Sürdürülebilir Kalkınma Amaçları
Yazarlar
- Jermsittiparsert, Kittisak(12)
- Suanpang, Pannee(5)
- Aljuaid, Mohammed(3)
- Erdugan, Müge Kepekçi(3)
- Fahlevi, Mochammad(3)
- Jamjuntr, Pitchaya(3)
- Kaewyong, Phuripoj(3)
- Taspinar, Ozgur(3)
- Aung, Yadanar(2)
- Eratam, N(2)
- Fitriyana, Susan(2)
- Geçmen, İlker(2)
- Heidler, Petra(2)
- Kamburoğlu, K(2)
- Karahan, S(2)
- Lotfizadeh, Masoud(2)
- Netwong, Titiya(2)
- Niamsorn, Chawalin(2)
- Pothipassa, Pattanaphong(2)
- Rahman, Farzana(2)
- Ranjbarzadeh, Ramin(2)
- Respati, Titik(2)
- Su, Tin Tin(2)
- Sönmez, G(2)
- Zarbakhsh, Payam(2)
- Abeje, Tayachew A.(1)
- Abid, Khadijah(1)
- Acharya, Swosti(1)
- Ahmad, Absar(1)
- Akaydin, Oyku(1)
- Akgül, Nazan Yırgın(1)
- Aksoy, S.(1)
- Aksoy, Secil(1)
- Al Majzoub, Hisham(1)
- Al-Sumaiti, Ameena Saad(1)
- Aliyev, Fuzuli(1)
- Aman, Nida(1)
- Anari, Shokofeh(1)
- Araz, Emre(1)
- Atulya K., N.(1)
Yayınlar
- MakaleAçık Erişim2022Tourism Service Scheduling in Smart City Based on Hybrid Genetic Algorithm Simulated Annealing Algorithm
Suanpang, Pannee; Jamjuntr, Pitchaya; Jermsittiparsert, Kittisak; Kaewyong, Phuripoj
The disruptions in this era have caused a leap forward in information technology being applied in organizations to create a competitive advantage. In particular, we see this in tourism services, as they provide the best solution and prompt responses to create value in experiences and enhance the sustainability of tourism. Since scheduling is required in tourism service applications, it is regarded as a crucial topic in production management and combinatorial optimization. Since workshop scheduling difficulties are regarded as extremely difficult and complex, efforts to discover optimal or near-ideal solutions are vital. The aim of this study was to develop a hybrid genetic algorithm by combining a genetic algorithm and a simulated annealing algorithm with a gradient search method to the optimize complex processes involved in solving tourism service problems, as well as to compare the traditional genetic algorithms employed in smart city case studies in Thailand. A hybrid genetic algorithm was developed, and the results could assist in solving scheduling issues related to the sustainability of the tourism industry with the goal of lowering production requirements. An operation-based representation was employed to create workable schedules that can more effectively handle the given challenge. Additionally, a new knowledge-based operator was created within the context of function evaluation, which focuses on the features of the problem to utilize machine downtime to enhance the quality of the solution. To produce the offspring, a machine-based crossover with order-based precedence preservation was suggested. Additionally, a neighborhood search strategy based on simulated annealing was utilized to enhance the algorithm's capacity for local exploitation, and to broaden its usability. Numerous examples were gathered from the Thailand Tourism Department to demonstrate the effectiveness and efficiency of the proposed approach. The proposed hybrid genetic algorithm's computational results show good performance. We found that the hybrid genetic algorithm can effectively generate a satisfactory tourism service, and its performance is better than that of the genetic algorithm.
- MakaleAçık Erişim2022Extensible Metaverse Implication for a Smart Tourism City
Suanpang, Pannee; Niamsorn, Chawalin; Pothipassa, Pattanaphong; Chunhapataragul, Thinnagorn; Netwong, Titiya; Jermsittiparsert, Kittisak
The metaverse is an innovation that has created the recent phenomenon of new tourism experiences from a virtual reality of a smart tourism destination. However, the existing metaverse platform demonstrated that the technology is still difficult to develop, as the service provider did not disclose the internal mechanisms to developers, and it was a closed system, which could not use or share the user's data across platforms. The aim of this paper was to design and develop an open metaverse platform called the extensible metaverse, which would allow new developers to independently develop the capabilities of the metaverse system. The acquisition of this new technology was conducted through requirements analysis, then the analysis and design of the new system architecture, followed by the implementation, and the evaluation of the system by the users. The results found that the extended metaverse was divided into three tiers that created labels, characters, and virtual objects. Furthermore, the linking tier combined the 3D elements, and the deployment tier compiled the results of the link to use all three parts by using the Blender program, Godot Engine, and PHP + WebGL as their respective key mechanisms. This system was tested in Suphan Buri province, Thailand, which was evaluated by 428 users. The results of the metaverse satisfaction, created tourism experience, and overall satisfaction of the variation of the satisfaction of using the metaverse were 86.0%, 79.7%, and 92.9%, respectively. The relative Chi-square (chi(2)/df) of 1.253 indicated that the model was suitable. The comparative fit index (CFI) was 0.984, the goodness-of-fit index (GFI) was 0.998, and the model based on the research hypothesis was consistent with the empirical data. The root mean square error of approximation (RMSEA) was 0.024. In conclusion, the extended metaverse is more flexible than other platforms and also creates the user's satisfaction and tourism experience in the smart destination to support sustainable tourism.
