mjl@ ltrby@ wl`lm最新文献_第6页

Studying the effect of temperature and resistances of series (Rs) and parallel (Rsh) on the performance of the solar cell (FTO/Zn2SnO4/CdS:O/CdTe/Cu2Te) using the SCAPS-1D program 利用SCAPS-1D程序研究了串联(Rs)和并联(Rsh)温度和电阻对FTO/Zn2SnO4/CdS:O/CdTe/Cu2Te太阳能电池性能的影响

mjl@ ltrby@ wl`lm Pub Date : 2022-12-01 DOI: 10.33899/edusj.2022.134830.1264

Awadh Al-Luhaiby, R. Rasool

{"title":"Studying the effect of temperature and resistances of series (Rs) and parallel (Rsh) on the performance of the solar cell (FTO/Zn2SnO4/CdS:O/CdTe/Cu2Te) using the SCAPS-1D program","authors":"Awadh Al-Luhaiby, R. Rasool","doi":"10.33899/edusj.2022.134830.1264","DOIUrl":"https://doi.org/10.33899/edusj.2022.134830.1264","url":null,"abstract":"For the purpose of knowing the effect of temperature, series resistance and parallel resistance on the performance of the solar cell (FTO/ Zn 2 SnO 4 / CdS:O/ CdTe/ Cu 2 Te) ، Using the simulation program SCAPS-1D, the study was carried out in three stages. The first stage of this study is to study the effect of temperature on the parameters of the solar cell ، It was found that the efficiency  decreases with increasing temperature . The second stage is to study the effect of series resistance (R s ) as an external factor and it was found that increasing the series resistance reduces the performance of the solar cell The third stage of the study is to study the effect of parallel resistance (R sh ) as an external factor as well on the performance of the solar cell. It was also found that increasing the parallelism resistance improves the performance of the solar cell and increases the output parameters. All phases of the study were installed by installing the default lighting spectrum on the global scale Am1.5, the temperature is 300K, the frequency is 1MHz, and the voltage is 0V. Also, the series resistance (R s ) and the parallel resistance (R sh ) were not activated in the first stage of the research, considering that the cell is an ideal cell.","PeriodicalId":33491,"journal":{"name":"mjl@ ltrby@ wl`lm","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41972649","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

Optimal Parameters for Spatial Distribution Modeling of Global Horizontal Solar Radiation in Iraq 伊拉克全球水平太阳辐射空间分布模拟的最优参数

mjl@ ltrby@ wl`lm Pub Date : 2022-12-01 DOI: 10.33899/edusj.2022.135381.1269

Mustafa Aljaff

引用次数: 0

Study of the Physico-chemical properties of groundwater for some villages north of Mosul city 摩苏尔市北部一些村庄地下水物理化学性质的研究

mjl@ ltrby@ wl`lm Pub Date : 2022-09-01 DOI: 10.33899/edusj.2022.134274.1252

Ahmed H. AL-Hamdani

引用次数: 0

Spectrofluorimetric determination of adrenaline and dopamine . 肾上腺素和多巴胺的荧光光谱测定。

mjl@ ltrby@ wl`lm Pub Date : 2022-09-01 DOI: 10.33899/edusj.2022.133845.1238

Mohamed Y. Dhamra, Theia’a N. Al-Sabha, Mohammed S. Al-Enizzi

引用次数: 0

Medical Images Classification Using Artificial Intelligence 基于人工智能的医学图像分类

mjl@ ltrby@ wl`lm Pub Date : 2022-09-01 DOI: 10.33899/edusj.2022.133358.1224

Tasneem Mustafa, J. Alneamy

引用次数: 0

Proposing a Model for Detecting Intrusion Network Attacks Using Machine Learning Techniques 提出一种利用机器学习技术检测入侵网络攻击的模型

mjl@ ltrby@ wl`lm Pub Date : 2022-09-01 DOI: 10.33899/edusj.2022.133867.1240

Teba Ali Jasem Ali, M. Jawhar

引用次数: 0

Pollution by crude oil and used engine oil and their impact on growth and concentration of some nutrients elements of flax and safflower plants. 原油和废机油的污染及其对亚麻和红花植物生长和某些营养元素浓度的影响。

