Pub Date : 2021-03-24DOI: 10.33897/FUJEAS.V1I2.347
Naveed Akhtar
That dominance, in any case, has gotten to be a risk. On Sunday, Solar Winds alarmed thousands of its clients that an “outside country state” had found a back entryway into its most well-known item, an instrument called Orion that makes a difference organizations screen blackouts on their computer systems and servers. The company uncovered that programmers snuck a malevolent code that gave them inaccessible get to customers’ systems into an upgrade of Orion. The hack started as early as Walk, Solar Winds conceded, giving the programmers bounty of time to get to the customers’ inside workings. The breach was not found until the unmistakable cybersecurity company FireEye, which itself employments Solar Winds, decided it had experienced a breach through the program. FireEye has not freely faulted that breach on the Solar Winds hack, but it allegedly affirmed that was the case to the tech location Krebs On Security on Tuesday. FireEye depicted the malware’s bewildering capabilities, from at first lying torpid up to two weeks, to stowed away. That was December 13, 2020. FireEye gauges programmers to begin with picked up get to in Walk 2020. For about eight months, malevolent on-screen characters carted absent untold sums of touchy information from contaminated organizations — and the total scope of the breach is still unfolding. Despite Microsoft seizing the code’s command and control server (a common component in botnet assaults as well), a few security specialists think the assailants may still have get to the Solar Winds Orion program system. Others are conjecturing that these programmers cleared out behind extra, yet-to-be-seen malevolent code.
无论如何，这种主导地位已经成为一种风险。周日，太阳风公司提醒了成千上万的客户，一个“境外国家”找到了进入其最知名产品的后门。该产品名为“猎户座”(Orion)，可以让组织在电脑系统和服务器上屏蔽停电情况。该公司发现，程序员在Orion的升级中偷偷植入了一段恶意代码，使他们无法访问客户的系统。太阳风承认，黑客早在Walk就开始了，这给了程序员充足的时间进入客户的内部工作。直到网络安全公司火眼(FireEye)(它自己也雇佣了太阳风公司)认定它通过该项目遭遇了一次入侵，才发现了漏洞。火眼并没有自由地指责太阳风的黑客攻击，但据称它在周二向技术机构克雷布斯安全公司(Krebs on Security)证实了这一点。FireEye描述了该恶意软件令人困惑的能力，从一开始休眠到两周，再到隐藏起来。那是2020年12月13日。FireEye测量程序员从2020年开始到2020年。在大约8个月的时间里，屏幕上的恶意角色从受污染的组织中带走了数不清的敏感信息，而这次入侵的总体范围仍在扩大。尽管微软抓住了代码的命令和控制服务器(也是僵尸网络攻击的常见组件)，但一些安全专家认为攻击者可能仍然可以进入太阳风猎户座程序系统。其他人则猜测，这些程序员清除了额外的、尚未被发现的恶意代码。
{"title":"Latest trends in the Cybersecurity after the solar wind hacking attack","authors":"Naveed Akhtar","doi":"10.33897/FUJEAS.V1I2.347","DOIUrl":"https://doi.org/10.33897/FUJEAS.V1I2.347","url":null,"abstract":"That dominance, in any case, has gotten to be a risk. On Sunday, Solar Winds alarmed thousands of its clients that an “outside country state” had found a back entryway into its most well-known item, an instrument called Orion that makes a difference organizations screen blackouts on their computer systems and servers. The company uncovered that programmers snuck a malevolent code that gave them inaccessible get to customers’ systems into an upgrade of Orion. The hack started as early as Walk, Solar Winds conceded, giving the programmers bounty of time to get to the customers’ inside workings. The breach was not found until the unmistakable cybersecurity company FireEye, which itself employments Solar Winds, decided it had experienced a breach through the program. FireEye has not freely faulted that breach on the Solar Winds hack, but it allegedly affirmed that was the case to the tech location Krebs On Security on Tuesday. FireEye depicted the malware’s bewildering capabilities, from at first lying torpid up to two weeks, to stowed away. That was December 13, 2020. FireEye gauges programmers to begin with picked up get to in Walk 2020. For about eight months, malevolent on-screen characters carted absent untold sums of touchy information from contaminated organizations — and the total scope of the breach is still unfolding. Despite Microsoft seizing the code’s command and control server (a common component in botnet assaults as well), a few security specialists think the assailants may still have get to the Solar Winds Orion program system. Others are conjecturing that these programmers cleared out behind extra, yet-to-be-seen malevolent code.","PeriodicalId":36255,"journal":{"name":"Iranian Journal of Botany","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83960998","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 : 2021-03-22DOI: 10.33897/FUJEAS.V1I2.340
S. Hayat
A neural network (NN)-based method for phone number classification or recognition is provided in this paper. The used network is a one-hidden-layer multilayer perceptron (MLP) classifier. Its training is based on backpropagation learning. I present the results of a Feed Forward Neural Network trained to classify phone numbers into four categories: Different training data were pre-processed and then tested to distinguish between four classes/patterns of phone numbers in order to train the FFNN. My goal is to provide a coalescence of the published research in this field and to arouse further research interest in and efforts to research the identified topics.
