bluuebunny/crossref_metadata_2025 huggingface dataset:
Travel time prediction with graph neural network: a case study in Bangkok Thailand
Authors:   , Buapang Sathita
Published: September 2023

Traffic prediction is an essential and challenging task for traffic management and commercial purposes. Machine learning methods for traffic prediction usually treat traffic conditions as time-series due to obvious temporal patterns. Recently, spatial relationships among roads in a road network have also been used to improve traffic prediction. This study proposes a novel method to predict traffic conditions such as speed using a graph convolutional neural network with a spectral adjacency matrix (GCN-Spectral). Unlike a spatial adjacency matrix representing physical connections between road segments, a spectral matrix represents the correlation between road segments regarding traffic conditions. The GCN-Spectral model is evaluated by comparing with a multi-layer perceptron model (MLP), as a non-spatial model, and a graph convolutional neural network with a spatial adjacency matrix (GCN-Spatial). The prediction results were analyzed with the robustness characteristics of the road segment in various dimensions. For example, the road length, time of the day, and day of the week. The error of results analysis aimed to explain model limitations and strong points. The data used in this study are GPS probe data collected from taxis in Bangkok. Empirical results show that the GCN-Spectral with a combination matrix model mostly outperforms GCN-Spatial models in the Bangkok dataset.

However, MLP performs the best in most cases in speed prediction tasks. The MLP works well every day of the week and time of day. In contrast, the GCN works well in late morning, evening, and on a weekday. The number of lanes in a road segment does not correlate with prediction error. And the road segment length has a weak correlation with the prediction error on GCN-Spectral with LSTM layers and GCN-Spectral with combination matrix. The travel time spent in the road segment is calculated using speed prediction, and relative to road segment length. The more extended the road segment is, the higher the error on travel time. The result found that the lowest error is from GCN-Spatial model.
A design of FPGA framework for quantum computing simulation
Authors:   , Jungjarassub Yaninee
Published: September 2023

​We use FPGA to optimize the simulation of quantum computing in two aspects. (a) The if-else state is used in place of tensor product calculation. This allows the tensor product of each quantum operator to be generated in a single clock cycle. (b) The pre-calculated lookup ROM is used for estimating the sine and cosine values. This facilitates the computation of quantum gates that are related to angle. To validate our work, we implement our design in VerilogHDL. The performance is evaluated using an FPGA simulator. The result shows a dramatic improvement in the simulation process comparing to those of simulation on classical computers.
Domestic customers' perceived value toward Thai cultural products
Authors:   , Deedenkeeratisakul Krittanan
Published: September 2023

As Thai cultural identity is one of the remarkable assets in Thai culture and has gained wider attention, there is a growing trend for the market to capture domestic customers' behavior. This study investigates consumers' value perceptions and their intentions to purchase Thai cultural products by extending the theory of consumption value through four values that inﬂuence perceived value of product attitude, which also affect purchase intention and customer satisfaction. Online Survey data from 412 people in Thailand were used to test the hypotheses, and content analysis of 9 in-depth interviewees was used to understand the product's perceptions better. 

The results indicated that four values (i.e., functional, social, emotional, and social responsibility) positively affect Thai cultural product purchase intention and customer satisfaction. Social responsibility is a significant value that people perceive and highly appreciate. Social value is highly perceived but hard to evaluate. People under 25 years old perceived social value as less than those over 56 years old as well as regular customers perceived this value as more than the non-frequent buyer. Functional value is the most significant value that people evaluate, especially quality and uniqueness, but they are less practical. Appearance and craftmanship of products is the most mentioned value but different experience and taste highly affect how respondents perceive emotional value. Males, LGTBQ, and the older generation focus on uniqueness and craftsmanship. In contrast, female and younger age groups tend to focus on product function. The findings offer implications for practitioners and policymakers in designing strategies that encourage people to purchase Thai cultural products. Companies should design strategies that apply product function with emotional-related value to improve social value using modern design and engaging content, such as storytelling, based on each product's background. Launching a campaign and focus on communication plan could be excellent tool to promote the products' selling point.
Multi-Modal Biometric-based Human Identification Using Deep Convolutional Siamese Neural Network
Authors:   , Aung Hsu
Published: September 2023

