King Mongkut's Institute of Technology Ladkrabang

CuO nanoparticles were synthesized by precipitation method using different precursors as copper nitrate (Cu(NO3)2) and copper chloride (CuCl2) with post-heating comparing between as-synthesized and after calcinations. Relevant properties of as-synthesized nanoparticles were investigated by X-ray diffraction (XRD), scanning electron microscope (SEM) and Fourier Transform Infrared (FTIR) Spectroscopy. Overall results suggest that the formation of CuO nanostructures with different shape, size and morphology can be achieved using different precursors via this process. The improvement in their crystallinity and purification can be further attained by post calcinations process.

Only a limited amount of research has been reported on factors influencing international location decisions for contemporary manufacturing operations. In this paper a comprehensive set of factors that may influence international location decisions is identified from an analysis of the existing literature. Results are presented from a Delphi study that used a worldwide panel of experts to investigate factors affecting international location decisions. Findings are reported on the motivations of firms in seeking to manufacture across national borders and the key steps that should be followed in making international location decisions. The top five major factors identified that may strongly influence international location decisions generally were: costs, infrastructure, labour characteristics, government and political factors and economic factors. Ten key sub‐factors identified were: quality of labour force, existence of modes of transportation, quality and reliability of modes of transportation, availability of labour force, quality and reliability of utilities, wage rates, motivation of workers, telecommunication systems, record of government stability and industrial relations laws. Additional sub‐factors of increasing importance include: protection of patents, availability of management resources and specific skills and system and integration costs. The factors identified have implications for management practice, for policy‐making by governments and other agencies and for academic research in international operations.

Metamaterials are artificial composites that acquire their electromagnetic properties from embedded subwavelength metallic structures. In theory, the effective electromagnetic properties of metamaterials at any frequency can be engineered to take on arbitrary values, including those not appearing in nature. As a result, this new class of materials can dramatically add a degree of freedom to the control of electromagnetic waves. The emergence of metamaterials fortunately coincides with the intense emerging interest in terahertz radiation (T-rays), for which efficient forms of electromagnetic manipulation are sought. Considering the scarcity of naturally existing materials that can control terahertz, metamaterials become ideal substitutes that promise advances in terahertz research. Ultimately, terahertz metamaterials will lead to scientific and technological advantages in a number of areas. This article covers the principles of metamaterials and reviews the latest trends in terahertz metamaterial research from the fabrication and characterization to the implementation.

Soluble microbial products (SMP), a significant component of effluent organic matter (EfOM), play an important role in membrane fouling and flux decline in wastewater reclamation/reuse applications. The SMP compounds of a microbial origin are derived during biological processes of wastewater treatment. They exhibit the characteristics of hydrophilic organic colloids and macromolecules. These high molecular weight compounds play an important role in creating high resistance of the membrane, leading to a reduction of permeate flux. The SMP fouling of RO, NF, and tight UF membranes is associated with formation of a cake/gel layer due to size (steric) exclusion. FTIR spectra of SMP- and EfOM-fouled membranes exhibited foulants' composition, consisting of polysaccharides, proteins, and/or aminosugar-like compounds. This finding reveals the important role of the SMP components as factors in membrane fouling and flux decline associated with EfOM source waters. Solids retention time (SRT) affects the characteristics and amounts of SMP, however, SRT did not affect flux decline trends of RO and NF membranes.

Radio-frequency (RF) hepatic ablation, offers an alternative method for the treatment of hepatic malignancies. We employed finite-element method (FEM) analysis to determine tissue temperature distribution during RF hepatic ablation. We constructed three-dimensional (3-D) thermal-electrical FEM models consisting of a four-tine RF probe, hepatic tissue, and a large blood vessel (10-mm diameter) located at different locations. We simulated our FEM analyses under temperature-controlled (90 degrees C) 8-min ablation. We also present a preliminary result from a simplified two-dimensional (2-D) FEM model that includes a bifurcated blood vessel. Lesion shapes created by the four-tine RF probe were mushroom-like, and were limited by the blood vessel. When the distance of the blood vessel was 5 mm from the nearest distal electrode 1) in the 3-D model, the maximum tissue temperature (hot spot) appeared next to electrodes A. The location of the hot spot was adjacent to another electrode 2) on the opposite side when the blood vessel was 1 mm from electrode A. The temperature distribution in the 2-D model was highly nonuniform due to the presence of the bifurcated blood vessel. Underdosed areas might be present next to the blood vessel from which the tumor can regenerate.

