Search results for: adaptive thermal comfort model

Authors: Diego Cruz, Helbert Arevalo, Diana Vernot

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In 2013, the Food and Agriculture Organization of the United Nations (FAO) said that insect production for food and feed could become an economic opportunity for rural women in developing countries. However, since then, just a few initiatives worldwide had tried to implement this kind of project in zones of tropical countries without previous experience in cricket production and insect human consumption, such as Colombia. In this project, ArthroFood company and the University of La Sabana join efforts to make a holistic multi-perspective analysis from biological, economic, culinary, and social sides of the Gryllodes sigillatus production by rural women of the municipality of La Mesa, Cundinamarca, Colombia. From a biological and economic perspective, G. sigillatus production in a 60m2 greenhouse was evaluated considering the effect of rearing density and substrates on final weight and length, developing time, survival rate, and proximate composition. Additionally, the production cost and labor hours were recorded for five months. On the other hand, from a socio- economic side, the intention of the rural women to implement cricket farms or micro-entrepreneurship around insect production was evaluated after developing ethnographies and empowerment, entrepreneurship, and cricket production workshops. Finally, the results of the elaboration of culinary recipes with cricket powder incorporating cultural aspects of the context of La Mesa, Cundinamarca, will be presented. This project represents Colombia's first attempt to create a social business model of cricket production involving rural women, academies, the private sector, and local authorities.

Keywords: cricket production, developing country, edible insects, entrepreneurship, insect culinary recipes

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Authors: A. N. Ghafar, O. A. Chaudhari, W. Oettel, P. Fontana

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This study is a part of the EU project GEOCOND-Advanced materials and processes to improve performance and cost-efficiency of shallow geothermal systems and underground thermal storage. In heat exchange boreholes, to improve the heat transfer between the pipes and the surrounding ground, the space between the pipes and the borehole wall is normally filled with geothermal grout. Traditionally, bentonite has been a crucial component in most commercially available geothermal grouts to assure the required stability and impermeability. The investigations conducted in the early stage of this project during the benchmarking tests on some commercial grouts showed considerable sensitivity of the rheological properties of the tested grouts to the mixing parameters, i.e., mixing time and velocity. Further studies on this matter showed that bentonite, which has been one of the important constituents in most grout mixes, was probably responsible for such behavior. Apparently, proper amount of shear should be applied during the mixing process to sufficiently activate the bentonite. The higher the amount of applied shear the more the activation of bentonite, resulting in change in the grout rheology. This explains why, occasionally in the field applications, the flow properties of the commercially available geothermal grouts using different mixing conditions (mixer type, mixing time, mixing velocity) are completely different than expected. A series of tests were conducted on the grout mixes, with and without bentonite, using different mixing protocols. The aim was to eliminate/reduce the sensitivity of the rheological properties of the geothermal grouts to the mixing parameters by replacing bentonite with polymeric (non-clay) stabilizers. The results showed that by replacing bentonite with a proper polymeric stabilizer, the sensitivity of the grout mix on mixing time and velocity was to a great extent diminished. This can be considered as an alternative for the developers/producers of geothermal grouts to provide enhanced materials with less uncertainty in obtained results in the field applications.

Keywords: flow properties, geothermal grout, mixing time, mixing velocity, rheological properties

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Authors: Deyadeen Ali Alshibani

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In the literature, the multi-armed bandit problem as a statistical decision model of an agent trying to optimize his decisions while improving his information at the same time. There are several different algorithms models and their applications on this problem. In this paper, we evaluate the Regret-regression through comparing with Q-learning method. A simulation on determination of optimal treatment regime is presented in detail.

Keywords: optimal, bandit problem, optimization, dynamic programming

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Authors: Sang Ho Lee, Tae Heon Moon, Youn Taik Leem, Kwang Woo Nam

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Knowledge and IT inputs to other industrial production have become more important as a key factor for the competitiveness of national and regional economies, such as knowledge economies in smart cities. Knowledge and IT industries lead the industrial innovation and technical (r)evolution through low cost, high efficiency in production, and by creating a new value chain and new production path chains, which is referred as knowledge and IT dynamics. This study aims to investigate the knowledge and IT dynamics in Korea, which are analyzed through the input-output model and structural path analysis. Twenty-eight industries were reclassified into seven categories; Agriculture and Mining, IT manufacture, Non-IT manufacture, Construction, IT-service, Knowledge service, Non-knowledge service to take close look at the knowledge and IT dynamics. Knowledge and IT dynamics were analyzed through the change of input output coefficient and multiplier indices in terms of technical innovation, as well as the changes of the structural paths of the knowledge and IT to other industries in terms of new production value creation from 1985 and 2010. The structural paths of knowledge and IT explain not only that IT foster the generation, circulation and use of knowledge through IT industries and IT-based service, but also that knowledge encourages IT use through creating, sharing and managing knowledge. As a result, this paper found the empirical investigation on the knowledge and IT dynamics of the Korean economy. Knowledge and IT has played an important role regarding the inter-industrial transactional input for production, as well as new industrial creation. The birth of the input-output production path has mostly originated from the knowledge and IT industries, while the death of the input-output production path took place in the traditional industries from 1985 and 2010. The Korean economy has been in transition to a knowledge economy in the Smart City.

