SCOPUS 2024

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OPTIMIZING LAST-MILE DELIVERY BY DEEP Q-LEARNING APPROACH FOR AUTONOMOUS DRONE ROUTING IN SMART LOGISTICS
(Regional Association for Security and crisis management, 2024) Pannee Suanpang; Pitchaya Jamjuntr; P. Suanpang; Department of Information Technology, Faculty of Science and Technology, Suan Dusit University, Bangkok, 10300, Thailand; email: pannee_sua@dusit.ac.th
The advancement technology of artificial intelligence and e-commerce has increased and this has called for new ways to improve last-mile transportation, which is regarded as an essential part of the logistics value chain, especially in smart logistics. This paper addresses the problem of developing effective routes for autonomous drones in last-mile logistics using deep Q-learning. This paper aims to improve the process of delivery by utilizing the flexibility and intelligence of self-driven autonomous drones in smart logistics transportation. The key challenge for the effective provision of last-mile delivery services remains the decision on the routing of many aerial drones in an indoor urban environment, concerning the restrictions of a time window for delivery, energy consumption and traffic. This paper implements a deep Q-learning paradigm that allows drones to relearn their flight paths and delivery strategy during the lifecycle, thereby reducing the cost in the long run while using the costing strategies as part of the reengineering process. The approach has been validated through extensive experimentation and simulations. Results obtained indicate that the delivery drones modified for the study attained the designed requirements of deep Q-learning, including optimal navigation and performance that attained 12.8% shorter delivery time, an increase in energy efficiency by 8.4%, and a route quality improvement of 20.1%. Furthermore, highlights the performance of the system in various situations where deep Q-learning and standard routing approaches are compared. This paper not only aids in the minimization of the last-mile delivery constraint by the use of shipping drones but also emphasizes the capacities of reinforcement learning strategies such as deep Q-learning in tackling the routing problems in smart logistics systems. At last, it advocates carrying on deeper into the application of reinforcement learning in the solving of complex optimization problems in various other fields. © 2024 Regional Association for Security and crisis management. All rights reserved.
Integrating Generative AI and IoT for Sustainable Smart Tourism Destinations
(Multidisciplinary Digital Publishing Institute (MDPI), 2024) Pannee Suanpang; Pattanaphong Pothipassa; P. Suanpang; Department of Information Technology, Faculty of Science & Technology, Suan Dusit University, Bangkok, 10300, Thailand; email: pannee_sua@dusit.ac.th
This paper aims to develop a groundbreaking approach to fostering inclusive smart tourism destinations by integrating generative artificial intelligence (Gen AI) with natural language processing (NLP) and the Internet of Things (IoT) into an intelligent platform that supports tourism decision making and travel planning in smart tourism destinations. The acquisition of this new technology was conducted using Agile methodology through requirements analysis, system architecture analysis and design, implementation, and user evaluation. The results revealed that the synergistic combination of these technologies was organized into three tiers. The system provides information, including place names, images, descriptive text, and an audio option for users to listen to the information, supporting tourists with disabilities. Employing advanced AI algorithms alongside NLP, developed systems capable of generating predictive analytics, personalized recommendations, and conducting real-time, multilingual communication with tourists. This system was implemented and evaluated in Suphan Buri and Ayutthaya, UNESCO World Heritage sites in Thailand, with 416 users participating. The results showed that system satisfaction was influenced by (1) the tourism experience, (2) tourism planning and during-trip factors (attention, interest, and usage), and (3) emotion. The relative Chi-square (_2/df) of 1.154 indicated that the model was suitable. The Comparative Fit Index (CFI) was 0.990, the Goodness-of-Fit Index (GFI) was 0.965, and the model based on the research hypothesis was consistent with the empirical data. This paper contributions significant advancements in the field of smart tourism by demonstrating the integration of Gen AI, NLP, and the IoT and offering practical solutions and theoretical insights that enhance accessibility, personalization, and environmental sustainability in tourism. © 2024 by the authors.
