Pub Date : 2022-12-01DOI: 10.33899/edusj.2022.134830.1264
Awadh Al-Luhaiby, R. Rasool
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.
{"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}
Pub Date : 2022-12-01DOI: 10.33899/edusj.2022.135381.1269
Mustafa Aljaff
{"title":"Optimal Parameters for Spatial Distribution Modeling of Global Horizontal Solar Radiation in Iraq","authors":"Mustafa Aljaff","doi":"10.33899/edusj.2022.135381.1269","DOIUrl":"https://doi.org/10.33899/edusj.2022.135381.1269","url":null,"abstract":"","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":"45001984","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}
Pub Date : 2022-09-01DOI: 10.33899/edusj.2022.134274.1252
Ahmed H. AL-Hamdani
{"title":"Study of the Physico-chemical properties of groundwater for some villages north of Mosul city","authors":"Ahmed H. AL-Hamdani","doi":"10.33899/edusj.2022.134274.1252","DOIUrl":"https://doi.org/10.33899/edusj.2022.134274.1252","url":null,"abstract":"","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":"43220519","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}
Pub Date : 2022-09-01DOI: 10.33899/edusj.2022.133845.1238
Mohamed Y. Dhamra, Theia’a N. Al-Sabha, Mohammed S. Al-Enizzi
A sensitive fluorometric method, with few steps and suitable for the daily routine, was made for examining adrenaline hydrochloride and dopamine hydrochloride. The reliance in this paper was on the nucleophilic substitution interaction of the mentioned drugs with 1,2-naphthoquinone sulfonate (NQS) in an aqueous pH 6 to give a fluorescent product with a maximum emission wave at ʎ em 471 nm after being excited at a maximum excitation wave at ʎ ex 300 nm. The plots have complied within the range of 0.01- 4.0, 0.01-2 µg/ml, and The detection limits (0.0062, 0.0027) and quantitation limits were (0.0207, 0.0091) µg/ml, for adrenaline and dopamine respectively. The accuracy (% recovery) was between (99.21% - 100.72%) and the relative standard deviation (RSD%) is better than 0.95%. It was also found that the formed product was in a ratio of 1:2 reagent to the drug. The estimation of adrenaline and dopamine has been successfully tested on the injection, and it is in good agreement with its approved value and with that of the British Pharmacopoeia method.
建立了一种灵敏、简便、适用于日常生活的盐酸肾上腺素和盐酸多巴胺荧光检测方法。本文的依赖性在于上述药物与1,2-萘醌磺酸盐（NQS）在pH 6的水溶液中的亲核取代相互作用，在以ʎex 300nm的最大激发波激发后，产生在654 em 471nm具有最大发射波的荧光产物。曲线符合0.01-4.0、0.01-2µg/ml的范围，肾上腺素和多巴胺的检测限（0.0062、0.0027）和定量限分别为（0.0207、0.0091）µg/ml。准确度（%回收率）在99.21%-100.72%之间，相对标准偏差（RSD%）优于0.95%。肾上腺素和多巴胺的测定已在该注射液上成功进行，与批准值和英国药典方法的测定值吻合良好。
{"title":"Spectrofluorimetric determination of adrenaline and dopamine .","authors":"Mohamed Y. Dhamra, Theia’a N. Al-Sabha, Mohammed S. Al-Enizzi","doi":"10.33899/edusj.2022.133845.1238","DOIUrl":"https://doi.org/10.33899/edusj.2022.133845.1238","url":null,"abstract":"A sensitive fluorometric method, with few steps and suitable for the daily routine, was made for examining adrenaline hydrochloride and dopamine hydrochloride. The reliance in this paper was on the nucleophilic substitution interaction of the mentioned drugs with 1,2-naphthoquinone sulfonate (NQS) in an aqueous pH 6 to give a fluorescent product with a maximum emission wave at ʎ em 471 nm after being excited at a maximum excitation wave at ʎ ex 300 nm. The plots have complied within the range of 0.01- 4.0, 0.01-2 µg/ml, and The detection limits (0.0062, 0.0027) and quantitation limits were (0.0207, 0.0091) µg/ml, for adrenaline and dopamine respectively. The accuracy (% recovery) was between (99.21% - 100.72%) and the relative standard deviation (RSD%) is better than 0.95%. It was also found that the formed product was in a ratio of 1:2 reagent to the drug. The estimation of adrenaline and dopamine has been successfully tested on the injection, and it is in good agreement with its approved value and with that of the British Pharmacopoeia method.","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":"41929201","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}
Pub Date : 2022-09-01DOI: 10.33899/edusj.2022.133867.1240
Teba Ali Jasem Ali, M. Jawhar
: At the present time, the reliance on computers is increasing in all aspects of life, so it is necessary to protect computer networks and computing resources from complex attacks against the network. This is performed by building tools, applications, and systems that detect attacks or anomalies adapting to ever-changing architectures and dynamically changing threats. The goal of this paper is to build a Network Intrusion Detection System (NIDS) based on deep learning techniques such as Convolutional Neural Network (CNN), which demonstrated its efficiency in predicting, classifying, and extracting high-level features in network traffic.