Keywords: knowledge and IT industries, input-output model, structural path analysis, dynamics of knowledge and it, knowledge economy, knowledge city and smart city

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Authors: Kai-Wei Ji, Dung-Ying Lin

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This study investigates the impact of transportation on housing prices in regions surrounding Taiwan's science parks. As these parks evolve into crucial economic and population growth centers, they attract an increasing number of residents and workers, significantly influencing local housing markets. This demographic shift raises important questions about the role of transportation in shaping real estate values. Our research examines four major science parks in Taiwan, providing a comparative analysis of how transportation conditions and population dynamics interact to affect housing price premiums. We employ an origin-destination (OD) matrix derived from pervasive traffic data to model travel patterns and their effects on real estate values. The methodology utilizes a bi-level framework: a genetic algorithm optimizes OD demand estimation at the upper level, while a user equilibrium (UE) model simulates traffic flow at the lower level. This approach enables a nuanced exploration of how population growth impacts transportation conditions and housing price premiums. By analyzing the interplay between travel costs based on OD demand estimation and housing prices, we offer valuable insights for urban planners and policymakers. These findings are crucial for informed decision-making in rapidly developing areas, where understanding the relationship between mobility and real estate values is essential for sustainable urban development.

Keywords: demand estimation, genetic algorithm, housing price, transportation

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Authors: Jane A. Luke

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Persistent pressure passed on to manufacturers from escalating consumer expectations and the ever growing global competitiveness have produced a rapidly increasing interest in the development of various manufacturing strategy models. Academic and industrial circles are taking keen interest in the field of manufacturing strategy. Many manufacturing strategies are currently centered on the traditional concepts of focused manufacturing capabilities such as quality, cost, dependability and innovation. Process capability indices was conducted assuming that the process under study is in statistical control and independent observations are generated over time. However, in practice, it is very common to come across processes which, due to their inherent natures, generate autocorrelated observations. The degree of autocorrelation affects the behavior of patterns on control charts. Even, small levels of autocorrelation between successive observations can have considerable effects on the statistical properties of conventional control charts. When observations are autocorrelated the classical control charts exhibit nonrandom patterns and lack of control. Many authors have considered the effect of autocorrelation on the performance of statistical process control charts. In this paper, the effect of autocorrelation on confidence intervals for different PCIs was included. Stationary Gaussian processes is explained. Effect of autocorrelation on PCIs is described in detail. Confidence intervals for Cp and Cpk are constructed for PCIs when data are both independent and autocorrelated. Confidence intervals for Cp and Cpk are computed. Approximate lower confidence limits for various Cpk are computed assuming AR(1) model for the data. Simulation studies and industrial examples are considered to demonstrate the results.

Keywords: autocorrelation, AR(1) model, Bissell’s approximation, confidence intervals, statistical process control, specification limits, stationary Gaussian processes

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Authors: Sejin Jung, Dongho Kang, Byungsik Kim

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Assessing the impact of climate change requires the use of a multi-model ensemble (MME) to quantify uncertainties between scenarios and produce downscaled outlines for simulation of climate under the influence of different factors, including topography. This study decreases climate change scenarios from the 13 global climate models (GCMs) to assess the impacts of future climate change. Unlike South Korea, North Korea lacks in studies using climate change scenarios of the CoupledModelIntercomparisonProject (CMIP5), and only recently did the country start the projection of extreme precipitation episodes. One of the main purposes of this study is to predict changes in the average climatic conditions of North Korea in the future. The result of comparing downscaled climate change scenarios with observation data for a reference period indicates high applicability of the Multi-Model Ensemble (MME). Furthermore, the study classifies climatic zones by applying the Köppen-Geiger climate classification system to the MME, which is validated for future precipitation and temperature. The result suggests that the continental climate (D) that covers the inland area for the reference climate is expected to shift into the temperate climate (C). The coefficient of variation (CVs) in the temperature ensemble is particularly low for the southern coast of the Korean peninsula, and accordingly, a high possibility of the shifting climatic zone of the coast is predicted. This research was supported by a grant (MOIS-DP-2015-05) of Disaster Prediction and Mitigation Technology Development Program funded by Ministry of Interior and Safety (MOIS, Korea).

Keywords: MME, North Korea, Koppen–Geiger, climatic zones, coefficient of variation, CV

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Authors: Rashida Rahmat Zohra, Afsheen Aman, Shah Ali Ul Qader

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Commercially important biopolymer, dextran, is enzymatically degraded into lower molecular weight fractions of vast industrial potential. Various organisms are associated with dextranase production, among which fungal, yeast and bacterial origins are used for commercial production. Dextranases are used to remove contaminating dextran in sugar processing industry and also used in oral care products for efficient removal of dental plaque. Among the hydrolytic products of dextran, isomaltooligosaccharides have prebiotic effect in humans and reduces the cariogenic effect of sucrose in oral cavity. Dextran derivatives produced by hydrolysis of high molecular polymer are also conjugated with other chemical and metallic compounds for usage in pharmaceutical, fine chemical industry, cosmetics, and food industry. Owing to the vast application of dextran and dextranases, current study focused on purification and analysis of kinetic parameters of dextranase from a newly isolated strain of Bacillus licheniformis KIBGE-IB25. Dextranase was purified up to 35.75 folds with specific activity of 1405 U/mg and molecular weight of 158 kDa. Analysis of kinetic parameters revealed that dextranase performs optimum cleavage of low molecular weight dextran (5000 Da, 0.5%) at 35ºC in 15 min at pH 4.5 with a Km and Vmax of 0.3738 mg/ml and 182.0 µmol/min, respectively. Thermal stability profiling of dextranase showed that it retained 80% activity up to 6 hours at 30-35ºC and remains 90% active at pH 4.5. In short, the dextranase reported here performs rapid cleavage of substrate at mild operational conditions which makes it an ideal candidate for dextran removal in sugar processing industry and for commercial production of low molecular weight oligosaccharides.