Virtual Learning Environment - Evaluation of LearnerÕs Behavior Using Topic Models
(Institute of Electrical and Electronics Engineers Inc., 2024) N.A. Deepak; Gyanendra Kumar; Aunkrisa Sangchumnong; R.S. Chaithra; Sur Singh Rawat; Aziz Nanthaamornphong; Girish B.C. Kumar; Manoj Gupta; N.A. Deepak; RV Institute of Technology and Management, Bengaluru, India; email: deepakna.rvitm@rvei.edu.in
Online learning platforms come with a number of difficulties. To identify the student who does not do the given assignment within the allotted time. Researchers have been attempting to solve this issue in the literature of late, however most algorithms are unable to produce linearly separable learner clusters and correctly classify the input documents. In an attempt to overcome these problems, the suggested methodology builds clusters of linearly separable learners by applying topic models such as Latent Dirichlet Allocation (LDA). First, the necessary features are retrieved and converted into an appropriate LDA of words and phrases. The topic-modeling algorithm (LDA) is then fed the words to create clusters of related content or learners. A number of experiments were carried out to assess how well various predictive models performed. The results show the topic-modeling algorithm LDA attains significant clustering of documents over the other state-of-art. © 2024 IEEE.
EXTENDING NETWORK INTRUSION DETECTION WITH ENHANCED PARTICLE SWARM OPTIMIZATION TECHNIQUES
(Academy and Industry Research Collaboration Center (AIRCC), 2024) Surasit Songma; Watcharakorn Netharn; Siriluck Lorpunmanee
The present research investigates how to improve Network Intrusion Detection Systems (NIDS) by combining Machine Learning (ML) and Deep Learning (DL) techniques, addressing the growing challenge of cybersecurity threats. A thorough process for data preparation, comprising activities like cleaning, normalization, and segmentation into training and testing sets, lays the framework for model training and evaluation. The study uses the CSE-CIC-IDS 2018 and LITNET-2020 datasets to compare ML methods (Decision Trees, Random Forest, XGBoost) and DL models (CNNs, RNNs, DNNs, MLP) against key performance metrics (Accuracy, Precision, Recall, and F1-Score). The Decision Tree model performed better across all measures after being fine-tuned with Enhanced Particle Swarm Optimization (EPSO), demonstrating the model's ability to detect network breaches effectively. The findings highlight EPSO's importance in improving ML classifiers for cybersecurity, proposing a strong framework for NIDS with high precision and dependability. This extensive analysis not only contributes to the cybersecurity arena by providing a road to robust intrusion detection solutions, but it also proposes future approaches for improving ML models to combat the changing landscape of network threats. © (2024), (Academy and Industry Research Collaboration Center (AIRCC)). All Rights Reserved.
Upgrading the Grass-roots Economy Through Community-Based Tourism under the Concepts of Innovative Business and Creative Economy
(Research and Development Institute Suan Dusit University, 2024) Wanphen Kuensman; Wipada Mukda; W. Mukda; Faculty of Management Science, Suan Dusit University, Bangkok, 10300, Thailand; email: Wanphen_3956@hotmail.com
This academic paper aims to study the upgrading of the grass-roots economy through community-based tourism under the concepts of innovative business and the creative economy. The grass-roots economy at the local community level needs to be strong and increase competitiveness this means it must be self-reliant through economic and behavioral restructuring by promoting the learning process of the community such as educating open exchange platform and organizing a community learning center or community information center to collect history. These efforts provide the community with a foundation for driving community-based tourism, enabling them to innovate, add value, and elevate the quality of products and services, thereby building trust among stakeholders. © 2024, Research and Development Institute Suan Dusit University. All rights reserved.
