Determination of effective university–industry joint research for photovoltaic technology transfer (UIJRPTT) in Thailand

Most of the literatures related to university–industry (U–I) and technology transfer assume that the collaboration particularly the U–I joint research is beneficial to both university and industry which as a result underpins the sustainable development of economics and living standards of developed and developing countries. The U–I joint research for photovoltaic technology transfer in a developing country like Thailand should have been increased considering the fact that (i) the government implemented various strategies to support the renewable energy research and market development, (ii) the university aimed to be “research-based university and (iii) the Thai photovoltaic industry struggle for competitiveness and survival in the global market. However, evidence revealed that the university and industry conducted little number of U–I joint projects. In this paper, we investigate the factors influencing the effective U–I joint research for photovoltaic technology transfer (UIJRPTT). In an attempt to better understand the influence of the factors, the path model with factors related to characteristics and perspectives of the university and the industry as well as joint research mechanism and their linkages to higher growth and improved economic and quality performance of the U–I joint research is developed and validated. The developed model empirically explains interaction between the factors and the outcome factors and can assist the government, the university and the industry to devise target strategies to improve the growth and performance of UIJRPTT.     

Design of Wearable Radio Frequency Identification Antenna

This paper focuses on the development of a wearable radio frequency identification (RFID) antenna to be embedded on shirt collars or cuffs. Wearable RFID tags tend to be conformal, and are required to reasonably meet design specifications even when under deformation. A simple circular dipole structure was selected as the base design for the antenna. Operating in the ultra-high frequency band at 866 MHz and over an operating range of around 5 m, the antenna is versatile enough to be used for a number of applications such as the tagging of patients in a hospital or for workers on dangerous construction sites. The designs presented account for the complex input impedance generally observed in RFID systems and the final design employs an intricate spiral structure to accommodate longer wavelengths. This resulted in a compact portable antenna able to meet device specifications.     

Membrane-less MFC based biosensor for monitoring wastewater quality

Microbial fuel cell (MFC), a bioelectrochemical device, can be used to produce bioelectric signals from hydrogen carriers, particularly organic compounds in wastewaters. The solid correlation between the signals and the hydrogen carrier concentration can be exploited in a biosensor for measuring wastewater quality. A small volume of the membrane-less SCMFCs were operated with various wastewater concentrations to investigate the relationship between the concentration of substrates with the current outputs and the performance of the SCMFCs. The results demonstrated that the detection times of current outputs from low to high peak were significantly short when using a low synthetic wastewater (SW) concentration of 25–1000 mg COD.L^?1. The correlation between the SW concentration and the current outputs was obtained up to 250 mg COD.L^?1 (R² = 0.96). When the SCMFCs were fed with distillery wastewater (DW) from low to high concentration (50–2000 mg COD.L^?1), it showed a detection times of the current as short. SCMFCs had a good correlation between the concentration of DW and the current outputs obtained up to 1200 mg COD.L^?1 (R² = 0.97). Maximum substrate reduction was found more than 90% when the initial SW concentration was in the range of 25–1000 mg COD.L^?1. While substrate reduction was more than 60% for the DW concentration in the range of 50–2000 mg COD, L^?1 was operated. In other words, this membrane-less SCMFCs are able to be a long starvation (5 days) and a high repeatability of the current output in both wastewaters. Indications proved that the detection time of current and substrate degradation were dependant on concentrations, types of substrate, and types of MFC.     

Applying memetic algorithm-based clustering to recommender system with high sparsity problem

A new recommendation method was presented based on memetic algorithm-based clustering. The proposed method was tested on four highly sparse real-world datasets. Its recommendation performance is evaluated and compared with that of the frequency-based, user-based, item-based, k-means clustering-based, and genetic algorithm-based methods in terms of precision, recall, and F1 score. The results show that the proposed method yields better performance under the new user cold-start problem when each of new active users selects only one or two items into the basket. The average F1 scores on all four datasets are improved by 225.0%, 61.6%, 54.6%, 49.3%, 28.8%, and 6.3% over the frequency-based, user-based, item-based, k-means clustering-based, and two genetic algorithm-based methods, respectively.     