Under the vision outlined in Thailand 4.0, critical thinking skills have become one of the key pillars of a new, knowledge-based economy. However, the 2015 Thailand Research Fund study that evaluated the logical thinking and analytical skills of 6,235 students in ten provinces of Thailand, found that the average score was 36.5%, with only 2.09% of all students passing. Recognizing the severity of the crisis, nine experts met in August 2017 as a focus group and were tasked by the researchers to help with the development of a new critical thinking learning management model. From this, a five-step learning management model was conceptualized, which the authors called the 'PUSCU Model'. By means of cluster random sampling, 69 students were selected, from which two sub-groups were formed. One group of 35 experimental studies students, and one group consisting of 34 traditional learning students. The PUSCU model was tested for 16 weeks, from November 2016 through February 2017. The Statistical Package for the Social Sciences (SPSS) 21 software was used to conduct a one-way Multivariate Analysis Of Variance (MANOVA) to determine whether there were any differences between the control and the experimental groups. The results indicated that the experimental group had higher average scores in terms of critical thinking ability and academic achievement, and its members were satisfied with a high level of the model performance, particularly, with the instructor's use of the developed learning materials.

Aedes aegypti mosquitoes infected with Wolbachia bacteria are currently being released for arbovirus suppression around the world. Their potential to invade populations and persist will depend on interactions with environmental conditions, particularly as larvae are often exposed to fluctuating and extreme temperatures in the field. We reared Ae. aegypti larvae infected with different types of Wolbachia (wMel, wAlbB and wMelPop-CLA) under diurnal cyclical temperatures. Rearing wMel and wMelPop-CLA-infected larvae at 26-37C reduced the expression of cytoplasmic incompatibility, a reproductive manipulation induced by Wolbachia. We also observed a sharp reduction in the density of Wolbachia in adults. Furthermore, the wMel and wMelPop-CLA infections were not transmitted to the next generation when mosquitoes were exposed to 26-37C across all life stages. In contrast, the wAlbB infection was maintained at a high density, exhibited complete cytoplasmic incompatibility, and was transmitted from mother to offspring with a high fidelity under this temperature cycle. These findings have implications for the potential success of Wolbachia interventions across different environments and highlight the importance of temperature control in rearing.

With the fast development in ad hoc wireless communications and vehicular technology, it is foreseeable that, in the near future, traffic information will be collected and disseminated in real-time by mobile sensors instead of fixed sensors used in the current infrastructure-based traffic information systems. A distributed network of vehicles such as a vehicular ad hoc network (VANET) can easily turn into an infrastructure-less self-organizing traffic information system, where any vehicle can participate in collecting and reporting useful traffic information such as section travel time, flow rate, and density. Disseminating traffic information relies on broadcasting protocols. Recently, there have been a significant number of broadcasting protocols for VANETs reported in the literature. In this paper, we classify and provide an in-depth review of these protocols.

A fault diagnostic and reconfiguration method for a cascaded H-bridge multilevel inverter drive (MLID) using artificial-intelligence-based techniques is proposed in this paper. Output phase voltages of the MLID are used as diagnostic signals to detect faults and their locations. It is difficult to diagnose an MLID system using a mathematical model because MLID systems consist of many switching devices and their system complexity has a nonlinear factor. Therefore, a neural network (NN) classification is applied to the fault diagnosis of an MLID system. Multilayer perceptron networks are used to identify the type and location of occurring faults. The principal component analysis is utilized in the feature extraction process to reduce the NN input size. A lower dimensional input space will also usually reduce the time necessary to train an NN, and the reduced noise can improve the mapping performance. The genetic algorithm is also applied to select the valuable principal components. The proposed network is evaluated with simulation test set and experimental test set. The overall classification performance of the proposed network is more than 95%. A reconfiguration technique is also proposed. The proposed fault diagnostic system requires about six cycles to clear an open-circuit or short-circuit fault. The experimental results show that the proposed system performs satisfactorily to detect the fault type, fault location, and reconfiguration.