{"title":"Phone numbers classificationwith feed-forward neural networks","authors":"S. Hayat","doi":"10.33897/FUJEAS.V1I2.340","DOIUrl":"https://doi.org/10.33897/FUJEAS.V1I2.340","url":null,"abstract":"A neural network (NN)-based method for phone number classification or recognition is provided in this paper. The used network is a one-hidden-layer multilayer perceptron (MLP) classifier. Its training is based on backpropagation learning. I present the results of a Feed Forward Neural Network trained to classify phone numbers into four categories: Different training data were pre-processed and then tested to distinguish between four classes/patterns of phone numbers in order to train the FFNN. My goal is to provide a coalescence of the published research in this field and to arouse further research interest in and efforts to research the identified topics.","PeriodicalId":36255,"journal":{"name":"Iranian Journal of Botany","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79794061","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 : 2021-03-22DOI: 10.33897/FUJEAS.V1I2.322
A. Khan
Any deprivation caused in the image signal can be thought as a noise. When any image signal is routed through wireless or wired medium it experiences deterioration because of channel characteristics. By knowing the type of noise interfered in the signal, we can use the pertinent filtering techniques to remove the noise from the image. Restoration of the image signal corrupted by noise is very essential for better communication. This paper provides the digital image handling techniques in MATLAB to restore the corrupted image. In this paper, different filtering methods have been discussed in the presence of two separate noise models that distort images. Four different techniques of filtering, ‘Mean/Average filtering', 'Median filtering', 'Adaptive median filtering' and 'Image Averaging' have been chosen against selected noise models. At the end of the paper we will compare which filtering technique works best for removing a particular noise.
