Vol 4 Issue 1最新文献_第2页

Performance Evaluation of Classification Algorithms for Intrusion Detection on NSL-KDD Using Rapid Miner 基于快速Miner的NSL-KDD入侵检测分类算法性能评价

Vol 4 Issue 1 Pub Date : 2022-02-19 DOI: 10.33411/ijist/2022040110

Zoraez Ashfaq Malik, Marriam Siddique, Z. J. Paracha, Azhar Imran, Amanullah Yasin, Abdul Hameed Butt

引用次数: 3

Non-invasive EEG based Feature Extraction framework for Major Depressive Disorder analysis 基于无创脑电图特征提取框架的重度抑郁症分析

Vol 4 Issue 1 Pub Date : 2022-02-13 DOI: 10.33411/ijist/2022040108

N. Bashir, Sanam Narejo, Bushra Naz, Mohammad Moazzam Jawed, Shahnawaz Talpur, Khurshid Aliev

{"title":"Non-invasive EEG based Feature Extraction framework for Major Depressive Disorder analysis","authors":"N. Bashir, Sanam Narejo, Bushra Naz, Mohammad Moazzam Jawed, Shahnawaz Talpur, Khurshid Aliev","doi":"10.33411/ijist/2022040108","DOIUrl":"https://doi.org/10.33411/ijist/2022040108","url":null,"abstract":"Depression and several other behavioral health disorders are serious public health concerns worldwide. Persistent behavioral health issues have a wide range of consequences that affect people personally, culturally and socially. Major depressive disorder (MDD) is a psychiatric ailment that affects people of all ages worldwide. It has grown into a major global health issue as well as an economic burden. Clinicians are using several medications to limit the growth of this disease at an early stage in young people. The goal of this research is to improve the depression diagnosis by altering Electroencephalogram (EEG) signals and extracting the Differential Entropy (DE) and Power Spectral Density (PSD), using machine learning and deep learning techniques. This study analyzed the EEG signals of 30 healthy people and 34 people with Major Depressive Disorder (MDD). K-nearest neighbors (KNN) had the highest accuracy among machine learning algorithms of 99.7%, while Support vector machine (SVM) had acquired 95.7% accuracy. The developed Deep Learning approach, convolution neural network (CNN), achieved 99.6% accuracy. With these promising results, this study establishes the viability of an Electroencephalogram based diagnosis of MDD.","PeriodicalId":243222,"journal":{"name":"Vol 4 Issue 1","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117310631","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

Tomato Disease Classification using Fine-Tuned Convolutional Neural Network 基于精细卷积神经网络的番茄病害分类

Vol 4 Issue 1 Pub Date : 2022-02-13 DOI: 10.33411/ijist/2022040109

Haseeb Younis, Muhammad Asad Arshed, Fawad Ul Hassan, M. Khurshid, Hadia Ghassan

{"title":"Tomato Disease Classification using Fine-Tuned Convolutional Neural Network","authors":"Haseeb Younis, Muhammad Asad Arshed, Fawad Ul Hassan, M. Khurshid, Hadia Ghassan","doi":"10.33411/ijist/2022040109","DOIUrl":"https://doi.org/10.33411/ijist/2022040109","url":null,"abstract":"Tomatoes have enhanced vitamins that are necessary for mental and physical health. We use tomatoes in our daily life. The global agricultural industry is dominated by vegetables. Farmers typically suffer a significant loss when tomato plants are affected by multiple diseases. Diagnosis of tomato diseases at an early stage can help address this deficit. It is difficult to classify the attacking disease due to its range of manifestations. We can use deep learning models to identify diseased plants at an initial stage and take appropriate measures to minimize loss through early detection. For the initial diagnosis and classification of diseased plants, an effective deep learning model has been proposed in this paper. Our deep learning-based pre-trained model has been tuned twofold using a specific dataset. The dataset includes tomato plant images that show diseased and healthy tomato plants. In our classification, we intend to label each plant with the name of the disease or healthy that is afflicting it. With 98.93% accuracy, we were able to achieve astounding results using the transfer learning method on this dataset of tomato plants. Based on our understanding, this model appears to be lighter than other advanced models with such considerable results and which employ ten classes of tomatoes. This deep learning application is usable in reality to detect plant diseases.","PeriodicalId":243222,"journal":{"name":"Vol 4 Issue 1","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115895673","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

