Sürdürülebilir Kalkınma Amaçları

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• MakaleAçık Erişim2025Scopus SJRQ2/r/munzur/606
  Innovative image encryption approach based on bitwise XOR high nonlinear S-boxes and random permutation

  Artuğer, Fırat

  With today's developing technologies, the need for new image encryption algorithms to encrypt images is inevitable. In this study, an innovative image encryption algorithm is proposed. The proposed algorithm first XORs each layer of the image with a unique and strong new key. Each layer is then subjected to a random permutation process. Each of the encrypted layers obtained here is finally passed through a new s-box structure with a high nonlinearity value. After these processes, all layers are combined to obtain an encrypted image. Thus, XOR and s-box confusion meet the criteria, while random permutation meets the diffusion criteria. In this study, both key and s-box structures were originally obtained with a chaotic Gaussian map. The outputs of the chaotic map were converted into bit sequences and five different sequences with a length of 1 million were obtained. All these arrays have successfully passed all NIST SP 800-22 tests. On the other hand, the proposed s-box structures surpassed many studies with nonlinearity values of 108, 108.5, and 108.75. The images were successfully encrypted with the proposed algorithm, and the encrypted images successfully completed tests such as NPCR-UACI, information entropy, histogram analysis, and correlation analysis. It is thought that this study will make many contributions to the fields of s-box development, random number generation, and image encryption.

  AtıfScopus3·OpenAlex3

  İncele
• MakaleAçık Erişim2024Scopus SJRQ2/r/munzur/1591
  Strong s-box construction approach based on Josephus problem

  Artuğer, Fırat

  There are two basic requirements for symmetric encryption algorithms. The first of these is diffusion. The second and most important is confusion. In these algorithms, this requirement is usually met by s-box structures. Therefore, s-box structures must be strong. So, a cryptographically good s-box will make the encryption algorithm difficult to crack. However, obtaining a strong s-box is a rather difficult problem. In this study, Josephus circle logic is used to solve this problem. Initially, with a random s-box structure, the elements are replaced according to their Josephus positions, and the s-box is made stronger. In the proposed algorithm, according to the Josephus logic, the elements that kill each other are replaced and this process continues until one element remains. The last 30 surviving elements are replaced with all elements. In this way, three different s-boxes were obtained. In two of them, the nonlinearity value was 110.5, and in one of them, the nonlinearity value was 110.75. Fixed points in the proposed s-box structures were identified and eliminated. In addition, it has been proven because of the analysis that the obtained s-box structures also meet other cryptographic requirements. In addition to leaving behind most studies in the literature, the proposed method will also provide strong s-box structures for encryption algorithms to be built in the future.

  AtıfScopus15·OpenAlex12

  İncele
• MakaleAçık Erişim2023Scopus SJRQ2/r/munzur/1587
  Application of the deep transfer learning framework for hydatid cyst classification using CT images

  Gul, Yeliz; Muezzinoglu, Taha; Kilicarslan, Gulhan; Dogan, Sengul; Tuncer, Turker

  Hydatid cyst, which causes important public health problems, is a disease frequently reported by radiologists. Classification of hydatid cyst types is very important to give the most suitable cure to patients. In order to decrease the misclassification rates of these cysts, machine learning is a good solution to create intelligent medical assistants. The primary objective of this work is to develop a new image classification framework to classify hydatid cyst types. Firstly, we collected a computed tomography (CT) image dataset. This CT image dataset consists of 2416 CT images with five classes (hydatid cyst types). We proposed a new deep feature engineering dataset framework for this dataset. This framework consists of (i) deep feature extraction by deploying transfer learning, (ii) iterative feature selection using INCA (iterative neighborhood component analysis), and (iii) classification. In the first phase—the feature extraction phase—we extracted deep features by deploying ten pretrained convolutional neural networks (CNNs). The used CNNs are commonly used CNNs, and the deep features have been extracted using the last pooling and fully connected layers of these networks. INCA has been applied to the generated deep features by each feature vector. k-nearest neighbors (kNN) classifier has been utilized to generate predicted values of these 10 CNNs using the selected features by INCA. Our proposed INCA-based deep feature extractor attained over 92% classification accuracy for each pretrained model. Our proposed framework reached over 92% classification accuracies, clearly demonstrating that our proposed framework is good image classification.

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  AtıfScopus10·WoS5·OpenAlex8

  İncele
• MakaleYalnız künye2021Scopus SJRQ2/r/munzur/2658
  Failure modes and effects analysis based on neutrosophic analytic hierarchy process: method and application

  Yucesan, Melih; Gul, Muhammet

  Failure modes and effects analysis (FMEA) is a commonly used method in risk evaluation. In this paper, a novel FMEA model based on neutrosophic analytic hierarchy process (NAHP) is proposed to overcome shortcomings of the risk prioritization of classical FMEA. Neutrosophic sets approach real-world decision-making problems from a three-aspect structure (i.e., truthiness, indeterminacy and falsity). Therefore, initially, AHP is merged with neutrosophic sets to assign importance weights to risk parameters in FMEA. The encountered failure modes are then prioritized with respect to the previously weighted risk parameters. Each element in AHP comparison matrices is considered as triangular neutrosophic numbers, and score functions are used to transform NAHP elements to deterministic values. The flexibility of determining the weight to each parameter of FMEA (severity, occurrence and detection) and evaluation of each failure mode against these parameters are more well-suited to the real decision-making condition. Finally, a case study in the textile industry is provided to show the applicability of the novel model. Sensitivity and comparative analysis are also performed to validate the results.

  AtıfScopus42·WoS27·OpenAlex33

  İncele
• MakaleYalnız künye2021Scopus SJRQ2/r/munzur/2533
  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.

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  AtıfScopus108·WoS93·OpenAlex103

  İncele
• MakaleYalnız künye2020Scopus SJRQ2/r/munzur/3533
  Hospital service quality evaluation: an integrated model based on Pythagorean fuzzy AHP and fuzzy TOPSIS

  Yucesan, Melih; Gul, Muhammet

  Providing better hospital service quality is one of the major concerns of healthcare industry in the world. Since health services in Turkey are provided in a very competitive environment, for making a better choice, the services delivered by the public and private hospitals should be evaluated according to the viewpoint of stakeholders in terms of satisfaction. In this study, a model proposal is presented based on the concept of Pythagorean fuzzy analytic hierarchy process and Pythagorean fuzzy technique for order preference by similarity to ideal solution method to provide an accurate decision-making process for evaluating the hospital service quality. We study under fuzzy environment to reduce uncertainty and vagueness, and use linguistic variables parameterized by Pythagorean fuzzy numbers. The proposed approach is separated from others with the integration of the methods in a way providing a systematic fuzzy decision-making process. A case study including 32 service quality criteria and two public and one private hospitals in Turkey assessed by 32 evaluators by medical staff, hospital executives, auxiliaries, and patients is performed to demonstrate the applicability and validity of the proposed approach. On conclusion, integrated model produces reliable and suggestive outcomes better representing the vagueness of decision-making process.

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  AtıfScopus164·WoS132·OpenAlex190

  İncele
• MakaleYalnız künye2020Scopus SJRQ2/r/munzur/3441
  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.

  AtıfScopus123·WoS96·OpenAlex113

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