Keywords: Bacillus licheniformis, dextranase, gel permeation chromatograpy, enzyme purification, enzyme kinetics

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Authors: Sun-Mi Park, Ji-Hyun Jung, Min-Jung Kang

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Software (SW) education is scheduled to be included in the National curriculum in South Korea by 2018. However, Korean national kindergarten curriculum has been excepted from the revision of the entire Korean national school curriculum including software education. Even though the SW education has not been considered a part of current national kindergarten curriculum, there is a growing interest of adopting software education into the ECE practice. Teachers might be a key element in introducing and implementing new educational change such as SW education. In preparation for the adoption of SW education in ECE, it might be necessary to figure out ECE teachers’ perception and attitudes toward early childhood software education. For this study, 219 ECE teachers’ concern level in SW education was surveyed by using the Stages of Concern Questionnaire (SoCQ). As a result, the teachers' concern level in SW education is the highest at stage 0-Unconcerned and is high level in stage 1-informational, stage 2-personal, and stage 3-management concern. Thus, a non-user pattern was mostly indicated. However, compared to a typical non-user pattern, the personal and informative concern level is slightly high. The 'tailing up' phenomenon toward stage 6-refocusing was shown. Therefore, the pattern aspect close to critical non-user ever appeared to some extent. In addition, a significant difference in concern level was shown at all stages depending on the awareness of necessity. Teachers with SW training experience showed higher intensity only at stage 0. There was statistically significant difference in stage 0 and 6 depending on the future implementation decision. These results will be utilized as a resource in building ECE teachers’ support system according to his or her concern level of SW education.

Keywords: concerns-based adoption model (CBAM), early childhood education teachers, software education, Stages of Concern (SoC)

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Authors: Shaibu Baanni Azumah, Ignatius Tindjina, Stella Obanyi, Tara N. Wood

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This study examined the effect of Urea Deep Placement (UDP) technology on the output of irrigated rice farmers in the northern region of Ghana. Multi-stage sampling technique was used to select 142 rice farmers from the Golinga and Bontanga irrigation schemes, around Tamale. A treatment effect model was estimated at two stages; firstly, to determine the factors that influenced farmers’ decision to adopt the UDP technology and secondly, to determine the effect of the adoption of the UDP technology on the output of rice farmers. The significant variables that influenced rice farmers’ adoption of the UPD technology were sex of the farmer, land ownership, off-farm activity, extension service, farmer group participation and training. The results also revealed that farm size and the adoption of UDP technology significantly influenced the output of rice farmers in the northern region of Ghana. In addition to the potential of the technology to improve yields, it also presents an employment opportunity for women and youth, who are engaged in the deep placement of Urea Super Granules (USG), as well as in the transplantation of rice. It is recommended that the government of Ghana work closely with the IFDC to embed the UDP technology in the national agricultural programmes and policies. The study also recommends an effective collaboration between the government, through the Ministry of Food and Agriculture (MoFA) and the International Fertilizer Development Center (IFDC) to train agricultural extension agents on UDP technology in the rice producing areas of the country.

Keywords: Northern Ghana, output , irrigation rice farmers, treatment effect model, urea deep placement

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Authors: Yohannes Bisa Biramo

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This study examined the meditational role of surface acting and deep acting on the relationship between calling orientation and work engagement of teachers in secondary schools of Wolaita Zone, Wolaita, Ethiopia. A predictive non-experimental correlational design was performed among 300 secondary school teachers. Stratified random sampling followed by a systematic random sampling technique was used as the basis for selecting samples from the target population. To analyze the data, Structural Equation Modeling (SEM) was used to test the association between the independent variables and the dependent variables. Furthermore, the goodness of fit of the study variables was tested using SEM to see and explain the path influence of the independent variable on the dependent variable. Confirmatory factor analysis (CFA) was conducted to test the validity of the scales in the study and to assess the measurement model fit indices. The analysis result revealed that calling was significantly and positively correlated with surface acting, deep acting and work engagement. Similarly, surface acting was significantly and positively correlated with deep acting and work engagement. And also, deep acting was significantly and positively correlated with work engagement. With respect to mediation analysis, the result revealed that surface acting mediated the relationship between calling and work engagement and also deep acting mediated the relationship between calling and work engagement. Besides, by using the model of the present study, the school leaders and practitioners can identify a core area to be considered in recruiting and letting teachers teach, in giving induction training for newly employed teachers and in performance appraisal.

