC PROTECTION OF EXISTING STRUCTURES WITH DISTRIBUTED NEGATIVE STIFFNESS DEVICES 利用分布式负刚度装置对现有结构进行抗震保护

Proceedings of the International Conference on New Trends in Applied Sciences Pub Date : 2023-12-01 DOI: 10.58190/icontas.2023.57

K. Kapasakalis, Spiridon Kapasakalis, Evangelos x Evangelos SAPOUNTZAKIS

{"title":"SEISMIC PROTECTION OF EXISTING STRUCTURES WITH DISTRIBUTED NEGATIVE STIFFNESS DEVICES","authors":"K. Kapasakalis, Spiridon Kapasakalis, Evangelos x Evangelos SAPOUNTZAKIS","doi":"10.58190/icontas.2023.57","DOIUrl":"https://doi.org/10.58190/icontas.2023.57","url":null,"abstract":"In this research study, the KDamper concept is extended (EKD device) and applied to multiple floors of existing multi-story building structures, aiming to reduce the structure dynamic responses due to earthquake excitations. The KDamper is a novel passive vibration absorption concept, based essentially on the optimal combination of appropriate stiffness elements, one of which has a negative value (NS). The mass requirements of KDamper are reduced, compared to the Tuned Mass Damper (TMD), as the NS element is implemented to the installed mass and the NS force is in phase with the inertia force, artificially amplifying it. Inspired by the concept of distributed TMDs (d-TMDs), multiple EKDs (d-EKDs) are installed and distributed along the height of the structure, for seismic protection. The design and spatial allocation of these EKDs are determined using a Harmony Search (HS) algorithm, which identifies optimal device parameters while adhering to structural constraints and limitations. Artificial accelerograms are generated and introduced as input to the optimization process. Based on the numerical results obtained, the d-EKD concept, outperforms the d-TMD in reducing the structural dynamic responses, introducing one order of magnitude smaller added oscillating masses. In addition, results indicate no significant alteration of the structural properties and eigenfrequencies due to the installation of the proposed EKD devices, despite the addition of masses and NS elements.","PeriodicalId":509439,"journal":{"name":"Proceedings of the International Conference on New Trends in Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139190278","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

ANALYSIS OF BIOLOGICAL DATA OF CATTLE AND WAVELET TRANSFORM BASED PREDICTION FOR OPTIMAL INSEMINATION PHASE 牛的生物数据分析和基于小波变换的最佳授精期预测

Proceedings of the International Conference on New Trends in Applied Sciences Pub Date : 2023-12-01 DOI: 10.58190/icontas.2023.60

Takumi Asaoka, Hiroto Noma, Tatsuya Komatsu, H. Oya, R. Miura, Koji Yoshioka

{"title":"ANALYSIS OF BIOLOGICAL DATA OF CATTLE AND WAVELET TRANSFORM BASED PREDICTION FOR OPTIMAL INSEMINATION PHASE","authors":"Takumi Asaoka, Hiroto Noma, Tatsuya Komatsu, H. Oya, R. Miura, Koji Yoshioka","doi":"10.58190/icontas.2023.60","DOIUrl":"https://doi.org/10.58190/icontas.2023.60","url":null,"abstract":"For farmers who maintain dairy cattle, artificial insemination (AI) is one of important events in cattle, because it may lead to lose money by missing out on AI. However, the accuracy for detection depends on the time and number of observations when the estrus behavior and signs for cattle during the estrus season are visually assessed by experts and farmers, and the detection accuracy via experts and farmers is approximately 60%. For farmers, it is obvious that improving reproductive efficiency can save time and money. Therefore, various detection strategies for AI timing such as pedometers and methods based on observation of hormone in estrus have been well studied. Additionally, a detection strategy based on variations for temperature corresponding to ovulation has also been presented. In particular, the accuracy of detection of AI timing based on monitoring the vaginal temperature is greater than that for other methods such as pedometer and so on, i.e., it seems that an optimal timing of AI based on vaginal temperature in cattle is more effective. Although there are some existing results for detection of AI timing based on vaginal temperature and vaginal electrical resistance data, further improvement of accuracy is required in practical use. In this paper, we propose an estimation method for the optimal AI timing by analyzing both vaginal temperature and vaginal electrical resistance data. In our approach, as preprocessing, MaMeMi filter and Gaussian kernel smoother are newly introduced for the purpose of reducing the effect of circadian rhythms and various noises. Moreover, we adopt continuous wavelet transformation to analyze biological data, and NSI (Normalized Spectrum Index) is calculated. Finally, the optimal timing for AI can be estimated by using the Mahalanobis distance. In this paper, we present the proposed estimation algorithm and evaluate the proposed approach.","PeriodicalId":509439,"journal":{"name":"Proceedings of the International Conference on New Trends in Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139193816","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

