Search results for: current practices in teacher training

Authors: Sanguk Nam, Van Ha Nguyen, Hanjung Song

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For low-power applications such as adapters for portable devices and USB chargers, the primary side regulation (PSR) fly-back converter is widely used in lieu of the conventional fly-back converter using opto-coupler because of its simpler structure and lower cost. In the literature, there has been studies focusing on the design of PSR circuit; however, the conventional sensing method in PSR circuit using RC delay has a lower accuracy as compared to the conventional fly-back converter using opto-coupler. In this paper, we propose a novel PWM/PFM controller using new sensing technique for the PSR fly-back converter which can control an accurate output voltage. The conventional PSR circuit can sense the output voltage information from the auxiliary winding to regulate the duty cycle of the clock that control the output voltage. In the sensing signal waveform, there has two transient points at time the voltage equals to Vout+VD and Vout, respectively. In other to sense the output voltage, the PSR circuit must detect the time at which the current of the diode at the output equals to zero. In the conventional PSR flyback-converter, the sensing signal at this time has a non-sharp-negative slope that might cause a difficulty in detecting the output voltage information since a delay of sensing signal or switching clock may exist which brings out an unstable operation of PSR fly-back converter. In this paper instead of detecting output voltage at a non-sharp-negative slope, a sharp-positive slope is used to sense the proper information of the output voltage. The proposed PRS circuit consists of a saw-tooth generator, a summing circuit, a sample and hold circuit and a peak detector. Besides, there is also the start-up circuit which protects the chip from high surge current when the converter is turned on. Additionally, to reduce the standby power loss, a second mode which operates in a low frequency is designed beside the main mode at high frequency. In general, the operation of the proposed PSR circuit can be summarized as following: At the time the output information is sensed from the auxiliary winding, a saw-tooth signal from the saw-tooth generator is generated. Then, both of these signals are summed using a summing circuit. After this process, the slope of the peak of the sensing signal at the time diode current is zero becomes positive and sharp that make the peak easy to detect. The output of the summing circuit then is fed into a peak detector and the sample and hold circuit; hence, the output voltage can be properly sensed. By this way, we can sense more accurate output voltage information and extend margin even circuit is delayed or even there is the existence of noise by using only a simple circuit structure as compared with conventional circuits while the performance can be sufficiently enhanced. Circuit verification was carried out using 0.35μm 700V Magnachip process. The simulation result of sensing signal shows a maximum error of 5mV under various load and line conditions which means the operation of the converter is stable. As compared to the conventional circuit, we achieved very small error only used analog circuits compare with conventional circuits. In this paper, a PWM/PFM controller using a simple and effective sensing method for PSR fly-back converter has been presented in this paper. The circuit structure is simple as compared with the conventional designs. The gained results from simulation confirmed the idea of the design

Keywords: primary side regulation, PSR, sensing technique, peak detector, PWM/PFM control, fly-back converter

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Authors: Qin Wei

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There has been an increased number of immigrants arriving in Canada and a concurrent rise in the number of immigrant youth suffering from drug abuse. Immigrant youths’ drug abuse has become a significant social and public health concern for researchers. This literature review explores the nature of immigrant youths’ drug abuse by examining the factors influencing the onset of substance misuse, the barriers that discourage youth to seek out treatment, and how to resolve addictions amidst immigrant youth. Findings from the literature demonstrate that diminished parental supervision, acculturation challenges, peer conformity, discrimination, and ethnic marginalization are all significant factors influencing youth to use drugs as an outlet for their pain, while culturally competent care and fear of family and culture-based addiction stigma act as barriers discouraging youth from seeking out addiction support. To resolve addiction challenges amidst immigrant youth, future research should focus on promoting and implementing culturally sensitive practices and psychoeducational initiatives into immigrant communities and within public health policies.

Keywords: approaches, barriers, drug abuse, Canada, immigrant youth, reasons

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Authors: Uduak Umoh, Imo Eyoh, Emmauel Nyoho

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This paper compares fuzzy-machine learning algorithms such as Support Vector Machine (SVM), and K-Nearest Neighbor (KNN) for the predicting cases of fire outbreak. The paper uses the fire outbreak dataset with three features (Temperature, Smoke, and Flame). The data is pre-processed using Interval Type-2 Fuzzy Logic (IT2FL) algorithm. Min-Max Normalization and Principal Component Analysis (PCA) are used to predict feature labels in the dataset, normalize the dataset, and select relevant features respectively. The output of the pre-processing is a dataset with two principal components (PC1 and PC2). The pre-processed dataset is then used in the training of the aforementioned machine learning models. K-fold (with K=10) cross-validation method is used to evaluate the performance of the models using the matrices – ROC (Receiver Operating Curve), Specificity, and Sensitivity. The model is also tested with 20% of the dataset. The validation result shows KNN is the better model for fire outbreak detection with an ROC value of 0.99878, followed by SVM with an ROC value of 0.99753.