{"title":"A comprehensive analysis of adaptive image restoration techniques in the presence of different noise models","authors":"A. Khan","doi":"10.33897/FUJEAS.V1I2.322","DOIUrl":"https://doi.org/10.33897/FUJEAS.V1I2.322","url":null,"abstract":"Any deprivation caused in the image signal can be thought as a noise. When any image signal is routed through wireless or wired medium it experiences deterioration because of channel characteristics. By knowing the type of noise interfered in the signal, we can use the pertinent filtering techniques to remove the noise from the image. Restoration of the image signal corrupted by noise is very essential for better communication. This paper provides the digital image handling techniques in MATLAB to restore the corrupted image. In this paper, different filtering methods have been discussed in the presence of two separate noise models that distort images. Four different techniques of filtering, ‘Mean/Average filtering', 'Median filtering', 'Adaptive median filtering' and 'Image Averaging' have been chosen against selected noise models. At the end of the paper we will compare which filtering technique works best for removing a particular noise.","PeriodicalId":36255,"journal":{"name":"Iranian Journal of Botany","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74996566","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 : 2020-12-21DOI: 10.22092/IJB.2020.342824.1281
محمدعلی قوامپور, سید عباس میرجلیلی, محمد جعفری, حسین آذرنیوند, سید اکبر جوادی
سرده Tamarix به دلیل عدم قطعیت تعداد گونهها، پراکنش و اهمیت اکولوژیکی در ایران، یکی از مهمترین موضوعات در ردهبندی تیره گز است. در این مطالعه، تنوع ژنتیکی و روابط خانوادگی 34 فرد از 8 جمعیت از 3 گونه Tamarix در استان اصفهان مورد بررسی قرار گرفت. ده آغازگر از نشانگر مولکولی CDDP برای بررسی تنوع ژنتیکی این سرده استفاده شد. 125 باند از ده آغازگر ایجاد شد، که از این تعداد 102 (16/80 درصد) چند شکلی بودند. آنالیز خوشهای جمعیتها را به سه گروه مجزا دستهبندی کرد. جریان بالای ژنی در میان گونههای Tamarix با استفاده از تجزیه و تحلیل PCoA تنوع زیادی در بین سه گونه Tamarix نشان داد، به طوری که نمونههای گونههای مختلف با هم گروهبندی شدند. تجزیه واریانس مولکولی نشان داد که تنوع ژنتیکی بین جمعیت (90٪) بیشتر از تنوع ژنتیکی درون جمعیت (10٪) است. بالاترین میانگین تنوع ژنتیکی نای (H) و شاخص تنوع شانون (I) در جمعیت حبیبآباد مشاهده شد. تجزیه و تحلیل دادهها نشان داد که صفات ریختشناختی و دادههای توالی DNA در سرده Tamarix کاملا با هم ارتباط ندارند، که میتواند با وجود تعداد زیاد دورگه بین گونهها و عدم تمایز ژنتیکی بین گونههای مورد مطالعه توجیه شود.
{"title":"تنوع ژنتیکی در میان جوامع گونههای گز با استفاده از نشانگر مولکولی CDDP","authors":"محمدعلی قوامپور, سید عباس میرجلیلی, محمد جعفری, حسین آذرنیوند, سید اکبر جوادی","doi":"10.22092/IJB.2020.342824.1281","DOIUrl":"https://doi.org/10.22092/IJB.2020.342824.1281","url":null,"abstract":"سرده Tamarix به دلیل عدم قطعیت تعداد گونهها، پراکنش و اهمیت اکولوژیکی در ایران، یکی از مهمترین موضوعات در ردهبندی تیره گز است. در این مطالعه، تنوع ژنتیکی و روابط خانوادگی 34 فرد از 8 جمعیت از 3 گونه Tamarix در استان اصفهان مورد بررسی قرار گرفت. ده آغازگر از نشانگر مولکولی CDDP برای بررسی تنوع ژنتیکی این سرده استفاده شد. 125 باند از ده آغازگر ایجاد شد، که از این تعداد 102 (16/80 درصد) چند شکلی بودند. آنالیز خوشهای جمعیتها را به سه گروه مجزا دستهبندی کرد. جریان بالای ژنی در میان گونههای Tamarix با استفاده از تجزیه و تحلیل PCoA تنوع زیادی در بین سه گونه Tamarix نشان داد، به طوری که نمونههای گونههای مختلف با هم گروهبندی شدند. تجزیه واریانس مولکولی نشان داد که تنوع ژنتیکی بین جمعیت (90٪) بیشتر از تنوع ژنتیکی درون جمعیت (10٪) است. بالاترین میانگین تنوع ژنتیکی نای (H) و شاخص تنوع شانون (I) در جمعیت حبیبآباد مشاهده شد. تجزیه و تحلیل دادهها نشان داد که صفات ریختشناختی و دادههای توالی DNA در سرده Tamarix کاملا با هم ارتباط ندارند، که میتواند با وجود تعداد زیاد دورگه بین گونهها و عدم تمایز ژنتیکی بین گونههای مورد مطالعه توجیه شود.","PeriodicalId":36255,"journal":{"name":"Iranian Journal of Botany","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87905282","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}
During a revision of the genus Cerastium L. in Iran, Cerastium ponticum Albov was identified and is reported as a new record from Iran and Flora Iranica area. Morphological characteristics, as well as a full description and distribution of the new record are provided. This taxon is also compared with its close relative species.
