Yazarlar
- Jermsittiparsert, Kittisak(8)
- Suanpang, Pannee(5)
- Jamjuntr, Pitchaya(3)
- Kaewyong, Phuripoj(3)
- Netwong, Titiya(2)
- Niamsorn, Chawalin(2)
- Pothipassa, Pattanaphong(2)
- Al-Sumaiti, Ameena Saad(1)
- Aljuaid, Mohammed(1)
- Chankoson, Thitinan(1)
- Chatchawanchanchanakij, Petcharaporn(1)
- Chunhapataragul, Thinnagorn(1)
- Elsayed, Salah K.(1)
- Fahlevi, Mochammad(1)
- Fuada, Noviati(1)
- Ghoneim, Sherif S. M.(1)
- Hajjiah, Ali(1)
- Harwijayanti, Bekti Putri(1)
- Indrawati, Lucia Rita(1)
- Marhaeni, A. A. I. N.(1)
- Mohamed, Mohamed A.(1)
- Prasetyo, Andjar(1)
- Rachmadhani, Arnis(1)
- Raharjo, Tri Weda(1)
- Sitorus, Jonni(1)
- Sudarmo, Lucia Rita(1)
- Wahyudianto, Heri(1)
- Waiyawuththanapoom, Phutthiwat(1)
- Wongmahesak, Kittisak(1)
- Yin, Fengyuan(1)
Yayınlar
- Kitap BölümüYalnız künye2025Balancing Innovation and Access: The Role of Intellectual Property in Healthcare
Wongmahesak, Kittisak
The pace of development in medical technology and pharmaceuticals is continuing to increase, making the impact that intellectual property (IP) has on healthcare even more important. The part of the chapter starts with types of IP patents, trademarks, copyrights, and trade secrets in healthcare research and development (R&D). On the one hand, it points out that strong IP protections spur innovation by enabling firms to capture a return on R&D spending, hence creating new issues about high drug prices and limited access among disadvantaged populations. The review also includes international trade agreements like the Trade-Related Aspects of Intellectual Property Rights (TRIPS) Agreement and Doha Declaration, which work for a strike of balance between IP rights and public health needs. The chapter advocates for the use of flexibilities within these frameworks such as compulsory licensing to improve access to life-saving treatments in public health emergencies. It concludes with a comparison of the ways in which IP is addressed in healthcare across nations illustrating that countries like India have found solutions where they prioritize public health and yet do not compromise on innovation. The chapter concludes with some ethical reflections on who should bear the cost in terms of lost profit when essential treatments are not accessible to those (M) CBs: patients, insurers, or pharm industries.
- MakaleAçık Erişim2023Adoption of the Green Economy through Branchless Rural Credit Banks during the COVID-19 Pandemic in Indonesia
Marhaeni, A. A. I. N.; Jermsittiparsert, Kittisak; Sudarmo, Lucia Rita; Indrawati, Lucia Rita; Prasetyo, Andjar; Fuada, Noviati; Rachmadhani, Arnis; Raharjo, Tri Weda; Wahyudianto, Heri; Harwijayanti, Bekti Putri
A green economy has an impact on improving welfare, but it takes continuous efforts to achieve it from various fields. Contribution in the context of banking on a small scale is one of the initiatives that can show participation in achieving a green economy. This study aims to explore people's behavior in financial transactions and analyze the practice of rural credit banks in encouraging the achievement of a green economy through the National Financial Inclusive Strategy (NFIS) program despite the COVID-19 pandemic. This study used quantitative approaches; observations were conducted at a certain time by collecting data taken directly as a complement to this study, as well as taking questionnaire data involving 363 samples and analyzing them using the structural equation model (SEM). The result is that green economic support is found in using paper for fewer savings transactions compared to branchless banking with conventional savings transactions. The high number of residents exposed to COVID-19 does not affect branchless banking. In addition, the use of branchless banking can show the penetration of financial literacy in the community. The results of the path analysis explain that perceived ease of use (7.468) and perceived usefulness (2.152) have an influence on attitude; intention is greatly influenced by attitude (15.357); and actual usage is influenced by intention (11.682). This research has specific implications for the Magelang City Rural Bank (MCRB), which needs to conduct market research to find out the potential of branchless banking that is specifically needed by the people of Magelang. Branchless banking innovation needs to be strengthened by presenting easy-to-understand and easy-to-use applications to improve the attitude of the Magelang people in adopting branchless banking applications and using them sustainably.
- MakaleAçık Erişim2023An Intelligent Recommendation for Intelligently Accessible Charging Stations: Electronic Vehicle Charging to Support a Sustainable Smart Tourism City
Suanpang, Pannee; Jamjuntr, Pitchaya; Kaewyong, Phuripoj; Niamsorn, Chawalin; Jermsittiparsert, Kittisak
The world is entering an era of awareness of the preservation of natural energy sustainability. Therefore, electric vehicles (EVs) have become a popular alternative in today's transportation system as they have zero emissions, save energy, and reduce pollution. One of the most significant problems with EVs is an inadequate charging infrastructure and spatially and temporally uneven charging demands. As such, EV drivers in many large cities frequently struggle to find suitable charging locations. Furthermore, the recent emergence of deep reinforcement learning has shown great promise for improving the charging experience in a variety of ways over the long term. In this paper, a Spatio-Temporal Multi-Agent Reinforcement Learning (STMARL) (Master) framework is proposed for intelligently public-accessible charging stations, taking into account several long-term spatio-temporal parameters. When compared to a random selection recommendation system, the experimental results demonstrate that an STMARL (master) framework has a long-term goal of lowering the overall charging wait time (CWT), average charging price (CP), and charging failure rate (CFR) of EVs.
- MakaleAçık Erişim2023The role of industry 4.0 in sustainable supply chain: Evidence from the textile industry
Chatchawanchanchanakij, Petcharaporn; Jermsittiparsert, Kittisak; Chankoson, Thitinan; Waiyawuththanapoom, Phutthiwat
The objective of this study was to examine the role of Industry 4.0 in the sustainable supply chain (SSC). The relationship between Industry 4.0, data storage, data assessment, performance evaluation, data inquiry and SSC were examined. To achieve the study objective, the mediation effect of data storage, data assessment, performance evaluation and data inquiry between Industry 4.0 and SSC was examined. Employees of textile companies were selected for data collection in Indonesia. Results of the study highlighted that Industry 4.0 had a significant positive effect on SSC. Better implementation of Industry 4.0 showed a positive effect on SSC. In addition to this, Industry 4.0 had a positive effect on data storage, data assessment, performance evaluation and data inquiry. Finally, data storage, data assessment, performance evaluation and data inquiry had a positive effect on SSC.
- 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 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 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.