Keywords: Machine Learning Algorithms , Interval Type-2 Fuzzy Logic, Fire Outbreak, Support Vector Machine, K-Nearest Neighbour, Principal Component Analysis

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Authors: Nevine Henry Wasef

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The research discusses how Egyptian citizens perceive the performance of public sector officials, particularly the ethical values manifested in their behavior. It aims at answering the question of how Egyptian citizens’ perception of public officials affects citizens' trust in the government at large and the process of public service delivery specifically. The hypothesis is that public opinion about civil servants’ ethical values would be proportional to citizens’ trust in the government, which means that the more citizens regard administrators with high ethical standards, the higher trust in the government they would have and vice versa. The research would focus on the independent variable of trust in the government and the dependent variable of public perception of administrators’ ethical performance. The data would be collected through surveys designed to measure the public evaluation of public officials they are interacting with and the quality of services delivered to them. The study concludes that implementing ethical values in public administration has a crucial role in improving citizens’ trust in the government based on various case studies of governments that successfully adopted ethical training programs for their civil servants.

Keywords: trust, distrust, ethics, performance, integrity, values, public service

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Authors: Firas M. Tuaimah, Huda M. Abdul Abbas

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Accurate Short Term Load Forecasting (STLF) is essential for a variety of decision making processes. However, forecasting accuracy can drop due to the presence of uncertainty in the operation of energy systems or unexpected behavior of exogenous variables. Interval Type 2 Fuzzy Logic System (IT2 FLS), with additional degrees of freedom, gives an excellent tool for handling uncertainties and it improved the prediction accuracy. The training data used in this study covers the period from January 1, 2012 to February 1, 2012 for winter season and the period from July 1, 2012 to August 1, 2012 for summer season. The actual load forecasting period starts from January 22, till 28, 2012 for winter model and from July 22 till 28, 2012 for summer model. The real data for Iraqi power system which belongs to the Ministry of Electricity.

Keywords: short term load forecasting, prediction interval, type 2 fuzzy logic systems, electric, computer systems engineering

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Authors: Varsha Rainson

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Artificial intelligence (AI) has great potential and can be used as a powerful tool of application in various domains and sectors. But with the application of AI, there comes a wide spectrum of concerns around bias, accountability, transparency, and privacy. Hence, there is a need for responsible AI, which can uphold ethical and accountable practices to ensure that things are transparent and fair. The paper is a combination of AI and cultural heritage preservation, with a greater focus on India because of the rich cultural legacy that it holds. India’s cultural heritage in itself contributes to its identity and the economy. In this paper, along with discussing the impact culture holds on the Indian economy, we will discuss the threats that the cultural heritage is exposed to due to pollution, climate change and urbanization. Furthermore, the paper reviews some of the exciting applications of AI in cultural heritage preservation, such as 3-D scanning, photogrammetry, and other techniques which have led to the reconstruction of cultural artifacts and sites. The paper eventually moves into the potential risks and challenges that AI poses in cultural heritage preservation. These include ethical, legal, and social issues which are to be addressed by organizations and government authorities. Overall, the paper strongly argues the need for responsible AI and the important role it can play in preserving India’s cultural heritage while holding importance to value and diversity.

Keywords: responsible AI, cultural heritage, artificial intelligence, biases, transparency

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Authors: J. S. Kim, N. P. Hong

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In this paper, a CMOS vector modulator designed for wireless backhaul system based on 802.11ac is presented. A poly phase filter and sign select switches yield two orthogonal signal paths. Two variable gain amplifiers with strongly reduced phase shift of only ±5 ° are used to weight these paths. It has a phase control range of 360 ° and a gain range of -10 dB to 10 dB. The current drawn from a 1.2 V supply amounts 20.4 mA. Using a 0.13 mm technology, the chip die area amounts 1.47x0.75 mm².