Assessment and Monitoring of VIIRS-DNB and SQML-L light Pollution in Lahore-Pakistan 巴基斯坦拉合尔地区VIIRS-DNB和SQML-L光污染评价与监测

Vol 4 Issue 1 Pub Date : 2022-02-10 DOI: 10.33411/ijist/2022040107

H. Nisar, Faiza Sarwar, S. A. Shirazi, Dania Amjad, Rana Waqar Aslam

{"title":"Assessment and Monitoring of VIIRS-DNB and SQML-L light Pollution in Lahore-Pakistan","authors":"H. Nisar, Faiza Sarwar, S. A. Shirazi, Dania Amjad, Rana Waqar Aslam","doi":"10.33411/ijist/2022040107","DOIUrl":"https://doi.org/10.33411/ijist/2022040107","url":null,"abstract":"The usage of artificial light is excessive and improper. Earth's night picture has changed significantly from space and studies have shown that over-exposure to artificial light in the night can influence animals, the environment and human beings. The purpose of this study was to monitor and measure skylights of Lahore City and temporary light pollution from 2012-2019. The Suite-Day/Night band of the Visible Image Radiometer was used for time changes analysis with GIS and Remote Sensing tools. Indicators were established as a table tool through zonal statistics, and a field survey was also undertaken to measure the Sky-Glow of Lahore with Sky Quality Meter-L. The results suggest that from 2012 to 2019, light pollution rose by 23.43 percent. Results suggest that around 53.99% of Lahore suffered from light pollution. The number of lights in Lahore has increased by 161.82 percent between 2012 and 2019. In the study period, the mean night light and the standard night light deviation were 127.87 and 98.22 percent, respectively. Lahore's night sky was heavily polluted by light. Lahore's average skylight is 17.15 meters above sea level, which means low quality skies at night. This research aims to provide people an insight into light pollution and the causes of local light pollution. Furthermore, this study aims to enhance public attention to light pollution mitigation attempts by governments and politicians.","PeriodicalId":243222,"journal":{"name":"Vol 4 Issue 1","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134186218","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: 3

Health Implications of Arsenic and Qualitative Deterioration of drinking Water from Underground Water Supply Lines of Lahore, Pakistan 巴基斯坦拉合尔地下供水线饮用水砷对健康的影响及水质恶化

Vol 4 Issue 1 Pub Date : 2022-02-04 DOI: 10.33411/ijist/2022040106

Hammad Mehmood, Rana Waqar Aslam, Allauddin Kakar, Waqas Abbas, Kanwal Javid, Muhammad Burhan Khalid, Muhammad Mohsin Tahir

{"title":"Health Implications of Arsenic and Qualitative Deterioration of drinking Water from Underground Water Supply Lines of Lahore, Pakistan","authors":"Hammad Mehmood, Rana Waqar Aslam, Allauddin Kakar, Waqas Abbas, Kanwal Javid, Muhammad Burhan Khalid, Muhammad Mohsin Tahir","doi":"10.33411/ijist/2022040106","DOIUrl":"https://doi.org/10.33411/ijist/2022040106","url":null,"abstract":"The study is a comparative analysis of water quality among two variant areas of Lahore. There are several problems regarding drinking water facilities. Drinkable water can be contaminated due to various reasons. Thus, the study highlights infrastructural causes (material of pipes and outdated pipes) of water contamination. Wall City and Gulberg are the study areas of this research. Gulberg area is far much better in various terms as compared to the wall city. Under this study, four parameters were selected for water quality pH, Total dissolved solids, E.coli and Arsenic. There were 13 water samples collected from each study area by random sampling. Samples were tested on the latest footing in this field. All results validate the problematic statement and highlight severe health effects. The results of these four parameters were far above the water quality standards declared by World Health Organization. Causes of these severe results include the outdated water pipes that are being laid down for the past several decades, for example Wall City area, etc. Results also depict low values in the Gulberg area which is recently developed as compared to the wall city. The comparative study also attests problem statement of the study.","PeriodicalId":243222,"journal":{"name":"Vol 4 Issue 1","volume":"705 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128103009","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

