Tunceli, Turkey
Tunceli, Turkey

Tunceli University is a university located in Tunceli, Turkey. It was established in 2008. Wikipedia.

Time filter

Source Type

Baskonus H.M.,Tunceli University
AIP Conference Proceedings | Year: 2017

In this study, we have applied the improved Bernoulli sub-equation function method to the generalized double combined Sinh-Cosh-Gordon equation. This method gives new analytical solutions such as complex and hyperbolic function solutions to the problem considered in this paper. Then, we plot the three and two dimensional surfaces of analytical solutions by using Wolfram Mathematica 9. © 2017 Author(s).

Kaval I.,Yuzuncu Yil University | Behcet L.,Bingöl University | Cakilcioglu U.,Tunceli University
Journal of Ethnopharmacology | Year: 2014

Ethnopharmacological relevance This paper provides significant ethnobotanical information on medicinal plants in the Geçitli Township in the Eastern Anatolia Region. Recording such data calls for urgency this is the first ethnobotanical study in which statistical calculations about plants are carried out by means of the FIC method in Eastern (Hakkari) part of Turkey. Aim of the study This study aims to identify the wild plants collected for medicinal purposes by locals of Geçitli which is located in the Eastern Anatolia Region of Turkey, and to identify the uses and local names of these wild plants. Materials and methods A field study had been carried out for a period of approximately 2 years (2008-2010). During this period, 70 plants taxa and one mushroom were collected. Demographic characteristics of participants, names of the local plants, their utilized parts and preparation methods were investigated and recorded. The plant taxa were collected within the scope of the study; and herbarium materials were prepared. In addition, the relative significance value of the taxa was determined, and informant consensus factor (FIC) was calculated for the medicinal plants included in the study. Results We have found out in the literature review of the plants included in our study that 70 plant taxa and one mushroom are already used for medicinal purposes while 11 plants are not available among the records in the literature. The most common families are Asteraceae, Apiaceae, Lamiaceae, Rosaceae, Euphorbiaceae, Fabaceae, and Malvaceae. We include in our study and report for the first time the medicinal uses of Alchemilla hessii Rothm., Cirsium pubigerum (Desf.) DC. var. spinosum Pet., Diplotaenia cachrydifolia Boiss., Euphorbia macrocarpa Boiss. & Buhse, Galium consanguineum Boiss., Inula helenium L. subsp. vanensis Grierson, Johrenia dichotoma DC. subsp. sintenisii Bornm., Pelargonium quercetorum Agnew, Rosa heckeliana Tratt. subsp. vanheurckiana (Crěp.) Ö. Nilsson, Salix aegyptiaca L., Taraxacum montanum (C.A. Mey.) DC. Names of local plants in Turkey vary especially due to vernaculars. The plants that the locals of Geçitli use are called with the same or different local names in various parts of Anatolia. Conclusion We found out that locals living in the research area use for therapeutic purpose 70 plants taxa and one mushroom which belong to 28 families. Turkish citizens with different ethnic backgrounds took the questionnaire. These people use these wild plants in treatment of several diseases. Comparison of the data obtained in this study with the experimental data obtained in the previous laboratory studies on the wild plants which grow in Geçitli proved ethnobotanical usages to a great extent. Literature review indicated that the therapeutic plants that grow in Geçitli are used in different parts of the world for the treatment of similar diseases. © 2014 Elsevier Ireland Ltd. All rights reserved.

Ozkaynak F.,Tunceli University | Ozer A.B.,Firat University
Physics Letters, Section A: General, Atomic and Solid State Physics | Year: 2010

It is important to design cryptographically strong S-Boxes in order to design secure systems. In this study, a strong, chaos-based S-Box design is proposed. Continuous-time Lorenz system is chosen as the chaotic system. Proposed methodology is analyzed and tested for the following criteria: Bijective property, nonlinearity, strict avalanche criterion, output bits independence criterion and equiprobable input/output XOR distribution. The results of the analysis show that the proposed cryptosystem is a highly reliable system suitable for secure communication. © 2010 Elsevier B.V.

Alatas B.,Tunceli University
Expert Systems with Applications | Year: 2012

When investigated carefully, chemical reactions possess efficient objects, states, process, and events that can be designed as a computational method en bloc. In this study, a novel computational method, which is robust and have less parameters than that of used in the literature, is intended to be developed inspiring from types and occurring of chemical reactions. The proposed method is named as artificial chemical reaction optimization algorithm, ACROA. In this study, one of the first applications of this method has been performed in classification rule discovery field of data mining and efficiency has been demonstrated. © 2012 Elsevier Ltd. All rights reserved.

Eristi H.,Tunceli University
Measurement: Journal of the International Measurement Confederation | Year: 2013

This paper proposes a new fault diagnosis approach based on combined wavelet transform and adaptive neuro-fuzzy inference system for fault section identification, classification and location in a series compensated transmission line. It performs an effective feature extraction approach based on norm entropy in order to obtain the features represented main frequency, harmonic and transient characteristics of the fault signals. The proposed method uses the samples of fault voltages and currents for one cycle duration from the inception of fault. The feasibility of the proposed method has been tested on a 400 kV, 300 km series compensated transmission line for all the ten types of faults using MATLAB/Simulink for a large data set of 23,436 fault cases comprising of all the 10 types of faults. Fault signals varying with fault resistance, fault inception angle, fault distance, load angle, percentage compensation level and source impedance are applied to the proposed algorithm. The results also indicate that the proposed method is robust to wide variation in system conditions and has higher fault diagnosis accuracy with regard to the other approaches in the literature for this problem. © 2012 Elsevier Ltd. All rights reserved.