Enhancement on compressive strength of Bangkok clay cement using novel high-strength polyethylene fibers
(Institute of Physics, 2024) Sakol Pochalard; Chalermpon Wungsumpow; Keeratikan Piriyakul; K. Piriyakul; Center of Excellence in Structural Dynamics and Urban Management, Science and Technology Research Institute, Department of Civil and Environmental Engineering Technology, College of Industrial Technology, King Mongkut's University of Technology North Bangkok, Bangkok, Thailand; email: keeratikan.p@cit.kmutnb.ac.th
This study aims to investigate the effect of novel high-strength polyethylene fibers on the unconfined compressive strength (UCS) behavior of concrete produced with admixed Bangkok clay cement. Bangkok clay samples were prepared at a liquid limit of 88% and were added to ordinary Portland cement (OPC) at 2, 4, 6, 8 and 10% by weight; polyethylene fibers were also added at 0.5, 1.0, 1.5, 2.0 and 2.5% by volume. These samples were cured for 7, 14, and 28 days and subjected to an unconfined compressive test. From the test results, the cement content of 8% by weight was the optimum, and a polyethylene fiber content of 1% by volume is recommended. Moreover, the novel high-strength polyethylene fiber with 0.2 mm in diameter and 6 mm in length provided the maximum UCS value. © Published under licence by IOP Publishing Ltd.
Influence of Various Factors on Hydrolytic Enzyme Activity and COD Removal Efficiency in Cassava Starch Wastewater by Marine Actinomycete Streptomyces sp. A1-3
(Research and Development Institute Suan Dusit University, 2024) Maliwan Kutako; Pattana Sillapachai; Yutthaya Yuyen; Paveena Tapaneeyaworawong; Nisa Siranonthana; Nongnuch Rungsawang; Janjarus Watanachote; J. Watanachote; Institute of Marine Science, Burapha University, Chonburi, 20131, Thailand; email: janjarus@buu.ac.th
Wastewater from the production line of cassava starch factories contains a significant amount of organic matter, necessitating treatment before discharging or reusing in the factory. Actinomycetes can produce various hydrolytic enzymes, especially carbohydrate-degrading enzymes, which are important in the biological wastewater treatment process because actinomycetes can utilize several growth substances such as sugar, polysaccharides and protein. In this research, the effects of carbon source, pH, salinity and incubation time on hydrolytic enzyme activity for producing reducing sugar of a marine actinomycete Streptomyces sp. A1-3 were evaluated. The maximum hydrolytic enzyme activity was found in the oatmeal yeast extract carboxymethyl cellulose (OYC) medium with a pH value of 4.0-6.2 and a cultivation time of 4 days. Salinities in the range of 0-35 practical salinity units (psu) had no effect on the hydrolytic enzyme activity of strain A1-3. Subsequently, the efficiency of Streptomyces sp. A1-3 in reducing the chemical oxygen demand (COD) in cassava starch wastewater was evaluated using a Completely Randomized Design (CRD). The control tank had no Streptomyces sp. A1-3, while in the treatment tank, strain A1-3 was added. Aeration was supplied throughout the 16-day experiment. Water samples were collected daily for COD analysis and to measure reducing sugar levels. Within the first 4 days, the efficiency of COD reduction by strain A1-3 was 50%, higher than that in the control tank. During days 7-9, the COD reduction value of strain A1-3 remained almost stable in the range of 58-63%. Adding NaCl to adjust the salinity to 17 psu on day 10 increased the COD reduction. Between days 12 and 15 of the experiment, the COD was reduced by 79-81.82%, significantly different from the control tank. However, at the end of the experiment, the COD value in both the control and treatment tanks was higher than the standard of the Ministry of Natural Resources and Environment (Thailand), indicating the need for further treatment of these wastewaters. © 2024, Research and Development Institute Suan Dusit University. All rights reserved.