{"title":"گزارش جدید گونه Cerastium ponticum Albov برای فلور ایران","authors":"Katayoun Poursakhi, Mostafa Assadi, Farrokh Ghahremaninejad","doi":"10.22092/IJB.2020.343022.1282","DOIUrl":"https://doi.org/10.22092/IJB.2020.343022.1282","url":null,"abstract":"During a revision of the genus Cerastium L. in Iran, Cerastium ponticum Albov was identified and is reported as a new record from Iran and Flora Iranica area. Morphological characteristics, as well as a full description and distribution of the new record are provided. This taxon is also compared with its close relative species.","PeriodicalId":36255,"journal":{"name":"Iranian Journal of Botany","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83521944","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 : 2020-12-21DOI: 10.22092/IJB.2020.343548.1290
سیدرضا صفوی, محمد امینی راد
گونه جدیدی از جنس Scorzonera (متعلق به زیرجنس Scorzonera و بخشه Nervosae) به همراه تعدادی تصویر معرفی میشود.Scorzonera alborzensis از کوه سیاهسنگ در البرز مرکزی جمعآوری شده است. این گونه از نظر ریختشناسی نزدیک به Scorzonera cinerea است و با توجه به اندازه و شکل ساقه، اندازه و نحوه پراکندگی برگها بر روی ساقه، اندازه برگههای گریبانی و همچنین اندازه فندقهها از آن متمایز میگردد. یک نقاشی و تصویر اسکن شده از نمونه تیپ گونه جدید نیز ارائه شده است.
{"title":"Scorzonera alborzensis، گونه جدیدی از زیرجنس Scorzonera و بخشه Nervosae (Asteraceae) از ایران","authors":"سیدرضا صفوی, محمد امینی راد","doi":"10.22092/IJB.2020.343548.1290","DOIUrl":"https://doi.org/10.22092/IJB.2020.343548.1290","url":null,"abstract":"گونه جدیدی از جنس Scorzonera (متعلق به زیرجنس Scorzonera و بخشه Nervosae) به همراه تعدادی تصویر معرفی میشود.Scorzonera alborzensis از کوه سیاهسنگ در البرز مرکزی جمعآوری شده است. این گونه از نظر ریختشناسی نزدیک به Scorzonera cinerea است و با توجه به اندازه و شکل ساقه، اندازه و نحوه پراکندگی برگها بر روی ساقه، اندازه برگههای گریبانی و همچنین اندازه فندقهها از آن متمایز میگردد. یک نقاشی و تصویر اسکن شده از نمونه تیپ گونه جدید نیز ارائه شده است.","PeriodicalId":36255,"journal":{"name":"Iranian Journal of Botany","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88382387","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 : 2020-07-23DOI: 10.33897/fujeas.v1i1.198
A. Shahid, Umair Abdullah
Abstract: Widespread use of Social networking sites has increased the privacy threat for every individual. Privacy and security problem are two major issues associated with social networks, as the majority of the social network users are not cautious about the usability of the social websites. Social media sites have become latent target regarding offenders because of the occurrence of sensitive information and lack of user awareness of privacy settings. The overall aim of this paper is to enhance awareness about privacy and security issues associated with social networks and to provide guidelines to users for secure usage of social websites. Descriptive research has been conducted as it takes up the majority of online surveying and because of its quantitative nature, it is considered as conclusive. The survey results show that most of the users have their real information on social networking sites and they don’t change privacy settings of their accounts on regular basis. Moreover, as per survey findings, most users accept friend requests and invitations of unknown persons on social networking sites. Results of this research study will be helpful to bring awareness among users about privacy setting and they will learn how to control the privacy settings of their accounts and what type of content should be uploaded on social networking sites.