Keywords: calling, surface acting, deep acting, work engagement, mediation, teachers

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Authors: Edda E. Falcone, Cinzia Federico, Sergio Bellomo, Lorenzo Brusca, Manfredi Longo, Walter D’Alessandro

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Although trace metals are an essential element for living beings, they can become toxic at high concentrations. Their potential toxicity is related not only to the total content in the environment but mostly upon their bioavailability. Volcanoes are important natural metal emitters and they can deeply affect the quality of air, water and soils, as well as the human health. Trace metals tend to accumulate in the tissues of living organisms, depending on the metal contents in food, air and water and on the exposure time. Birds are considered as bioindicators of interest, because their feathers directly reflects the metals uptake from the blood. Birds are exposed to the atmospheric pollution through the contact with rainfall, dust, and aerosol, and they accumulate metals over the whole life cycle. We report on the first data combining the rainfall metal content in three different areas of Mt Etna, variably fumigated by the volcanic plume, and the metal contents in the feathers of pigeons, collected in the same areas. Rainfall samples were collected from three rain gauges placed at different elevation on the Eastern flank of the volcano, the most exposed to airborne plume, filtered, treated with HNO₃ Suprapur-grade and analyzed for Fe, Cr, Co, Ni, Se, Zn, Cu, Sr, Ba, Cd and As by ICP-MS technique, and major ions by ion chromatography. Feathers were collected from single individuals, in the same areas where the rain gauges were installed. Additionally, some samples were collected in an urban area, poorly interested by the volcanic plume. The samples were rinsed in MilliQ water and acetone, dried at 50°C until constant weight and digested in a mixture of 2:1 HNO₃ (65%) - H₂O₂ (30%) Suprapur-grade for 25-50 mg of sample, in a bath at near-to-boiling temperature. The solutions were diluted up to 20 ml prior to be analyzed by ICP-MS. The rainfall samples most contaminated by the plume were collected at close distance from the summit craters (less than 6 km), and show lower pH values and higher concentrations for all analyzed metals relative to those from the sites at lower elevation. Analyzed samples are enriched in both metals directly emitted by the volcanic plume and transported by acidic gases (SO₂, HCl, HF), and metals leached from the airborne volcanic ash. Feathers show different patterns in the different sites related to the exposure to natural or anthropogenic pollutants. They show abundance ratios similar to rainfall for lithophile elements (Ba, Sr), whereas are enriched in Zn and Se, known for their antioxidant properties, probably as adaptive response to oxidative stress induced by toxic metal exposure. The pigeons revealed a clear heterogeneity of metal uptake in the different parts of the volcano, as an effect of volcanic plume impact. Additionally, some physiological processes can modify the fate of some metals after uptake and this offer some insights for translational studies.

Keywords: bioindicators, environmental pollution, feathers, trace metals, volcanic plume

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Authors: Saman Namvarrechi, Armin A. Dormeny, Javad Dargahi, Mojtaba Kahrizi

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Since last two decades, minimally invasive surgery (MIS) has grown significantly due to its advantages compared to the traditional open surgery like less physical pain, faster recovery time and better healing condition around incision regions; however, one of the important challenges in MIS is getting an effective sensing feedback within the patient’s body during operations. Therefore, surgeons need efficient tactile sensing like determining the hardness of contact tissue for investigating the patient’s health condition. In such a case, MIS tactile sensors are preferred to be able to provide force/pressure sensing, force position, lump detection, and softness sensing. Among different pressure sensor technologies, the piezoelectric operating principle is the fittest for MIS’s instruments, such as catheters. Using PVDF with its copolymer, TrFE, as a piezoelectric material, is a common method of design and fabrication of a tactile sensor due to its ease of implantation and biocompatibility. In this research, PVDF-TrFE polymer is deposited via spin-coating method and treated with various post-deposition processes to investigate its piezoelectricity and amount of electroactive β phase. These processes include different post thermal annealing, the effect of spin-coating speed, different layer of deposition, and the presence of additional hydrate salt. According to FTIR spectroscopy and SEM images, the amount of the β phase and porosity of each sample is determined. In addition, the optimum experimental study is established by considering every aspect of the fabrication process. This study clearly shows the effective way of deposition and fabrication of a tactile PVDF-TrFE based sensor and an enhancement methodology to have a higher β phase and piezoelectric constant in order to have a better sense of touch at the end effector of biomedical devices.

Keywords: β phase, minimally invasive surgery, piezoelectricity, PVDF-TrFE, tactile sensor

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Authors: Aayushi Lyngwa, Bimal Kishore Sahoo

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The study discusses the relationship between cognitive ability and the level of education attained by the tribal street entrepreneurs on their financial literacy. It is driven by the objective of examining the effect of cognitive ability on financial ability on the one hand and determining the effect of the same on financial literacy on the other. A field experiment was conducted on 203 tribal street vendors in the north-eastern Indian state of Mizoram. This experiment's calculations are conditioned by providing each question scores like math score (cognitive ability), financial score and debt score (financial ability). After that, categories for each of the variables, like math category (math score), financial category (financial score) and debt category (debt score), are generated to run the regression model. Since the dependent variable is ordinal, an ordered logit regression model was applied. The study shows that street vendors' cognitive and financial abilities are highly correlated. It, therefore, confirms that cognitive ability positively affects the financial literacy of street vendors through the increase in attainment of educational levels. It is also found that concerning the type of street vendors, regular street vendors are more likely to have better cognitive abilities than temporary street vendors. Additionally, street vendors with more cognitive and financial abilities gained better monthly profits and performed habits of bookkeeping. The study attempts to draw a particular focus on a set-up which is economically and socially marginalized in the Indian economy. Its finding contributes to understanding financial literacy in an understudied area and provides policy implications through inclusive financial systems solutions in an economy limited to tribal street vendors.