- MakaleAçık Erişim2022Detection of Natural and Simulated Periodontal Defects Using Cone-Beam Computed Tomography and Digital Intraoral Radiography
Misirli, Melis; Aksoy, Secil; Tumer, Hayriye; Bilginaylar, Kani; Karaoglulari, Suzan; Berberoglu, Atilla; Orhan, Kaan; Icen, Murat
Objectives: In this study, it was aimed to compare the diagnostic value of cone beam computed tomography (CBCT) and digital intraoral periapical imaging methods in the diagnosis of periodontal defects, and the comparison of observers practicing dentistry in the field of periodontology and 3 other observers specialized in various branches was evaluated. Methods: 7 dry mandible and 5 dry maxilla were used in this study. A total of 111 artificial and natural defects (dehiscence, furca, fenestration, vertical defects) on the anterior, premolar and molar region were imaged with digital imaging techniques using different exposure parameters and scanned with CBCT. Results: According to the results of this study, CBCT is a more reliable method in the evaluation of all periodontal defects compared to CCD and PSP. 60 and 70 kVp with 0.01 irradiation time in CCD and 70 kVp 0.25 irradiation time in PSP is not suitable for detecting defects owing to high contrast. In the evaluation of periodontal defects, there was no single observer who had good results, different imaging methods and varying results were obtained in different defects. Conclusion: This study showed that the CBCT method has some diagnostic value for detecting all natural and simulated periodontal defects but it should only be used in cases where clinical evaluation and conventional radiographic imaging do not provide the information necessary for an adequate diagnosis and proper periodontal treatment planning.
- MakaleAçık Erişim2022Integration of Kouprey-Inspired Optimization Algorithms with Smart Energy Nodes for Sustainable Energy Management of Agricultural Orchards
Suanpang, Pannee; Pothipassa, Pattanaphong; Jermsittiparsert, Kittisak; Netwong, Titiya
Energy expenditures are now the main cost for two businesses that generate huge incomes each year for Thailand, which are agribusiness and community tourism. As entrepreneurs have to share a portion of their income as energy utility bills each month. This is a factor which results in them getting a low net return. Recognizing the need for energy management for sustainable use in agriculture focusing on durian cultivation in Kantharalak district and community tourism in Sisaket province, this research used a newly developed optimization algorithm called Kouprey-inspired optimization (KIO) to assist energy management in smart agriculture to support community-based tourism. This was initiated with a smart energy node to reduce the energy and labor costs for volcanic durian planting and accommodation in community-based tourist attractions in Sisaket province. The results showed that the combination of the KIO algorithm and smart energy node allowed for efficient management of the volcanic durian orchards and the use of clean energy in combination with traditional electric power for volcanic durian cultivation and community-based tourism. As the research area in Sisaket province had eight hours of solar power per day, this was sufficient for smart agriculture and community-based tourism in the daytime and in the evening. Furthermore, this allowed operators in both the agricultural and tourism sectors to reduce the labor costs of the durian orchard business and community-based tourism by about 30%, and in the energy sector, the costs could be reduced by 50%. As a consequence, this prototype would lead to the expansion and trial in durian orchards in the Eastern Economic Corridor area, which is an important economic area producing durian for export of the country.
