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In control system design, it is important to determine the controller type and controller parameters appropriately. PID controllers are mostly preferred in many applications. At the same time, it is known that PID controllers are insufficient to control higher order oscillatory systems with time delay. In such systems, PIDA controller is preferred instead of traditional PID controller. This paper presents a hybrid algorithm based optimization method for the control of higher order oscillatory systems with time delay. A hybrid algorithm combining the advantages of firefly and genetic algorithm is used to determine PIDA controller parameters. In the proposed method, a multi-criteria objective function is suggested by taking the settling and rising time, percent overshoot and steady state error criteria from the time response parameters. Two simulation studies are conducted to evaluate the performance of the proposed method, and the results are compared with some studies from the literature. In addition, the parameter uncertainties of the systems are analyzed and the robustness performance evaluations of the designed controllers are made. It is seen from the results obtained that the proposed method improves the transient and steady state response of higher order oscillatory systems with time delay and offers a fast and effective tuning method. [ABSTRACT FROM AUTHOR]

Nowadays it is important to store sensitive data and restrict its usage only to authorized people or institutions. In general, solutions for Data Leakage Prevention (DLP) ignores malicious attacks on documents and algorithms using fingerprinting and regular expressions are used. However, content-based attacks are successful evading those algorithms. In this paper an algorithm robust against malicious content-based attacks is proposed, which is independent of the attack executed. Transposition, sentence structure alteration, modification, obfuscation attacks are taken into consideration within the scope of paper. N-gram, charactergram, k-skip-n-gram and LSA methods are used in the feature extraction step, for having better classification results under attacks. The extracted features are passed to a Vote Classifier consisting of Support Vector Machine, Random Forest and Multi-Layer Perceptron classifiers. Additionally, the effects of instrumenting Spell-Correction in different steps of the algorithm is evaluated, which is effective against modification attacks. [ABSTRACT FROM AUTHOR]

Recent studies show that the performance of Evolutionary Algorithms often depends on choosing appropriate parameter configurations. Thus, researchers have generally tuned these parameters either looking at the similar research areas in the literature or manually, e.g. Grid Search. However, searching the parameter manually is laborious and timeconsuming; therefore, meta-optimization techniques have become commonly used methods to adjust parameters of an algorithm. These techniques can be classified in two widespread manners: off-line, tuning parameters of an algorithm before the algorithm initiates, and on-line, tuning the parameters while it is working. In this paper, Bipolar Matching Tendency (BMT) algorithm has been chosen as the selection method of a Genetic Algorithm (GA). The new obtained algorithm is named GA-BMT and has been used for the first time as an online metaoptimizer. In addition, the paper utilizes two search algorithms (Grid Search, Coarse to Fine Search) with three meta-optimization methods (Standard GA, Particle Swarm Optimization, GA-BMT) to investigate the best parameter settings of the Standard GA for 17 test functions, and offers a comparative work by comparing their results. Furthermore, non-parametric statistical tests, Friedman and Wilcoxon Signed Rank, were performed to demonstrate the significance of the results. Based on the all results that achieved, GA-BMT presents a reasonable achievement. [ABSTRACT FROM AUTHOR]

In this paper, it is aimed to express more accurately the intuitionistic fuzzy values expressed by the decision-makers for intuitionistic fuzzy parameterized intuitionistic fuzzy soft sets. For this purpose, virtual intuitionistic fuzzy parameterized intuitionistic fuzzy soft sets are proposed by defining the concepts of virtual lower and upper intuitionistic fuzzy approaches. Moreover, the basic set operations for this hybrid set type are examined together with their associated properties. In addition, a decision-making algorithm focusing on virtual intuitionistic fuzzy parameterized intuitionistic fuzzy soft sets is constructed. Finally, an analysis of the obtained results was made. [ABSTRACT FROM AUTHOR]