Keywords: CMOS, phase shifter, backhaul, 802.11ac

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Authors: Thomas Ruppert, Shana Jones, J. Scott Pippin

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State and federal government agencies within the United States have recently invested substantial resources into studies of future flood risk conditions associated with climate change and sea-level rise. A review of numerous case studies has uncovered several key themes that speak to an overall incoherence within current flood risk assessment procedures in the U.S. context. First, there are substantial local differences in the quality of available information about basic infrastructure, particularly with regard to local stormwater features and essential facilities that are fundamental components of effective flood hazard planning and mitigation. Second, there can be substantial mismatch between regulatory Flood Insurance Rate Maps (FIRMs) as produced by the National Flood Insurance Program (NFIP) and other 'current condition' flood assessment approaches. This is of particular concern in areas where FIRMs already seem to underestimate extant flood risk, which can only be expected to become a greater concern if future FIRMs do not appropriately account for changing climate conditions. Moreover, while there are incentives within the NFIP’s Community Rating System (CRS) to develop enhanced assessments that include future flood risk projections from climate change, the incentive structures seem to have counterintuitive implications that would tend to promote moral hazard. In particular, a technical finding of higher future risk seems to make it easier for a community to qualify for flood insurance savings, with much of these prospective savings applied to individual properties that have the most physical risk of flooding. However, there is at least some case study evidence to indicate that recognition of these issues is prompting broader discussion about the need to move beyond FIRMs as a standalone local flood planning standard. The paper concludes with approaches for developing climate adaptation and flood resilience strategies in the U.S. that move away from the social welfare model being applied through NFIP and toward more of an informed risk approach that transfers much of the investment responsibility over to individual private property owners.

Keywords: climate change adaptation, flood risk, moral hazard, sea-level rise

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Authors: Siyanda S. Biyela, Willie A. Cronje

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This paper presents a desktop study of comparing two different wave energy to electricity technologies (WECs) using a techno-economic approach. This techno-economic approach forms basis of a framework for rapid comparison of current and future technologies. The approach also seeks to assist in investment and strategic decision making expediting future deployment of wave energy harvesting in South Africa.

Keywords: cost of energy (COE) tool, sea state, wave energy converter (WEC), WEC-Sim

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Authors: Shideh Mohseni Movahed, Mansoureh Safari

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Intelligent drug delivery systems (IDDS) are innovative technological innovations and clinical way to advance current treatments. These systems differ in technique of therapeutic administration, intricacy, materials and patient compliance to address numerous clinical conditions that require different pharmacological therapies. IDDS capable of releasing an active molecule at the proper site and at a amount that adjusts in response to the progression of the disease or to certain functions/biorhythms of the organism is particularly appealing. In this paper, we describe the most recent advances in the development of intelligent drug delivery systems.

Keywords: drug delivery systems, IDDS, medicine, health

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Authors: Azeez O. Ganiyu

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Climate change is expected to lead to substantial changes in rainfall patterns in southwest Nigeria, and this may have substantial consequence for forest management and for conservation outcomes throughout the region. We examine three different forest types across an environmental spectrum from semi-arid to humid subtropical and consider their response to water shortages and other environmental stresses; we also explore the potential consequence for conservation and timber production by considering impacts on forest structure and limiting stand density. Analysis of a series of scenarios provides the basis for a critique of existing management practices and suggests practical alternatives to develop resilient forests with minimal diminution of production and environmental services. We specifically discuss practical silviculture interventions that are feasible at the landscape-scale, that are economically viable, and that have the potential to enhance resilience of forest stands. We also discuss incentives to encourage adoption of these approaches by private forest owners. We draw on these case studies in southwestern Nigeria to offer generic principle to assist forest researchers and managers faced with similar challenges elsewhere.

Keywords: climate change, forest, future, silviculture, Nigeria

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Authors: Freda E. Asem, R. D. Osei, D. B. Sarpong, J. K. Kuwornu

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While market access remains important, Ghana’s major handicap is her inability to sustain export growth on the open market. The causes of these could be attributed to inefficiency, lack of competitiveness and supply-side constraints. This study examined the challenges faced by smallholder horticultural farmers and how it relates to their technical efficiency. The study employed mixed methods to address the problem. Using the Millennium Development Account (MiDA) Farmer Based Organization survey data on farm households in 23 districts in Ghana, the study assessed the technical efficiency of smallholder horticultural farmers (taking into account production risks). Focus group discussions (FGDs) and in-depth interviews were also conducted on smallholder mango, pineapple, and chilli pepper farmers selected districts in Ghana. Results revealed the constraints faced by smallholder horticultural farmers to be marketing, training, funding, accessibility, and affordability of inputs, land, access to credit, and the disconnect between themselves and policy makers and implementers.