Biometric recognition is a critical task in security control systems. Although face biometric has long been granted the most accepted and practical biometric for human recognition, it can be easily stolen and imitated. It also has challenges getting reliable facial information from the low-resolution camera. In contrast, a gait physical biometric has been recently used for recognition. It can be more complicated to replicate and can also be taken from reliable information from the poor-quality camera. However, human body recognition has remained a problem since the lack of full-body detail within a short distance. Moreover, the unimodal biometric system still has constraints with the intrinsic factors of each trait. Recently, a deep Convolutional Neural Network (deepCNN) has been firmly applied to many fields in recognition research. Nevertheless, it needs a lot of labelled data for training. Biometrics data acquisition and labelling for creating large-scale datasets are still problematic. In this thesis, we propose a multimodal approach by combining two biometrics using a deep Convolutional Neural Network with a distance learning based Siamese Neural Network for human recognition. The proposed network model learns discriminative spatio-temporal features from gait and facial features. The extracted features from the two biometrics are fused into a common feature space at the feature level and sensor level methods for multimodal recognition. This study conducted experiments on the publicly available CASIA-B gait dataset, Yale-B faces dataset and a walking videos dataset of 25 users. The proposed model achieves a 97.3 % classification accuracy with an 0.97 F1 score and a 0.004 Equal Error Rate (EER). The proposed SNN model also achieves a 90.4% True Positive Rate (TPR) on gait and 89.7 % TPR on face modality, and 98.4% TPR on the multimodal system. The experimental results demonstrate that the system can classify people by learned features on Gait energy (GE)  and Low-resolution (LR) face images directly. The proposed multimodal recognition performance evaluation is compatible in comparison to other multimodal recognition methods.
Topology optimization for CNN using neuroevolution
Authors:   , Operiano Kevin
Published: September 2023

In the recent years, the architecture of the convolutional neural networks has become much deeper and more complex to improve their performance. Consequently, they require large datasets and a considerable amount of computational resources. However, in some applications such as medical imaging analysis, datasets are scarce and difficult to collect. In these cases, deep networks cannot be trained enough, which makes them susceptible to overfitting. Moreover, not all institutions have access to abundant computational resources. Designing a small network that performs as well as a deep network requires expertise and a great effort. Neuroevolution is therefore proposed to automatically discover an optimal convolutional neural network architecture for a given dataset. Neuroevolution is a method inspired by natural selection and previously applied in artificial neural networks to optimize their architecture. With meticulous implementation, neuroevolution can find small convolutional neural network architectures that are on par with deep architectures. The experiments conducted confirm that different proposed neuroevolution implementation can achieve accuracies comparable to those of deep architectures as observed in the accuracies of the generic neuroevolution, steady-state neuroevolution, and ResNet-34 (91.59%, 91.00% and 89.25% respectively). In addition, the neuroevolution performed in a specific object detection application with a limited dataset (i.e., dangerous objects X-ray) has demonstrated that it can find architectures that have modest depths but have performances similar to the deep network. In an experiment, the YOLOv3 with neuroevolution backbone has 47 blocks and 63.8% accuracy, whereas the original YOLOv3 has 106 blocks and 52.9% accuracy. Conclusively, the proposed neuroevolution methods can achieve all the objectives of this dissertation as they effectively aid in creating alternative to deep networks but without performance loss.
Hybrid GNS3 and Mininet-WiFi emulator for survivable SDN backbone network supporting wireless IoT traffic
Authors:   , Han May
Published: September 2023

This thesis has designed and implemented an emulated testbed for fault-tolerant delay awareness routing for wireless sensor traffic by using software-defined networking (SDN) at the backbone network. In this work, the hybrid form of GNS3 and Mininet-WiFi emulation network testbed is proposed to build an emulated SDN-based backbone network in GNS3 and an emulated IPv6 over Low Power Personal Area Network (6LoWPAN) in Mininet-WiFi. Three virtual machines are used to set up the hybrid emulated SDN-based network testbed. The Mininet-WiFi platform which is used to build the emulated 6LoWPAN sensor network is installed in two virtual machines separately and the third virtual machine is GNS-VM.

In the proposed SDN-based backbone network, there are three available paths to carry the sensor traffic from two sensor networks to the server network, and Open Virtual Switch (OVS) supporting the OpenFlow protocol is used to establish an SDN-based backbone network. The python-based RYU SDN framework is used as the logically centralized SDN controller which controls eight OVS nodes located in three paths in an out-of-band connection. In this thesis, the routing algorithm is based on delay, packet loss ratio, and the number of hops parameters to decide the optimal path for the sensor traffic or the data plane traffic. The routing algorithm is developed and executed in the centralized RYU controller. There are two main tasks for the provider edge node connected to the two sensor networks (i) to measure the delay, packet loss ratio, and the number of hops (ii) to send the measurement result to the centralized RYU controller. The information which is sent by the provider edge node is important for the SDN controller to decide the optimal path and then install the necessary OpenFlow rules to the OVS node to establish the data plane.