Güç sistemleri, üretim aşamasından tüketim aşamasına kadar karmaşık bir yapıdadır. Elektrik enerjisinin tüketiciye sürekli, güvenilir, kaliteli ve ekonomik olarak ulaştırılması üretim/iletim/dağıtım aşamalarında kesintisiz ve optimize edilmiş enerji akışının sağlanmasına bağlıdır. Optimum Yük Akışı (OYA) problemi jeneratörler/bara gerilimleri, kademe değiştiricileri aktif/reaktif gücü güvenli sınırlarında tutup, yakıt maliyeti ve aktif/reaktif güç kayıpları gibi parametrelerini optimize etmeyi hedefler. Bu nedenle güç sistemlerinde OYA probleminin etkili bir yöntemle optimize edilmesi önemlidir. Bu yayın, OYA problemini çözmek için yeni bir sezgisel algoritma olan İyileştirilmiş Su Çevrim Algoritması (İSÇA)'nı kullanmaktadır. Önerilen yöntem farklı amaç fonksiyonlarına sahip IEEE 30 bara güç sistemi üzerinde uygulanmıştır. Önerilen yöntemin etkinliği ve esnekliği literatürde yakın zamanda yayınlanmış diğer sezgisel yöntemlerin sayısal sonuçlarıyla karşılaştırılarak tartışılmıştır. Bu çalışmada İSÇA yöntemiyle IEEE 30 bara güç sistemine ait önemli sonuçlarından biri olan yakıt maliyetinin sonucu 798.9021 $/s hesaplanmıştır. Bu veri, çalışmada bildirilen güncel yöntemlere ait yakıt maliyeti sonuçlarından daha iyidir. Ayrıca bu yayında sunulan yöntem gerçek bir güç sistemi olan 154 kV Güney Marmara iletim sisteminin bir kesitinin sanal modeline uygulanarak, gerçek zamanlı bir sistemde aktif güç kayıplarının azaltılmasının sağlanabileceği gösterilmiştir. Power systems are getting more complex structure from production to consumption stages. The continuous, reliable, quality and economical delivery of electrical energy to the consumer depends on ensuring uninterrupted and optimized energy flow during the production/transmission/distribution stages. Optimum Power Flow (OPF) problem goals to optimize the parameters such as fuel cost, active/reactive power losses, etc by keeping the generators/bus voltages, tap setting and active/reactive power within their secure limits. Therefore, it is important to optimize load flow in power systems with an effective method. This paper uses a recent heuristic algorithm, named as the Modified Water Cycle Algorithm (MWCA), for the OPF problem. For the purpose demonstrate the effectiveness of the recommended method, it has been analyzed on the IEEE 30 bus power system for varied object functions. The validity and flexibility of this algorithm are discussed by comparison with numerical conclusion of the many newly published heuristic methods in the literature. In this study, the result of the of fuel cost, which is important results of the IEEE 30 bus test system, is computed using MWCA as $798.9021/s. This value is best the fuel cost results of various methods reported in the study. In addition, this method, has applied to a part of the virtual model of 154 kV South Marmara transmission system to show that the active power losses of transmission system could be reduced in a realtime system. [ABSTRACT FROM AUTHOR]

With the use of computers in every field, the usage intensity of processors is increasing day by day. In order to cope with this intensity, processors need to be constantly updated and improved. Various scheduling algorithms are being developed every day in order to continuously improve and accelerate the processors and to cope with the processing intensity. The main purpose of the scheduling algorithms is to increase the efficiency of the processor. For this, the processor needs to make a planning between the pending processes. Planning can be done by giving different priorities or using different methods. In order to increase the efficiency of the processor, in this paper, existing algorithms were examined. Round Robin Algorithm was improved using Genetic Algorithm. It is aimed to find the optimum values by selecting the quantum value according to the pending processes and their parameters. When the developed new method compared with the existing standard algorithms, it is observed that the waiting time and the turnaround time were shorter than the other algorithms. [ABSTRACT FROM AUTHOR]

