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Articles 1 - 9 of 9
Full-Text Articles in Computer Engineering
Enhancing Informative Frame Filtering By Water And Bubble Detection In Colonoscopy Videos, Ashok Dahal, Junghwan Oh, Wallapak Tavanapong, Johnny S. Wong, Piet C. De Groen
Enhancing Informative Frame Filtering By Water And Bubble Detection In Colonoscopy Videos, Ashok Dahal, Junghwan Oh, Wallapak Tavanapong, Johnny S. Wong, Piet C. De Groen
Johnny Wong
Colonoscopy has contributed to a marked decline in the number of colorectal cancer related deaths. However, recent data suggest that there is a significant (4-12%) miss-rate for the detection of even large polyps and cancers. To address this, we have been investigating an ‘automated feedback system’ which informs the endoscopist of possible sub-optimal inspection during colonoscopy. A fundamental step of this system is to distinguish non-informative frames from informative ones. Existing methods for this cannot classify water/bubble frames as non-informative even though they do not carry any useful visual information of the colon mucosa. In this paper, we propose a …
A Data-Driven Approach To Cubesat Health Monitoring, Serbinder Singh
A Data-Driven Approach To Cubesat Health Monitoring, Serbinder Singh
Master's Theses
Spacecraft health monitoring is essential to ensure that a spacecraft is operating properly and has no anomalies that could jeopardize its mission. Many of the current methods of monitoring system health are difficult to use as the complexity of spacecraft increase, and are in many cases impractical on CubeSat satellites which have strict size and resource limitations. To overcome these problems, new data-driven techniques such as Inductive Monitoring System (IMS), use data mining and machine learning on archived system telemetry to create models that characterize nominal system behavior. The models that IMS creates are in the form of clusters that …
A Novel Approach For Extracting Ideal Exemplars By Clustering For Massivetime-Ordered Datasets, Ömer Faruk Ertuğrul
A Novel Approach For Extracting Ideal Exemplars By Clustering For Massivetime-Ordered Datasets, Ömer Faruk Ertuğrul
Turkish Journal of Electrical Engineering and Computer Sciences
The number and length of massive datasets have increased day by day and this yields more complex machine learning stages due to the high computational costs. To decrease the computational cost many methods were proposed in the literature such as data condensing, feature selection, and filtering. Although clustering methods are generally employed to divide samples into groups, another way of data condensing is by determining ideal exemplars (or prototypes), which can be used instead of the whole dataset. In this study, first the efficiency of traditional data condensing by clustering approach was confirmed according to obtained accuracies and condensing ratios …
An Intelligent Pso-Based Energy Efficient Load Balancing Multipath Technique In Wireless Sensor Networks, Sukhchandan Randhawa, Sushma Jain
An Intelligent Pso-Based Energy Efficient Load Balancing Multipath Technique In Wireless Sensor Networks, Sukhchandan Randhawa, Sushma Jain
Turkish Journal of Electrical Engineering and Computer Sciences
To provide a reliable and efficient service, load balancing plays an important role in wireless sensor networks (WSNs). There is a need to maximize the network lifetime for WSNs applications with periodic generation of data. Due to the relationship between energy consumption and network sensor node lifetime, energy consumption in a network should be minimized and balanced in order to increase network lifetime. Energy-efficient load-balancing techniques are needed to solve this problem. In this paper, a particle swarm optimization (PSO)-based energy-efficient load-balancing technique is proposed, in which the required number of routing paths and energy consumption of different nodes and …
Unsupervised Learning Of Allomorphs In Turkish, Burcu Can
Unsupervised Learning Of Allomorphs In Turkish, Burcu Can
Turkish Journal of Electrical Engineering and Computer Sciences
One morpheme may have several surface forms that correspond to allomorphs. In English, ed and $d$ are surface forms of the past tense morpheme, and $s$, es, and ies are surface forms of the plural or present tense morpheme. Turkish has a large number of allomorphs due to its morphophonemic processes. One morpheme can have tens of different surface forms in Turkish. This leads to a sparsity problem in natural language processing tasks in Turkish. Detection of allomorphs has not been studied much because of its difficulty. For example, tü and di are Turkish allomorphs (i.e. past tense morpheme), but …
An Adaptive Clustering Segmentation Algorithm Based On Fcm, Jun Yang, Yun-Sheng Ke, Mao-Zheng Wang
An Adaptive Clustering Segmentation Algorithm Based On Fcm, Jun Yang, Yun-Sheng Ke, Mao-Zheng Wang
Turkish Journal of Electrical Engineering and Computer Sciences
The cluster number and the initial clustering centers must be reasonably set before the analysis of clustering in most cases. Traditional clustering segmentation algorithms have many shortcomings, such as high reliance on the specially established initial clustering center, tendency to fall into the local maximum point, and poor performance with multithreshold values. To overcome these defects, an adaptive fuzzy C-means segmentation algorithm based on a histogram (AFCMH), which synthesizes both main peaks of the histogram and optimized Otsu criterion, is proposed. First, the main peaks of the histogram are chosen by operations like histogram smoothing, merging of adjacent peaks, and …
A Clustering Approach Using A Combination Of Gravitational Search Algorithm And K-Harmonic Means And Its Application In Text Document Clustering, Mina Mirhosseini
A Clustering Approach Using A Combination Of Gravitational Search Algorithm And K-Harmonic Means And Its Application In Text Document Clustering, Mina Mirhosseini
Turkish Journal of Electrical Engineering and Computer Sciences
Data clustering is one of the most popular techniques of information management, which is used in many applications of science and engineering such as machine learning, pattern reorganization, image processing, data mining, and web mining. Different algorithms have been suggested by researchers, where the evolutionary algorithms are the best in data clustering and especially in big datasets. It is illustrated that GSA-KM, which is a combination of the gravitational search algorithm (GSA) and K-means (KM), is superior over some other comparative evolutionary methods. One of the drawbacks of this approach is dependency on the initial seeds. In this paper, a …
Semantics-Based Summarization Of Entities In Knowledge Graphs, Kalpa Gunaratna
Semantics-Based Summarization Of Entities In Knowledge Graphs, Kalpa Gunaratna
Browse all Theses and Dissertations
The processing of structured and semi-structured content on the Web has been gaining attention with the rapid progress in the Linking Open Data project and the development of commercial knowledge graphs. Knowledge graphs capture domain-specific or encyclopedic knowledge in the form of a data layer and add rich and explicit semantics on top of the data layer to infer additional knowledge. The data layer of a knowledge graph represents entities and their descriptions. The semantic layer on top of the data layer is called the schema (ontology), where relationships of the entity descriptions, their classes, and the hierarchy of the …
Proposing A New Clustering Method To Detect Phishing Websites, Morteza Arab, Mohammad Karim Sohrabi
Proposing A New Clustering Method To Detect Phishing Websites, Morteza Arab, Mohammad Karim Sohrabi
Turkish Journal of Electrical Engineering and Computer Sciences
Phishing websites are fake ones that are developed by ill-intentioned people to imitate real and legal websites. Most of these types of web pages have high visual similarities to hustle the victims. The victims of phishing websites may give their bank accounts, passwords, credit card numbers, and other important information to the designers and owners of phishing websites. The increasing number of phishing websites has become a great challenge in e-business in general and in electronic banking specifically. In the present study, a novel framework based on model-based clustering is introduced to fight against phishing websites. First, a model is …