Yazar "AGÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü" için Mühendislik Fakültesi listeleme
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Kablosuz Sualtı Algılayıcı Ağlarında Katmanlar Arası İletişim Ve Fırsatçı Spektrum Erişimi
Güngör, Vehbi Çağrı; Tuna, Gürkan (TUBİTAK, 2018)Dünyamızın üçte ikisinden fazlası sularla kaplıdır. Denizlerden, göllerden ve nehirlerden oluşan sualtı dünyası doğal kaynaklar (petrol, doğalgaz ve değerli mineraller) bakımından oldukça zengin olup insanoğlu tarafından ... -
Knowledge based response correction method for design of reconfigurable N-shaped microstrip patch antenna using inverse ANNs
Aoad, Ashrf; Simsek, Murat; Aydin, Zafer (WILEY, 2017)Artificial neural networks (ANNs) have been often used for engineering design problems. In this work, an inverse model of a reconfigurable N-shaped microstrip patch antenna which is formed by ANN is considered to find ... -
Learning management systems on blended learning courses: An experience-based observation
Kuran, Mehmet Şükrü; Pedersen, Jens Myrup; Elsner, Raphael (SPRINGER, 2018)This paper gives an overview of Learning Management System (LMS) features based on observations on a blended learning course under the Erasmus+ project COLIBRI. We explain the main features of LMSes under two main categories: ... -
Lifetime Analysis of Energy Harvesting Underwater Wireless Sensor Nodes
Erdem, H. Emre; Gungor, V. Cagri (IEEE345 E 47TH ST, NEW YORK, NY 10017 USA, 2017)The application of Wireless Sensor Networks (WSNs) in underwater environments poses various challenges. One of the most important problems is the limited lifetime of underwater sensor nodes. Considering how challenging and ... -
Lifetime Analysis of Error Control Schemes on Wireless Sensor Networks in Industrial Environments
Tekin, Nazli; Gungor, V. Cagri (IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA, 2019)Due to the harsh channel conditions of the industrial environment, the data transmission over wireless channel suffers from erroneous packets. The energy consumption of error control schemes is of vital importance for ... -
Lifetime analysis of wireless sensor nodes in different smart grid environments
Eris, Cigdem; Saimler, Merve; Gungor, Vehbi Cagri; Fadel, Etimad; Akyildiz, Ian F (SPRINGER, 2014)Wireless sensor networks (WSNs) can help the realization of low-cost power grid automation systems where multi-functional sensor nodes can be used to monitor the critical parameters of smart grid components. The WSN-based ... -
Linear vs. Non-Linear Embedding Methods in Recommendation Systems
Gurler, Kerem; Coskun, Mustafa; Karagenc, Safak; Orun, Gokhan; Pak, Burcu Kuleli; Gungor, Vehbi Cagri (Institute of Electrical and Electronics Engineers Inc., 2022)Predicting customer interest in items is very crucial in direct marketing as it can potentially boost sales. Data mining techniques are developed to predict which items a particular user might be interested in based on ... -
LRP: Link quality-aware queue-based spectral clustering routing protocol for underwater acoustic sensor networks
Faheem, Muhammad; Tuna, Gurkan; Gungor, Vehbi Cagri (WILEY111 RIVER ST, HOBOKEN 07030-5774, NJ, 2017)Recently, underwater acoustic sensor networks (UASNs) have been considered as a promising approach for monitoring and exploring the oceans in lieu of traditional underwater wireline instruments. As a result, a broad range ... -
Machine learning algorithms against hacking attack and detection success comparison
Yavuz L.; Soran A.; Onen A.; Muyeen S.M. (Institute of Electrical and Electronics Engineers Inc., 2020)Power system protection units has got enormous importance with the growing risk of cyber-attacks. To create sustainable and well protected system, power system data must be healthy. For that purpose, many machine learning ... -
Machine Learning Analysis of Inflammatory Bowel Disease-Associated Metagenomics Dataset
Hacilar, Hilal; Nalbantoglu, O. Ufuk; Bakir-Gungor, Burcu (IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA, 2018)There is an ongoing interplay between humans and our microbial communities. The microorganisms living in our gut produce energy from our food, strengthen our immune system, break down foreign products, and release metabolites ... -
Machine learning approaches for underwater sensor network parameter prediction