- MakaleAçık Erişim2022Autonomous Energy Management by Applying Deep Q-Learning to Enhance Sustainability in Smart Tourism Cities
Suanpang, Pannee; Jamjuntr, Pitchaya; Jermsittiparsert, Kittisak; Kaewyong, Phuripoj
Autonomous energy management is becoming a significant mechanism for attaining sustainability in energy management. This resulted in this research paper, which aimed to apply deep reinforcement learning algorithms for an autonomous energy management system of a microgrid. This paper proposed a novel microgrid model that consisted of a combustion set of a household load, renewable energy, an energy storage system, and a generator, which were connected to the main grid. The proposed autonomous energy management system was designed to cooperate with the various flexible sources and loads by defining the priority resources, loads, and electricity prices. The system was implemented by using deep reinforcement learning algorithms that worked effectively in order to control the power storage, solar panels, generator, and main grid. The system model could achieve the optimal performance with near-optimal policies. As a result, this method could save 13.19% in the cost compared to conducting manual control of energy management. In this study, there was a focus on applying Q-learning for the microgrid in the tourism industry in remote areas which can produce and store energy. Therefore, we proposed an autonomous energy management system for effective energy management. In future work, the system could be improved by applying deep learning to use energy price data to predict the future energy price, when the system could produce more energy than the demand and store it for selling at the most appropriate price; this would make the autonomous energy management system smarter and provide better benefits for the tourism industry. This proposed autonomous energy management could be applied to other industries, for example businesses or factories which need effective energy management to maintain microgrid stability and also save energy.
- MakaleAçık Erişim2021In vitro assessment of periapical lesions created in sheep mandibles by using high resolution ultrasonography and cone beam computed tomography
Kamburoğlu, K; Çakmak, EE; Eratam, N; Sönmez, G; Karahan, S
- MakaleAçık Erişim2021A Secured Social-Economic Framework Based on PEM-Blockchain for Optimal Scheduling of Reconfigurable Interconnected Microgrids
Yin, Fengyuan; Hajjiah, Ali; Jermsittiparsert, Kittisak; Al-Sumaiti, Ameena Saad; Elsayed, Salah K.; Ghoneim, Sherif S. M.; Mohamed, Mohamed A.
Optimal scheduling of reconfigurable interconnected microgrids is a precious and critical task for the residential consumers especially with the integration of renewable energy sources, dispatchable units and energy storage systems. In this regard, not only the optimal scheduling of the microgrids in a realistic and correlated environment is a necessity, but also the guarantied security and the prevention of cyber-attacks are mandatory tasks for the operators. This article first addresses these issues by developing a novel framework based on blockchain for secured data transaction from the individual microgrids' components to the central control unit and then tries to find the optimal scheduling plan using stochastic programming based on point estimate method (PEM). Through such a hybrid PEM-blockchain based framework, the interconnected microgrids can supply the residential loads in a fully reliable, economic and secured structure. We also consider a social-economic framework to not only minimize the total operating cost of the microgrids, but also benefit the customers by enhancing the social factors through the optimal switching. Considering the complex and nonlinear nature of the problem, an effective corrected crow search (CCS) algorithm is deployed to find the most optimal operating point for the microgrids. The quality and capabilities of the proposed model are investigated using a practical residential interconnected microgrid. The results show that the optimal switching could reduce the total operation cost from $22,716 to $21,935 (3.56% reduction). Also, the average energy not supplied (AENS) has reduced from 1.4115 to 1.352 kWh/customer.yr (4.40% reduction), which are notable values. The results advocate the quality and functionality of the proposed framework.
- MakaleAçık Erişim2020Dermatological Findings in Female and Male Fibromyalgia Patients
Şentürk, Ahmet İlteriş; Ürkmez, Berna; Erdugan, Müge Kepekçi; Taspinar, Ozgur; Araz, Emre; Erdugan, Murat
Introduction: Fibromyalgia syndrome (FMS) is a chronic disease characterized by widespread musculoskeletal pain andhypersensitivity at some points of the body. Our study aims to investigate whether there is a difference between male andfemale FMS patients and male and female healthy volunteers concerning dermatological findings.Methods: Sixty female and 60 male patients, who were diagnosed with FMS, were included in the study group; 60 femaleand 60 male healthy volunteers were included in the control group in this study. Fibromyalgia Impact Questionnaire andthe Beck Depression Inventory were applied to all participants at the time of admission. All participants were examined bya dermatologist, and dermatological diagnoses were recorded. The results of the patients in both groups were comparedand statistically analyzed.Results: In the examination of dermatological diagnoses, it was found that the incidence of lichen simplex chronicus wassignificantly higher in female FMS patients than in healthy female participants (p=0.006).Discussion and Conclusion: Based on the results of this study, our findings suggest that dermatological examination inpatients with FMS should be given more importance within a holistic examination approach.
