Munzur ÜniversitesiMunzur ÜniversitesiAçık Erişim Arşivi · RDL Open

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  • MakaleYalnız künye2021Scopus SJRQ1
    Electrocoagulation induced treatment of indigo carmine textile dye in an aqueous medium: the effect of process variables on efficiency evaluated using biochemical response of Gammarus pulex

    Tanyol, Mehtap; Yildirim, Nuran Cikcikoglu; Alparslan, Dilek

    Indigo carmine removal from aqueous solutions was investigated by the electrocoagulation process and biochemical responses of Gammarus pulex to solutions before and after treatment were studied. Electrocoagulation experiments in the first stage were carried out with central composite design (CCD) using response surface methodology (RSM). Optimization of process variables that maximize indigo carmine removal by electrocoagulation process was carried out by using a second-order model within the studied test range of various process variables. According to the optimization results, optimum conditions for obtaining 82.55% maximum indigo carmine removal were pH 5.86, a current density of 13.31 mA/cm2, an indigo carmine concentration of 20.01 mg/L, and a time period of 115.80 min. Under optimum conditions for indigo carmine removal, the amount of sludge formed was 0.928 kg/m3, electrode consumption was 0.0305 kg/m3, and energy consumption was 7.461 kWh/m3. The operating cost was calculated as 0.79 US$/m3 under treatment conditions where optimum indigo carmine removal was achieved. In the second stage, G. pulex was exposed to treated and untreated synthetic indigo carmine solutions obtained from experiments according to optimum conditions in order to investigate the biochemical response for 24 and 96 h. Treatment efficiency was evaluated with superoxide dismutase (SOD), catalase (CAT), glutathione S-transferase (GST), and cytochrome P450 1A1 (CYP1A1) biomarkers. Results clearly showed that the electrocoagulation process was a simple and effective treatment method for the decolorization of wastewaters containing indigo carmine dye. The bioassays used in the present study provided good credibility for checking the detoxification of treated and untreated indigo carmine solutions.

    • SDG 6 · Temiz Su ve Sanitasyon
    • SDG 12 · Sorumlu Üretim ve Tüketim
    AtıfScopus14WoS12OpenAlex16
    ScopusWeb of SciencePubMedİncele
  • MakaleYalnız künye2021Scopus SJRQ2
    A modified failure modes and effects analysis using interval-valued spherical fuzzy extension of TOPSIS method: case study in a marble manufacturing facility

    Gul, Muhammet; Ak, M. Fatih

    Failure modes and effects analysis (FMEA) is a commonly used step-by-step approach to assess potential failures existing in a product or process design. In this paper, a modified FMEA model based on an interval-valued spherical fuzzy extension of technique for order preference by similarity to ideal solution (IVSF-TOPSIS) is proposed to cope with drawbacks of the traditional risk priority number (RPN) computation. Spherical fuzzy sets are the integration of Pythagorean fuzzy sets and neutrosophic sets. They provide more freedom to experts in decision making by including the degree of membership, non-membership, and hesitation of fuzzy sets. Therefore, initially, TOPSIS is merged with a special branch of spherical sets “interval-valued spherical fuzzy sets” to determine priorities of emerged failures. As a novelty to traditional RPN of FMEA, three parameters called cost, prevention, and effectiveness in addition to the existed parameters of severity, occurrence and detection are attached to the proposed approach. Weights of these parameters are determined via an interval-valued spherical weighted arithmetic mean operator (IVSWAM). As a demonstration, a case study in a marble manufacturing facility is provided to show the applicability of the novel model. Results show that the most crucial failure modes concern with the maintenance and repairing works of the factory and the lack of technical periodic checks of lifting vehicles regarding “block area: crane” failures. Some comparative and validation studies are also performed to test the solidity of the approach.