Keywords: productivity, gender, policy, efficiency, constraints

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Authors: Atuhurra Jesse, N'guessan Yves-Roland Douha, Pabitra Lenka

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The detection of diseases within plants has attracted a lot of attention from computer vision enthusiasts. Despite the progress made to detect diseases in many plants, there remains a research gap to train image classifiers to detect the cacao swollen shoot virus disease or CSSVD for short, pertinent to cacao plants. This gap has mainly been due to the unavailability of high quality labeled training data. Moreover, institutions have been hesitant to share their data related to CSSVD. To fill these gaps, image classifiers to detect CSSVD-infected cacao plants are presented in this study. The classifiers are based on VGG16, ResNet50 and Vision Transformer (ViT). The image classifiers are evaluated on a recently released and publicly accessible KaraAgroAI Cocoa dataset. The best performing image classifier, based on ResNet50, achieves 95.39\% precision, 93.75\% recall, 94.34\% F1-score and 94\% accuracy on only 20 epochs. There is a +9.75\% improvement in recall when compared to previous works. These results indicate that the image classifiers learn to identify cacao plants infected with CSSVD.

Keywords: CSSVD, image classification, ResNet50, vision transformer, KaraAgroAI cocoa dataset

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Authors: Josua K. Junias, Fillemon N. Nangolo, Petrina T. Johaness

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The deterioration of pavement can lead to the formation of potholes, which cause the wheels of a vehicle to experience unusual and uneven movement. In addition, improper loading practices of heavy vehicles can result in dynamic loading of the pavement due to the vehicle's response to the irregular movement caused by the potholes. Previous studies have only focused on the effects of either the road's uneven surface or the asymmetrical loading of the vehicle, but not both. This study aimed to model the pavement's dynamic response to heavy vehicles under different loading configurations and wheel movements. A sample of 225 cases with symmetrical and asymmetrical loading and kinematic movements was used, and 27 validated 3D pavement-vehicle interactive models were developed using SIMWISE 4D. The study found that the type of kinematic movement experienced by the heavy vehicle affects the pavement's dynamic loading, with eccentrically loaded, asymmetrically kinematic heavy vehicles having a statistically significant impact. The study also suggests that the mass of the vehicle's suspension system plays a role in the pavement's dynamic loading.

Keywords: eccentricities, pavement dynamic loading, vertical displacement dynamic response, heavy vehicles

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Authors: Radha Rajamma, Susheela Palanisamy

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The use of chemical fertilizers and pesticides has posed a serious threat to the environment, cause disturbance to the soil ecosystem, pollute the water causing serious health problems. The indigenous practices such as herbal spray, phyto-alternatives, etc. offer harmless alternatives in integrated pest management. The use of plant materials has become an integral part of insect pest management because of their cheap and non-toxic nature. Hence an investigation has been made to determine the bio-efficacy of vermiwash and two leaf extracts, Azadirachta indica and Vitex negundo against mealy bug, Paracoccus marginatus. The results on the effect of vermitechnologies on the activity of mealy bug indicated the effectiveness of vermiwash foliar application in suppressing the pest activity. Accumulative mortality of mealy bug increased gradually with the increase of exposure intervals. The combined treatment of vermiwash with Azadirachta indica reported the highest mortality percentage of 96% followed by the individual treatment of leaf extracts. Hence vermiwash was proved to be the most effective in enhancing the potency of mealy bug and decreased LC50 of the target insect.

Keywords: Azadirachta indica, Paracoccus marginatus, vermiwash, Vitex negundo

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Authors: M. Kowalski, M. Życzkowski, M. Karol

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Current quantum key distribution systems (QKD) offer low bit rate of up to single MHz. Compared to conventional optical fiber links with multiple GHz bitrates, parameters of recent QKD systems are significantly lower. In the article we present the conception of application of the Compressed Sensing method for compression of quantum information. The compression methodology as well as the signal reconstruction method and initial results of improving the throughput of quantum information link are presented.