- MakaleAçık Erişim2020HCAB-SMOTE: A Hybrid Clustered Affinitive Borderline SMOTE Approach for Imbalanced Data Binary Classification
Al Majzoub, Hisham; Elgedawy, Islam; Akaydin, Oyku; Ulukok, Mehtap Kose
Binary datasets are considered imbalanced when one of their two classes has less than 40% of the total number of the data instances (i.e., minority class). Existing classification algorithms are biased when applied on imbalanced binary datasets, as they misclassify instances of minority class. Many techniques are proposed to minimize the bias and to increase the classification accuracy. Synthetic Minority Oversampling Technique (SMOTE) is a well-known approach proposed to address this problem. It generates new synthetic data instances to balance the dataset. Unfortunately, it generates these instances randomly, leading to the generation of useless new instances, which is time and memory consuming. Different SMOTE derivatives were proposed to overcome this problem (such as Borderline SMOTE), yet the number of generated instances slightly changed. To overcome such problem, this paper proposes a novel approach for generating synthesized data instances known as Hybrid Clustered Affinitive Borderline SMOTE (HCAB-SMOTE). It managed to minimize the number of generated instances while increasing the classification accuracy. It combines undersampling for removing majority noise instances and oversampling approaches to enhance the density of the borderline. It uses k-means clustering on the borderline area and identify which clusters to oversample to achieve better results. Experimental results show that HCAB-SMOTE outperformed SMOTE, Borderline SMOTE, AB-SMOTE and CAB-SMOTE approaches which were developed before reaching HCAB-SMOTE, as it provided the highest classification accuracy with the least number of generated instances.
- MakaleAçık Erişim2019Efficacy of Peloidotherapy in Patients with Subacromial Impingement Syndrome
Erdugan, Müge Kepekçi; Taspinar, Ozgur; Barut, Yasemin; Geçmen, İlker
The main purpose of our study is to investigate the efficacy of peloidotherapy applied at home in subacromial impingement syndrome and applied at the hospital. 73 female patients who were diagnosed with subacromial impingement syndrome were enrolled on one-sided shoulder. The patients were divided into two different groups, the treatment group (n = 42) and the control group (n = 31). Peloid therapy was performed in the Peloid therapy unit to direct contact with the skin in patients with treatment group. The patients in the control group applied the Peloid therapy at home with their own facilities. Both groups continued their routine medical treatment and home exercise programs. In the evaluation, DASH-T (Disabilities of the Arm, Shoulder and Hand) scores were used to assess the patient's shoulder functions..VAS (Visual Analogue Scale) was used for pain and health Assessment Questionnaire HAQ (Health Assessment Questionnaire) was used for general conditions.In the study group, in terms of DASH and HAQ scores, there was no significant difference after treatment (P > 0.05).In the study of Peloidotherapy in the study group, more positive results were obtained in pain parameters according to peloidotherapy applications in the control group. Studies are needed to increase the number of cases in the future.
- MakaleAçık Erişim2018The Effect of Dry Needle Treatment on Sleep in Fibromyalgia
Huriye, Uğur Arslan; Urkmez, Berna; Erdugan, Müge Kepekçi; Şentürk, İlteriş Ahmet; Geçmen, İlker; Taspinar, Ozgur; Basar, Hatice Melek
Objective: Our open-label clinical trial; to investigate the effect of dry needling on sleep problems in fibromyalgia patients with trigger points. Material and Method: Informed consent forms were obtained from a total of 100 patients with trigger points in the upper trapezius and rhomboid muscles who were under regular medical treatment, and followed up with a diagnosis of fibromyalgia for at least six months in the outpatient clinic. All patients were evaluated with FIQ (Fibromyalgia Impact Questionnaire), BDI (Beck Depression Scale), PSQI (Pittsburg Sleep Quality Index) and VAS (Visual Analog Scale). The patients were divided into two groups by computer-assisted simple randomization. In the study group, 50 fibromyalgia patients with trigger points were given a total of three dry needle injections to the upper trapezius and rhomboid muscles for a total of three weeks at weekly intervals, while 50 fibromyalgia patients with trigger points in the control group were not given any needling. One month after the first evaluation questionnaires of all patients (all of the study and control groups), the FIQ, BDI, PSQI scores were checked again and the patients were questioned by VAS (Visuel Pain Scale). Results: There was a statistically significant difference in FIQ, PSQI and VAS scores when the groups were compared in terms of amounts of change (respectively; p<0.001, p=0.007 ve p=0.035). Conclusion: In our study, it was observed that dry needles applied to trigger points of fibromyalgia patients had a statistically significant contribution to patients in terms of FIQ, PSQI and VAS values.