Performance evaluation of a 10 kWp PV power system prototype for isolated building in Thailand

This paper describes the design and testing of a 10 kW_p photovoltaic (PV) system and summarizes its performance results after the first 6 months of operation. This system functions as a stand-alone power system that is used to supply electricity for isolated buildings and is designed for integration with a micro-grid system (MGS), which is the future concept for a renewable energy-based power network system for Thailand. The system is comprised of the following components. An array with three different types of PV modules consisting amorphous thin film of 3672 W, polycrystalline solar cell of 3600 W and hybrid solar cell of 2880 W, making up a total peak power of 10.152 kW. In addition, there are three grid-connected inverters of 3.5 kW each, three bi-directional inverters of 3.5 kW each and an energy storage system of 100 kWh. After the first 6 months of system operation, it was found that all the components and the overall system had worked effectively. In total, the system had generated about 7852 kWh and the average electricity production per day was 43.6 kWh. The average efficiency of amorphous thin film panel, polycrystalline panel, hybrid solar cell panel and entire PV panel system was 6.26%, 10.48%, 13.78% and 8.82%, respectively. From the analysis of the daily energy production, daily energy consumption and energy storage, the results seem to indicate that there was some mismatching between energy supply and demand in the system. However, this can be overcome by integrating the system to a micro-grid network whereby the energy from the system can be diverted to other loads when there is a surplus and additional energy can be drawn from external sources and fed to the system when the internal supply is insufficient.     

Automatic cervical cell segmentation and classification in Pap smears

Cervical cancer is one of the leading causes of cancer death in females worldwide. The disease can be cured if the patient is diagnosed in the pre-cancerous lesion stage or earlier. A common physical examination technique widely used in the screening is Papanicolaou test or Pap test. In this research, a method for automatic cervical cancer cell segmentation and classification is proposed. A single-cell image is segmented into nucleus, cytoplasm, and background, using the fuzzy C-means (FCM) clustering technique. Four cell classes in the ERUDIT and LCH datasets, i.e., normal, low grade squamous intraepithelial lesion (LSIL), high grade squamous intraepithelial lesion (HSIL), and squamous cell carcinoma (SCC), are considered. The 2-class problem can be achieved by grouping the last 3 classes as one abnormal class. Whereas, the Herlev dataset consists of 7 cell classes, i.e., superficial squamous, intermediate squamous, columnar, mild dysplasia, moderate dysplasia, severe dysplasia, and carcinoma in situ. These 7 classes can also be grouped to form a 2-class problem. These 3 datasets were tested on 5 classifiers including Bayesian classifier, linear discriminant analysis (LDA), K-nearest neighbor (KNN), artificial neural networks (ANN), and support vector machine (SVM). For the ERUDIT dataset, ANN with 5 nucleus-based features yielded the accuracies of 96.20% and 97.83% on the 4-class and 2-class problems, respectively. For the Herlev dataset, ANN with 9 cell-based features yielded the accuracies of 93.78% and 99.27% for the 7-class and 2-class problems, respectively. For the LCH dataset, ANN with 9 cell-based features yielded the accuracies of 95.00% and 97.00% for the 4-class and 2-class problems, respectively. The segmentation and classification performances of the proposed method were compared with that of the hard C-means clustering and watershed technique. The results show that the proposed automatic approach yields very good performance and is better than its counterparts.     

Production of hydrogen and methane by one and two stage fermentation of food waste

Anaerobic digestion is an attractive process for generation of hydrogen and methane, which involves complex microbial processes on decomposition of organic wastes and subsequent conversion of metabolic intermediates to hydrogen and methane. Comparative performance of a sequential hydrogen and methane fermentation in two stage process and methane fermentation in one stage process were tested in batch reactor at varying ratios of feedstock to microbial inoculum (F/M) under mesophilic incubation. F/M ratios influence biogas yield, production rate, and potential. The highest H₂ and CH₄ yields of 55 and 94 mL g⁻¹ VS were achieved at F/M of 7.5 in two stage process, while the highest CH₄ yield of 82 mL g⁻¹ VS in one stage process was observed at the same F/M. Acetic and butyric acids are the main volatile fatty acids (VFAs) produced in the hydrogen fermentation stage with the concentration range 10–25 mmol L⁻¹. Little concentrations of VFAs were accumulated in methane fermentation in both stage processes. Total energy recovery in two stage process is higher than that in one stage by 18%. This work demonstrated two stage fermentation achieved a better performance than one stage process.     

Reliability evaluation of ultra-thin CSP using new flip-chip bonding technology––double-sided CSP and single-sided CSP

A high-density packaging technology has been developed that uses new flip-chip bonding technology with a thin IC and a thin substrate. Numerical analysis with the finite element method as well experiments clearly showed that deflection of the IC and reliability were affected by the IC thickness. Consequently, reliability could be improved by reducing IC thickness. The dependency of the life in single-sided chip-size packages (CSPs) could be expressed using a normal stress value in thickness, which is computed by the IC thickness and substrate type and thickness. The dependency of the life in double-sided CSPs could be expressed using a shear stress value in the vertical cross section, which is computed in IC thickness and substrate type and thickness, respectively.Moreover, a double-sided flip-chip approach solved the problem of warpage. A high-capacity memory card of 512 MB was put to practical use by applying these results. This increased the Si density by four times over that of a conventional CSP.