Periodicals of Engineering and Natural Sciences最新文献

First Morphological and Genetic Record and Confirmation of Korean Rockfish Sebastes schlegelii Hilgendorf, 1880 in the Black Sea Coast of Türkiye 台湾黑海沿岸韩国岩鱼(sebases schlegelii Hilgendorf, 1880)首次形态、遗传记录及确认

Periodicals of Engineering and Natural Sciences Pub Date : 2023-08-10 DOI: 10.28978/nesciences.1363941

Deniz YAĞLIOĞLU, Servet Ahmet DOĞDU, Cemal TURAN

引用次数: 0

Conducting Polymer Films on Zn Deposited Carbon Electrode 在锌碳电极上导电聚合物薄膜

Periodicals of Engineering and Natural Sciences Pub Date : 2023-08-07 DOI: 10.28978/nesciences.1342013

A. Ozyilmaz

引用次数: 0

The Genotoxic Damage in Cyprinus carpio Exposed to Abamectin 阿维菌素对鲤的遗传毒性损害

Periodicals of Engineering and Natural Sciences Pub Date : 2023-07-12 DOI: 10.28978/nesciences.1338147

F. Turan, A. Ergenler

引用次数: 0

A low-cost podoscope for extracting morphological features of the foot 一种用于提取足部形态特征的低成本足镜

Periodicals of Engineering and Natural Sciences Pub Date : 2023-06-12 DOI: 10.21533/pen.v11i3.3676

Ruba Musaid, A. Ghazwan, Waleed A. Al-Saadan

{"title":"A low-cost podoscope for extracting morphological features of the foot","authors":"Ruba Musaid, A. Ghazwan, Waleed A. Al-Saadan","doi":"10.21533/pen.v11i3.3676","DOIUrl":"https://doi.org/10.21533/pen.v11i3.3676","url":null,"abstract":"Foot morphology evaluation techniques are commonly used to evaluate foot abnormalities. The foot is essential for keeping the biomechanical performance of the lower extremities. It is responsible for the support of body balance and stability during gait. For the qualitative examination of foot morphology, many podoscopes have been designed. However, these podoscopes are mainly expensive, complex to operate, and have low accessibility. As a consequence the goal of this research was to create a simple, low-cost podoscope to assess the plantar footprint. In addition to providing a visual representation of the supporting regions. The proposed system enables accurate estimation of clinical indexes of foot deformities. With bare feet, bipedal support, and orthostatic posture, the participant was placed on the podoscope. Doom camera was used to capture the image of the plantar of the foot, and the data was sent to a computer via LAN connection. Based on image processing techniques, the proposed podoscope can automatically estimate the Arch Index, the Chippaux-Smirak Index, the Staheli Index, and Wejsflog's index.Ten samples were tested by the proposed podoscope, and the calculated parameters defining foot deformities are presented. The proposed podoscope appears to have the advantages of simplicity, being portable, inexpensive enabling rapid and precise footprint assessment with correct diagnoses, as well as a record for future assessments, and being economically viable in countries with people having low socio-economic status.","PeriodicalId":37519,"journal":{"name":"Periodicals of Engineering and Natural Sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49542091","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

Investigation of Groundwater Zooplankton Fauna from Water Wells in Kilis Province from Türkiye 基利斯省采井地下水浮游动物区系调查

Periodicals of Engineering and Natural Sciences Pub Date : 2023-06-10 DOI: 10.28978/nesciences.1338127

Ã. Bozkurt

引用次数: 0

Occurrence of the Scalloped Ribbonfish Zu cristatus (Lampridiformes) in the Gulf of Antalya, Türkiye 土耳其安塔利亚湾扇贝带鱼的分布

Periodicals of Engineering and Natural Sciences Pub Date : 2023-06-05 DOI: 10.28978/nesciences.1338121

F. Cagiltay, Erkan Biçer, Alper Yildiz, M. Gökoğlu

引用次数: 0

Evaluation of Antimicrobial Activities of Salvia verbenaca 马鞭草的抗菌活性评价

Periodicals of Engineering and Natural Sciences Pub Date : 2023-06-03 DOI: 10.28978/nesciences.1309249