    • SDG 9 · Sanayi, Yenilikçilik ve Altyapı
    AtıfScopus108WoS93OpenAlex103
    ScopusWeb of Scienceİncele
  • MakaleAçık Erişim2021Scopus SJRQ1
    Occurrence of micropollutants in the Yesilirmak River Basin, Turkey

    Kucuk, Elif; Pilevneli, Tolga; Onder Erguven, Gokhan; Aslan, Sibel; Olgun, Elmas Ö.; Canlı, Oltan; Unlu, Kahraman; Dilek, Filiz B.; Ipek, Ubeyde; Avaz, Gulsen

    The European Water Framework Directive (WFD) (2000/60/EC) is the most visionary piece of European environmental legislation that aims to achieve good water status of both surface water and groundwater bodies. The Directive provides a fundamental basis for surface water monitoring activities in the European Member States. The objective of this study is to investigate the occurrence of micropollutants in the Yesilirmak River and to develop a cost-effective monitoring strategy based on spatiotemporal data. A 2-year seasonal monitoring program was conducted between 2016 and 2018, and the water samples were analyzed for 45 priority substances as defined by the WFD and 250 national river basin–specific pollutants. In the basin, 166 pollutants were quantified in at least one of the samples with individual concentrations ranging from 6 × 10−6μg/L to 100 mg/L. Fifty-four pollutants with a frequency of occurrence greater than 5% were selected for further evaluation. Based on statistical evaluation of the data, 20 pollutants were identified as the pollutants of primary concern. These 20 pollutants were grouped under three categories (metals, biocides, and industrial organic compounds) and their spatiotemporal distributions in the basin were assessed to establish a monitoring strategy specific to each pollutant category. The results of the study revealed that the common season for the monitoring of all pollutant categories was the spring. This study provides a generic methodology for the development of a cost-effective water quality monitoring strategy, which can be applicable for use in different basins and pollutant datasets.

    • SDG 6 · Temiz Su ve Sanitasyon
    AtıfScopus13OpenAlex14
    ScopusWeb of SciencePubMedİncele
  • MakaleYalnız künye2021Scopus SJRQ1
    Green supplier selection for textile industry: a case study using BWM-TODIM integration under interval type-2 fuzzy sets

    Celik, Erkan; Yucesan, Melih; Gul, Muhammet

    Although environmental awareness has reached a high level, enterprises—regardless of their working domains—follow the concept of greenness for their practices. This awareness among the stakeholders and supply chain experts has a positive impact on the purchasing departments of enterprises in various sectors to consider greenness in their procurement processes. The critical decision that must be made in green supply chain management (GSCM) is supplier selection. In the textile industry, a highly competitive market in recent years, suppliers for this industry have crucial roles in business activities considering environmental issues. Therefore, green supplier selection (GSS) in the textile industry is considered a must-be process for the stakeholders. In this study, a GSS problem is tackled as a multi-criteria decision process. Best worst method (BWM) and TODIM (an acronym in Portuguese of interactive and multi-criteria decision-making) methods are merged under an improved fuzzy concept of interval type-2 fuzzy sets (IT2FSs). In determining green suppliers’ evaluation criteria, BWM with interval type-2 fuzzy numbers (IT2F-BWM) is used. In selecting green suppliers, an interval type-2 fuzzy TODIM (IT2F-TODIM) is applied. Considering the characteristics of IT2FSs, BWM, and TODIM methods either individually and in integrated style, the proposed approach can handle uncertainty in the decision-making of GSS. To demonstrate the applicability of the approach, a case study in the Turkish textile industry is performed. Three green supplier alternatives (S1, S2, and S3) are assessed under forty-two sub-criteria. The study shows the most significant sub-criteria are recognized as dye and print quality, product design and pattern suitability, profit on the product, variation in price, and purchase cost. S2 green supplier has been selected as the most appropriate one. A sensitivity analysis is also fulfilled to check variation in the ranking of green suppliers.