Keywords: quantum key distribution systems, fiber optic system, compressed sensing

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Authors: Kholod J. Alotaibi, Andrew M. Gravell

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A study was conducted in which 212 software developers in higher education institutions in Saudi Arabia were surveyed to gather an indication of their understanding of the concept of usability, their acceptance of its importance, and to see how well its principles are applied. Interviews were then held with 20 of these developers, and a demonstration of Usage-Centred Design was attempted, a highly usability focused software development methodology, at one select institution for its redesign of an e-learning exam system interface during the requirements gathering phase. The study confirms the need to raise awareness of usability and its importance, and for Usage-Centred Design to be applied in its entirety, also need to encourage greater consultation with potential end-users of software and collaborative practices. The demonstration of Usage-Centred Design confirmed its ability to capture usability requirements more completely and precisely than would otherwise be the case, and hence its usefulness for developers concerned with improving software usability. The concluding discussion delves on the challenges for promoting usability and Usage-Centred Design in light of the research results and findings and recommendations are made for the same.

Keywords: usability, usage-centred, applying principles of usage-centred, Saudi Arabia

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Authors: A. Basheer Ahamadhu, Kiran Kaur, Zainab Ajab Mohideen, Sukmawati Muhammad, Noor Azlinda Wan Jan

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Library management facing favorable conditions and unexpected challenges in the century of information technology. They were having been under pressure to meet their duties to meet the information needs of customers. An information technology has brought big changes to the traditional methods of library work. Libraries need to evaluate, measuring effect information technology to them. This would equip them with the knowledge to make effective information technology to enhance their services. Recognizing the importance of development an electronic library, this research investigated their willingness to change from the traditional library based on the level of automation for the digital library initiatives, review both of the problems associated with digital library and public and terms to be considered for future growth. The main components have been inspected, such as grip library, demographic automations and digitization projects, digital library related to budgetary problems, the thought leader in the electronic library practices library, and the situation viewed for future growth. Libraries have run several digitization projects, at the level of institutions and countries but still needs more efforts in order to bring it to higher levels.

Keywords: academic library, electronic library, information technology, information commons, web pages library

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Authors: Temitope Adewale, Oladapo Raji

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The study was designed to investigate the assessment of women's involvement in fishing. In order to give the study a direction, five research questions, as well as two hypotheses, were postulated, and a total of fifty (50) respondents each were selected from two local government areas for the study. This brings a total of one hundred (100) respondents selected from these local government areas in Lagos state. The outcome of the finding indicates that the percentage of the respondents’ age, 49% was between 31 and 35 years, 56% has a working experience of 6-10 years, 61% were married, 69% had secondary education as their educational level. However, findings show that socio-economic characteristics (x2 =15.504, df=6, p < 0.05) and income (r=0.83, p < 0.05) have a significant relationship on the fishing. It was established that the Women in Fish production/processing were faced with a lot of constraints such as high cost of inputs, inadequate electricity supply, lack of adequate capital, non-availability of the improved oven, non-availability of extension agents, inadequate fish landing, lack of transportation facilities, lack of training on financial management and loan acquisition which affected the level of output of women in Fish processing adversely.

Keywords: women, fishing, agriculture, Lagos

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Authors: Hang Zhou, Limin Zhu

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This paper investigates the fabrication of microstructures on Si surfaces by using electrochemical anodic oxidation with agarose stamps. The fabricating process is based on a selective anodic oxidation reaction that occurs in the contact area between a stamp and a Si substrate. The stamp which is soaked in electrolyte previously acts as a current flow channel. After forming the oxide patterns as an etching mask, a KOH aqueous is used for the wet etching of Si. A complicated microstructure array of 1 cm2 was fabricated by the method with high accuracy.

Keywords: microstructures, anodic oxidation, silicon, agarose stamps

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Authors: Zhang Bian, Zhao Jijun

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The urban layout of Xi’an city (the capital Chang’an in the Tang dynasty) was shaped by feudal etiquette, but this dominant factor was replaced by modern city planning during the period of the Republic of China. This makes Xi’an a representative case to explore the transformation process of Chinese cities in the early 20^th century. By analyzing the contrast and connection between the historical texts of city planning and the realistic construction activities recorded by the maps and images, this paper reviews the transformation process of the urban space of Xi’an in the early 20^th century and divides it into four phases according to important events that significantly impacted planning and construction activities. Based on this, the entire transformation of Xi’an’s city planning and practices can be characterized by three aspects: 1) the dominant force of the city plan and construction changed with the establishment of modern city administrations; 2) the layout of the city was continuously broadened to meet the demand of modern economy and city life; and, 3) the ritual space was transformed into practical space for commercial and recreational activities.