TÜBİTAK has introduced the Incentive Program for International Scientific Publications (UBYT) in 1993 in order to increase the quantity, quality and impact of TR-addressed publications indexed in Web of Science (WoS) and support their authors. Some changes take place from time to time in the algorithms used in the program to identify publications to be supported and to calculate the amounts of monetary support to be paid. The new support algorithm introduced in 2019 aims to improve the shortcomings of the previous one. This paper is a comparative investigation of the impact of the new algorithm on supported journals, publications and the amounts of payments. For this, we first compare the functioning of the old and new support algorithms. We then analyze the impact of the new algorithm on the Program's supported journals lists as well as on the publications having article influence scores (AIS) that were supported in 2015 according to the old algorithm. Findings show that ongoing problems such as providing relatively more support to low impact publications and paying different amounts to publications in different fields do not seem to have completely been solved with the new algorithm. We discuss the major issues with performance-based research funding systems that solely use bibliometric measures to determine the impact of publications and offer some suggestions. [ABSTRACT FROM AUTHOR]

This paper studies how a group of delivery workers in Barcelona were able to organize a successful traditional and a social media strategy in order to claim for their rights as waged workers. They created a union, RidersxDerechos, and they also decided to create a worker's cooperative, Mensakas, with their own application and algorithm. We will study how they were able to re-appropriate technology and to use digital communities to spread alternative discourses. We have used different methodologies: traditional content analysis in Media, debate analysis in Social Media, qualitative ethnography. We noticed that RidersxDerechos access to media was very successful (300 piece of news analyzed) thanks to strikes and court trials, facilitating a change of perspective in the treatment of platform economy in Media. Media were following up the digital entrepreneurship rhetoric until then. Along with the traditional media strategy they developed a diversified communicative pathway in social media (Twitter, Instagram, Facebook, and Goteo) that helped them to establish alliances with riders from other cities and countries. We focused on more than 25.000 tweets. Finally, they proposed a new way to use technology by creating their own app and algorithms for their working cooperative, Mensakas. Crowdfunding was also used to fund it and to spread an alternative working storytelling from Silicon Valley's. [ABSTRACT FROM AUTHOR]

This paper presents a filled function method to solve economic load dispatch (ELD) of the thermal unit. The proposed method can take care of ELD considering nonlinearity such as valve point loading. The effectiveness of the proposed algorithm has been verified on three different test systems with equality and inequality constraint. Simulation results show that the filled function method is less sensitive to initial values of parameters and is more effective than other previously developed algorithms. In addition, the proposed algorithm is highly promising for the large-scale system. [ABSTRACT FROM AUTHOR]

Nowadays, a lot of data hiding algorithms for binary images have been proposed in the literature. The main purpose of these algorithms is to provide data hiding with high capacity and high visual quality. The pattern based data hiding algorithms are commonly used to achieve this purpose. In this paper, a new data hiding algorithm is suggested. This algorithm is based on minesweeper game for binary images. Neighborhood degree is calculated by selecting mine value as 0 or 1. The size of 3x3 non overlapping blocks have been used to determine neighborhood degree. Data hiding process is implemented by modifying the obtained neighborhood degree. Hamming distance is calculated to keep distortion in minimum level. In the selection of similar blocks with different neighborhood degrees, privacy of the algorithm is provided by using random number generators. The experimental results showed that the proposed data hiding algorithm resulted successfully. [ABSTRACT FROM AUTHOR]

This paper presents a high-performance vector control strategy for Multilevel Inverter (MLI) fed induction motor drive system. In the proposed drive system, an adaptive and online trained sugeno type neuro-fuzzy speed controller is used to improve the speed tracking performance. The generation of Pulse Width Modulation (PWM) patterns for multilevel inverter is obtained using space vector PWM algorithm. The complete drive system is implemented in real time using DS1104 controller card. Using the experimental setup, the performance of the proposed drive system is tested under different speed commands, mechanical parameter variations and load disturbances. The experimental results show that control performance of the proposed drive system is satisfactory. [ABSTRACT FROM AUTHOR]