    • SDG 12 · Sorumlu Üretim ve Tüketim
    AtıfScopus88WoS72OpenAlex100
    ScopusWeb of SciencePubMedİncele
  • Kitap BölümüYalnız künye2021
    Fine–kinney occupational risk assessment method and its extensions by fuzzy sets: A state-of-the-art review

    Gul, Muhammet; Mete, Suleyman; Serin, Faruk; Celik, Erkan

    The Fine–Kinney method (Fine in J Saf Res 3:157–166, 1971; Kinney and Wiruth in Practical risk analysis for safety management. Naval Weapons Center, pp 1–20, 1976), which was first introduced as an occupational health and safety risk analysis tool in the 1970s, is a systematic methodology that provides a mathematical formula for calculating the risk that arises due to a specified hazard. In the traditional version of Fine–Kinney as suggested in its original version, a risk score (RS) is calculated as a result of mathematical multiplication of probability (P), exposure (E), and consequence (C) parameters. These calculated risk scores are used to establish priorities for the corrective efforts in order to eliminate risks or reduce their effects to a reasonable level. This simple and useful method is preferred and implemented by small and medium-sized enterprises. In the academic literature, it has been applied for many risk analysis problems, although it includes several drawbacks recently revealed. In this method, no weight assignment is made for each risk parameter. Also, it is hard to assess consequence, exposure, and probability, precisely. Multi-criteria decision making (MCDM) is a pool of methods used in occupational health and safety risk analysis both by international standard-setting organizations and scholars from the literature. In classical MCDM methods, performance values and weights of decision criteria are known precisely and are specified with crisp numbers. However, many real-world problems contain uncertainties, and the knowledge and judgment of experts cannot be expressed precisely. Fuzzy-based MCDM methods, which are developed to reflect types and degrees of uncertainties better, produce more accurate results compared to classical methods. In this chapter, we first present the basics of Fine–Kinney method, including its implementing procedure, basic terminology, and drawbacks. Then, we provide a state-of-the-art review of Fine–Kinney occupational risk assessment method and its extensions by fuzzy sets. Graphical results obtained from the review are demonstrated to show the current state. Future work suggestions are also included to the chapter to show the possible gaps and possible opportunities.

    AtıfScopus12OpenAlex12
    Scopusİncele
  • Kitap BölümüYalnız künye2021
    Fine–kinney-based occupational risk assessment using interval type-2 fuzzy qualiflex

    Gul, Muhammet; Mete, Suleyman; Serin, Faruk; Celik, Erkan

    In this chapter, we improved Fine–Kinney occupational risk assessment approach with interval type-2 fuzzy QUALIFLEX (IT2FQUALIFLEX). QUALIFLEX is an outranking multi-attribute decision-making method proposed by an extension of the Paelinck’s (Pap Reg Sci Assoc 36:59–74,[1]), generalized Jacquet-Lagreze’s permutation method. Similar to other outranking solution-based approaches, it considers the solution which is a comparison of hazards. In this chapter, we adapted the interval type-2 fuzzy sets (IT2FSs) into QUALIFLEX as it reflects the uncertainty well in decision-making. IT2FQUALIFLEX algorithm under the Fine–Kinney concept provides a useful and solid approach to the occupational health and safety risk assessment. In addition to proposing this new approach, a case study is performed in the chrome plating unit. A validation is also performed in this study. Finally, the proposed approach is implemented in Python.

    • SDG 3 · Sağlık ve Kaliteli Yaşam
    AtıfScopus7OpenAlex7
    Scopusİncele
  • Kitap BölümüYalnız künye2021
    Fine–kinney-based occupational risk assessment using interval type-2 fuzzy topsis