In this thesis, the measurement result of delay aware routing algorithm is reported. Another consideration is that the implemented routing algorithm is fault-tolerant with the measurement result of rerouting time when the selected optimal path is failed. The programmability of SDN due to the separation of control and data planes is the key benefit for us as the routing behavior is easily customizable, especially for IoT sensor networks in this work.
Identification and counting white blood cell subtypes with convolutional neural network
Authors:   , Worsito Singgih
Published: September 2023

White blood cell (WBC) has five subtypes namely neutrophil, eosinophil, basophil, lymphocyte, and monocyte which play specific roles in the immune system and against diseases. The object detection model applied to microscopic objects is introduced to assist experts in performing tasks in blood analysis. Unbalanced cell composition of WBC subtypes to be detected is a challenge in building a model in Convolutional Neural Network (CNN). This research aims to build models in recognizing and counting WBC subtypes with neural networks constructed from augmented data enrichment. CNN is demonstrated in this study with the YOLOv5s, YOLOv5l, and YOLOv5x models to detect and count WBC subtypes. Generating three different datasets, the first is raw data with a limited and unbalanced amount, the second dataset is augmented data with geometric operation based, and the third dataset is augmented data with image enhancement based. The experimental results show that in recognition and counting systems for the five subtypes of WBC, the best model among the three models of the YOLOv5 family is YOLOv5l. The best accuracy among built models is YOLOv5l from the augmentation with image enhancement based which has an accuracy of Mean Average Precision (mAP) mAP@.5 0.995 and 0.988 mAP@.5:.95 at 600 epochs of training.
Real-time image super-resolution reconstruction for system on chip FPGA
Authors:   , Ruangsang Watchara
Published: September 2023

In recent years, image super-resolution (SR) techniques based on Convolutional Neural Network (CNN) have achieved impressive attention from computer vision scholars and artificial intelligence (AI) companies. Due to the necessity of using the SR algorithms in real-world applications, designing an efficient and lightweight SR algorithm that improves the sharpness and visual quality of the SR results is a critical issue in real-time hardware implementation. To address these issues, we proposed the Multi-FusNet of Cross Channel Network (MFCC) network by constructing the groups of Residual-in-Residual architecture under the multi-path cascading framework. Additionally, a residual connection is used to transfer the low-level features of the early layer to the reconstructed SR image. The proposed SR model is initially trained with the GPU's training image dataset. To implement our trained model in System on Chip FPGA, the size of the proposed model is required to reduce. We convert the floating-point checkpoint into a fixed-point integer checkpoint in the quantization procedure. According to the experimental results, the proposed method reduces the number of network parameters significantly (8.4 times compared to RCAN), can execute fast in System On Chip FPGA, around 30 frames per second, and image accuracy of the proposed method in terms of PSNR value does not decrease over 1 dB.
Key Success Factors Identification for Logistics Outsourcing in Myanmar
Authors:   , Htoon Pyae
Published: September 2023

The purpose of this paper is to identify the key success factors that have a profound effect on the service quality of outsourced logistics functions in the import/export sector of trade business in Myanmar and rank them accordingly to their importance when outsourcing logistics functions. The paper states the critical elements required for logistics service providers to compete for high customer satisfaction in Yangon, Myanmar. Fuzzy TOPSIS methodology with triangular fuzzy numbers is used to identify the key success factors and rank them in order of their relative closeness to the ideal solution. The findings suggest that soft factors such as skilled logistic professionals and relationship building are ranked higher than hard factors such as supply chain integration and information technology in the developing country of Myanmar with its low maturity of the logistics outsourcing market. The scope of this study and the unstable political situation during the study constrains the ability to generalise the findings in other sectors of the market. This paper uses the Fuzzy TOPSIS approach to rank the key success factors of logistic outsourcing, and future research with different approaches of multi-criteria decision making may be carried out and compared with this study.
ESTUDIO DE LAS BARRERAS LINGÜÍSTICAS Y CULTURALES DE LOS ESTUDIANTES DE INTERCAMBIO TAILANDESES EN MÉXICO Y ELABORACIÓN DE MATERIALES AUDIOVISUALES PREPARATORIOS
Authors:   , Krajangjai Atapon
Published: September 2023