The purpose of this study was to investigate the factors determining the behavioral intention of using food delivery apps (FDAs) during COVID-19 pandemics, under a case study of Bangkok, Thailand. The study was necessitated by the increased use of FDAs during the lockdown; online transactions were considered important in preventing the spread of the virus. The study used quantitative techniques involving structural equation model (SEM) to evaluate the effects of exogenous variables on endogenous variables. Primary data were collected from people who had installed and used FDAs. The findings indicated that performance expectancy, effort expectancy, social influence, timeliness, task technology fit, perceived trust, and perceived safety significantly influence the behavioral intention to use (BIU) to use food delivery apps during the COVID-19 pandemic. To this end, effort should be intensified to study and understand FDAs as it pertains to safety and usage.

In the smart grid, the large scale wind power penetration tends to expand vastly. Nevertheless, due to the intermittent power generation from wind, this may cause a problem of large frequency fluctuation when the load-frequency control (LFC) capacity is not enough to compensate the unbalance of generation and load demand. Also, in the future transport sector, the plug-in hybrid electric vehicle (PHEV) is widely expected for driving in the customer side. Generally, the power of PHEV is charged by plugging into the home outlets as the dispersed battery energy storages. Therefore, the vehicle-to-grid (V2G) power control can be applied to compensate for the inadequate LFC capacity. This paper focuses on the new coordinated V2G control and conventional frequency controller for robust LFC in the smart grid with large wind farms. The battery state-of-charge (SOC) is controlled by the optimized SOC deviation control. The structure of frequency controller is a proportional integral (PI) with a single input. To enhance the robust performance and robust stability against the system uncertainties, the PI controller parameters and the SOC deviation are optimized simultaneously by the particle swarm optimization based on the fixed structure mixed H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> /H∞ control. Simulation results show the superior robustness and control effect of the proposed coordinated controllers over the compared controllers.

Emerging technologies toward a connected vehicle-infrastructure-pedestrian environment and big data have made it easier and cheaper to collect, store, analyze, use, and disseminate multi-source data. The connected environment also introduces new approaches to flexible control and management of transportation systems in real time to improve overall system performance. Given the benefits of a connected environment, it is crucial that we understand how the current intelligent transportation system could be adapted to the connected environment.

The primary objective of this research was the development of a problem-based learning model using a virtual learning environment (VLE) for undergraduate students in the Photography for Communication Arts course. The model supports and enhances students' learning, achievements and problem-solving skills. An efficiency test for the model revealed an above average set of criteria at 80/83.93, which conformed to the research hypothesis. The principles of instructional systems design (ISD) and systems approach were integrated into the design and assessment phases of model development, which resulted in more effective management of relevant instructional courses and materials. Based on its efficiency and potential application to real-life situations, the model has been deemed suitable by experts. The selected student group in the problem-based learning model via VLE achieved higher test scores compared to a group of students in a normal classroom with a statistical significance of .05. Because students learn using models that promote self-awareness and make it possible to choose their own topic of study employing resources provided by VLE, an assessment of their work quality found that they gained more knowledge of information technology as well as access to up-to-date information. Students are able to choose the most comfortable time to study. The model encourages students to learn through participation, practice problem-solving skills on an individual basis, and exchange ideas with other members of a group. The virtual environment involves many forms of media and materials that stimulate students' interest in learning and results in higher satisfaction. The gap in the communication channel between students and teachers is reduced due to easier and more informal communication.

