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Verification of Karci Algorithm’s Efficiency for Maximum Independent Set Problem in Graph Theory 图论中最大独立集问题Karci算法有效性的验证
IF 0.5
Computer Science-AGH Pub Date : 2022-04-27 DOI: 10.53070/bbd.1090368
A. Karcı
{"title":"Verification of Karci Algorithm’s Efficiency for Maximum Independent Set Problem in Graph Theory","authors":"A. Karcı","doi":"10.53070/bbd.1090368","DOIUrl":"https://doi.org/10.53070/bbd.1090368","url":null,"abstract":"The maximum independent set problem is an NP-complete problem in graph theory. The Karci Algorithm is based on fundamental cut-sets of given graph, and node with minimum independence values are selected for maximum independent set. In this study, the analytical verification of this algorithm for some special graphs was analysed, and the obtained results were explained. The verification of Karci’s Algorithm for maximum independent set was handled in partial.","PeriodicalId":41917,"journal":{"name":"Computer Science-AGH","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2022-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47422960","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
Erratum: “Vehicle Routing Using Machine Learning Based Ant Colony Optimization, Computer Science, IDAP-2021, Special Issue, 2021” 勘误:“车辆路线使用基于机器学习的蚁群优化，计算机科学，IDAP-2021，特刊，2021”
IF 0.5
Computer Science-AGH Pub Date : 2022-03-19 DOI: 10.53070/bbd.1090329
Sinan Kami̇lçelebi̇, Sümeyya Ilkin, S. Sahin
{"title":"Erratum: “Vehicle Routing Using Machine Learning Based Ant Colony Optimization, Computer Science, IDAP-2021, Special Issue, 2021”","authors":"Sinan Kami̇lçelebi̇, Sümeyya Ilkin, S. Sahin","doi":"10.53070/bbd.1090329","DOIUrl":"https://doi.org/10.53070/bbd.1090329","url":null,"abstract":"Erratum— In the article titled \"Vehicle Routing Using Machine Learning Based Ant Colony Optimization\" published in the 2021 IDAP-21 Special Issue of the Computer Science Journal at 261-273 page intervals; it was noticed that some erroneous reporting and typo errors were made in the algorithm results presented in Tables [4, 5-12] and Table 16 by the authors. The authors apologize to the readers and other parties for these mistakes. Corrections and explanations made in order to eliminate the erroneous reporting in the article are presented. These corrections and improvements presented below increase the originality of the study.","PeriodicalId":41917,"journal":{"name":"Computer Science-AGH","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2022-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43019390","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
SEPARATION OF DOMESTIC WASTE WITH DEEP LEARNING TECHNIQUES 用深度学习技术分离生活垃圾
IF 0.5
Computer Science-AGH Pub Date : 2022-03-19 DOI: 10.53070/bbd.1071536
Yunus Emre Karaca, Serpil Aslan, Cengiz Hark
{"title":"SEPARATION OF DOMESTIC WASTE WITH DEEP LEARNING TECHNIQUES","authors":"Yunus Emre Karaca, Serpil Aslan, Cengiz Hark","doi":"10.53070/bbd.1071536","DOIUrl":"https://doi.org/10.53070/bbd.1071536","url":null,"abstract":"Thanks to the rapid development of deep learning technology, smart systems used in almost every part of our daily life are being developed. Developed applications not only made our lives easier, but also contributed positively to nature. Traditional waste separation methods fall short in terms of efficiency and accuracy. In addition to its high cost, it can also cause problems in terms of environmental risks. In recent years, artificial intelligence, machine learning and the deep learning techniques it brings have become a popular method for solving complex problems such as organic, household and packaging waste sorting. In this study, the problem of separation of domestic wastes, which is of great importance in terms of both human and living life and the protection of nature, is discussed. In the artificial intelligence cluster; Classification performances were compared by using popular conventional neural network (CNN) based ResNet-50, DenseNet-121, Inception-V3, VGG16 architectures to detect and sort household waste with deep learning, a sub-branch of machine learning.","PeriodicalId":41917,"journal":{"name":"Computer Science-AGH","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2022-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49383762","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
