Başlık için Bilgisayar Mühendisliği Bölümü Koleksiyonu listeleme
Toplam kayıt 265, listelenen: 57-76
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A Data Mining Method For Refining Groups In Data Using Dynamic Model Based Clustering
(IEEE, 2013)A new data mining method is proposed for determining the number and structure of clusters, and refining groups in multivariate heterogeneous data set including groups, partly and completely overlapped group structures ... -
Data Mining Techniques in Direct Marketing on Imbalanced Data using Tomek Link Combined with Random Under-sampling
(Association for Computing Machinery, 2021)Determining the potential customers is very important in direct marketing. Data mining techniques are one of the most important methods for companies to determine potential customers. However, since the number of potential ... -
A Deep Ensemble Approach for Long-Term Traffic Flow Prediction
(SPRINGER, 2024)In the last 50 years, with the growth of cities and increase in the number of vehicles and mobility, traffic has become troublesome. As a result, traffic flow prediction started to attract attention as an important research ... -
A deep learning approach with Bayesian optimization and ensemble classifiers for detecting denial of service attacks
(WILEY, 111 RIVER ST, HOBOKEN 07030-5774, NJ USA, 2020)Detecting malicious behavior is important for preventing security threats in a computer network. Denial of Service (DoS) is among the popular cyber attacks targeted at web sites of high-profile organizations and can ... -
Deep learning approaches for vehicle type classification with 3-D magnetic sensor
(ELSEVIER, 2022)In the Intelligent Transportation Systems, it is crucial to determine the type of vehicles to improve traffic management, increase human comfort, and enable future development of transport infrastructures. This paper presents ... -
Deep learning based semantic segmentation and quantification for MRD biochip images
(ELSEVIER SCI LTD, 2022)Microfluidic platforms offer prominent advantages for the early detection of cancer and monitoring the patient response to therapy. Numerous microfluidic platforms have been developed for capturing and quantifying the tumor ... -
A deep neural network approach with hyper-parameter optimization for vehicle type classification using 3-D magnetic sensor
(ELSEVIER, 2023)The identification of vehicle types plays a critical role in Intelligent Transportation Systems. In this study, battery-operated, easy-to-install, low-cost 3-D magnetic traffic sensors have been developed for vehicle type ... -
Design of a Tri band 5-Fingers Shaped Microstrip Patch Antenna with an Adjustable Resistor
(IEEE, 2014)This paper presents a tri band 5-fingers shaped microstrip patch antenna, which resonates initially at dual band of 3.2 GHz and 5.2 GHz frequencies for VSWR < 2. The antenna is modified by adding an adjustable resistor ... -
Designing and Modelling Selective Replication for Fault-tolerant HPC Applications
(IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA, 2017)Fail-stop errors and Silent Data Corruptions (SDCs) are the most common failure modes for High Performance Computing (HPC) applications. There are studies that address fail-stop errors and studies that address SDCs. However ... -
The Determination of Distinctive Single Nucleotide Polymorphism Sets for the Diagnosis of Behçet's Disease
(Institute of Electrical and Electronics Engineers Inc., 2021)Behçet's Disease (BD) is a multi-system inflammatory disorder in which the etiology remains unclear. The most probable hypothesis is that genetic tendency and environmental factors play roles in the development of BD. In ... -
Developing a label propagation approach for cancer subtype classification problem
(TUBITAK SCIENTIFIC & TECHNICAL RESEARCH COUNCIL TURKEYATATURK BULVARI NO 221, KAVAKLIDERE, ANKARA 00000, TURKEY, 2022)Cancer is a disease in which abnormal cells grow uncontrollably and invade other tissues. Several types of cancer have various subtypes with different clinical and biological implications. Based on these differences, ... -
Developing structural profile matrices for protein secondary structure and solvent accessibility prediction
(OXFORD UNIV PRESS, GREAT CLARENDON ST, OXFORD OX2 6DP, ENGLAND, 2019)Motivation: Predicting secondary structure and solvent accessibility of proteins are among the essential steps that preclude more elaborate 3D structure prediction tasks. Incorporating class label information contained in ... -
Development of Knowledge Based Response Correction for a Reconfigurable N-Shaped Microstrip Antenna Design
(IEEE, 2015)This study presents the use of prior knowledge of inverse artificial neural network (ANN) to model and optimize a reconfigurable N-shaped microstrip antenna. Three accurate prior knowledge inverse ANNs with large amount ... -
Dimensionality reduction for protein secondary structure and solvent accesibility prediction
(IMPERIAL COLLEGE PRESS, 57 SHELTON ST, COVENT GARDEN, LONDON WC2H 9HE, ENGLAND, 2018)Secondary structure and solvent accessibility prediction provide valuable information for estimating the three dimensional structure of a protein. As new feature extraction methods are developed the dimensionality of the ... -
Disaster-resilient lightpath routing in WDM optical networks
(SPRINGER, 2022)Optical network serves as a core network with huge capacity and a multitude of high-speed data transmission. Natural disasters and physical attacks showed signifcant impacts on the optical networks such as damages the ... -
Disaster-Resilient Optical Network Survivability: A Comprehensive Survey
(MDPI, ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND, 2018)Network survivability endeavors to ensure the uninterrupted provisioning of services by the network operators in case of a disaster event. Studies and news reports show that network failures caused by physical attacks and ... -
Discovering Potential Taxonomic Biomarkers of Type 2 Diabetes From Human Gut Microbiota via Different Feature Selection Methods
(FRONTIERS MEDIA SAAVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE CH-1015, SWITZERLAND, 2021)Human gut microbiota is a complex community of organisms including trillions of bacteria. While these microorganisms are considered as essential regulators of our immune system, some of them can cause several diseases. In ... -
EDHRP: Energy efficient event driven hybrid routing protocol for densely deployed wireless sensor networks
(ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD, 2015)Efficient management of energy resources is a challenging research area in Wireless Sensor Networks (WSNs). Recent studies have revealed that clustering is an efficient topology control approach for organizing a network ... -
The Effect of Different Classifiers on Recursive Cluster Elimination in the Analysis of Transcriptomic Data
(Institute of Electrical and Electronics Engineers Inc., 2023)Gene expression data with limited sample size and a large number of genes are frequently encountered in genetic studies. In such high-dimensional data, identification of genes that distinguish between disease states is ... -
Effect of Recursive Cluster Elimination with Different Clustering Algorithms Applied to Gene Expression Data
(Institute of Electrical and Electronics Engineers Inc., 2023)Feature selection (FS) is an effective tool in dealing with high dimensionality and reducing computational cost. Support Vector Machines – Recursive Cluster Elimination (SVM-RCE) is one of several algorithms that have ...