The number of undescribed species of lichenized fungi has been estimated at roughly 10,000. Describing and cataloging these would take the existing number of taxonomists several decades; however, the support for taxonomy is in decline worldwide. In this paper we emphasize the dire need for taxonomic expertise in lichenology. We bring together 103 colleagues from institutions worldwide to describe a total of 100 new species of lichenized fungi, representing a wide taxonomic and geographic range. The newly described species are: Acarospora flavisparsa, A. janae, Aderkomyces thailandicus, Amandinea maritima, Ampliotrema cocosense, Anomomorpha lecanorina, A. tuberculata, Aspicilia mansourii, Bacidina sorediata, Badimia multiseptata, B. vezdana, Biatora epirotica, Buellia sulphurica, Bunodophoron pinnatum, Byssoloma spinulosum, Calopadia cinereopruinosa, C. editae, Caloplaca brownlieae, C. decipioides, C. digitaurea, C. magnussoniana, C. mereschkowskiana, C. yorkensis, Calvitimela uniseptata, Chapsa microspora, C. psoromica, C. rubropulveracea, C. thallotrema, Chiodecton pustuliferum, Cladonia mongkolsukii, Clypeopyrenis porinoides, Coccocarpia delicatula, Coenogonium flammeum, Cresponea ancistrosporelloides, Crocynia microphyllina, Dictyonema hernandezii, D. hirsutum, Diorygma microsporum, D. sticticum, Echinoplaca pernambucensis, E. schizidiifera, Eremithallus marusae, Everniastrum constictovexans, Fellhanera borbonica, Fibrillithecis sprucei, Fissurina astroisidiata, F. nigrolabiata, F. subcomparimuralis, Graphis caribica, G. cerradensis, G. itatiaiensis, G. marusa, Gyalideopsis chicaque, Gyrotrema papillatum, Harpidium gavilaniae, Hypogymnia amplexa, Hypotrachyna guatemalensis, H. indica, H. lueckingii, H. paracitrella, H. paraphyscioides, H. parasinuosa, Icmadophila eucalypti, Krogia microphylla, Lecanora mugambii, L. printzenii, L. xanthoplumosella, Lecidea lygommella, Lecidella greenii, Lempholemma corticola, Lepraria sekikaica, Lobariella sipmanii, Megalospora austropacifica, M. galapagoensis, Menegazzia endocrocea, Myriotrema endoflavescens, Ocellularia albobullata, O. vizcayensis, Ochrolechia insularis, Opegrapha viridipruinosa, Pannaria phyllidiata, Parmelia asiatica, Pertusaria conspersa, Phlyctis psoromica, Placopsis imshaugii, Platismatia wheeleri, Porina huainamdungensis, Ramalina hyrcana, R. stoffersii, Relicina colombiana, Rhizocarpon diploschistidina, Sticta venosa, Sagenidiopsis isidiata, Tapellaria albomarginata, Thelotrema fijiense, Tricharia nigriuncinata, Usnea galapagona, U. pallidocarpa, Verrucaria rhizicola, and Xanthomendoza rosmarieae. In addition, three new combinations are proposed: Fibrillithecis dehiscens, Lobariella botryoides, and Lobariella pallida.

Analyzing microRNAs (miRNAs) within urine extracellular vesicles (EVs) is important for realizing miRNA-based, simple, and noninvasive early disease diagnoses and timely medical checkups. However, the inherent difficulty in collecting dilute concentrations of EVs (<0.01 volume %) from urine has hindered the development of these diagnoses and medical checkups. We propose a device composed of nanowires anchored into a microfluidic substrate. This device enables EV collections at high efficiency and in situ extractions of various miRNAs of different sequences (around 1000 types) that significantly exceed the number of species being extracted by the conventional ultracentrifugation method. The mechanical stability of nanowires anchored into substrates during buffer flow and the electrostatic collection of EVs onto the nanowires are the two key mechanisms that ensure the success of the proposed device. In addition, we use our methodology to identify urinary miRNAs that could potentially serve as biomarkers for cancer not only for urologic malignancies (bladder and prostate) but also for nonurologic ones (lung, pancreas, and liver). The present device concept will provide a foundation for work toward the long-term goal of urine-based early diagnoses and medical checkups for cancer.

Workload balancing in cloud computing is still challenging problem, especially in Infrastructure as a Service (IaaS) in the cloud model. A problem that should not occur during cloud access is a host or server being overloaded or underloaded, which may affect the processing time or may result in a system crash. Therefore, to prevent these problems, an appropriate schedule of access should be considered so that the system can distribute tasks across all available resources, which is called load balancing. The load balancing technique should ensure that all Virtual Machines (VMs) are used appropriately. In this paper, an independent task scheduling approach in cloud computing is proposed using a Multi-objective task scheduling optimization based on the Artificial Bee Colony Algorithm (ABC) with a Q-learning algorithm,which is a reinforcement learning technique that helps the ABC algorithm work faster, called the MOABCQ method. The proposed method aims to optimize scheduling and resource utilization, maximize VM throughput, and create load balancing between VMs based on makespan, cost, and resource utilization, which are limitations of concurrent considerations. Performance analysis of the proposed method was compared using CloudSim with the existing load balancing and scheduling algorithms: Max-Min, FCFS, HABC_LJF, Q-learning, MOPSO, and MOCS algorithms in three datasets: Random, Google Cloud Jobs (GoCJ), and Synthetic workload. The experimental results indicated that the algorithms used MOABCQ approach outperformed the other algorithms in terms of reducing makespan, reducing cost, reducing degree of imbalance, increasing throughput and average resource utilization.