    Gul, Muhammet; Mete, Suleyman; Serin, Faruk; Celik, Erkan

    This chapter proposed an improved Fine–Kinney occupational risk assessment approach using a well-known MCDM method “TOPSIS” under interval type-2 fuzzy set concept. It is defined as a technique for order preference by similarity to ideal solution by Hwang and Yoon [1]. It is based on separation from ideal and anti-ideal solution concept. Since the initial crisp data-based version is insufficient by time in reflecting the uncertainty in decision-maker’s opinions, fuzzy sets are integrated to the TOPSIS algorithm to provide a solid and comprehensive method. Interval type-2 fuzzy set is an improved version of the type-1 fuzzy set. It is also a special version of a general type-2 fuzzy set. Since general type-2 fuzzy systems contain complex computational operations, they cannot be easily applied to real-world problems such as occupational risk assessment. Interval type-2 fuzzy sets are the most frequently used type-2 fuzzy sets due to their ability in handling more uncertainty and producing more accurate and solid results. The Fine–Kinney concept is merged with the interval type-2 fuzzy set concept and TOPSIS for the first time through the literature. To demonstrate the applicability of the proposed approach, a case study is carried out in a chrome plating unit of a gun factory. Some beneficial validation and sensitivity analysis are also performed. Finally, as a creative contribution of our book, the implementation of the proposed approach in Python is performed.

    AtıfScopus2OpenAlex3
    Scopusİncele
  • MakaleYalnız künye2020Scopus SJRQ1
    A deep convolutional neural network model for automated identification of abnormal EEG signals

    Yıldırım, Özal; Baloglu, Ulas Baran; Acharya, U. Rajendra

    Electroencephalogram (EEG) is widely used to monitor the brain activities. The manual examination of these signals by experts is strenuous and time consuming. Hence, machine learning techniques can be used to improve the accuracy of detection. Nowadays, deep learning methodologies have been used in medical field to diagnose the health conditions precisely and aid the clinicians. In this study, a new deep one-dimensional convolutional neural network (1D CNN) model is proposed for the automatic recognition of normal and abnormal EEG signals. The proposed model is a complete end-to-end structure which classifies the EEG signals without requiring any feature extraction. In this study, we have used the EEG signals from temporal to occipital (T5–O1) single channel obtained from Temple University Hospital EEG Abnormal Corpus (v2.0.0) EEG dataset to develop the 1D CNN model. Our developed model has yielded the classification error rate of 20.66% in classifying the normal and abnormal EEG signals.

    • SDG 3 · Sağlık ve Kaliteli Yaşam
    AtıfScopus164OpenAlex211
    ScopusWeb of Scienceİncele
  • MakaleYalnız künye2020Scopus SJRQ2
    Analytical and finite element solutions of continuous contact problem in functionally graded layer

    Kaya, Yusuf; Polat, Alper; Özşahin, Talat Şükrü

    In this study, we solve the continuous contact problem of two layers with different material properties, loaded with two rigid flat blocks and resting on a rigid plane, by analytical and finite element methods. All surfaces are assumed to be frictionless. The upper layer is the functionally graded layer (FG), the height h1, the underlying layer is homogeneous, and the height is h2. It is assumed that the FG layer is isotropic and that the shear modulus and density change exponentially. The FG layer is loaded by means of two rigid flat blocks whose external loads are Q and P (per unit thickness in z direction). In the analytical solution of the problem, stress and displacement expressions are substituted in the boundary conditions and the problem is demoted to singular integral equations where the contact stresses are the unknown functions. These singular integral equations are solved numerically using the Gauss–Chebyshev integration formulas. Two-dimensional finite element analysis of the problem is performed using the ANSYS package program. The analyses are performed for different shear modulus ratios (μ2/μ-h1), distances between the blocks ((c − b)/h1) and inhomogeneity parameters (βh1). The contact stresses under the blocks, the normal stresses (σy) between interfaces of the FG layer and the homogeneous layer and between the homogeneous layer and rigid plane are also measured. In addition, the initial separation load and the initial separation distances (χcr, λcr) of the FG layer and homogeneous layer are determined. The results are presented comparatively as graphs and tables.