Keywords: financial literacy, education, street entrepreneurs, tribals, cognitive ability, financial ability, ordered logit regression.

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Authors: Eki Farlen, Akas

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Condition assessment of oil-paper-insulated power transformers, particularly of water content, is becoming increasingly important for aged transformers. As insulation ages, it can produce water, which reduces its dielectric strength, accelerates the cellulose ageing process, and causes gas bubbles to form at high temperatures. This paper mainly assesses the life condition of oil-paper insulation system of Inter Bus Transformer (IBT) 30 MVA, 150/30 kV in PT PLN-Substation Jelok that has been operating for 41 years, since 1974. Valuable information about the condition of high voltage insulation may be obtained by measuring its dielectric response. This paper describes in detail the interpretation of Dielectric Response Analysis (DIRANA) measurements and the test result compared to other insulation tests to get deep information for diagnostic, such as Tan delta test, oil characteristic test and Dissolve Gas Analysis (DGA) test. This paper mainly discusses the parameter relationship between moisture content, water content, acidity, oil conductivity and dissipation factor. The result and analysis show that IBT 30 MVA Jelok phase U and W had just been ageing due to high acidity level (>0.2 mgKOH/g) which cause high moisture in cellulose/paper (%) are in wet category about 4.7% and 5% and water content in oil (ppm) about 3.13 ppm and 3.33 ppm at temperature 20°C. High acidity level can make oxidation process and produce water in paper and particle which can decrease the value of Interfacial Tension (IFT) below 22 mN/m (poor category) for both phase U and W. Even if paper insulation of transformer are in wet condition, dissipation factor and capacitance at the same frequency (50 Hz) from both measurement DIRANA test and Tangent delta test give the same result (almost), the results are 0.69% and 0.71% (<1%), it may be acceptable and should not be investigated. The DGA results show that TDCG are in level one (1) condition and there are no found a Key Gases, it means that transformers had no failure during operation like arching, partial discharge and thermal in oil or cellulose.

Keywords: diagnostic, inter-bus transformer, oil-paper insulation, moisture, dissipation factor

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Authors: Lin-Han Chiang Hsieh, Hsiao-Yi Lin

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This study aims to determine the impact of the disclosure of flood potential map on housing prices. The disclosure is supposed to mitigate the market failure by reducing information asymmetry. On the other hand, opponents argue that the official disclosure of simulated results will only create unnecessary disturbances on the housing market. This study identifies the impact of the disclosure of the flood potential map by comparing the hedonic price of flood potential before and after the disclosure. The flood potential map used in this study is published by Taipei municipal government in 2015, which is a result of a comprehensive simulation based on geographical, hydrological, and meteorological factors. The residential property sales data of 2013 to 2016 is used in this study, which is collected from the actual sales price registration system by the Department of Land Administration (DLA). The result shows that the impact of flood potential on residential real estate market is statistically significant both before and after the disclosure. But the trend is clearer after the disclosure, suggesting that the disclosure does have an impact on the market. Also, the result shows that the impact of flood potential differs by the severity and frequency of precipitation. The negative impact for a relatively mild, high frequency flood potential is stronger than that for a heavy, low possibility flood potential. The result indicates that home buyers are of more concern to the frequency, than the intensity of flood. Another contribution of this study is in the methodological perspective. The classic hedonic price analysis with OLS regression suffers from two spatial problems: the endogeneity problem caused by omitted spatial-related variables, and the heterogeneity concern to the presumption that regression coefficients are spatially constant. These two problems are seldom considered in a single model. This study tries to deal with the endogeneity and heterogeneity problem together by combining the spatial fixed-effect model and geographically weighted regression (GWR). A series of literature indicates that the hedonic price of certain environmental assets varies spatially by applying GWR. Since the endogeneity problem is usually not considered in typical GWR models, it is arguable that the omitted spatial-related variables might bias the result of GWR models. By combing the spatial fixed-effect model and GWR, this study concludes that the effect of flood potential map is highly sensitive by location, even after controlling for the spatial autocorrelation at the same time. The main policy application of this result is that it is improper to determine the potential benefit of flood prevention policy by simply multiplying the hedonic price of flood risk by the number of houses. The effect of flood prevention might vary dramatically by location.