A Bibliometric Analysis of Keywords of HyFlex Learning for the English Language Learning Skills of Teacher Students
(School of Liberal Arts, King Mongkut's University of Technology Thonburi, 2024) Thip Khumyoo; Niroumon Suwannasri; Akkrawat Wongthitikun; Jira Jitsupa; Jittree Jampeetong; J. Jitsupa; Faculty of Education, Suan Dusit University, Thailand; email: jira_jit@dusit.ac.th
Listening, speaking, reading, and writing are important skills in English language learning. However, some students are not successful in learning English due to several factors. The model for improving the English learning skills of students is essential. However, except for the HyFlex learning model, no suitable model for learners has been found following the new normal. This research, therefore, identify the bibliographic keywords of HyFlex learning for the English learning skills of teacher students. According to a total of 465 documents published in the Scopus database, 40 articles met the research inclusion criteria and keywords related to HyFlex learning could be used to guide the development of the model of English language learning skills of students. Findings, the keywords of HyFlex learning for the English learning skills of teacher students 42 keywords related to Hyflex learning that clustered into seven categories: Higher education, Learning environment, Teaching and learning model, Digital technology for learning, Teacher, Student, and English language. © 2024, School of Liberal Arts, King Mongkut's University of Technology Thonburi. All rights reserved.
A new Approach of Generalized Fractional Integrals in Multiplicative Calculus and Related Hermite-Hadamard-Type Inequalities with Applications
(Walter de Gruyter GmbH, 2024) Muhammad Aamir Ali; Michal Fe_kan; Chanon Promsakon; Thanin Sitthiwirattham; M. Fe_kan; Department of Mathematical Analysis and Numerical Mathematics, Comenius University in Bratislava, Bratislava, Mlynsk‡ dolina, 842 48, Slovakia; email: michal.feckan@fmph.uniba.sk
The primary goal of this paper is to define Katugampola fractional integrals in multiplicative calculus. A novel method for generalizing the multiplicative fractional integrals is the Katugampola fractional integrals in multiplicative calculus. The multiplicative Hadamard fractional integrals are also novel findings of this research and may be derived from the special situations of Katugampola fractional integrals. These integrals generalize to multiplicative Riemann-Liouville fractional integrals and multiplicative Hadamard fractional integrals. Moreover, we use the Katugampola fractional integrals to prove certain new Hermite-Hadamard and trapezoidal-type inequalities for multiplicative convex functions. Additionally, it is demonstrated that several of the previously established inequalities are generalized from the newly derived inequalities. Finally, we give some computational analysis of the inequalities proved in this paper. © 2024 Mathematical Institute Slovak Academy of Sciences.
_-Contraction of HardyÐRogers type in supermetric spaces with applications
(Springer Nature, 2024) Kamaleldin Abodayeh; Syed Khayyam Shah; Muhammad Sarwar; Varaporn Wattanakejorn; Thanin Sitthiwirattham; S.K. Shah; Department of Mathematics, University of Malakand, Chakdara Dir(L), Khyber Pakhtunkhwa, 18800, Pakistan; email: khayyamshah0@gmail.com; V. Wattanakejorn; Mathematics Department, Faculty of Science and Technology, Suan Dusit University, Bangkok, 10300, Thailand; email: varaporn_wat@dusit.ac.th
This article focuses on studying some fixed-point results via _-contraction of HardyÐRogers type in the context of supermetric space and ordered supermetric space. We also introduced rational-type z-contraction on supermetric space. For authenticity, some illustrative examples and applications have been included. © The Author(s) 2024.
Development of sweet fermented rice (Khao-Mak) production using a pure culture of Amylomyces rouxii TISTR 3182 by the mixture design approach
(Springer, 2024) Sujaya Rittisorn; Manida Chorum; Sorayaporn Ratchakit; Nattawan Klaeabangthong; Srisuda Samaimai; Thanasak Lomthong; T. Lomthong; Division of Biology, Faculty of Science and Technology, Rajamangala University of Technology, Thanyaburi, Pathum Thani, 12110, Thailand; email: thanasak_l@rmutt.ac.th
A mixture design approach was used to investigate how different types of glutinous rice impacted the production of sweet fermented rice (Khao-Mak) using a pure culture of Amylomyces rouxii TISTR 3182. White glutinous rice provided the highest total soluble solids (TSS) and alcohol content (24.3 ± 0.35oBrix and 2.0 ± 0.14%, respectively). The combination of black glutinous rice (88%) with white glutinous rice (12%) gave the highest total phenolic content (TPC) at 120.21 ± 2.20Êµg GAE/mL. The optimal combination was chosen for large-scale production, yielding 22.00 ± 0.5oBrix, 1.63 ± 0.23%, and 102.98 ± 0.76Êµg GAE/mL of TSS, alcohol, and TPC, respectively. Thin-layer chromatography (TLC) revealed that the sugar obtained from the fermentation was glucose. Scanning electron microscopy (SEM) showed that growth of the fungal strain hydrolyzed the rice structure during fermentation. The crude extract of sweet fermented rice, fermented using a pure fungal strain culture through a biotechnological approach, suppressed the growth of Staphylococcus aureus DMST 2933 and Salmonella sp. ATCC 13311. © Association of Food Scientists & Technologists (India) 2024.