This research consists of a triple objective: 1) to study the language and cultural difficulties experienced by Thai exchange students in Mexico, 2) to analyze the causes and effects of such difficulties towards the adaptation of Thai students in Mexico, and 3) to elaborate a proposal of preparatory audiovisual materials that help these students to overcome both language and cultural barriers in Mexico. The research methodology consists of the data collection from the questionnaire taken by a sample group of 84 Thai AFS exchange students in Mexico during the academic year from 2009 to 2019, and the interviews conducted with 8 students of the same group. In terms of language difficulties, their communication skills prior to the departure to Mexico were evaluated on average as "very low". Due to the inadequate proficiency of Spanish, most of the surveyed population struggled “significantly” when communicating in Spanish with Mexicans. In terms of cultural difficulties, most of the Thai students admitted to struggling “fairly hard" to adjust in Mexico. The issues that received significant high scores, ranging from most impactful to least impactful, were as follows: unpunctuality, late lunch and dinner times, physical contact on sensitive parts of the body for Thais, curriculum of Mexican host schools which was not compatible with those in Thailand, social space of Mexicans compared to the personal space of Asians, such as Thais. In addition, a proposal of 13 preparatory lessons for Thai exchange students in Mexico has been presented. Their contents are mainly based on the results from the questionnaire and interviews with the target group. Finally, an audiovisual material on the topic "doing the grocery shopping" has been elaborated as a pilot lesson.
Environmental ethics, survival and apocalypse: an analysis of Margaret Atwood’s Maddaddam Trilogy
Authors:   , Kururatphan Sarawut
Published: September 2023

This thesis examines the connection of ethics and survival in the pre- and post-apocalyptic worlds in Margaret Atwood's MaddAddam trilogy: Oryx and Crake (2003), The Year of the Flood (2009), and MaddAddam (2013). It investigates the author’s imaginings of a dystopian society marked by rampant technocratic capitalism and unchecked scientism in Oryx and Crake. Applying Murray Bookchin's social ecology to shed light on the root causes of the apocalypse, it argues that hierarchical ideology and diversiform inequality deeply rooted in society lead to warped ethics, affecting the crisis. This thesis also examines environmental ethics which is embedded in the belief system of God’s Gardeners in The Year of the Flood. Employing Arne Naess’s deep ecology as a theoretical framework, it discusses how the eco-centric teachings and lifestyle of this group may serve as an alternative ethical model to help increase the chance of survival. Furthermore, analyzing the God’s Gardeners’ interactions with other beings in MaddAddam, this thesis explores Atwood’s conception of posthuman ethics and the gradual process of human characters’ shift from anthropocentrism to ecocentrism. It also contends that this ideological transformation is essential for the new posthuman reality, in which humans and nonhumans have to ensure the interspecies survival and peaceful coexistence. Finally, it argues that the art of storytelling is dispensable for such an ethical transition and the impartation of beneficent values to posterity.
A study of Chinese young learners' beliefs in eil project-based language learning in rural schools
Authors:   , Zheng Xiaoli
Published: September 2023

This study explored  learners' beliefs about English as an international language through project-based language learning in a Chinese rural school. Three English teachers and 102 Grade 6 Chinese EFL learners participated over two separate phases. Phase I explored how teachers implemented the project-based language learning via classroom observation and semi-structured interviews. The findings from this phase were used to construct the six aspects of the EIL project-based language learning questionnaire in Phase 2. The questionnaire was developed to explore learners beliefs about EIL and project-based language learning in a Chinese rural school. The questionnaire revealed that the learners strongly believed in learning English as an international language through project-based language learning. Five aspects received similar positive responses, namely, collaboration, authenticity, intellectual challenge and accomplishment, and project management and reflection. However, only the aspect of public product received a more negative response.
Challenges of urban forest park restoration on post-closure landfill : perception and future engagement from the local communities
Authors:   , Fitri Intan
Published: September 2023

Urban forest park development is considered a promising planning tool in tackling some of the problems associated with urbanisation, such as pollution and urban heat island effects. Individual perceptions are pivotal in the urban forest park development. Their significant factors were aimed to address the community's needs and increase the recognition through the disruptive change of land function and urban living toward urban forest park development. The framework of local community engagement in urban forest park development was proposed. Field observation and questionnaires survey of 168 respondents were selected from five villages located 50 meters-1000 meters radius from the site. In-depth interviews were conducted with 15 key stakeholders who had roles and responsibilities involving the project of ecological restoration on the On-Nut post-closure landfill. The former and current village chiefs, Prawet district government, non-government organizations, and a state enterprise were collected. Referring to the urban forest development on the post-closure landfill, the perception of communities through their needs was significantly found both negative and positive impacts. The study assessed the local needs which were socioeconomic, and environmental quality affected by the urban ecological restoration. Only occupation, and income were significant adverse impacts caused by the urban forest development. To develop the urban forest on the landfill, the study showed project framework development process should the concerns on sources of incomes interrupted by the project replacement. Moreover, the study referring to the concerns to develop the pre-construction of project, the well-being focussing on local occupation and incomes should be included in the target setting. Challenges of sense of ownership and local community awareness on the Green Bangkok 2030 were stated by stakeholder; therefore, they should be integrated into the key steps of engagement framework development. The study found that there were six steps based on the community perception on the urban forest development: (1) well-being and environment service goals, (2) assessing the community needs leaned from other urban forest models, (3) assessing existing conditions, not only the environmental quality, but also vulnerable socioenconomic aspects, (4) addressing the challenges such as the ownership and awareness, (5) generating the feedbacks, and (6) evaluating the obtained feedbacks and setting new goals. The benefits of these steps can lead to the implementation of engagement of sustainable development.
Improvement of selection criteria and prioritisation for neoantigen prediction
Authors:   , Pearngam Phorutai
Published: September 2023