Keywords: flood potential, hedonic price analysis, endogeneity, heterogeneity, geographically-weighted regression

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Authors: Tahani Aljohani, Jialin Yu, Alexandra. I. Cristea

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The more an educational system knows about a learner, the more personalised interaction it can provide, which leads to better learning. However, asking a learner directly is potentially disruptive, and often ignored by learners. Especially in the booming realm of MOOC Massive Online Learning platforms, only a very low percentage of users disclose demographic information about themselves. Thus, in this paper, we aim to predict learners’ demographic characteristics, by proposing an approach using linguistically motivated Deep Learning Architectures for Learner Profiling, particularly targeting gender prediction on a FutureLearn MOOC platform. Additionally, we tackle here the difficult problem of predicting the gender of learners based on their comments only – which are often available across MOOCs. The most common current approaches to text classification use the Long Short-Term Memory (LSTM) model, considering sentences as sequences. However, human language also has structures. In this research, rather than considering sentences as plain sequences, we hypothesise that higher semantic - and syntactic level sentence processing based on linguistics will render a richer representation. We thus evaluate, the traditional LSTM versus other bleeding edge models, which take into account syntactic structure, such as tree-structured LSTM, Stack-augmented Parser-Interpreter Neural Network (SPINN) and the Structure-Aware Tag Augmented model (SATA). Additionally, we explore using different word-level encoding functions. We have implemented these methods on Our MOOC dataset, which is the most performant one comparing with a public dataset on sentiment analysis that is further used as a cross-examining for the models' results.

Keywords: deep learning, data mining, gender predication, MOOCs

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Authors: Harshit Mittal, Neeraj Garg

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Hand symbol recognition is a pivotal component in the domain of computer vision, with far-reaching applications spanning sign language interpretation, human-computer interaction, and accessibility. This research paper discusses the approach with the integration of the Canny Edge algorithm and convolutional neural network. The significance of this study lies in its potential to enhance communication and accessibility for individuals with hearing impairments or those engaged in gesture-based interactions with technology. In the experiment mentioned, the data is manually collected by the authors from the webcam using Python codes, to increase the dataset augmentation, is applied to original images, which makes the model more compatible and advanced. Further, the dataset of about 6000 coloured images distributed equally in 5 classes (i.e., 1, 2, 3, 4, 5) are pre-processed first to gray images and then by the Canny Edge algorithm with threshold 1 and 2 as 150 each. After successful data building, this data is trained on the Convolutional Neural Network model, giving accuracy: 0.97834, precision: 0.97841, recall: 0.9783, and F1 score: 0.97832. For user purposes, a block of codes is built in Python to enable a window for hand symbol recognition. This research, at its core, seeks to advance the field of computer vision by providing an advanced perspective on hand sign recognition. By leveraging the capabilities of the Canny Edge algorithm and convolutional neural network, this study contributes to the ongoing efforts to create more accurate, efficient, and accessible solutions for individuals with diverse communication needs.

Keywords: hand symbol recognition, computer vision, Canny edge algorithm, convolutional neural network

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Authors: Aaron Liggett

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This research focuses on the visionary proposal made by the Olmsted Brothers Landscape Architecture firm in the 1920s for a network of interconnected parkways in Los Angeles. Their envisioned parkways aimed to address environmental and cultural strains by providing green space for recreation, wildlife habitat, and stormwater management while serving as multimodal transportation routes. Although the parkways were never constructed, through an evidence-based approach, this research presents a framework for evaluating the potential functionality and success of the parkways by modeling and visualizing their quantitative and qualitative landscape performance and benefits. Historical documents and innovative digital modeling tools produce detailed analysis, modeling, and visualization of the parkway designs. A set of 1928 construction documents are used to analyze and interpret the design intent of the parkways. Grading plans are digitized in CAD and modeled in Sketchup to produce 3D visualizations of the parkway. Drainage plans are digitized to model stormwater performance. Planting plans are analyzed to model urban forestry and biodiversity. The EPA's Storm Water Management Model (SWMM) predicts runoff quantity and quality. The USDA Forests Service tools evaluate carbon sequestration and air quality. Spatial and overlay analysis techniques are employed to assess urban connectivity and the spatial impacts of the parkway designs. The study reveals how the integration of blue infrastructure, green infrastructure, and transportation infrastructure within the parkway design creates a multifunctional landscape capable of offering alternative spatial and temporal uses. The analysis demonstrates the potential for multiple functional, ecological, aesthetic, and social benefits to be derived from the proposed parkways. The analysis of the Olmsted Brothers' proposed Los Angeles parkways, which predated contemporary ecological design and resiliency practices, demonstrates the potential for providing multiple functional, ecological, aesthetic, and social benefits within urban designs. The findings highlight the importance of integrated blue, green, and transportation infrastructure in creating a multifunctional landscape that simultaneously serves multiple purposes. The research contributes new methods for modeling and visualizing landscape performance benefits, providing insights and techniques for informing future designs and sustainable development strategies.

Keywords: landscape architecture, ecological urban design, greenway, landscape performance

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Authors: Myung-Soo Lee, Sun-Jin Jo, Kyoung-Sae Na, Joo-Eon Park

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Early intervention after a disaster is important for recovery of disaster victims and each country has its own professional mental health service system such as Disaster Psychiatric Assistant Team in Japan and Crisis Counseling Program in the USA. The purpose of this study was to determine key prior components of the Korean Disaster Psychiatric Assistant Team (K-DPAT) for building up Korean disaster mental health service system. We conducted an Analytic Hierarchy Process(AHP) with disaster mental health experts using pairwise comparison questionnaire which compares the relative importance of the key components of Korean disaster mental health service system. Forty-one experts answered the first online survey, and among them, 36 responded to the second. Ten experts were participated in panel meeting and discussed the results of the survey and AHP process. Participants decided the relative importance of the Korean disaster mental health service system regarding initial professional intervention as follows. K-DPAT could be organized at a national level (43.0%) or regional level (40.0%). K-DPAT members should be managed (59.0%) and educated (52.1%) by national level than regional or local level. K-DPAT should be organized independent of the preexisting mental health system (70.1%). Funding for K-DPAT should be from the Ministry of Public Safety and the system could be managed by Ministry of Health (65.8%). Experts agreed K-DPAT leader is suitable for key decision maker for most types of disaster except infectious disease. We expect new model for disaster mental health services can improve insufficiency of the system such as fragmentation and decrease the unmet needs of early professional intervention for the disaster victims.