{"title":"Privacy Threats on Social Networking Websites","authors":"A. Shahid, Umair Abdullah","doi":"10.33897/fujeas.v1i1.198","DOIUrl":"https://doi.org/10.33897/fujeas.v1i1.198","url":null,"abstract":"Abstract: Widespread use of Social networking sites has increased the privacy threat for every individual. Privacy and security problem are two major issues associated with social networks, as the majority of the social network users are not cautious about the usability of the social websites. Social media sites have become latent target regarding offenders because of the occurrence of sensitive information and lack of user awareness of privacy settings. The overall aim of this paper is to enhance awareness about privacy and security issues associated with social networks and to provide guidelines to users for secure usage of social websites. Descriptive research has been conducted as it takes up the majority of online surveying and because of its quantitative nature, it is considered as conclusive. The survey results show that most of the users have their real information on social networking sites and they don’t change privacy settings of their accounts on regular basis. Moreover, as per survey findings, most users accept friend requests and invitations of unknown persons on social networking sites. Results of this research study will be helpful to bring awareness among users about privacy setting and they will learn how to control the privacy settings of their accounts and what type of content should be uploaded on social networking sites.","PeriodicalId":36255,"journal":{"name":"Iranian Journal of Botany","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83910270","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 : 2020-07-22DOI: 10.33897/fujeas.v1i1.201
Aqib Rehman
Software developed and then deployed in a real world environment is inevitable to exhibit some undesirable behavior. Therefore, developers need to provide maintenance facilities to enable the bugs causing the undesirable behavior to be fixed. However, prior to fixing the bug, the suspicious part of the code needs to be identified. For this purpose, they usually perform fault localization. This can be done manually as well as automatically. Several techniques exist in the literature for fault localization. However, most of them are static based techniques because they do not depend on a specific programming language along with the possibility to work on underdeveloped software and some other benefits. These techniques are largely based on lexical matching of terms which leads to mismatch of terms, large precision value because of limited vocabulary of a programming language and some techniques consider the semantics but it is computationally expensive to localize faults through this. In this paper we have proposed a fault localization technique which is based on the machine learning concept of word embedding. Our proposed approach aims at looking at the relatedness between the bug terms and source code artifact. We mined the bug repositories and software change repositories to train the word embedding model on the mined repositories data. On the arrival of a new bug, the cluster of the bugs from the model is searched and the files from the software change repositories are retrieved which are used for fixing those bugs. We have compared the results of our approach with the latest technique proposed in year 2018 Pointwise Mutual Information (PMI) and Normalized Google Distance (NGD) which consider the context and also with existing lexical techniques Vector Space Model (VSM) and the semantic based method Latent Semantic Indexing (LSI). We have used the benchmark dataset “MoreBugs” which has been widely used in this domain. The results show that our approach outperforms other techniques.