A tumour-specific neoantigen-based cancer vaccine is a potentially powerful treatment option, which utilises unique mutated peptides from tumour cells to boost the immune response and selectively attack cancer cells. Thus, the characterisation of the specifically targeted peptides that can be selectively recognised by the immune system is essential for this approach. However, a major problem in neoantigen prediction is obtaining false positives, leading to poor outcomes in clinical research and practice. This thesis aims to address some of the computational issues in neoantigen prediction, including developing more reliable statistics for assessing peptide binding to a major histocompatibility complex (MHC) protein and using machine learning to predict which peptides will generate an immune response. Specifically, the thesis introduces an approach for parameter estimation using the modified expectation maximisation (EM) framework with the method of moments for a two-component beta mixture model, representing the distribution of true and false scores from peptide binding prediction. The estimated parameters obtaining from the model can be further used for estimating false discovery rate (FDR) or a local peptide-level statistic such as the posterior error probability (PEP) to develop a robust method for MHC binding peptide selection. Next, the thesis introduces a new immunogenicity prediction model to classify immunogenic and non-immunogenic peptides using machine learning. A data set was assembled containing peptides classes as immunogenic and non-immunogenic peptides, and peptide features of physicochemical properties and homology features were used for constructing the Random Forest classifier for immunogenicity prediction. The two innovations were assembled into an end-to-end pipeline that provides the final probability described true MHC binding ability and the potential for immunogenicity. The final probability of MHC binding and T cell recognition provides a statistical framework to guide users in defining the appropriate thresholds, and prioritising peptides with the highest chance for being real neoantigens.
Preventing occupational respiratory disease from exposures in office building : case study COVID-19
Authors:   , Phapant Panupant
Published: September 2023

The COVID‐19 pandemic has affected human life in every possible way, and, alongside this, the need has been felt that office buildings and workplaces must have protective and preventive layers against COVID‐19 transmission so that a smooth transition from ‘work from home’ to work from office’ is possible. The present study reviews international agency regulations, country regulations, updated journal articles, etc., to critically understand lessons learned from COVID‐19 and evaluate the expected changes in sustainability requirements of office buildings and workplaces. The built environment, control environment, and regulatory environment around office buildings and workplaces have been put under test on safety grounds during the pandemic. Country regulation, agency regulations, and operational guidelines need to bring behavioral changes required to protect workers from the COVID‐19 pandemic.

This study also investigates the ability of COVID-19’s measures by comparing certified (LEED, TREES, and WELL) and non-certified office buildings in Bangkok, Thailand. Certified building in this study mainly implemented COVID-19 prevention measures. For non-certified buildings, two buildings mostly implemented COVID-19 strategies (>90%), and others are less implemented (< 90%). Providing negative pressure, installing infiltration, using touchless technology, and implementing mental health policy are the most difficult to apply. However, alternative strategies were implemented until no clusters were found in all case studies. 

Additionally, an in-depth interview and the Rating scale have been used to explore building satisfaction. The study shows that building satisfaction in all building types increased during this period. The certified building is the most satisfied before COVID-19, while the non-certified building with the good measure is the most pleased during this time because many strategies have been implemented. Moreover, health and comfort criteria have been examined for building occupants, including temperature & humidity, indoor air quality, spatial, visual, and acoustic. Visual is the most satisfying characteristic before COVID-19 while distancing during this period, and it is the most significant aspect that has increased significantly.