This work presents the synthesis gas production from gasification of plastic waste, i.e. polyethylene (PE) and polypropylene (PP). The steam gasification is modeled by using AspenPlusTM simulation software. The effects of gasifier temperature and steam to feed (S/F) mass ratio were examined to determine the suitable synthesis gas mole flow rate. The simulation results showed that gasifier should be operated at 900 °C with optimal S/F mass ratio as 1.5. Considering the influence of PE/PP mass ratio, the results indicated that the PE/PP mass ratio of 100/0 or pure PE can provide the maximum synthesis gas flow rate of 21 kmol/hr and H2/CO ratio of 2.1.

The use of polymeric materials (PMs) and polymeric films (PMFs) has increased in medicine and dentistry. This increasing interest is attributed to not only the excellent surfaces of PMs and PMFs but also their desired mechanical and biological properties, low production cost, and ease in processing, allowing them to be tailored for a wide range of applications. Specifically, PMs and PMFs are used in dentistry for their antimicrobial, drug delivery properties; in preventive, restorative and regenerative therapies; and for corrosion and friction reduction. PMFs such as acrylic acid copolymers are used as a dental adhesive; polylactic acids are used for dental pulp and dentin regeneration, and bioactive polymers are used as advanced drug delivery systems. The objective of this article was to review the literatures on the latest advancements in the use of PMs and PMFs in medicine and dentistry. Published literature (1990-2017) on PMs and PMFs for use in medicine and dentistry was reviewed using MEDLINE/PubMed and ScienceDirect resources. Furthermore, this review also explores the diversity of latest PMs and PMFs that have been utilized in dental applications, and analyzes the benefits and limitations of PMs and PMFs. Most of the PMs and PMFs have shown to improve the biomechanical properties of dental materials, but in future, more clinical studies are needed to create better treatment guidelines for patients.

Knowledge of electrical tissue conductivity is necessary to determine deposition of electromagnetic energy and can further be used to diagnostically differentiate between normal and neoplastic tissue. We measured 17 rats with a total of 24 tumours of the K12/TRb rat colon cancer cell line. In each animal we measured in vivo hepatic tumour and normal tissue conductivity at seven frequencies from 10 Hz to 1 MHz, at different tumour stages between 6 and 12 weeks after induction. Conductivity of normal liver tissue was 1.26 +/- 0.15 mS cm(-1) at 10 Hz, and 4.61 +/- 0.42 mS cm(-1) at 1 MHz. Conductivity of tumour was 2.69 +/- 0.91 mS cm(-1) at 10 Hz, and 5.23 +/- 0.82 mS cm(-1) at 1 MHz. Conductivity was significantly different between normal and tumour tissue (p < 0.05). We determined the percentage of necrosis and fibrosis at the measurement site. We fitted the conductivity data to the Cole-Cole model. For the tumour data we determined Spearman's correlation coefficients between the Cole-Cole parameters and age, necrosis, fibrosis and tumour volume and found significant correlation between necrosis and the Cole-Cole parameters (p < 0.05). We conclude that necrosis within the tumour and the associated membrane breakdown is likely responsible for the observed change in conductivity.

This paper proposes coordinated control of blade pitch angle of wind turbine generators and plug-in hybrid electric vehicles (PHEVs) for load frequency control of microgrid using model predictive controls (MPCs). The MPC is an effective model-based predictive control, which calculates future control signals by optimization method using plant model, current, and past signals of the system. The MPC-based PHEVs' power control can be used to reduce frequency fluctuation of microgrid effectively. However, for large system, large number of PHEVs is needed to produce satisfying frequency deviation. In order to reduce the number of PHEVs, the smoothing of wind power production by pitch angle control using MPC method is proposed and is coordinated with PHEVs control in this paper. The simulation results confirm that the coordinated control of pitch angle and PHEVs using MPCs is able to reduce the number of PHEVs and the frequency fluctuation can be maintained significantly. In addition, the proposed method is robust to the system parameters variation over proportional-integral derivative controllers.