Keywords: city space, the early 20th century, transformation, Xi’an city

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Authors: Joel Bonales, Venecia Solorzano, Carlos Garcia

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A great percentage of the wastewater generated in developing countries don’t receive any treatment, which leads to numerous environmental impacts. In response to this, a paradigm change in the current wastewater treatment model based on large scale plants towards a small and medium scale based model has been proposed. Nevertheless, small scale wastewater treatment (SS-WTTP) with novel technologies such as anaerobic digesters, as well as the utilization of derivative co-products such as biogas, still presents diverse environmental impacts which must be assessed. This study consisted in a Life Cycle Assessment (LCA) performed to a SS-WWTP which treats wastewater from a small commercial block in the city of Morelia, Mexico. The treatment performed in the SS-WWTP consists in anaerobic and aerobic digesters with a daily capacity of 5,040 L. Two different scenarios were analyzed: the current plant conditions and a hypothetical energy use of biogas obtained in situ. Furthermore, two different allocation criteria were applied: full impact allocation to the system’s main product (treated water) and substitution credits for replacing Mexican grid electricity (biogas) and clean water pumping (treated water). The results showed that the analyzed plant had bigger impacts than what has been reported in the bibliography in the basis of wastewater volume treated, which may imply that this plant is currently operating inefficiently. The evaluated impacts appeared to be focused in the aerobic digestion and electric generation phases due to the plant’s particular configuration. Additional findings prove that the allocation criteria applied is crucial for the interpretation of impacts and that that the energy use of the biogas obtained in this plant can help mitigate associated climate change impacts. It is concluded that SS-WTTP is a environmentally sound alternative for wastewater treatment from a systemic perspective. However, this type of studies must be careful in the selection of the allocation criteria and replaced products, since these factors have a great influence in the results of the assessment.

Keywords: biogas, life cycle assessment, small scale treatment, wastewater treatment

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Authors: Ninlawat Phuangchoke, Waraporn Viyanon, Setta Sasananan

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The most important process of the water treatment plant process is the coagulation using alum and poly aluminum chloride (PACL), and the value of usage per day is a hundred thousand baht. Therefore, determining the dosage of alum and PACL are the most important factors to be prescribed. Water production is economical and valuable. This research applies an artificial neural network (ANN), which uses the Levenberg–Marquardt algorithm to create a mathematical model (Soft Jar Test) for prediction chemical dose used to coagulation such as alum and PACL, which input data consists of turbidity, pH, alkalinity, conductivity, and, oxygen consumption (OC) of Bangkhen water treatment plant (BKWTP) Metropolitan Waterworks Authority. The data collected from 1 January 2019 to 31 December 2019 cover changing seasons of Thailand. The input data of ANN is divided into three groups training set, test set, and validation set, which the best model performance with a coefficient of determination and mean absolute error of alum are 0.73, 3.18, and PACL is 0.59, 3.21 respectively.

Keywords: soft jar test, jar test, water treatment plant process, artificial neural network

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Authors: Ila Shrestha

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Bridim Village Development Committee (VDC) is one of the medicinal plants hot spots of Nepal. It is located on a ridge above the lower Langtang Khola, steep and narrow spot in between 1944 m to 4833 m altitude. The study area is homogeneously inhabited by Tamang communities. An investigation on folk herbal medicine on the basis of traditional uses of medicinal plants was done in 2014. The local traditional healers, elder men and women, traders and teachers, were consulted as key informants for documentation of indigenous knowledge on the medicinal plants. It was found that altogether seventy-one medicinal plant species belonging to sixty genera and thirty-three families were used by local people for twenty-seven diseases. Roots of thirty-four species were the most frequently used plant parts and bigger numbers of species were found to be used in fever of ten species. Most medicines were prepared in the form of juice of forty species. The attempt of the study was to document ethno medicinal practices to treat different diseases in the study area for conservation of indigenous knowledge.

Keywords: Bridim village, ethnomedicine, national park, plants

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Authors: Naritphol Boonyakiat

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This research attempts to investigate the relationship between corporate social responsibility and students’ job performance of the Silpakorn University’s internship program within various organizations. The goal of this study is to fill the literature gap by gaining an understanding of corporate social responsibility that fundamentally relate to students’ job performance within the organizations. Thus, this study will focus on the outcomes that derive from selected employers’ qualitative assessment and evaluation forms from various companies. The results represent the perceptions of students towards the corporate social responsibility aspects and their job performance evaluation from the employers in various organizations. The findings indicate that corporate social responsibility has significant effects on students’ job performance. This study may assist us in gaining a better understanding of the integrated aspects of university and workplace environments to discover how to allocate optimally university’s resources and management approaches to gain benefits from corporate social responsibility practices toward students’ job performance within an organizational setting. Therefore, there is good reason to believe that the findings can contribute to research in the area of CSR and students’ job performance as an essential aspect of long-term success sustainability.