G. Dulger, B. Dulger

引用次数: 1

Profile of digital literacy of mathematics education students in online learning and its relationship with learning motivation 在线学习数学教育学生数字素养概况及其与学习动机的关系

Periodicals of Engineering and Natural Sciences Pub Date : 2023-05-30 DOI: 10.21533/pen.v11i3.3537

R. Rusli, Abdul Rahman, Hastuty Musa, M. Botto-Tobar, Rahmat Hidayat

引用次数: 0

Road conditions monitoring using semantic segmentation of smartphone motion sensor data 基于智能手机运动传感器数据语义分割的路况监测

Periodicals of Engineering and Natural Sciences Pub Date : 2023-05-24 DOI: 10.21533/pen.v11i3.3608

E. Mahmood, Nizar Zaghden, M. Mejdoub

{"title":"Road conditions monitoring using semantic segmentation of smartphone motion sensor data","authors":"E. Mahmood, Nizar Zaghden, M. Mejdoub","doi":"10.21533/pen.v11i3.3608","DOIUrl":"https://doi.org/10.21533/pen.v11i3.3608","url":null,"abstract":"Many studies and publications have been written about the use of moving object analysis to locate a specific item or replace a lost object in video sequences. Using semantic analysis, it could be challenging to pinpoint each meaning and follow the movement of moving objects. Some machine learning algorithms have turned to the right interpretation of photos or video recordings to communicate coherently. The technique converts visual patterns and features into visual language using dense and sparse optical flow algorithms. To semantically partition smartphone motion sensor data for any video categorization, using integrated bidirectional Long Short-Term Memory layers, this paper proposes a redesigned U-Net architecture. Experiments show that the proposed technique outperforms several existing semantic segmentation algorithms using z-axis accelerometer and z-axis gyroscope properties. The video sequence's numerous moving elements are synchronised with one another to follow the scenario. Also, the objective of this work is to assess the proposed model on roadways and other moving objects using five datasets (self-made dataset and the pothole600 dataset). After looking at the map or tracking an object, the results should be given together with the diagnosis of the moving object and its synchronization with video clips. The suggested model's goals were developed using a machine learning method that combines the validity of the results with the precision of finding the necessary moving parts. Python 3.7 platforms were used to complete the project since they are user-friendly and highly efficient platforms.","PeriodicalId":37519,"journal":{"name":"Periodicals of Engineering and Natural Sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47289417","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

Enhancing smart home energy efficiency through accurate load prediction using deep convolutional neural networks 利用深度卷积神经网络进行准确的负荷预测，提高智能家居能源效率

Periodicals of Engineering and Natural Sciences Pub Date : 2023-05-22 DOI: 10.21533/pen.v11i3.3606

Suaad M. Saber, Geehan Sabah Hassan, Mohanad Sameer Jabbar, Jamal Fadhil Tawfeq, Ahmed Dheyaa Radhi, Poh Soon JosephNg

{"title":"Enhancing smart home energy efficiency through accurate load prediction using deep convolutional neural networks","authors":"Suaad M. Saber, Geehan Sabah Hassan, Mohanad Sameer Jabbar, Jamal Fadhil Tawfeq, Ahmed Dheyaa Radhi, Poh Soon JosephNg","doi":"10.21533/pen.v11i3.3606","DOIUrl":"https://doi.org/10.21533/pen.v11i3.3606","url":null,"abstract":"The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical energy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute parameters of electrical energy consumption. The method considers the timeseries homes of the information and offers parallelization of large-scale facts processing with magnificent operational efficiency, considering the timeseries aspects of the information and the problematic inherent correlations between variables. The exams have been done using the UCI public dataset, and the experimental findings validate the method's efficacy, which has clear, sensible implications for setting up intelligent strength grid dispatching.","PeriodicalId":37519,"journal":{"name":"Periodicals of Engineering and Natural Sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41471351","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