Eristi H.,Tunceli University | Demir Y.,Firat University
IET Generation, Transmission and Distribution | Year: 2012

In this study, a new approach for the classification of power quality events is presented. Also, power quality disturbances, which occur in each phase of the power system after a fault event, are classified with the proposed system. In the proposed recognition system, three-phase voltage signals are used in order to identify the type of power quality events. Three-phase voltage signals are subjected to normalisation and segmentation processes. A wavelet transform method is used in order to obtain the distinctive features of event signals. An efficient feature vector, which represents the distinctive characteristics of three-phase event voltage signals and reduces data size, is extracted by applying the two-stage feature extraction process. Power quality event types are determined by using a support vector machine classifier. At the last stage of intelligent recognition system, types of power quality disturbances regarding each fault event are identified by doing a further analysis. Real power system data are used to evaluate the performance of the proposed approach. According to the obtained results, proposed intelligent recognition system classifies power quality event types with a high accuracy. The analyses and results also show that the proposed approach is efficient, reliable and applicable. © 2012 The Institution of Engineering and Technology.

Koluman A.,National Food Reference Laboratory | Dikici A.,Tunceli University
Critical Reviews in Microbiology | Year: 2013

Emerging foodborne pathogens are challenging subjects of food microbiology with their antibiotic resistance and their impact on public health. Campylobacter jejuni, Salmonella spp. and Verotoxigenic Escherichia coli (VTEC) are significant emerging food pathogens, globally. The decrease in supply and increase in demand lead developed countries to produce animal products with a higher efficiency. The massive production has caused the increase of the significant foodborne diseases. The strict control of food starting from farm to fork has been held by different regulations. Official measures have been applied to combat these pathogens. In 2005 EU declared that, an EU-wide ban on the use of antibiotics as growth promoters in animal feed would be applied on 1 January 2006. The ban is the final step in the phasing out of antibiotics used for non-medical purposes. It is a part of the Commission's strategy to tackle the emergence of bacteria and other microbes resistant to antibiotics, due to their overexploitation or misuse. As the awareness raises more countries banned application of antibiotics as growth promoter, but the resistance of the emerging foodborne pathogens do not represent decrease. Currently, the main concern of food safety is counter measures against resistant bugs. © 2013 Informa Healthcare USA, Inc.

Eristi H.,Tunceli University | Demir Y.,Firat University
Expert Systems with Applications | Year: 2010

This paper presents a new approach for automatic classification of power quality events, which is based on the wavelet transform and support vector machines. In the proposed approach, an effective single feature vector representing three phase event signals is extracted after signals are applied normalization and segmentation process. The kernel and penalty parameters of the support vector machine (SVM) are determined by cross-validation. The parameter set that gives the smallest misclassification error is retained. ATP/EMTP model for six types of power system events, namely phase-to-ground fault, phase-to-phase fault, three-phase fault, load switching, capacitor switching and transformer energizing, are constructed. Both the noisy and noiseless event signals are applied to the proposed algorithm. Obtained results indicate that the proposed automatic event classification algorithm is robust and has ability to distinguish different power quality event classes easily. © 2009 Elsevier Ltd. All rights reserved.

Balbey M.,Tunceli University
International Journal of Energy Economics and Policy | Year: 2015

This study examines the causal relationships between economic growth, carbon dioxide emission and foreign direct investment (FDI) and evaluates the environmental kuznets curve (EKC) hypothesis for Turkey in 1974-2011. Firstly, the causality relationships investigated by using the Johansen Cointegration test, The Granger Causality Test, Impulse-Response and Variance Decomposition Analysis of vector autoregression model (VAR) model. The causality relationships display that FDI (LFDI) and economic growth (LGDP) have a significant effect on carbon dioxide emissions (LCO2). Moreover, impulse-response functions and variance-decompositions of VAR model support these relationships among LGDP, LCO2 and LFDI. Secondly, the study investigates the validity of the EKC hypothesis in Turkey for the period 1974-2011 by using regression model approach for the various EKC model forms such as linear, quadratic, and cubic. Consequently, economic growth leads to degradation of environment and depletion of natural resources. It must be the major aim to obtain a sustainable economic growth by less CO2 emissions and consuming less energy. Moreover, the policy makers may take account exogenous impacts such as foreign investments to plan energy policies, and to maintain economic growth against global climate warming. © 2015, Econjournals. All rights reserved.

Alatas B.,Tunceli University
Expert Systems with Applications | Year: 2011

Heuristic based computational algorithms are densely being used in many different fields due to their advantages. When investigated carefully, chemical reactions possess efficient objects, states, process, and events that can be designed as a computational method en bloc. In this study, a novel computational method, which is more robust and have less parameters than that of used in the literature, is intended to be developed inspiring from types and occurring of chemical reactions. The proposed method is named as Artificial Chemical Reaction Optimization Algorithm, ACROA. Applications to multiple-sequence alignment, data mining, and benchmark functions have been performed so as to put forward the performance of developed computational method. © 2010 Elsevier Ltd. All rights reserved.

Loading Tunceli University collaborators
Loading Tunceli University collaborators