{"title":"Proposing a Model for Detecting Intrusion Network Attacks Using Machine Learning Techniques","authors":"Teba Ali Jasem Ali, M. Jawhar","doi":"10.33899/edusj.2022.133867.1240","DOIUrl":"https://doi.org/10.33899/edusj.2022.133867.1240","url":null,"abstract":": At the present time, the reliance on computers is increasing in all aspects of life, so it is necessary to protect computer networks and computing resources from complex attacks against the network. This is performed by building tools, applications, and systems that detect attacks or anomalies adapting to ever-changing architectures and dynamically changing threats. The goal of this paper is to build a Network Intrusion Detection System (NIDS) based on deep learning techniques such as Convolutional Neural Network (CNN), which demonstrated its efficiency in predicting, classifying, and extracting high-level features in network traffic.","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":"45205234","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}
Pub Date : 2022-09-01DOI: 10.33899/edusj.2022.133858.1239
Mostafa Y. Ismail, Hussein Saber Mohammed ali
: 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.
{"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}
Pub Date : 2022-09-01DOI: 10.33899/edusj.2022.134024.1245
A. Ali, Nada Nimat Saleem
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?”.
{"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}
Pub Date : 2022-09-01DOI: 10.33899/edusj.2022.133711.1236
Ahmed Alkaddo, Dujan Albaqal
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.
{"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}
Pub Date : 2022-09-01DOI: 10.33899/edusj.2022.134166.1249
S. Ibrahim, G. Dhaher
. This paper deals with the spatial prediction in Geostatistics. This paper depend on interpellation methods of spatial statistic (ordinary kriging technique) to combination with fuzzy logic under uncertainty for spatial data prediction. This work includes the best linear unbiased estimator prediction by using formals of linear prediction and variance kriging to find prediction by Appling on real spatial data. The data adopted from real spatial data represented the depth of real underground water wells with real location from Mosul city/Iraq. We took (100) real data with locations in study area. We applied empiricism variogram function to get the properties of variogram function. We combination between kriging technique with fuzzy logic (Mamdani Fuzzy Model). To get the best Mathematical model under uncertainty. We getting the results between kriging and fuzzy logic using Matlab language.This study is a continuation of the research conducted in this context Which is very important to highlight.
{"title":"Combination of Fuzzy Logic and Kriging Technique Under Uncertainty for Spatial Data Prediction","authors":"S. Ibrahim, G. Dhaher","doi":"10.33899/edusj.2022.134166.1249","DOIUrl":"https://doi.org/10.33899/edusj.2022.134166.1249","url":null,"abstract":". This paper deals with the spatial prediction in Geostatistics. This paper depend on interpellation methods of spatial statistic (ordinary kriging technique) to combination with fuzzy logic under uncertainty for spatial data prediction. This work includes the best linear unbiased estimator prediction by using formals of linear prediction and variance kriging to find prediction by Appling on real spatial data. The data adopted from real spatial data represented the depth of real underground water wells with real location from Mosul city/Iraq. We took (100) real data with locations in study area. We applied empiricism variogram function to get the properties of variogram function. We combination between kriging technique with fuzzy logic (Mamdani Fuzzy Model). To get the best Mathematical model under uncertainty. We getting the results between kriging and fuzzy logic using Matlab language.This study is a continuation of the research conducted in this context Which is very important to highlight.","PeriodicalId":33491,"journal":{"name":"mjl@ ltrby@ wl`lm","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69838410","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}
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