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Heart disease is a deadly disease that large population of people around the world suffers from. When considering death rates and large number of people who suffers from heart disease, it is revealed how important early diagnosis of heart disease. Traditional way of diagnosis is not sufficient for such an illness. Developing a medical diagnosis system based on machine learning for prediction of heart...
The remote controls which are used to control the robots are very expensive. In addition, one remote control is required for each robot. The goal of this work is to control multi robots at the same time by publish a single ROS message using one Android device. The user can drive robots with help of a variety of sensors and camera data which are displayed on the Android device screen, even if the user...
Recommender systems help people to find items of interest by utilizing past user interactions (such as product views, ratings, and purchases). Today many e-commerce sites and large scale web applications use recommender systems and provide their customers personalized products. In this work we will share our recent experience in developing a job recommender system based on collaborative filtering...
In this study, from the problems of graph theory to the Maximum Independent set problem belonging to NP-Hard complexity class, were searched solutions close to optimal quality by using genetic algorithms from artificial intelligence techniques. Unlike most of the studies in the literature, the initial population of the genetic algorithm has not been determined at random and has been created with various...
Millions of data are collected daily in the social media environment. This data mostly reflects people's ideas in a certain topic. Emotion analysis is a new data mining subfield and is usually concerned with information extraction and identification from emotions in social media. Twitter is a platform where users share their ideas through messages. These messages can be classified to analyze the feelings...
The purpose of this study is to examine generalized self-efficacy and attitudes of the F.M.V. Işık University Engineering Faculty students of Introduction to Programming Course (CSE101) with respect to student gender and course language (Turkish-English). A total of 114 university students, 40 female and 74 male, participated in the research. In order to measure students' self-efficacy perceptions,...
Clustering is an important tool for analyzing gene expression data. Many clustering algorithms have been proposed for the analysis of gene expression data. In this article we have clustered real life gene expression data via K-Means which is one of clustering algorithms. Also, we have proposed a new method determining the initial cluster centers for K-means. We have compared results of our method...
Deep learning is a subfield of machine learning which uses artificial neural networks that is inspired by the structure and function of the human brain. Despite being a very new approach, it has become very popular recently. Deep learning has achieved much higher success in many applications where machine learning has been successful at certain rates. In particular It is preferred in the classification...
In this work, we generalise the categorical syllogistic logic in several dimensions to a relatively expressive logic that is sufficiently powerful to encompass a wider range of linguistic semantics. The generalisation is necessary in order to eliminate the existential ambiguity of the quantifiers and to increase expressiveness, practicality, and adaptivity of the syllogisms. The extended semantics...
It is important to use healthy communication and appropriate routing techniques to increase performance in wireless body area networks. At present, the biggest problem of sensor nodes that bring such networks into the uneasiness is limited energy resources. In this paper, it is proposed to make road selection by calculating the distances of the nodes and the battery levels while making the routing...
Recommender systems provide recommendations about various products and services to their users while using other users data. Their success is imperative for both users and the e-commerce sites utilizing such systems. Providing accurate and dependable recommendations increases user satisfaction that results selling more products and services. Image-based recommender systems are receiving increasing...
In this study, we investigated Cellular Automata form is discrete computational model working on more than one cell as pattern attractor. Cellular Automata is a computational model works on grid space discretely. State of a cell at time t+1 is updated depends its own state and neighboring states. Properties of rules in rule vector, characterization of attractor's state in Multiple Attractor Cellular...
Digital forensics is a multi-disciplinary science area that sets standards for the collection, storage, compilation and analysis of electronic data. To evaluate data in judicial information, the evidence must have certain standards. The evidence includes many types of data such as audio, video and text that exist in electronic devices. Especially biometric data that contain specific information about...
This study presents Migrating Birds Optimization (MBO) which is a novel meta-heuristic algorithm for the solution of 0-1 multidimensional knapsack problem. In the study, the basic migrating birds optimization algorithm is used and change is made to the only neighborhood structure of this algorithm for adapting to the addressed problem. The performance of the algorithm is examined on the test problems...
We studied the texts in Kazakh and determined the parts of speech that define the text mood. Based on the conducted studies a lot of phrases were identified as determining the mood of the text. The technique of fuzzy inference associated with the estimation of the general level of the hotel state on the basis of the calculated criterion for each aspect is proposed. The criterion is measured in percent...
In this paper, we study Vehicle Routing Problem (VRP) for Blood Transporters (BTs) and propose an efficient vehicle routing scheme for blood transportation between hospitals or Donor/Client Sites (DCSs) within a region that is based on Artificial Intelligence. It is assumed that each BT in a fleet of vehicles starts and completes its route at a blood-bank while visiting a subset of DCSs using the...
In this research, we have developed a web based TaqMan Array Cards (TMDK) Data Management System that responds to the needs of collecting, sharing and uploading data of many surveillance projects, and a Ct-value prediction algorithm to determine target gene existence in sample. Any epidemic case can rapidly be detected and comparative evaluations can be done for the results of different sites while...
This survey highlights issues in clustering which hinder in achieving optimal solution or generates inconsistent outputs. We called such malignancies as dark patches. We focus on the issues relating to clustering rather than concepts and techniques of clustering. For better insight into the issues of clustering, we categorize dark patches into three classes and then compare various clustering methods...
The amount of data circulating on the Internet is increasing day by day. With the increasing use of social media in particular, the importance of analyzing these data is increasing. The use of machine learning approaches to analyze large amounts of data is still popular today. Today, the social network Facebook is the most popular social networking sites. In this study, some data taken on Facebook...
An intrusion detection system (IDS) monitors the network traffic looking for suspicious or malicious activities or policy violations, which could represent an attack or unauthorized access. Traditional systems were designed to detect known attacks but cannot identify unknown threats. They most commonly detect known threats based on predefined rules or behavioral analysis through baselining the network...
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