Role of Microbes in Modern Food Industry 微生物在现代食品工业中的作用

Vol 4 Issue 1 Pub Date : 2022-01-28 DOI: 10.33411/ijist/2022040105

Sumaira Mazhar, R. Yasmeen, Afeefa Chaudhry, Khadija Summia, M. Ibrar, Sadia Amjad, Ehtisham Ali

引用次数: 1

Spatial Patterns of LRTI among Children in Lahore 拉合尔地区儿童LRTI的空间格局

Vol 4 Issue 1 Pub Date : 2022-01-28 DOI: 10.33411/ijist/2022040104

Shaista Manaf, Dr. Ibtisam Butt

{"title":"Spatial Patterns of LRTI among Children in Lahore","authors":"Shaista Manaf, Dr. Ibtisam Butt","doi":"10.33411/ijist/2022040104","DOIUrl":"https://doi.org/10.33411/ijist/2022040104","url":null,"abstract":"Lower Respiratory Tract Infection (LRTI) is the leading global cause of morbidity and mortality in children of 1 month in developing countries. The aim of this research was to examine the spatial patterns of children under LRTI in Lahore, Pakistan. The records of all patients of LRTIs among children <5 years, admitted in the four different public sector hospitals of Lahore from 2017-2021 were analyzed. The collected data was processed and analyzed in SPSS 22.0 for the chi-square test (P<0.0.5), Multiple linear regression and ANOVA were calculated to assess the association of these variables. Town-wise distribution of diseases was mapped in ArcGIS 10.5. There were 2,609 pediatrics patients admitted and major cases in the year 2021. All the patients were distributed in four age groups, <2m, 2-12m, 13-24m, 25-60m. The most common diagnosis was Bronchopneumonia with (77.50%), Bronchiolitis (11.84%), Pneumonia (6.86%), and Bronchitis (3.79%). A significant increasing trend was found in Bronchopneumonia. In town-wise analysis, out of 2,609 patients, 977 patients were observed in Allama Iqbal Town. The peak season of the disease was seen in winter Dec-Feb. LRTI is a leading cause of childhood hospitalization in Lahore, Pakistan. These results may guide health authorities to determine where and when to effectively allocate resources for the prevention and control of LRTI.","PeriodicalId":243222,"journal":{"name":"Vol 4 Issue 1","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129605207","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

Realization of Presentation layer information of Legacy Java Enterprise Applications Through Design Pattern’s Recovery 通过设计模式的恢复实现遗留Java企业应用程序的表示层信息

Vol 4 Issue 1 Pub Date : 2022-01-26 DOI: 10.33411/ijist/2022040103

Zaigham Mushtaq, G. Rasool

{"title":"Realization of Presentation layer information of Legacy Java Enterprise Applications Through Design Pattern’s Recovery","authors":"Zaigham Mushtaq, G. Rasool","doi":"10.33411/ijist/2022040103","DOIUrl":"https://doi.org/10.33411/ijist/2022040103","url":null,"abstract":"The presentation layer is the outermost layer of an application that provides user interface and communication services. This layer is responsible for session management, controlling client access, and validations within data from the client .In legacy enterprise applications like Java Enterprise Edition Platform (Java EE),the design considerations of the presentation layer are spread over different design patterns and cross-language constructs. Resultantly, the analysis of such applications becomes quite challenging due to their heterogeneity, essentially required for the extraction of design-level information and further modernization. In this research ,a flexible technique is presented to extract presentation tier information based on customizable feature types by recovering instances of presentation tier patterns of the Java Enterprise Edition Platform. The proposed approach is evaluated on well-operative open-source Enterprise Applications. The validation results demonstrate the extraction of presentation tier information through Design Pattern’s recovery.This prototype is validated on the repository of source code of Java applications as well on open source java applications.","PeriodicalId":243222,"journal":{"name":"Vol 4 Issue 1","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133993317","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 Review on Transformation of Monolithic Applications towards Microservices Environment 单片应用向微服务环境的转变综述