The gaps and barriers of the execution are used to explore the challenge and propose additional solutions for fighting the crisis and other respiratory diseases such as flu and influenza. By actor-network analysis, lack of law and regulation for healthy building, lack of expenditure, and lack of knowledge are the significant barriers. So, additional building assessments have been proposed, including healthy building concept design, engineering measures, and supporting and educational strategies have to be implemented to develop sustainable and better-living conditions.
Investigating consumers' perspective and impact on green cosmetics and personal care products in Thailand
Authors:   , Suphasomboon Tawalhathai
Published: September 2023

This study aims to investigate consumers’ perspectives and impact on green cosmetics and personal care products in Thailand. Specifically, it explores the sustainability movement for the cosmetics and personal care industry, analyzes Thai consumer behavioral intention toward the consumption of green cosmetics and personal care products, and evaluates the impact of related policies that may affect green business transitions and consumers’ intention to purchase green cosmetics and personal care products. The movement of industry and related policies were analyzed by means of Life Cycle Thinking approach. Hypotheses were formulated based on The Perceived Value Theory with extended factors of environmental concern and green policy. A mixed methods of qualitative and quantitative studies were conducted through online surveys of 423 consumers and in-depth interviews with 30 consumers, 8 local and international companies, and 4 governmental agencies and NGOs.

The qualitative analysis shows a strong correlation between circular economy practices, green production processes, environmental certifications, and eco-labeling schemes aligned with sustainability objectives. However, the sustainability concepts were not fully embedded and integrated into policy development and business strategies, which resulted in barriers to sustainable practices. In addition, the quantitative results from PLS-SEM show that the perceived functional value and environmental concern have significant impacts on consumer purchase intention. However, the influence of emotional value and social value was not supported. Meanwhile, the green policy is a strong predictor of environmental concern which indirectly correlates to the perceived value and purchase intention of green cosmetics and personal care products.

These findings offer contributions toward extending the knowledge on how multidimensional consumer values coincide and influence behavioral intention. Linking functional value with environmental considerations should be aligned with the proposed policy recommendations in undertaking sustainability impact assessment throughout a product’s life cycle, enforcing codes of practice relating to waste and packaging waste management, regulating sustainability and green-related terms for marketing and communication, making corporate sustainability reporting mandatory, and developing green taxation system to promote green consumption and production and reduce environmental footprints, to move toward a holistic approach to sustainable development.
Football as a tactical innovation for mobilization: a study of FC Barcelona and the Catalan independence movement
Authors:   , Seangkumchoo Phawin
Published: September 2023

The Catalan Independence Movement is the movement in the Northern region of Spain which aims to be independent from Spain cause of problems in politics and economic. The Catalan mobilization not only marches on the street but also plays their role through the Spanish political procedure. In Catalan, the referendum on independence was issued in 2009-2011, 2014, and 2017. This study focuses on the Catalan mobilization tactical innovation which uses football as a tool against Spain. In this case, football which was used mean ‘FC Barcelona,’ one of the famous football club in the world.

This study aims to identify how football play role in the Catalan struggle. With the theory of tactical Innovation, social movement will disrupt normal situation to attract interest of group’s opponent and the society (McAdam and Snow, 2010). This study explores through sources such as analyzing mainly research articles, interviews, reports, and other media outlets. 

FC Barcelona has an impact on the Catalan Independence Movement in 3 three dimensions. First, Barça as representation of the Catalan values. Second, Barça as a save space for Catalan mobilization. And third, Barça as an instrument to foster Catalan identity. The club promoted the Catalan struggle issue to the world. One of the important keys to achieving aims is the creativity of the new tactical forms; therefore, Catalan mobilization use ‘football’ as creativity to create the new tactical innovation to protest.
EU-Vietnam FTA: Implications for Thailand
Authors:   , Promkhatkaew Uthaipan
Published: September 2023

In 2007, the EU launched a region-to-region Free Trade Agreement (FTA) with the ASEAN; however, negotiations were suspended in 2009, and the EU subsequently decided to negotiate bilateral FTAs with individual ASEAN member states. Thailand, a parliamentary democratic country, launched the first round of trade negotiations with the EU in 2013, but they were put on hold due to the military coup in 2014. On the other hand, the EU still continued to negotiate and ultimately concluded the FTA with Vietnam in 2020 despite the fact that Vietnam is one of the world’s five remaining communist states. This has raised skepticism among academics and cast doubt on the EU’s values and its pragmatism. This study aims to find the reason why the EU preferred to negotiate an FTA with Vietnam. The study analyzes the data from historical, geopolitical, and economic perspectives, covering EU’s trade and investment policy after 2012 and assess their implications for Thailand in any future FTA negotiation with the EU.