Brain Cancer Tumor Detection by U-Net Deep Learning Algorithm from MRI Images
(Institute of Electrical and Electronics Engineers Inc., 2024) Utpal Chandra Das; Watit Benjapolakul; Manoj Gupta; Timporn Vitoonpong; Pannee Suanpang; Chanyanan Somthawinpongsai; Sujin Butdisuwan; Aziz Nanthaamornphong; U.C. Das; Center of Excellence in Artificial Intelligence, Machine Learning and Smart Grid Technology, Department of Electrical Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, 10330, Thailand; email: dasutpal999@gmail.com
This research looks at the genomic subtypes of low-grade glioma tumors and their shape characteristics by deep learning magnetic resonance image (MRI) segmentation. We analyzed preoperative imaging and genetic data from 110 patients with low-grade glioma from the Cancer Genome Atlas. Three shape features were recovered to quantify the two- and three-dimensional aspects of the malignancies. Based on gene expression, DNA copy number, IDH mutation, 1p/19q co-deletion, DNA methylation, and microRNA, previously identified clusters were found in genomic data. We used the exact trait test to investigate the connection between chromosomal clusters and imaging traits. Our findings show a significant correlation between the margin fluctuation-bounding ellipsoid volume ratio and the RNA Seq clusters. Furthermore, a correlation was discovered between RNA-seq clusters and angular standard deviation. The U-net deep learning algorithm demonstrated a test accuracy of 94\% and a mean Dice coefficient of 90\%. These findings suggest that tumor shape characteristics derived from MRI can be projected through genomic subtypes in lower-grade gliomas. © 2024 IEEE.
Physical Activity and Heart Rate Variability Among Middle Age to Older Adults with Heart Failure: The State of Science
(Research and Development Institute Suan Dusit University, 2024) Sattha Prakobchai; Kijja Suwan; Manida Dechakul; S. Prakobchai; Faculty of Nursing, Suan Dusit University, Bangkok, 10700, Thailand; email: sattha_pra@dusit.ac.th
Physical activity or exercise relates to the physiological responses especially in heart rate variability (HRV). HRV is a predictor of prognosis of heart failure and cardiac functions. However, little is known about the relationship of physical activity, HRV improvement and autonomic regulation in heart failure of older adults. The purpose of this state of science review is to synthesize the evidence that shows the effects of physical activity or exercise, HRV and physiological outcomes. The literature searched includes 12 studies from four electronic databases (PsycInfo, Pubmed, Scopus and CINAHL). The findings revealed that physical activity or exercise will improve HRV. This review showed that physical activity improves cardiac autonomic function (nerohormornal activation, sympathetovocal balance, baroreceptor reflex) and inhibits alpha 2 antagonist to improve HR reserve and RR intervals and prevent premature ventricular contraction (PVC). However, the level of physical activity and intensity are not clear. Tailored interventions or community-based programs will be effective in order to maintain physical activity and functional outcomes. A higher HRV is related to the functional capacity compared to the lower. Therefore, healthcare providers should regularly assess heart rate variability among heart failure patients to determine the threshold and recovery for physical functioning in regards to the stress form physical activity. © 2024, Research and Development Institute Suan Dusit University. All rights reserved.