Vol 4 Issue 1 Pub Date : 2022-01-22 DOI: 10.33411/ijist/2022040101

Zaigham Mushtaq, Najia Saher, Faisal Shazad, Sana Iqbal, Anam Qasim

{"title":"A Review on Transformation of Monolithic Applications towards Microservices Environment","authors":"Zaigham Mushtaq, Najia Saher, Faisal Shazad, Sana Iqbal, Anam Qasim","doi":"10.33411/ijist/2022040101","DOIUrl":"https://doi.org/10.33411/ijist/2022040101","url":null,"abstract":"The traditional monolithic approach is widely employed in centralized software development, deployment, and reusability, as the modules are tightly connected, causing several challenges in programming. The study utilized different techniques for the easy transformation of several running monolithic applications to micro services including, Angular 2, REST API, Web application and several other architectural approaches are discussed. This review paper highlights the significance of microservices and the transformation of monolithic applications towards microservices. As multiple software applications are an integral part of a traditional monolithic application, the modules cannot be extended separately, and different modules cannot use various technology stacks. So, monolithic source code must be migrated to the microservice platform in order to extend `the lifecycle of applications in today's environment. However, due to structural complexity, scattered application logic, and dependency upon external framework libraries, the transformation towards a microservices platform is quite challenging. A Microservice architecture is a container of loosely coupled independent services making a flexible system. In this study, potential areas for the transformation of monolithic application source code are highlighted. Furthermore, key challenges and open research issues in this area are highlighted, requiring the research community's attention. The study concludes that Microservices are not a one-size-fits-all solution for every challenging situation. Monolithic transformation requires significant amount of time and effort on the part of everyone in the business.","PeriodicalId":243222,"journal":{"name":"Vol 4 Issue 1","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133449013","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 Deep Learning Framework for Multi Drug Side Effects Prediction with Drug Chemical Substructure 基于药物化学子结构的多药物副作用预测的深度学习框架

Vol 4 Issue 1 Pub Date : 2022-01-22 DOI: 10.33411/ijist/2022040102

Muhammad Asad Arshed, Shahzad Mumtaz, O. Riaz, Waqas Sharif, Saima Abdullah

{"title":"A Deep Learning Framework for Multi Drug Side Effects Prediction with Drug Chemical Substructure","authors":"Muhammad Asad Arshed, Shahzad Mumtaz, O. Riaz, Waqas Sharif, Saima Abdullah","doi":"10.33411/ijist/2022040102","DOIUrl":"https://doi.org/10.33411/ijist/2022040102","url":null,"abstract":"Nowadays, side effects and adverse reactions of drugs are considered the major concern regarding public health. In the process of drug development, it is also considered the main cause of drug failure. Due to the major side effects, drugs are withdrawan from the market immediately. Therefore, in the drug discovery process, the prediction of side effects is a basic need to control the drug development cost and time as well as launching of an effective drug in the market in terms of patient health recovery. In this study, we have proposed a deep learning model named “DLMSE” for the prediction of multiple side effects of drugs with the chemical structure of drugs. As it is a common experience that a single drug can cause multiple side effects, that’s why we have proposed a deep learning model that can predict multiple side effects for a single drug. We have considered three side effects (Dizziness, Allergy, Headache) in this study. We have collected the drug side effects information from the SIDER database. We have achieved an accuracy of ‘0.9494’ with our multi-label classification based proposed model. The proposed model can be used in different stages of the drug development process.","PeriodicalId":243222,"journal":{"name":"Vol 4 Issue 1","volume":"58 1-2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133070930","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