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Innovations in technology that have enabled efficient wireless tiny devices propelled the concept of Internet of Things. It is expected that mobile data traffic will experience 8-fold growth between 2015 and 2020 and the number of mobile connected devices will reach 11.6 billion by 2020. Main factors of this exponential growth and wide acceptance are the integration of several technologies and communications...
Deep Learning is appealing for learning from large amounts of unlabeled/unsupervised data, making it attractive for extracting meaningful representations and patterns from big data. Deep learning, by its simplest definition, is expressed as the application of machine learning methods to the big data. In this study, it was investigated how to apply hierarchical deep learning models for the problems...
The identification of association relationships in buying patterns of customers is an important problem to make proper decision by business companies. Current most research works utilizes commonly traditional Apriori algorithm to solve this problem. In this paper, a modified version of Apriori algorithm, and its combination with Eclat algorithm is suggested. Applying this approach to a case study...
With today's increasing use of technology, the physical resources that provide the infrastructure have begun to be inadequate and created the concept of virtualization. As virtualization is preferred in physical machines, it also ensures that the network structures that provide the infrastructure are better managed and used more efficiently. There is no need for migrations in virtual networks with...
OWA (Ordered Weighted Averaging) operator provides a general class of parameterized mean type aggregation operators. It is an important tool, having ability to reflect the strategy of a Decision Maker in decision making problems. The idea of using a stress function to generate the OWA weights was introduced in this study. We introduce a new fuzzy c-regression models (FCRM) based approach to obtain...
In this paper, the trend of Business Intelligence (BI) adoption and maturity has been evaluated. Special emphasis was given to the small-to-medium enterprises (SME) business adoption and intensive review of BI maturity model in for the contemporary business world. Therefore, this study surveyed research works that reveal most determinants for BI efficiency. The survey has extract what lead organization...
Since breast cancer is a common disease in society all over the world, early diagnosis is of vital importance in order to treat patients before it reaches an irreversible phase. Expert systems are being developed to make it easier to diagnose the disease. In this study, an ensemble of neural networks named radial basis function network (RBFN), generalized regression neural network (GRNN) and feed...
EEG (Electroencephalography) signals are used in different fields increasingly with the development of technology because they contain a lot of important information. In recent years, a great deal of these studies has been carried out about the concrete meaning of the signals. Most of these systems are called BBA (Brain Computer Interface) systems. Various applications have been developed with BBA...
Positioning and location tracking are two major needs of the modern era; in which logistics, industry automation, smart buildings/cities and the Internet of Things concepts are trending topics and are constantly evolving. Introduction of the Global Positioning System (GPS) solved the issue well for outdoor scenarios, however, it is not a reliable solution for indoors, where satellite communication...
Artificial neural networks (ANN) are among the nonlinear prediction techniques popular in the last two decades. Recent studies show that ANN can be modeled with different training techniques. ANN is usually trained by the backpropagation method (BP). In this study, ANN structures were trained by using artificial bee colony algorithm (ABC) and, weight and bias values were tried to be determined. ABC...
In this study, a system has been developed to provide meaning and classification of e-mails according to their contents. The aim of the work is to develop an intelligent inbox to assist in awareness of information security. In the designed system, a client is developed that can connect to the server and receive e-mails. A two-step analysis is performed on the received e-mails. For both stage analysis,...
It is expected that server rooms equipped with expensive and complex devices must be reliable and stable. However, excessive environmental factors such as temperature and humidity can cause very serious effects on the devices and can lead to unrecoverable data losses or financial losses. In this study, a WSN (Wireless Sensor Network) was designed for real time monitoring the temperature, humidity,...
Swarm intelligence or evolutionary computation algorithms search possible solutions in a predetermined search space of an optimization problem. In some cases candidate solutions go out of search space during the search. In such situations, search space limitation techniques or boundary conditions are used for sway up this outcast individual into search space. The boundary conditions are classified...
Using fuzzy neighborhood relations in density-based clustering, like in Fuzzy Joint Points (FJP) algorithm, yields more robust and autonomous algorithms. Even though the fuzzy neighborhood based clustering methods are proven to be fast enough, such that tens of thousands of data can be handled under a second, the space complexity is still a limiting factor. In this study, a transformed FJP algorithm...
Neuroendocrine tumors (NET) are a heterogeneous group of tumors that can develop in almost every localization of the body. The study is the computation of the Ki-67 proliferation index, which is an important information for physicians, from the NET images. The physician control evaluations were carried out on histopathologic forms taken from healthy and NET-diagnosed patients with the designed automated...
Identifying structure of genes in Human genomes highly depends upon accurate recognition of boundaries between exons and introns, i.e. splice sites. Hence, development of new methods for effective detection of splice sites is essential. DNA encoding approaches are used for feature extraction from gene sequences, while machine learning methods are used for classification of splice sites using those...
Cyber-attacks wasorganized in a simple and random way in the past. However attacks are carried out systematically and long term nowadays. In addition, the high calculation volume and continuous changes in network data distribution have made it more difficult to analyze data and detect abnormal behaviors within. For this reason, big data solutions have become essential. In this paper, firstly network...
Today, with the development of the internet, documents containing information such as articles, news, web pages are produced and stored in digital environment. However, the increase in the number of media where people are able to add new contents such as social media, Twitter, and blog has increased the amount of information on the internet to enormous size. However, it is very difficult and time-consuming...
In this work, a hybrid method that includes metaheuristic algorithms has been proposed for solving optimization problems. The proposed method was implemented as employing three metaheuristic algorithms which are Artificial Bee Colony, Differential Evolution and Particle Swarm Optimization in an order. The success of the developed method is presented by testing on 12 continuous optimization test functions...
With the widespread usage of information and communication technologies rapidly and the increase in data storage and transformation electronically it is very important to provide personal data security and raising security awareness in public. One of the most problematic issues about information technologies are the ones relating with personal and vital data security. Within the context of this study...
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