A VARIANT OF THE PROXIMAL GRADIENT METHOD FOR CONSTRAINED CONVEX MINIMIZATION PROBLEMS
(Mathematical Research Press, 2024) Suparat Kesornprom; Kunrada Kankam; Papatsara Inkrong; Nattawut Pholasa; Prasit Cholamjiak; P. Cholamjiak; School of Science, University of Phayao, Phayao, 56000, Thailand; email: prasit.ch@up.ac.th
This paper presents a new variant of the proximal gradient algorithm based on double inertial extrapolation to solve a constrained convex minimization problem in real Hilbert spaces. We discuss its weak convergence, including numerical image and signal recovery experiments to support the main results. Some comparisons with other algorithms are also provided. The experiments demonstrate that our method converges better than the other methods in the literature. ©2024 Journal of Nonlinear Functional Analysis.
An inertial projective forward-backward-forward algorithm for constrained convex minimization problems and application to cardiovascular disease prediction
(International Scientific Research Publications, 2024) Prasit Cholamjiak; Watcharaporn Cholamjiak; Kunrada Kankam; P. Cholamjiak; School of Science, University of Phayao, Phayao, 56000, Thailand; email: prasit.ch@up.ac.th; W. Cholamjiak; School of Science, University of Phayao, Phayao, 56000, Thailand; email: watcharaporn.ch@up.ac.th; K. Kankam; Elementary Education Program, Faculty of Education, Suan Dusit University Lampang Center, Lampang, 52100, Thailand; email: kunradazzz@gmail.com
In this paper, we introduce a novel machine learning algorithm designed for the classification of cardiovascular diseases. The proposed inertial projected forward-backward-forward algorithm is developed to address constrained minimization in Hilbert spaces, with a specific focus on improving the accuracy of disease classification. Utilizing inertial techniques, the algorithm employs a projected forward-backward-forward strategy, demonstrating convergence under mild conditions. Evaluation of the algorithm employs four essential performance metrics-accuracy, F1-score, recall, and precision to gauge its effectiveness compared to alternative classification models. Results indicate significant performance gains, achieving peak metrics of 77.50% accuracy, 71.57% precision, 91.27% recall, and 80.23% F1-score, thereby surpassing established benchmarks in machine learning models for cardiovascular disease classification. © 2025 All rights reserved.
Blockchain of things (BoT) innovation for smart tourism
(John Wiley and Sons Ltd, 2024) Pannee Suanpang; Pattanaphong Pothipassa; Chompunuch Jittithavorn; C. Jittithavorn; College of Management, University of Phayao, Bangkok, 10330, Thailand; email: chompunuch.ji@up.ac.th
This study aims to (a) develop the innovation of BoT prototype; and (b) provide an effective platform to recommend tourists activity, implement and trials blockchain prototype for booking travel activities, whether booking travel programs, air ticket booking hotel stay visits to attractions and payment of goods and services, and evaluate tourist intention to use BoT. The developed architecture enables the integration of blockchain technology capabilities into IoT technology based on high performance of usability, stability, accuracy, and completeness. The BoT prototype is evaluated by 428 users to support smart tourism. This support is significant and the level includes the BoT functional benefit (security, process, and availability) that is positively related to the intention to adopt BoT, and user benefit (trust, usability) is also positive related with intention to adopt BoT. This study significantly contributes to revolutionizing the tourism industry by implementing BOT in smart tourism destinations to gain competitive advantage. © 2024 John Wiley & Sons Ltd.
A study on the existence results of boundary value problems of fractional relaxation integro-differential equations with impulsive and delay conditions in Banach spaces
(American Institute of Mathematical Sciences, 2024) Saowaluck Chasreechai; Sadhasivam Poornima; Panjaiyan Karthikeyann; Kulandhaivel Karthikeyan; Anoop Kumar; Kirti Kaushik; Thanin Sitthiwirattham; K. Karthikeyan; Department of Mathematics, KPR Institute of Engineering and Technology, Coimbatore, Tamil Nadu, 641407, India; email: karthiphd2010@yahoo.co.in; T. Sitthiwirattham; Research Group for Fractional Calculus Theory and Applications, Science and Technology Research Institute, King MongkutÕs University of Technology North Bangkok, Bangkok, 10800, Thailand; email: thanin.sit@dusit.ac.th
The aim of this paper was to provide systematic approaches to study the existence of results for the system fractional relaxation integro-differential equations. Applied problems require definitions of fractional derivatives, allowing the utilization of physically interpretable boundary conditions. Impulsive conditions serve as basic conditions to study the dynamic processes that are subject to sudden changes in their state. In the process, we converted the given fractional differential equations into an equivalent integral equation. We constructed appropriate mappings and employed the SchaeferÕs fixed-point theorem and the Banach fixed-point theorem to show the existence of a unique solution. We presented an example to show the applicability of our results. © 2024 the Author(s), licensee AIMS Press.