The findings of the study offer insight into how historical, geopolitical, and economic factors have all influenced the EU’s decision-making processes in negotiating the FTA with Vietnam. From the historical standpoint, history shapes the relationship between EU and Vietnam, in particular the relations between Vietnam and France which acts as the bridge between Vietnam and the EU and vice versa. This also applies to ASEAN as a whole. From geopolitical standpoint, Vietnam’s strategic location in the Southeast Asia and the engagement with Vietnam is an interesting policy option for the EU that wants to play a more proactive role in the region. This engagement would allow the EU to project its influence in the Southeast Asia region and balance against growing Chinese power. From political standpoint, the EU’s adoption of “Principled Pragmatism” as a new guiding principle for its foreign policy and using trade as one of its foreign policy tools, coupled with historical and geopolitical contexts, have underpinned EU’s efforts to conclude trade negotiations with Vietnam. As far as economy is concerned, the study reveals that Vietnam and Thailand share similar attributes to a certain extent as both countries mostly import and export the same type of products to the EU with only some slight differences. It can thus be concluded that the EU’s decision to conclude trade negotiations with trading partners such as Vietnam and Thailand are largely attributed to political reasons as opposed to economic interests. In assessing the implications for Thailand, the study indicates Vietnam’s efforts in negotiating FTA with the EU in various areas. Internal trade promotion policies, politics and international relations play an important role in determining trade negotiations with the EU. Rapidly changing global trends such as Green Deal and Friend-Shoring have amplified the complexity of conditions and factors that determine the pace of FTA negotiations with the EU, which could present a challenge for Thailand.
Development of a device for postural change while sitting for the prevention of neck or low back pain in office workers
Authors:   , Akkarakittichoke Nipaporn
Published: September 2023

The objective of this thesis was to develop a device for postural change while sitting for the prevention of neck or low back pain in office workers. This thesis was divided into four stages: 1) to evaluate the effects of postural shifting frequency on perceived musculoskeletal discomfort during 1 hour of sitting in healthy office workers; 2) to evaluate the effects of the postural shift intervention on the 12-month incidence of the onset of neck and low back pain in high-risk office workers; 3) to investigate the efficacy of postural shift interventions on recovery duration and recurrence of neck and low back pain among high-risk office workers, and 4) to identify variables that moderate the effects of postural shifts interventions on the development of neck and low back pain in office workers. The finding of the first study showed that a postural shift frequency of 20-30 times/h significantly led to lower perceived discomfort in the neck, shoulder, upper back, and low back compared to a postural shift frequency of 10 times/h during 1 hour of sitting. These findings were used to develop a custom-designed device for postural change while sitting by the author and engineering team. The device consisted of three components: a seat pad, processor, and smartphone application. The device collected sitting behavior data and provided recommended postural shifting by gradually pumping air into various parts of the seat pad. The device had good to excellent validity and consistency. The results of the study two and three revealed that office workers who received the postural shift intervention significantly reduced the 12-month incidence rate, shortened recovery time, and reduced recurrence of neck and low back pain. Finally, the finding of the fourth study showed that workers who worked more hours/day and who endorsed higher levels of psychological work demand gained more benefits from the postural shift intervention regarding the prevention of neck pain development than those in the control group. In addition, the workers who had no lumbar support gained more benefits from the postural shift intervention regarding the prevention of low back pain development than those in the control group.
Health risk assessment of toxic metals in commonly consumed salad leafy vegetables in Bangkok
Authors:   , Hlyan Zin
Published: September 2023

The objectives of this study were 1) to investigate concentrations of toxic metals including As, Cd, and Pb in the commonly consumed salad leafy vegetables which were sold in Bangkok, and 2) to assess potential human health risks of As, Cd, and Pb exposure via salad leafy vegetables consumption. A total of 120 samples were randomly collected from local fresh markets in Bangkok. The total concentrations of toxic metals were determined by an inductively coupled plasma mass spectroscopy (ICP-MS). Total concentrations of As, Cd and Pb in coral lettuce (CL), red coral (RC) and green oak (GO) for soil cultivation varied from 0.0207 to 0.2603 mg/kg, 0.0280 to 2.4862 mg/kg, and 0.0174 to 0.5314 mg/kg, respectively. For the hydroponic vegetables, total concentrations of As, Cd and Pb ranged from 0.0225 to 0.0943 mg/kg, 0.0223 to 0.4168 mg/kg, and 0.0095 to 0.3091 mg/kg, respectively. According to the health risk assessment, the HQ values of As, Cd, and Pb ranked in the following order: adults > adolescents > children. For soil cultivation, the average HQ values of As, Cd and Pb were 0.19 to 0.80, 0.24 to 2.29, and 0.04 to 0.14. Meanwhile, the average HQ values of As, Cd and Pb exposure from the hydroponically grown salad vegetables were 0.13 to 0.30, 0.11 to 0.38, and 0.02 to 0.08, respectively. According to the HQ values, Cd in RC consumption was higher than the acceptable non-cancer risk of 1 (HQ≥1). On the other hand, the GO and CL were safe for consumption as the HQ values for As and Pb were lower than 1 (HQ<1). As a consequence of the regular lettuce consumption, the adult population may develop non-cancer health risks (e.g., diabetes, kidney disease, and heart attack).
Effective traffic signal timing for intersections in Bangkok
Authors:   , Tantipanichaphan Kasidech
Published: September 2023