A New Region Based Active Contour Method Developed Using Gauss Filters 利用高斯滤波器提出了一种新的基于区域的主动轮廓方法
IF 0.5
Computer Science-AGH Pub Date : 2022-02-01 DOI: 10.53070/bbd.1038469
Kazım Hanbay
{"title":"A New Region Based Active Contour Method Developed Using Gauss Filters","authors":"Kazım Hanbay","doi":"10.53070/bbd.1038469","DOIUrl":"https://doi.org/10.53070/bbd.1038469","url":null,"abstract":"Aktif kontur yöntemleri görüntü bölütlemede sıklıkla kullanılmaktadır. Bu yöntemler kenar temelli ve bölge temelli yöntemler olarak ikiye ayrılabilir. Yöntemlerin her ikisi de nesne sınırlarını elde etmek için ham görüntü verisini kullanmaktadır. Önerilen yöntemler başlangıç kontur konumu, parametre bağımlılığı, gürültü duyarlılığı ve düzensiz görüntü yoğunlukları gibi bazı zorlu problemlere sahiptir. Bu çalışmada, orijinal ACM with SBGFRLS yönteminin α parametresinin otomatik olarak hesaplanmasını sağlayan yeni bir yaklaşım geliştirilmiştir. Bu parametre giriş görüntüsünün gauss türev filtreleri kullanılarak otomatik olarak hesaplanmıştır. Hesaplanan parametre düzey küme fonksiyonunda iteratif olarak kullanılmıştır. Deneysel sonuçlar, iyileştirilmiş ACM with SBGFRLS yönteminin daha yüksek bölütleme doğrulukları sağladığını göstermektedir.","PeriodicalId":41917,"journal":{"name":"Computer Science-AGH","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49080240","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
PAPSMEAR IMAGE SEGMENTATION WITH CONTRASTIVE LEARNING BASED GENERATIVE ADVERASRİAL NETWORKS 基于对比学习的生成式adverasrİal网络Papsmear图像分割
IF 0.5
Computer Science-AGH Pub Date : 2022-01-29 DOI: 10.53070/bbd.1038007
Sara Altun, M. F. Talu
{"title":"PAPSMEAR IMAGE SEGMENTATION WITH CONTRASTIVE LEARNING BASED GENERATIVE ADVERASRİAL NETWORKS","authors":"Sara Altun, M. F. Talu","doi":"10.53070/bbd.1038007","DOIUrl":"https://doi.org/10.53070/bbd.1038007","url":null,"abstract":"PapSmear görsellerinin otomatik olarak rahim ağzı kanser varlığının tespit edilmesi aktif bir \u0000çalışma alanıdır. PapSmear görüntülerinde nesnelerin dağılımı sürekli yer değiştirmektedir. Bu \u0000çalışmada, Çekişmeli Üretken Ağlar (ÇÜA) ve karşılaştırmalı öğrenme tekniklerinden parça tabanlı \u0000yöntemler kullanılarak PapSmear görüntü bölütlemesi yapılmıştır. Kıyaslanan yöntemler CycleGAN, \u0000CUT, FastCUT, DCLGAN ve SimDCL yöntemidir. Tüm yöntemler eşlenmemiş görüntüler üzerinde \u0000çalışmaktadır. Bu yöntemler bir birlerini temel alarak geliştirilmişlerdir. DCLGAN ve SimDCL yöntemi \u0000CUT ve CycleGAN yönteminin birleşimidir. Bu yöntemlerde maliyet fonksiyonları, ağ sayıları \u0000değişkenlik göstermektedir. Bu çalışmada yöntemler ayrıntılı bir şekilde incelenmiştir. Yöntemlerin \u0000birbirine benzerlik ve farklılıkları gözlemlenmiştir. Bölütleme yapıldıktan sonra hem görsel hem de \u0000ölçüm metrikleri kullanılarak bulunan sonuçlara yer verilmiştir. Ölçüm metriği olarak FID, KID, PSNR \u0000ve LPIPS yöntemleri kullanılmıştır. Yapılan deneysel çalışmalar, DCLGAN ve SimDCL yönteminin \u0000PapSmear bölümletlemede kıyaslanan yöntemler arasında daha iyi oldukları olduğu gözlemlenmiştir. \u0000CycleGAN yönteminin ise diğer yöntemlerden daha başarısız olduğu gözlemlenmiştir.","PeriodicalId":41917,"journal":{"name":"Computer Science-AGH","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2022-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48349760","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
Gramian Angular Field Transformation-Based Intrusion Detection 基于Gramian角场变换的入侵检测
IF 0.5
Computer Science-AGH Pub Date : 2022-01-01 DOI: 10.7494/csci.2022.23.4.4406
Duygu Sinanc
{"title":"Gramian Angular Field Transformation-Based Intrusion Detection","authors":"Duygu Sinanc","doi":"10.7494/csci.2022.23.4.4406","DOIUrl":"https://doi.org/10.7494/csci.2022.23.4.4406","url":null,"abstract":"","PeriodicalId":41917,"journal":{"name":"Computer Science-AGH","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71329783","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
Efficient multi-classifier wrapper feature-selection model: Application for dimension reduction in credit scoring 高效多分类器包装特征选择模型:在信用评分降维中的应用
IF 0.5
Computer Science-AGH Pub Date : 2022-01-01 DOI: 10.7494/csci.2022.23.1.4120