Super-Resolution Methods for Endoscopic Imaging: A Review
(Institute of Electrical and Electronics Engineers Inc., 2024) Mansoor Hayat; Manoj Gupta; Pannee Suanpang; Aziz Nanthaamornphong; M. Hayat; Dept. of Electrical Engineering, Chulalongkorn University, Bangkok, Thailand; email: 6471015721@student.chula.ac.th
This review paper presents a comprehensive analysis of recent advancements in super-resolution applications in endoscopic imaging. It synthesizes findings from multiple cutting-edge research papers, each contributing unique methodologies and results. The review highlights the progression from traditional techniques to deep learning models, and attention mechanisms. Emphasis is placed on the practical application of these advancements in enhancing the quality of images for minimally invasive surgery, ultimately contributing to improved surgical outcomes. This synthesis not only showcases the current state of the field but also identifies potential areas for future research and development. © 2024 IEEE.
Exploring the Association Between Loneliness, Subjective Cognitive Decline, and Quality of Life Among Older Thai Adults: A Convergent Parallel Mixed-Method Study
(SAGE Publications Inc., 2024) Panawat Sanprakhon; Wachira Suriyawong; Orranuch Chusri; Peerayut Rattanaselanon; W. Suriyawong; Faculty of Nursing, Chiang Mai University, Chiang Mai, Thailand; email: suriyawo@msu.edu
Examining the rising prevalence of subjective cognitive decline as an early indicator of dementia in adults, this study investigates its complex interaction with loneliness and quality of life in individuals with preclinical dementia. Using a convergent parallel mixed-method approach, we employed Structural Equation Modeling on a cohort of 149 older adults. Qualitative insights were derived from focused group discussions and in-depth semi-structured interviews with a cohort of 23 older adults. Loneliness emerges as a pivotal contributor, exerting a discernible partial indirect effect on quality of life through subjective cognitive decline (indirect effect = _0.145, p =.006). Noteworthy differentials surfaced, with the impact of subjective cognitive decline on quality of life heightened in those with chronic diseases (__2 = 6.139, p =.013). Loneliness, wielding a palpable impact, intricately interlaces with quality of life, the nexus of which is intricately mediated by subjective cognitive decline. © The Author(s) 2024.
A STUDY OF FRACTIONAL HERMITE-HADAMARD-MERCER INEQUALITIES FOR DIFFERENTIABLE FUNCTIONS
(World Scientific, 2024) Thanin Sitthiwirattham; Miguel Vivas-Cortez; Muhammad Aamir Ali; HŸseyin Budak; Ibrahim Avci; M. Vivas-Cortez; School of Physical and Mathematical Sciences, Faculty of Exact and Natural Sciences Pontifical Catholic, University of Ecuador, Quito, Av. 12 October 1076, Section, 17-01-2184, Ecuador; email: mjvivas@puce.edu.ec
In this work, we prove a parameterized fractional integral identity involving differentiable functions. Then, we use the newly established identity to establish some new parameterized fractional Hermite-Hadamard-Mercer-type inequalities for differentiable function. The main benefit of the newly established inequalities is that these inequalities can be converted into some new Mercer inequalities of midpoint type, trapezoidal type, and Simpson's type for differentiable functions. Finally, we show the validation of the results with the help of some mathematical examples and their graphs. © The Author(s)

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