Keywords: corporate social responsibility, job performance, university students, internship program

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Authors: Valentina Zhang

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While facial expression is a complex and individualized behavior, all facial emotion recognition (FER) systems known to us rely on a single facial representation and are trained on universal data. We conjecture that: (i) different facial representations can provide different, sometimes complementing views of emotions; (ii) when employed collectively in a discussion group setting, they enable more accurate emotion reading which is highly desirable in autism care and other applications context sensitive to errors. In this paper, we first study FER using pixel-based DL vs semantics-based DL in the context of deepfake videos. Our experiment indicates that while the semantics-trained model performs better with articulated facial feature changes, the pixel-trained model outperforms on subtle or rare facial expressions. Armed with these findings, we have constructed an adaptive FER system learning from both types of models for dyadic or small interacting groups and further leveraging the synthesized group emotions as the ground truth for individualized FER training. Using a collection of group conversation videos, we demonstrate that FER accuracy and personalization can benefit from such an approach.

Keywords: neurodivergence care, facial emotion recognition, deep learning, ground truth for supervised learning

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Authors: Nadia Masood Khan, Muhammad Salman Khan, Gul Muhammad Khan

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Cardiologists perform cardiac auscultation to detect abnormalities in heart sounds. Since accurate auscultation is a crucial first step in screening patients with heart diseases, there is a need to develop computer-aided detection/diagnosis (CAD) systems to assist cardiologists in interpreting heart sounds and provide second opinions. In this paper different algorithms are implemented for automated heart sound classification using unsegmented phonocardiogram (PCG) signals. Support vector machine (SVM), artificial neural network (ANN) and cartesian genetic programming evolved artificial neural network (CGPANN) without the application of any segmentation algorithm has been explored in this study. The signals are first pre-processed to remove any unwanted frequencies. Both time and frequency domain features are then extracted for training the different models. The different algorithms are tested in multiple scenarios and their strengths and weaknesses are discussed. Results indicate that SVM outperforms the rest with an accuracy of 73.64%.

Keywords: pattern recognition, machine learning, computer aided diagnosis, heart sound classification, and feature extraction

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Authors: Kuo-Wei Hsu, Wei-Chin Lo

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In these years, urban agriculture development has been wide spreading all over the world. The development of urban agriculture is an evolution process of highly urbanization, as well as an agricultural phenomenon closely related to the development of economy, society and culture in urban areas. It provides densely populated areas with multi-functional uses of land, impacting strategic development of both large and small towns in the area. In addition, the participation of social enterprises keeps industrial competitiveness and makes gains when facing rapid transformation of industrial structures and new patterns of lifestyles in urban areas. They create better living conditions as well as protect the environment with innovative business beliefs, which give new ways for development of urban agriculture. Also, through building up the value chain, these social enterprises are capable of creating value for urban agriculture. Most of research regarding to social enterprises currently explore the relationship between corporate responsibilities and its role play, operational mode and performance and organizational patterns. Merely some of them discuss the function of social entrepreneurship in the development of urban agriculture. Moreover, none of them have explored the value creation for development of urban agriculture processed by social enterprises, as well as how social enterprises operate to increase competitive advantages, which make it possible to achieve industrial innovation, increase corporate value and even provide services with value creation. Therefore, this research mainly reviews current business patterns and operational conditions of social enterprises. This research endowed social responsibilities, and discusses current development process of urban agriculture. This research adopts Value Chain perspective to discuss key factors for value creation with respect to the development of urban agriculture processed by social enterprises. Thereby after organization and integration this research develops the prospect of value creation referring to urban agriculture processed by social enterprises and builds the value chain for urban agriculture. In conclusion, this research explored the relationship between value chain and value creation, which relates to values of customer, enterprise, society and economy referring to the development of urban agriculture uniquely, in consideration of the participation of social enterprises, and hence built the connection between value chain and value creation in the development of urban agriculture by social enterprises. The research found, social enterprises help to enhance the connection between the enterprise value and society value, mold corporate image with social responsibility and create brand value, and therefore impact the increase of economic value.