{"title":"A Word Embedding Model for Fault Localization using Bug and Software Change Repositories","authors":"Aqib Rehman","doi":"10.33897/fujeas.v1i1.201","DOIUrl":"https://doi.org/10.33897/fujeas.v1i1.201","url":null,"abstract":"Software developed and then deployed in a real world environment is inevitable to exhibit some undesirable behavior. Therefore, developers need to provide maintenance facilities to enable the bugs causing the undesirable behavior to be fixed. However, prior to fixing the bug, the suspicious part of the code needs to be identified. For this purpose, they usually perform fault localization. This can be done manually as well as automatically. Several techniques exist in the literature for fault localization. However, most of them are static based techniques because they do not depend on a specific programming language along with the possibility to work on underdeveloped software and some other benefits. These techniques are largely based on lexical matching of terms which leads to mismatch of terms, large precision value because of limited vocabulary of a programming language and some techniques consider the semantics but it is computationally expensive to localize faults through this. In this paper we have proposed a fault localization technique which is based on the machine learning concept of word embedding. Our proposed approach aims at looking at the relatedness between the bug terms and source code artifact. We mined the bug repositories and software change repositories to train the word embedding model on the mined repositories data. On the arrival of a new bug, the cluster of the bugs from the model is searched and the files from the software change repositories are retrieved which are used for fixing those bugs. We have compared the results of our approach with the latest technique proposed in year 2018 Pointwise Mutual Information (PMI) and Normalized Google Distance (NGD) which consider the context and also with existing lexical techniques Vector Space Model (VSM) and the semantic based method Latent Semantic Indexing (LSI). We have used the benchmark dataset “MoreBugs” which has been widely used in this domain. The results show that our approach outperforms other techniques.","PeriodicalId":36255,"journal":{"name":"Iranian Journal of Botany","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90581755","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 : 2020-07-22DOI: 10.33897/fujeas.v1i1.200
Adeel Ahmed, Riqza Shabbir, Atifa Afzal, Muhammad Akmal, Sahar Fatimah
Nowadays social networking is an essential part of everyone’s life to communicate with different people around the globe. Due to improvement in expertise networks are growing rapidly and becoming more complex. Through social networking, we can identify different communities that help us to get information about different people and their work in different fields. In social networks, community detection is one of the hot areas. In this paper, we have analyzed a co-authorship network of political science and ranked the authors on the basis of common centrality measures. Finding reveals that these common centrality measures can be useful indicators for impact analysis.
{"title":"Applying Centrality Measures for Impact Analysis in Coauthor ship Network","authors":"Adeel Ahmed, Riqza Shabbir, Atifa Afzal, Muhammad Akmal, Sahar Fatimah","doi":"10.33897/fujeas.v1i1.200","DOIUrl":"https://doi.org/10.33897/fujeas.v1i1.200","url":null,"abstract":"Nowadays social networking is an essential part of everyone’s life to communicate with different people around the globe. Due to improvement in expertise networks are growing rapidly and becoming more complex. Through social networking, we can identify different communities that help us to get information about different people and their work in different fields. In social networks, community detection is one of the hot areas. In this paper, we have analyzed a co-authorship network of political science and ranked the authors on the basis of common centrality measures. Finding reveals that these common centrality measures can be useful indicators for impact analysis.","PeriodicalId":36255,"journal":{"name":"Iranian Journal of Botany","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79941352","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 : 2020-07-22DOI: 10.33897/fujeas.v1i1.199
Adeel Ahmed, Tanveer Ahmed
Community detection is a fundamental problem in social networks. These networks detect communities based on link analysis and strong connection strengths, but cannot reflect Author’s from different research areas. To address the problem of community detection, we have done a study for “Analyzing patterns of collaboration in co-authorship network using Modularity and Centrality Measures”. This analysis study uses combine features of Modularity with centrality measure to effectively detect community of different author’s having different research collaboration with different interests in domain of Computer Networks and Database Systems. Experiment of Dataset shown that this approach is better detect best authors from specific domain having high collaboration with other coauthors and presents information to the researcher’s that have relative interest in relative author’s community.
{"title":"Assessing Research Collaboration in Database Systems and Computer Networks by Analysis of Coauthorship Network","authors":"Adeel Ahmed, Tanveer Ahmed","doi":"10.33897/fujeas.v1i1.199","DOIUrl":"https://doi.org/10.33897/fujeas.v1i1.199","url":null,"abstract":"Community detection is a fundamental problem in social networks. These networks detect communities based on link analysis and strong connection strengths, but cannot reflect Author’s from different research areas. To address the problem of community detection, we have done a study for “Analyzing patterns of collaboration in co-authorship network using Modularity and Centrality Measures”. This analysis study uses combine features of Modularity with centrality measure to effectively detect community of different author’s having different research collaboration with different interests in domain of Computer Networks and Database Systems. Experiment of Dataset shown that this approach is better detect best authors from specific domain having high collaboration with other coauthors and presents information to the researcher’s that have relative interest in relative author’s community.","PeriodicalId":36255,"journal":{"name":"Iranian Journal of Botany","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80695756","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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