Bouaguel Waad
{"title":"Efficient multi-classifier wrapper feature-selection model: Application for dimension reduction in credit scoring","authors":"Bouaguel Waad","doi":"10.7494/csci.2022.23.1.4120","DOIUrl":"https://doi.org/10.7494/csci.2022.23.1.4120","url":null,"abstract":"","PeriodicalId":41917,"journal":{"name":"Computer Science-AGH","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71329720","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
Human Gesture Recognition using Hidden Markov Models and Sensor Fusion 基于隐马尔可夫模型和传感器融合的人体手势识别
IF 0.5
Computer Science-AGH Pub Date : 2022-01-01 DOI: 10.7494/csci.2022.23.2.3745
Emmanuel Domínguez Ramón, R. Díaz-Hernández, L. A. Robles
{"title":"Human Gesture Recognition using Hidden Markov Models and Sensor Fusion","authors":"Emmanuel Domínguez Ramón, R. Díaz-Hernández, L. A. Robles","doi":"10.7494/csci.2022.23.2.3745","DOIUrl":"https://doi.org/10.7494/csci.2022.23.2.3745","url":null,"abstract":"","PeriodicalId":41917,"journal":{"name":"Computer Science-AGH","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71329731","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
Çekişmeli Üretici Ağlar ile Denim Kumaşından Otomatik Bıyık Desen Üretimi 自动波浪偏移制造商与海上轰炸机生产
IF 0.5
Computer Science-AGH Pub Date : 2021-12-03 DOI: 10.53070/bbd.1019451
Emrullah Şahi̇n, M. F. Talu
{"title":"Çekişmeli Üretici Ağlar ile Denim Kumaşından Otomatik Bıyık Desen Üretimi","authors":"Emrullah Şahi̇n, M. F. Talu","doi":"10.53070/bbd.1019451","DOIUrl":"https://doi.org/10.53070/bbd.1019451","url":null,"abstract":"Denim kumaşları üzerine çizilen bıyık desenleri lazer ışın cihazıyla oluşturulmaktadır. Bu cihazın istenilen bıyık desenini çizebilmesi için desen görselinin hazırlanması gerekir. Müşteriden alınan numune kotlardaki bıyık desenlerinin görsele aktarılabilmesi için Photoshop programında uzmanlaşmış bir personelin ortalama 2-3 saat süren bir çalışma yapması gerekir. Bu durum üretim hızının yavaşlamasına ve insana bağlı hataların ortaya çıkmasına neden olmaktadır. Bu çalışmada, müşteriden alınacak örnek kot numunelerindeki bıyık desenlerini otomatik algılayarak desen görselini üreten yeni bir yaklaşım önerilmektedir. Bu yaklaşımda, bıyık desen görüntülerinin üretilebilmesi için çekişmeli üretici ağlar (Generative adversarial network-GAN) içerisinde yer alan Pix2Pix mimarisinin güncellenmiş bir versiyonu kullanılmaktadır. Kot ve bıyık desen görsellerinden inşa edilen bir veri kümesiyle eğitimin yapılmış ve personele bağlı farklı bıyık deseni üretiminin önüne geçilmiştir. Yapılan deneysel çalışmalar sonucunda, bıyık desen görseli üretim hızı bir saniyenin altına düşerken, üretim doğruluğu %89 seviyelerinde olduğu görülmektedir. Bir sonraki çalışmada veri kümesindeki görsellerin standardizasyonu sağlanarak doğruluğun arttırılması hedeflenmektedir.","PeriodicalId":41917,"journal":{"name":"Computer Science-AGH","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47607944","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
Validities of Fractional Order Derivatives in Literatures Such as Riemann-Liouville, Euler, Caputo and Grünwald-Letnikov 分数阶导数在Riemann-Liouville、Euler、Caputo和Grünwald Letnikov等文献中的有效性
IF 0.5
Computer Science-AGH Pub Date : 2021-10-29 DOI: 10.53070/bbd.982188
A. Karcı
{"title":"Validities of Fractional Order Derivatives in Literatures Such as Riemann-Liouville, Euler, Caputo and Grünwald-Letnikov","authors":"A. Karcı","doi":"10.53070/bbd.982188","DOIUrl":"https://doi.org/10.53070/bbd.982188","url":null,"abstract":"– In this paper, it has been proven that it would be more accurate to accept Euler, Riemann-Liouville, Caputo, and Grünwald-Letnikov methods as curve fitting or amplitude shifting methods without derivative definition. Since these derivative methods do not cause to shift extremum points of corresponding relations/functions to zero (the roots of relations/functions which are derived by taking fractional order derivative such as Euler, Riemann-Liouville, Caputo, and Grünwald-Letnikov methods).","PeriodicalId":41917,"journal":{"name":"Computer Science-AGH","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2021-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43308590","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
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