COMPARISON OF VISION TRANSFORMERS AND CONVOLUTIONAL NEURAL NETWORKS FOR SKIN DISEASE CLASSIFICATION 比较视觉变换器和卷积神经网络在皮肤病分类中的应用

Proceedings of the International Conference on New Trends in Applied Sciences Pub Date : 2023-12-01 DOI: 10.58190/icontas.2023.51

Muhammet Fatih Aslan

{"title":"COMPARISON OF VISION TRANSFORMERS AND CONVOLUTIONAL NEURAL NETWORKS FOR SKIN DISEASE CLASSIFICATION","authors":"Muhammet Fatih Aslan","doi":"10.58190/icontas.2023.51","DOIUrl":"https://doi.org/10.58190/icontas.2023.51","url":null,"abstract":"Skin diseases are one of the most common diseases in humans. Due to its many various symptoms and types, computer vision studies have been frequently applied to its diagnosis and classification. Previous studies have frequently used machine learning methods and deep learning-based Convolutional Neural Networks (CNN) for skin disease diagnosis. Although deep learning-based applications have achieved great success in terms of detection accuracy, research continues to ensure the desired performance. However, Vision Transformer (ViT), recently proposed as a competitive alternative to CNNs, is gaining increasing popularity. This paper compares ResNet18 and ResNet50 networks, important CNN models, with ViT for classifying skin disease. The comparison is applied on a dataset containing a small number of samples. In the application performed on a dataset containing skin disease images, ViT provides 68.93% classification accuracy, while ResNet18 and ResNet50 classification accuracy is 61.65% and 61.17%, respectively. Other metrics calculated along with the accuracies also prove the superiority of ViT over ResNet models. However, ViT has a big disadvantage in terms of training time.","PeriodicalId":509439,"journal":{"name":"Proceedings of the International Conference on New Trends in Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139190726","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

A Hyper Parametrized Deep Learning Model for Analyzing Heating and Cooling Loads in Energy Efficient Buildings 用于分析节能建筑供热和制冷负荷的超参数化深度学习模型

Proceedings of the International Conference on New Trends in Applied Sciences Pub Date : 2023-12-01 DOI: 10.58190/icontas.2023.54

E. M. Abdelkader, N. Elshaboury, Eslam Ali, Ghasan Alfalah, Ahmed Mansour, Abobakr Alsakkaf

{"title":"A Hyper Parametrized Deep Learning Model for Analyzing Heating and Cooling Loads in Energy Efficient Buildings","authors":"E. M. Abdelkader, N. Elshaboury, Eslam Ali, Ghasan Alfalah, Ahmed Mansour, Abobakr Alsakkaf","doi":"10.58190/icontas.2023.54","DOIUrl":"https://doi.org/10.58190/icontas.2023.54","url":null,"abstract":"The huge increase in energy consumption in recent decades, has made it cumbersome to anticipate energy usage in the residential sector. However, despite substantial advancements in computation and simulation, the modelling of residential building energy use is still in need of improvement for efficient and reliable solutions. To this end, the overarching objective of this research study is to construct a self-adaptive model (HBO-DL) for predicting the amounts of heating and cooling loads in residential buildings. The developed HBO-DL model is envisioned on coupling Bayesian optimization with deep learning neural network. Five statistical metrics of mean absolute percentage error (MAPE), root mean squared error (RMSE), root mean squared logarithmic error (RMSLE), mean absolute error (MAE) and normalized root mean squared error (NRMSE), are leveraged to measure and test the accuracies of the developed HBO-DL. Analytical results explicated that the developed HBO-DL model can endorse informed decision-making and foster energy conservation in built environment.","PeriodicalId":509439,"journal":{"name":"Proceedings of the International Conference on New Trends in Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139187765","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

Utilizing Random Forests for the Classification of Pudina Leaves through Feature Extraction with InceptionV3 and VGG19 通过 InceptionV3 和 VGG19 提取特征，利用随机森林对杜鹃花叶进行分类

Proceedings of the International Conference on New Trends in Applied Sciences Pub Date : 2023-12-01 DOI: 10.58190/icontas.2023.48

Elham Tahsin Yasin, Murat Koklu

引用次数: 0