Keywords: analytic hierarchy process, decision making, disaster, DPAT, mental health services

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Authors: Linda D. F. Bambara, Marie Sawadogo

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Jatropha curcas (jatropha) is the plant that has been the most studied for biofuel production in West Africa. There exist however other plants such as Balanites aegyptiaca (balanites) that have been targeted as a potential feedstock for biofuel production. This biomass could be an alternative feedstock for the production of straight vegetable oil (SVO) at costs lower than jatropha-based SVO production costs. This study aims firstly to determine, through an MILP model, the optimal organization that minimizes the costs of the oilseeds supply of two biomass conversion units (BCU) exploiting respectively jatropha seeds and the balanitès seeds. Secondly, the study aims to carry out a comparative study of these costs obtained for each BCU. The model was then implemented on two theoretical cases studies built on the basis of the common practices in Burkina Faso and two scenarios were carried out for each case study. In Scenario 1, 3 pre-processing locations ("at the harvesting area", "at the gathering points", "at the BCU") are possible. In scenario 2, only one location ("at the BCU") is possible. For each biomass, the system studied is the upstream supply chain (harvesting, transport and pre-processing (drying, dehulling, depulping)), including cultivation (for jatropha). The model optimizes the area of land to be exploited based on the productivity of the studied plants and material losses that may occur during the harvesting and the supply of the BCU. It then defines the configuration of the logistics network allowing an optimal supply of the BCU taking into account the most common means of transport in West African rural areas. For the two scenarios, the results of the implementation showed that the total area exploited for balanites (1807 ha) is 4.7 times greater than the total area exploited for Jatropha (381 ha). In both case studies, the location of pre-processing “at the harvesting area” was always chosen for scenario1. As the balanites trees were not planted and because the first harvest of the jatropha seeds took place 4 years after planting, the cost price of the seeds at the BCU without the pre-processing costs was about 430 XOF/kg. This cost is 3 times higher than the balanites's one, which is 140 XOF/kg. After the first year of harvest, i.e. 5 years after planting, and assuming that the yield remains constant, the same cost price is about 200 XOF/kg for Jatropha. This cost is still 1.4 times greater than the balanites's one. The transport cost of the balanites seeds is about 120 XOF/kg. This cost is similar for the jatropha seeds. However, when the pre-processing is located at the BCU, i.e. for scenario2, the transport costs of the balanites seeds is 1200 XOF/kg. These costs are 6 times greater than the transport costs of jatropha which is 200 XOF/kg. These results show that the cost price of the balanites seeds at the BCU can be competitive compared to the jatropha's one if the pre-processing is located at the harvesting area.

Keywords: Balanites aegyptiaca, biomass conversion, Jatropha curcas, optimization, post-harvest operations

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Authors: Satyananda Behera, Ritwik Sarkar

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In iron and steel industries, MgO–C refractories are widely used in basic oxygen furnaces, electric arc furnaces and steel ladles due to their excellent corrosion resistance, thermal shock resistance, and other excellent hot properties. Conventionally magnesia carbon refractories contain about 8-20 wt% of carbon but the use of carbon is also associate with disadvantages like oxidation, low fracture strength, high heat loss and higher carbon pick up in steel. So, MgO-C refractory having low carbon content without compromising the beneficial properties is the challenge. Nano carbon, having finer particles, can mix and distribute within the entire matrix uniformly and can result in improved mechanical, thermo-mechanical, corrosion and other refractory properties. Previous experiences with the use of nano carbon in low carbon MgO-C refractory have indicated an optimum range of use of nano carbon around 1 wt%. This optimum nano carbon content was used in MgO-C compositions with flaky graphite followed by aluminum and silicon metal powder as an anti-oxidant. These low carbon MgO-C refractory compositions were prepared by conventional manufacturing techniques. At the same time 16 wt. % flaky graphite containing conventional MgO-C refractory was also prepared parallel under similar conditions. The developed products were characterized for various refractory related properties. Nano carbon containing compositions showed better mechanical, thermo-mechanical properties, and oxidation resistance compared to that of conventional composition. Improvement in the properties is associated with the formation of in-situ ceramic phase-like aluminum carbide, silicon carbide, and magnesium aluminum spinel. Higher surface area and higher reactivity of N220 nano carbon black resulted in greater formation in-situ ceramic phases, even at a much lower amount. Nano carbon containing compositions were found to have improved properties in MgO-C refractories compared to that of the conventional ones at much lower total carbon content.