mjl@ ltrby@ wl`lm Pub Date : 2022-09-01 DOI: 10.33899/edusj.2022.133858.1239

Mostafa Y. Ismail, Hussein Saber Mohammed ali

{"title":"Pollution by crude oil and used engine oil and their impact on growth and concentration of some nutrients elements of flax and safflower plants.","authors":"Mostafa Y. Ismail, Hussein Saber Mohammed ali","doi":"10.33899/edusj.2022.133858.1239","DOIUrl":"https://doi.org/10.33899/edusj.2022.133858.1239","url":null,"abstract":": This study aims to show the effect of soil contamination with crude oil and its derivatives on the dry weight and Nutrient minerals on flax ( Linum usitatissimum L.) and safflower ( Carthamus tinctorius L.). This experiment was carried out in plastic pots and under Plastic house conditions, the treatment was carried out with crude oil, used car's engine oil and used generator's engine oil at three concentrations 1-2-3% for each treatment, in addition to the comparison treatment. The results showed a significant decrease in the dry weight of the shoot systems of flax and safflower when treated with crude oil at a concentration of 3% amounted to 0.043-0.124 g, respectively, and the dry weight of the root systems amounted to 0.022-0.015 g, respectively. There was also a significant decrease in the concentration of calcium in the shoot system of flax and safflower plants when treated with crude oil and used generator oil at a concentration of 3% amounted to (1,900-1.950) mgg, respectively. The calcium concentration has also decreased in the root system of flax and safflower plants when treated with used generator and car oil at the concentration 3% amounted to 1.500-1.600 mgg, respectively. Potassium concentration decreased in the shoot and root systems of flax and safflower plants when treated with generator engine oil and crude oil at a concentration of 3% and reached 6.900-10.45 and 4.150-8.800 mgg, respectively, compared to the control treatment and other treatments.","PeriodicalId":33491,"journal":{"name":"mjl@ ltrby@ wl`lm","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41818412","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 Software Systems attributes based on quality factors using linguistic knowledge and machine learning: A review. 基于语言知识和机器学习的质量因素的软件系统属性分类:综述。

mjl@ ltrby@ wl`lm Pub Date : 2022-09-01 DOI: 10.33899/edusj.2022.134024.1245

A. Ali, Nada Nimat Saleem

{"title":"Classification of Software Systems attributes based on quality factors using linguistic knowledge and machine learning: A review.","authors":"A. Ali, Nada Nimat Saleem","doi":"10.33899/edusj.2022.134024.1245","DOIUrl":"https://doi.org/10.33899/edusj.2022.134024.1245","url":null,"abstract":"Both the functionality and the non-functionality for what the software system does and does not do within software systems requirements are documented in a Software Requirements Specification (SRS). In requirements engineering, system requirements classify into several categories such as functional, quality and constraint classes. Therefore, we evaluate several machine learning approaches as well as methodologies mentioned in previous literature in terms of automatic requirements extraction, then classification is performed based on methodically reviewing many previous works on software requirements classification to assist software engineers in selecting the best requirement classification technique. The study aims to obtain answers for several questions: “What were machine learning algorithms used for the classification process of the requirements?”, “How do these algorithms work and how are they evaluated?”, “What methods were used for extracting features from a text?”, “What evaluation criteria were used in comparing results?”, and “Which machine learning techniques and methods provided the highest accuracy?”.","PeriodicalId":33491,"journal":{"name":"mjl@ ltrby@ wl`lm","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41691276","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

Implementation of OCR using Convolutional Neural Network (CNN): A Survey 使用卷积神经网络（CNN）实现OCR：综述

mjl@ ltrby@ wl`lm Pub Date : 2022-09-01 DOI: 10.33899/edusj.2022.133711.1236

Ahmed Alkaddo, Dujan Albaqal

{"title":"Implementation of OCR using Convolutional Neural Network (CNN): A Survey","authors":"Ahmed Alkaddo, Dujan Albaqal","doi":"10.33899/edusj.2022.133711.1236","DOIUrl":"https://doi.org/10.33899/edusj.2022.133711.1236","url":null,"abstract":"Recently, character recognition and deep learning have caught the attention of many researchers. Optical Character Recognition (OCR) usually takes an image of the character as input and generates the identical character as output. The important role that OCR does is to transform printed materials into digital text files. Convolutional Neural Network (CNN) is an influential model that is generous with bright results in optical character recognition (OCR). The state-of-the-art performance which exists in deep neural networks is usually used to handle frequently recognition and classification problems. Many applications are using it, for instance, robotics, traffic monitoring, articles digitization, etc. CNN is designed to adaptively and automatically learn features by using many kinds of layers (convolution layers, pooling layers, and fully connected layers). In this paper we will go through the advantages and recent usage of CNN in OCR and why it’s important to use it in handwritten and printed text recognition and what subjects we can use this technique for. Researchers are progressively using CNN for the machine-printed characters and recognition of handwritten, that is because CNN architectures are suitable for recognition tasks by inputting some images.","PeriodicalId":33491,"journal":{"name":"mjl@ ltrby@ wl`lm","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45109049","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

Combination of Fuzzy Logic and Kriging Technique Under Uncertainty for Spatial Data Prediction 不确定条件下模糊逻辑和Kriging技术相结合的空间数据预测

mjl@ ltrby@ wl`lm Pub Date : 2022-09-01 DOI: 10.33899/edusj.2022.134166.1249

S. Ibrahim, G. Dhaher

引用次数: 1