    AtıfScopus18WoS19OpenAlex14
    ScopusWeb of Scienceİncele
  • MakaleAçık Erişim2020Scopus SJRQ2
    Statistical evaluation of the bioremediation performance of Ochrobactrum thiophenivorans and Sphingomonas melonis bacteria on Imidacloprid insecticide in artificial agricultural field

    Onder Erguven, Gokhan; Demirci, Ulas

    Background: Pesticides are applied directly on the soil or on the vegetation, and thus, they can reach the receiving environment easily. In this way, environmental damage that stems from pesticides also affects public health and the natural habitat. Pesticides are one of the most harmful pollutant groups in terms of human health, fauna and the environment. They penetrate the application field and the applicator right after the application and start to show adverse effects. Methods: The bioremediation of the Imidacloprid (C9H10ClN5O2) insecticide, which is used commonly in Mediterranean climate, was compared with some soil bacteria in artificially prepared fields. For this purpose, firstly, it was determined whether the soil samples taken from a field where cotton was cultivated in Adana in Turkey was suitable for bioremediation. Then, the bacteria were isolated from these soils with the 16sRNA method. The enhanced microbial consortia of these isolated bacteria were inoculated to the artificial fields, meanwhile, the recommended concentrations of Imidacloprid were added to these agricultural fields. Imidacloprid, Chemical Oxygen Demand (COD), Biochemical Oxygen Demand (BOD5) and Total Organic Carbon (TOC) measurements were performed every day for two weeks on the filtrate samples taken from the artificial fields. Results: As a result of the monitoring, it was determined that Ochrobactrum thiophenivorans (Ot) and Sphingomonas melonis (Sm) species and their mixtures could eliminate the Imidacloprid pesticide within two weeks’ time. The removal efficiencies were 100% for active ingredient for each bacterium and their mixtures while COD were 97% and 96% for Ot. and Sm., respectively. TOC and BOD5 removal rates were 97% for both types and their mixtures in one or two-week period. Mixture of Ot and Sm shows 98.5% for COD, BOD5 parameters and 97.5% for TOC parameter. Conclusions: The results that will be obtained will help in the rehabilitation of the receiving environments that are exposed to pesticides in our country and take precautions to avoid the accumulation of pesticides in the body of the humans who are at the top of the food chain.

    AtıfScopus23
    ScopusPubMedİncele
  • MakaleYalnız künye2020Scopus SJRQ2
    An FMEA-based TOPSIS approach under single valued neutrosophic sets for maritime risk evaluation: the case of ship navigation safety

    Başhan, Veysi; Demirel, Hakan; Gul, Muhammet

    As in terrestrial facilities, safety is one of the most important issue in ships. Vessels navigating in many parts of the world face many different, tough and dangerous navigational risks. In this context, twenty-three fundamental risks which are frequently encountered in ship navigation were considered in this study and examined by an FMEA-based TOPSIS approach under single valued neutrosophic sets. Because of the lack of data in the literature, the opinions of the experts (Masters) who have many years of experience in the sector were taken. As a result of the study, extreme weather conditions, injury of crew, loss of input of sensory equipment (depth, gyro, speed etc.), struck by ropes, exposure to high speed machineries under high pressures, loss of maneuverability are very important among these risks. Considering these risks, corrective-preventive action plans and managerial implications for ship navigation have been presented. Consequently, the results of this study have an important warning and solution recommendation regarding ship navigation risks.

    AtıfScopus123WoS96OpenAlex113
    ScopusWeb of Scienceİncele
  • BildiriYalnız künye2020Scopus SJRQ3
    Dynamic Features Spaces and Machine Learning: Open Problems and Synthetic Data Sets

    Kaya, Sema Kayapinar; Navarro-Arribas, Guillermo; Torra, Vicenç; Huynh, V.; Entani, T.; Jeenanunta, C.; Inuiguchi, M.; Yenradee, P.