Keywords: urban agriculture development, value chain, social enterprise, urban systems

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Authors: Jaspreet Singh, Gurvinder Singh, Prabhsimran Singh, Rajinder Singh, Prithvipal Singh, Karanjeet Singh Kahlon, Ravinder Singh Sawhney

Abstract:

Morphological evaluation of Indian languages is one of the burgeoning fields in the area of Natural Language Processing (NLP). The evaluation of a language is an eminent task in the era of information retrieval and text mining. The extraction and classification of knowledge from text can be exploited for sentiment analysis and morphological evaluation. This study coalesce morphological evaluation and sentiment analysis for the task of classification of farmer suicide cases reported in Punjab state of India. The pre-processing of Punjabi text involves morphological evaluation and normalization of Punjabi word tokens followed by the training of proposed model using deep learning classification on Punjabi language text extracted from online Punjabi news reports. The class-wise accuracies of sentiment prediction for four negatively oriented classes of farmer suicide cases are 93.85%, 88.53%, 83.3%, and 95.45% respectively. The overall accuracy of sentiment classification obtained using proposed framework on 275 Punjabi text documents is found to be 90.29%.

Keywords: deep neural network, farmer suicides, morphological processing, punjabi text, sentiment analysis

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Authors: V. Saccà, A. Sarica, F. Novellino, S. Barone, T. Tallarico, E. Filippelli, A. Granata, P. Valentino, A. Quattrone

Abstract:

The work aim was to evaluate how well Random Forest (RF) and Support Vector Machine (SVM) algorithms could support the early diagnosis of Multiple Sclerosis (MS) from resting-state functional connectivity data. In particular, we wanted to explore the ability in distinguishing between controls and patients of mean signals extracted from ICA components corresponding to 15 well-known networks. Eighteen patients with early-MS (mean-age 37.42±8.11, 9 females) were recruited according to McDonald and Polman, and matched for demographic variables with 19 healthy controls (mean-age 37.55±14.76, 10 females). MRI was acquired by a 3T scanner with 8-channel head coil: (a)whole-brain T1-weighted; (b)conventional T2-weighted; (c)resting-state functional MRI (rsFMRI), 200 volumes. Estimated total lesion load (ml) and number of lesions were calculated using LST-toolbox from the corrected T1 and FLAIR. All rsFMRIs were pre-processed using tools from the FMRIB's Software Library as follows: (1) discarding of the first 5 volumes to remove T1 equilibrium effects, (2) skull-stripping of images, (3) motion and slice-time correction, (4) denoising with high-pass temporal filter (128s), (5) spatial smoothing with a Gaussian kernel of FWHM 8mm. No statistical significant differences (t-test, p < 0.05) were found between the two groups in the mean Euclidian distance and the mean Euler angle. WM and CSF signal together with 6 motion parameters were regressed out from the time series. We applied an independent component analysis (ICA) with the GIFT-toolbox using the Infomax approach with number of components=21. Fifteen mean components were visually identified by two experts. The resulting z-score maps were thresholded and binarized to extract the mean signal of the 15 networks for each subject. Statistical and machine learning analysis were then conducted on this dataset composed of 37 rows (subjects) and 15 features (mean signal in the network) with R language. The dataset was randomly splitted into training (75%) and test sets and two different classifiers were trained: RF and RBF-SVM. We used the intrinsic feature selection of RF, based on the Gini index, and recursive feature elimination (rfe) for the SVM, to obtain a rank of the most predictive variables. Thus, we built two new classifiers only on the most important features and we evaluated the accuracies (with and without feature selection) on test-set. The classifiers, trained on all the features, showed very poor accuracies on training (RF:58.62%, SVM:65.52%) and test sets (RF:62.5%, SVM:50%). Interestingly, when feature selection by RF and rfe-SVM were performed, the most important variable was the sensori-motor network I in both cases. Indeed, with only this network, RF and SVM classifiers reached an accuracy of 87.5% on test-set. More interestingly, the only misclassified patient resulted to have the lowest value of lesion volume. We showed that, with two different classification algorithms and feature selection approaches, the best discriminant network between controls and early MS, was the sensori-motor I. Similar importance values were obtained for the sensori-motor II, cerebellum and working memory networks. These findings, in according to the early manifestation of motor/sensorial deficits in MS, could represent an encouraging step toward the translation to the clinical diagnosis and prognosis.

Keywords: feature selection, machine learning, multiple sclerosis, random forest, support vector machine

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