Uyan, Osman Gokhan; Akbas, Ayhan; Gungor, Vehbi Cagri (ELSEVIER, 2023)Underwater Acoustic Sensor Networks (UASNs) have recently attracted scientists due to its wide range of real -world applications. However, there are design challenges in UASNs, such as limited network lifetime and low ... -
Machine Learning based Beamwidth Adaptation for mmWave Vehicular Communications
Manic, Setinder; Foh, Chuan Heng; Kose, Abdulkadir; Lee, Haeyoung; Leow, Chee Yen; Chatzimisios, Periklis; Moessner, Klaus; Klaus, Moessner (Institute of Electrical and Electronics Engineers Inc., 2023)The incorporation of mmWave technology in vehicular networks has unlocked a realm of possibilities, propelling the advancement of autonomous vehicles, enhancing interconnectedness, and facilitating communication for ... -
Machine learning based classifcation of cells into chronological stages using singlecell transcriptomics
Singh, Sumeet Pal; Janjuha, Sharan; Chaudhuri, Samata; Reinhardt, Susanne; Kränkel, Annekathrin; Dietz, Sevina; Eugster, Anne; Bilgin, Halil; Korkmaz, Selçuk; Zararsız, Gökmen; Ninov, Nikolay; Reid, John E. (NATURE PUBLISHING GROUP, MACMILLAN BUILDING, 4 CRINAN ST, LONDON N1 9XW, ENGLAND, 2018)Age-associated deterioration of cellular physiology leads to pathological conditions. The ability to detect premature aging could provide a window for preventive therapies against age-related diseases. However, the techniques ... -
Machine Learning based Early Prediction of Type 2 Diabetes: A New Hybrid Feature Selection Approach using Correlation Matrix with Heatmap and SFS
Akbas, Ayhan; Buyrukoğlu, Selim (İstanbul Teknik Üniversitesi, 2022)A new hybrid machine learning method for the prediction of type 2 diabetes is introduced and explained in detail. Also outcomes are compared with the similar researches. Early prediction of diabetes is crucial to take ... -
Man-hour Prediction for Complex Industrial Products
Unal, Ahmet Emin; Boyar, Halit; Pak, Burcu Kuleli; Cem Yildiz, Mehmet; Erten, Ali Erman; Gungor, Vehbi Cagri (Institute of Electrical and Electronics Engineers Inc., 2023)Accurately predicting the cost is crucial for the success of complex industrial projects. There can be several sources contributing to the cost. Traditional methods for cost estimation may not provide the required ... -
A Methodology for Comparing the Reliability of GPU-Based and CPU-Based HPCs
Cini, Nevin; Yalcin, Gulay (ASSOC COMPUTING MACHINERY, 2 PENN PLAZA, STE 701, NEW YORK, NY 10121-0701 USA, 2020)Today, GPUs are widely used as coprocessors/accelerators in High-Performance Heterogeneous Computing due to their many advantages. However, many researches emphasize that GPUs are not as reliable as desired yet. Despite ... -
Micro-Electromechanical Systems for Underwater Environments
Gungor, Vehbi Cagri; Tuna, Gurkan (IGI GLOBAL701 E CHOCOLATE AVE, STE 200, HERSEY, PA 17033-1240 USA, 2017)Underwater networking technologies have brought us unforeseen ways to explore the unexplored aquatic environment and this way provided us with a large number of different kinds of applications for environmental, scientific, ... -
microBiomeGSM: the identification of taxonomic biomarkers from metagenomic data using grouping, scoring and modeling (G-S-M) approach
Bakir-Gungor, Burcu; Temiz, Mustafa; Jabeer, Amhar; Wu, Di; Yousef, Malik (FRONTIERS MEDIA SA, 2023)Numerous biological environments have been characterized with the advent of metagenomic sequencing using next generation sequencing which lays out the relative abundance values of microbial taxa. Modeling the human microbiome ... -
miRcorrNet: machine learning-based integration of miRNA and mRNA expression profiles, combined with feature grouping and ranking
Yousef, Malik; Goy, Gokhan; Mitra, Ramkrishna; Eischen, Christine M.; Jabeer, Amhar; Bakir-Gungor, Burcu (PEERJ INC341-345 OLD ST, THIRD FLR, LONDON EC1V 9LL, ENGLAND, 2021)A better understanding of disease development and progression mechanisms at the molecular level is critical both for the diagnosis of a disease and for the development of therapeutic approaches. The advancements in high ... -
miRdisNET: Discovering microRNA biomarkers that are associated with diseases utilizing biological knowledge-based machine learning
Jabeer, Amhar; Temiz, Mustafa; Bakir-Gungor, Burcu; Yousef, Malik (Frontiers Media S.A., 2023)During recent years, biological experiments and increasing evidence have shown that microRNAs play an important role in the diagnosis and treatment of human complex diseases. Therefore, to diagnose and treat human complex ...