    Dynamic feature spaces appear when different records or instances in databases are defined in terms of different features. This is in contrast with usual (static) feature spaces in standard databases, where the schema of the database is known and fixed. Then, all records in the database have the same set of variables, attributes or features. Dynamic feature mining algorithms are to extract knowledge from data on dynamic feature spaces. As an example, spam detection methods have been developed from a dynamic feature space perspective. Words are taken as features and new words appearing in new emails are, therefore, considered new features. In this case, the problem of spam detection is represented as a classification problem (a supervised machine learning problem). The relevance of dynamic feature spaces is increasing. The large amounts of data currently available or received by systems are not necessarily described using the same feature spaces. This is the case of distributed databases with data about customers, providers, etc. Industry 4.0, Internet of Things, and RFIDs are and will be a source of data in dynamic feature spaces. New sensors added in an industrial environment, new devices connected into a smart home, new types of analysis and new types of sensors in healthcare, all are examples of dynamic feature spaces. Machine learning algorithms are needed to deal with these type of scenarios. In this paper we motivate the interest for dynamic feature mining, we give some examples of scenarios where these techniques are needed, we review some of the existing solutions and its relationship with other areas of machine learning and data mining (e.g., incremental learning, concept drift, topic modeling), we discuss some open problems, and we discuss synthetic data generation for this type of problem.

    AtıfScopus4WoS3OpenAlex3
    ScopusWeb of Scienceİncele
  • MakaleYalnız künye2019Scopus SJRQ2
    Investigation of the anti-apoptotic activity of ozone therapy in rainbow trout macrophages infected with Yersinia ruckeri

    Küçükgül, Azime; Küçükgül, Altuğ; Gönenci, Ramazan; Özsoy, Şule Yurdagül; Kutlu, Banu; Işgör, Mehmet Mustafa

    Yersinia ruckeri is the causal agent of enteric redmouth (ERM) in trout. This study aimed to investigate the effectiveness of nontoxic ozone on Y. ruckeri-infected trout cells in in vitro conditions. Rainbow trout macrophages (RTS-11) were exposed to Y. ruckeri for 24 h after being incubated with the ozonized medium at nontoxic concentration. Effective concentrations of nontoxic ozone (3 gamma) and bacteria (1.5 x 108 cfu/mL) were determined by viability tests. The expression of caspases 1, 3, 8, and 12 was determined by real-time PCR and protein levels investigated by ELISA method. Apoptotic-necrotic cell ratios were determined by acridine orange and ethidium bromide staining. Bacterial stimulations of caspases (1, 3, 8, and 12) were suppressed by ozone mostly at the translational level. While bacterial infection increased the count of apoptotic and necrotic cells at different stages, ozone significantly reduced this condition. Obtained data indicate possible use of nontoxic ozone as a safe and effective treatment alternative for increasing host defenses and eliminating the infection in the case of yersiniosis in fish.

    • SDG 3 · Sağlık ve Kaliteli Yaşam
    AtıfWoS1OpenAlex3
    ScopusWeb of Scienceİncele
  • Derleme MakaleAçık Erişim2019
    Stochastic multi-criteria decision-making: an overview to methods and applications

    Celik, Erkan; Gul, Muhammet; Yucesan, Melih; Mete, Suleyman

    Background: The alternatives selection problem with multi-criteria in stochastic form variables is called as stochastic multi-criteria decision-making. The stochasticity of the criteria is considered using stochastic dominance, prospect theory, and regret theory. Main text: In this paper, a total 61 papers are reviewed and analyzed based on method(s) used in stochastic multi-criteria decision-making problem, method used in stochasticity, specific objective, application area, and so on classification. All papers with respect to classification aspects are examined their real or empirical applications. Moreover, the studies are statistically investigated to present the latest trends of stochastic multi-criteria decision-making. Conclusions: This detailed review study ensures a comprehension for researchers on stochastic multi-criteria decision-making in respect of showing up-to-date literature and potential research areas to be concentrated in the future. It is observed that the stochastic multi-criteria decision-making problem has an attractive approach by researchers.

    AtıfScopus19WoS15OpenAlex19
    ScopusWeb of Scienceİncele
  • Dergi
    Journal of Environmental Health Science and Engineering
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  • Dergi
    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
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  • Dergi
    Studies in Fuzziness and Soft Computing
    İncele
  • Dergi
    Beni-Suef University Journal of Basic and Applied Sciences
    İncele
  • Dergi
    Chemical Research in Chinese Universities
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  • Dergi
    Afrika Matematika
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