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Scholarships are given to students who are studied in university by public institutions and organizations such as Yüksek Öğrenim Kredi ve Yurtlar Kurumu by taking different criterions into account. The students who deserve to have scholarship are detected by examining information in the forms that are given to student to detect the person who needs the scholarship. This process is causing time loose...
Unemployment, poverty and similar problems that have come to the fore with the increase in population in our country have caused the municipalities to take charge in the field of social assistance and social services. For this purpose, it is very important that the municipalities that undertake social assistance and social service tasks are able to use the present data quickly during distribution...
This paper investigates an efficient modal method for reducing weak transmission stability boundaries and identifying voltage control areas. This method divides the power system network into regions to eventually reduce the control candidates for each controller and minimize the interaction between each voltage control area. To determine the optimized number of areas, proper selection of threshold...
This paper presents a study of the operating performance of an efficient high power and low cost three-phase and three-level power rectifier as a complementary reactive power source. Simulation and experimental (final version) results are presented to support the above ideas.
Unstructured document and archive stacks that are formed in the past years are growing in size faster these days and they need to be clarified with various methods. This increases the interest in natural language processing discipline day by day and makes it more popular. In this study, we've tried to calculate the similarities between document stacks, that no information is presented onbehalf of...
Log analysis plays an important role for computer failure diagnosis. With the ever increasing size and complexity of logs, the task of analyzing logs has become cumbersome to carry out manually. For this reason, recent research has focused on automatic analysis techniques for large log files. However, log messages are texts with certain formats and it is very challenging for automatic analysis to...
There is a worldwide trend towards the integration of renewable energy in the form of distributed generation, leading to the formation of microgrids. Connection of these sources introduces new issues in the operation and management of distribution systems. An important issue is that of islanding, where the microgrid remains energized locally while isolated from the main grid. It is important to detect...
Identifying dependencies between classes is an essential activity when maintaining and evolving software applications. It is also known that JavaScript developers often use classes to structure their projects. This happens even in legacy code, i.e., code implemented in JavaScript versions that do not provide syntactical support to classes. However, identifying associations and other dependencies between...
This paper studies the relationship between China stock market performances and investors' attention, where the attention is measured by the page view of China's largest stock forum. The results show that trading volume, intraday volatility and liquidity have positive effects on investors' attention, while the effects of stock return to the attention is not significant. Finally, we demonstrate that...
In order to improve primary energy utilization, achieve economical operation of distribution network, comprehensively consider the concentration / compensation needs of various groups under typical load levels, and to gain understanding of characteristics of different types of user loads, the present paper proposes a hierarchical cluster algorithm to enhance the cohesion of a distribution feeder load...
We present here an implementation of the novel test called binary 0-1 test which is a chaos detection method and applied to the sunspot time series. This method seems to represent a useful improvement for the non-stationary time series chaotic characteristic analysis and computationally low cost. It is concluded that the monthly mean relative sunspot time series from January 1749 to December 2014...
The adaptability of the classical top-k frequent item sets mining algorithms is unsatisfied when being applied to some large datasets with both large scales of transactions and items. In this work, an algorithm called SIBA (sampling, improved bat algorithm (BA)) is proposed to solve this problem. SIBA applies BA and improves it by cloud model to search frequent item sets from a large number of items...
There are different types of embedded portable iDevices which can be used in criminal activities. The most commonly used gadget in the field of embedded portable iDevices is the iPad. Techniques used to acquire data from iPad include jail breaking, using inbuilt operating system utilities and using forensic tools (open source, freeware or commercial). Data integrity is a vital element of digital forensics...
This paper highlights the importance of measuring systemic risk of commercial banks. Conditional Value-at-Risk (CoVaR) is used to measure the degree of "risk externalities" that a specific bank contributes to the whole banking system. Our analysis not only presents current levels of systemic risk of individual banks but also the changes with time passes. There is some evidence that larger...
In the context of business-to-business (B2B) commerce, one of the most significant strategic activity for marketing and sales teams is to accurately estimate a company's demand for IT products that can be fulfilled by HP. This metric is known as Account level Total Addressable Market (A-TAM) within the HP community. Accurate A-TAM estimates are vital for developing superior marketing strategies, optimizing...
Data mining has been used in several studies to uncover hidden information within dataset and to predict outcomes after application of algorithms. In this study, neural connection was adapted as data mining tool where supervised multilayer perceptron which is the architecture with back propagation learning algorithms was used on a new automobile data after application of clustering to remove outliers...
We present Mining Zinc, a novel system for constraint-based pattern mining. It provides a declarative approach to data mining, where a user specifies a problem in terms of constraints and the system employs advanced techniques to efficiently find solutions. Declarative programming and modeling are common in artificial intelligence and in database systems, but not so much in data mining, by building...
Pattern mining is one of the most well-studied sub fields in exploratory data analysis. While there is a significant amount of literature on how to discover and rank item sets efficiently from binary data, there is surprisingly little research done in mining patterns from real-valued data. In this paper we propose a family of quality scores for real-valued item sets. We approach the problem by considering...
The paper presents a passive islanding detection scheme for both synchronous and inverter based distributed generations interfaced to microgrid using Decision Tree. The scheme involves extraction of different features at target DG location and builds the Decision Tree for intelligent anti-islanding protection. Extensive simulations are carried out including wide variations in system loading and power...
Sequential pattern mining is an essential data mining technique that has been widely applied to many real world applications. However, traditional algorithms generally suffer from the scalability problem when dealing with big data. In this paper, we aim to significantly upgrade the scale and propose Sequential PAttern Mining algorithm based on MapReduce model on the Cloud (abbreviated as SPAMC). Derived...
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