The increasing number of on-road vehicles in Bangkok, as well as the traffic flow conditions, are causing many problems for the citizens. To alleviate the problem, effective traffic signal management by optimizing traffic signal timing can be used. As a result, the goal of this research is to improve Bangkok's traffic signal system and management by establishing an effective green light time at intersections in order to increase the vehicle flow rate. The mathematical model is designed to maximize the number of vehicles leaving intersections. Six Bangkok intersections are selected for the experiments. According to the experimental results, the optimization model outperforms current practice by increasing the number of vehicles leaving the intersection. The overall vehicle flow rate improves by 23.04%. Furthermore, combining the intersections together will allow the synchronization of vehicle flow from one intersection to another.
Total quality and innovation management in hospital
Authors:   , Tonjang Suebsakul
Published: September 2023

Previously, quality of care and customers' satisfaction in healthcare services is fulfilled only through total quality management (TQM) which as a core management philosophy, as adopted by many healthcare organizations. Nevertheless, TQM focuses on incremental improvement may prove insufficient to address the new technology and innovation-driven organization with a faster pace. Therefore, this research aimed to integrate quality and innovation management in healthcare affecting healthcare performance. To propose the key factor of both TQM and innovation management in healthcare, we conducted a systematic literature review. Then, TQM and innovation management factors were combined and integrated with ISO 56002 as to the core axis that corresponds to the dimensions in TQIM-H. The TQIM-H is comprised of seven dimensions had a highly positive effect on sustainable innovation. Then, the developed TQIM-H was integrated with the theory of inventive problem solving (TRIZ) through the Delphi method with 30 healthcare experts, resulting in the TQIM-H inventive principle. The TQIM-H inventive principle was confirmed and validated by using confirmatory factor analyses (CFA) and structural equation modeling (SEM). Finally, a TQIM-H program was developed from the knowledge and key characteristics related to the TQIM-H concept obtained in the previous step. The program with a user-friendly user interface would help innovators in understanding TQIM-H which would then help guide healthcare innovation development. After using the TQIM-H program, the feasibility and acceptability of the TQIM-H program were evaluated based on the Technology Acceptance Theory (TAM).
Does South Korea's Melon chart ranking influence k-pop artists' Youtube views?
Authors:   , Tipsotikul Farsai
Published: September 2023

Although K-pop has been diffused throughout the world by YouTube and become globalized, artist’s success is still evaluated by their reputation within the domestic market. Amidst the intense competition in the South Korean music industry, it’s inevitable that artists would hope their songs perform well on the domestic chart as it’s a way to gain public attention. Thus, it leads to the question; “Are some artists putting too much stress on the domestic performances when the global market is also an opportunity?”. To answer the question, this study analyzes the data by quantitative approach to examine whether Melon chart ranking, a music streaming platform with the highest number of users in South Korea, predicts K-pop artist’s overall YouTube views. In other words, whether the domestic popularity predicts the global popularity.

Results showed that there was no Granger Causality in Melon chart ranking predicting overall YouTube views as overall YouTube views also showed significance in predicting Melon chart ranking. Two-way prediction was present in most songs which means Melon chart ranking of a song and artist’s overall YouTube views move along together in terms of popularity and South Korea’s Melon chart ranking is not a leading indicator that brings about artists’ global popularity.
GIS mapping evaluation of stroke service areas in Bangkok using emergency medical services
Authors:   , Sreemongkol Kiatirat
Published: September 2023

Nowadays, stroke is the leading cause of death in Thailand. Patients must be treated within 4.5 hours from symptom onset to increase recovery rate. Time is therefore a critical factor of the success or failure of the treatments.  The objective of this research is to investigate the service coverage of various healthcare centers through current Emergency Medical Services (EMS) in Bangkok. To get service coverages for Stroke in Bangkok, the updated speed of the traffic and the amount of time it takes for each mode of transport for the pre-hospital stroke process are collected and examined using GIS mapping. The findings compare service coverages for different healthcare groupings, namely, non-network and network stroke healthcare centers. The result of this research shows that the service coverages of each hospital depend on the availability of rt-PA facility.  Current total stroke service area covers approximately 90.4% of Bangkok but with different service density in each sub-district level.  This study recommends guidelines for building new networks and adding healthcare centers to supplement existing networks in order to increase service coverage.