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The prediction of power outputs generated from photovoltaic (PV) systems at different times is necessary for reliable and economical use of solar panels. The prediction of the power output is also very important in terms of factors such as installation of solar panels, guidance of electricity companies, energy management and distribution. In this study, we propose an Artificial Neural Network (ANN)...
Cluster computing combines the resources of multiple computers as they act like a single high-performance computer. In this study, a computer cluster consisting of Lustre distributed file system with one cluster server based on Slurm resource management system and thirteen calculation nodes were built by using available and inert computers that have different processors. Different bioinformatics algorithms...
Link Prediction is a fundamental problem in the social networks analysis. In order to solve this problem supervised learning algorithms, which include one fuzzy rule based algorithm were applied in this study. Besides supervised learning algorithms, an unsupervised strategy is also applied to compare the supervised and unsupervised results. Two different networks are chosen for the experiments: a...
In this empirical study we develop forecasting models for electricity demand using publicly available data and three models based on machine learning algorithms. It compares accuracy of these models using different evaluation metrics. The data consist of several measurements and observations related to the electricity market in Turkey from 2011 to 2016. It is available in different time granularities...
Breast biopsies based on the results of mammography and ultrasound have been diagnosed as benign at a rate of approximately 40 to 60 percent. Negative biopsy results have negative impacts on many aspects such as unnecessary operations, fear, pain, and cost. Therefore, there is a need for a more reliable technique to reduce the number of unnecessary biopsies in the diagnosis of breast cancer. So, computer-aided...
The quality of life of people is increasing together with the developing technologies. One of the most important factors affecting daily life is smart cities. The quality of life of people is positively affected by emerging this concept in recent years. Autonomous vehicles confront with the term of the smart city and have become even more popular in recent years. In this study, a system of traffic...
Central examinations are one of the measurement and evaluation tools used throughout the world to select from among the participants, to rank, to reduce the number of candidates before the interview or determine whether the level of education varies between regional and demographic criteria. A more objective measurement and evaluation can be made through the questioning of multiple choice questions...
The increase in the size of the data used in natural language processing activities brings with it time and space constraints. Thus, it is important to both store and access data efficiently. This study includes experiments for storing the term-document index, which will be used in a natural language processing project, effectively in memory. For this purpose, the indexed data is compressed using...
Image classification is one of the important problems in the field of machine learning. Deep learning architectures are used in many machine learning applications such as image classification and object detection. The ability to manipulate large image clusters and implement them quickly makes deep learning a popular method in classifying images. This study points out the success of the convolutional...
With the technology improvements, managing a large amount of multimedia objects such as audio, video, picture or a combination of these has become possible. Multimedia data needs more real time storage and high data transfer than traditional textual and numeric data. In addition to these requirements, significant amount of computation is demanded for multimedia applications to serve many users at...
Software engineering principles require that software should comply with particular design rules. However, expressing design rules in a developer friendly manner is an open problem. Besides, these rules are easily broken during development. As a result, design flaws usually occur in software products. In this paper, an approach is proposed to define design rules and to provide compliance between source...
In recent years, lightweight cryptography has become essential especially for the resource-constrained devices to ensure data protection and security. The selection of suitable cryptographic algorithm which is directly linked to requirements of the system will have dynamically effect on following such metrics like performance of the device, hardware resource cost, the area, speed, efficiency, computation...
Identification of human activities is a popular pattern recognition problem. In order to solve this problem, solutions based on machine learning are popularly used. Solutions based on the principle of collecting and processing classified data from one person are often used for non-real-time solutions. In this study, a system design is presented in which real time processing of the received acceleration...
Semantic similarity of texts is one of the important areas of Natural Language Processing, and there are several approaches to measure similarity: statistical, WordNet based, and hybrid. For all of these approaches, a lexical knowledge is used such as corpus or semantic network. WordNet is one of the most preferred and mature lexical knowledge base. In this study, we have focused on measuring semantic...
Many sentences create certain impressions on people. These impressions help the reader to have an insight about the sentence via some entities. In NLP, this process corresponds to Named Entity Recognition (NER). NLP algorithms can trace a lot of entities in the sentence like person, location, date, time or money. One of the major problems in these operations are confusions about whether the word denotes...
In this study, shallow parsing is applied on Turkish sentences. These sentences are used to train and test the per-formances of various learning algorithms with various features specified for shallow parsing in Turkish.
Wireless communication technology is spreading rapidly to all areas of our lives. The technology, which has a wide range of applications from radios, intelligent home systems, automation applications to GPS units, was used in monitoring the workers working in mines in this study. Most of the mining area underground mining is risky and the possibility of accident (gas jams, the explosion and dents,...
Identifying the sense of a word within a context is a challenging problem and has many applications in natural language processing. This assignment problem is called word sense disambiguation (WSD). Many papers in the literature focus on English language and data. Our dataset consists of 1400 sentences translated to Turkish from the Penn Treebank Corpus. This paper seeks to address and discuss 6 different...
The high reliance on the Internet observed recently makes the quests of mobile networks capacity demand and reliability crucial in mobile networks design and management. The next generation mobile networks is anticipated to address the problem of increasing capacity demand by employing various techniques such as Massive MIMO, Heterogeneous Networks (HetNets), and millimeter wave (mm-Wave). Nevertheless,...
Public transport applications, which aim to propose the ideal route to end users, have commonly been used by passengers. However, the ideal route for public transport varies depending on the preferences of users. The shortest path is preferred by most users as a primary criterion for the ideal route. According to our research, Dijkstra's Algorithm is mostly used in order to find shortest path. However,...
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