Keywords: N220nano carbon black, refractory properties, conventionally manufacturing techniques, conventional magnesia carbon refractories

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Authors: Nathalie Baeza-Kallee, Raphaël Bergès, Victoria Hein, Stéphanie Cabaret, Jeremy Garcia, Abigaëlle Gros, Emeline Tabouret, Aurélie Tchoghandjian, Carole Colin, Dominique Figarella-Branger

Abstract:

Glioblastoma (GBM) contains cancer stem cells that are resistant to treatment. GBM cancer stem cell expresses glycolipids recognized by the A2B5 antibody. A2B5, induced by the enzyme ST8 alpha-N-acetyl-neuraminide alpha-2,8-sialyl transferase 3 (ST8Sia3), plays a crucial role in the proliferation, migration, clonogenicity, and tumorigenesis of GBM cancer stem cells. Our aim was to characterize the resulting effects of neuraminidase that remove A2B5 in order to target GBM cancer stem cells. To this end, we set up a GBM organotypic slice model; quantified A2B5 expression by flow cytometry in U87-MG, U87-ST8Sia3, and GBM cancer stem cell lines, treated or not by neuraminidase; performed RNAseq and DNA methylation profiling; and analyzed the ganglioside expression by liquid chromatography-mass spectrometry in these cell lines, treated or not with neuraminidase. Results demonstrated that neuraminidase decreased A2B5 expression, tumor size, and regrowth after surgical removal in the organotypic slice model but did not induce a distinct transcriptomic or epigenetic signature in GBM CSC lines. RNAseq analysis revealed that OLIG2, CHI3L1, TIMP3, TNFAIP2, and TNFAIP6 transcripts were significantly overexpressed in U87-ST8Sia3 compared to U87-MG. RT-qPCR confirmed these results and demonstrated that neuraminidase decreased gene expression in GBM cancer stem cell lines. Moreover, neuraminidase drastically reduced ganglioside expression in GBM cancer stem cell lines. Neuraminidase, by its pleiotropic action, is an attractive local treatment against GBM.

Keywords: cancer stem cell, ganglioside, glioblastoma, targeted treatment

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Authors: Pei-Ti Hsu, I-Ju Chen, Jeu-Jung Chen, Cheng-Fen Chang, Shiu-Yan Yang

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Taiwan now is an aging society Research on the elderly should not be confined to caring for seniors, but should also be focused on ways to improve health and the quality of life. Senior citizens who participate in volunteer services could become less lonely, have new growth opportunities, and regain a sense of accomplishment. Thus, the question of how to get the elderly to participate in volunteer service is worth exploring. Apply the Transtheoretical Model to understand stages of change in regular volunteer service and voluntary service behaviour among the seniors. 1525 adults over the age of 65 from the Renai district of Keelung City were interviewed. The research tool was a self-constructed questionnaire and individual interviews were conducted to collect data. Then the data was processed and analyzed using the IBM SPSS Statistics 20 (Windows version) statistical software program. In the past six months, research subjects averaged 9.92 days of volunteer services. A majority of these elderly individuals had no intention to change their regular volunteer services. We discovered that during the maintenance stage, the self-efficacy for volunteer services was higher than during all other stages, but self-perceived barriers were less during the preparation stage and action stage. Self-perceived benefits were found to have an important predictive power for those with regular volunteer service behaviors in the previous stage, and self-efficacy was found to have an important predictive power for those with regular volunteer service behaviors in later stages. The research results support the conclusion that community nursing staff should group elders based on their regular volunteer services change stages and design appropriate behavioral change strategies.

Keywords: seniors, stages of change in regular volunteer services, volunteer service behavior, self-efficacy, self-perceived benefits

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Authors: Modi M. Ahmed, Noor Al-Dousari, Ali M. Al-Dousari

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Cornulaca aucheri is an annual herb consider as disturbance indicator currently visible and widely distributed in disturbed lands in Liyah area. Such area is suffered from severe land degradation due to multiple interacting factors such as, overgrazing, gravel and sand quarrying, military activities and natural process. The restoration program is applied after refilled quarries sites and levelled the surface irregularities in order to rehabilitate the natural vegetation and wildlife to its original shape. During the past 10 years of rehabilitation, noticeable greenery healthy cover of Cornulaca sp. are shown specially around artificial lake and playas. The existence of such species in high density it means that restoration program has succeeded and transit from bare ground state to Cornulaca and annual forb state. This state is lower state of Range State Transition Succession model, but it is better than bare soil. Cornulaca spp is native desert plant grows in arid conditions on sandy, stony ground, near oasis, on sand dunes and in sandy depressions. The sheep and goats are repulsive of it. Despite its spiny leaves, it provides good grazing for camels and is said to increase the milk supply produced by lactating females. It is about 80 cm tall and has stems that branched from the base with new faster greenery growth in the summer. It shows good environmental potential to be managed as natural types used for the restoration of degraded lands in desert areas.

Keywords: land degradation, range state transition succession model, rehabilitation, restoration program

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Authors: Shanawaz Patil, Mohamed Haneef, K. S. Narayanaswamy

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In the recent years, aluminum metal matrix composites were most widely used, which are finding wide applications in various field such as automobile, aerospace defense etc., due to their outstanding mechanical properties like low density, light weight, exceptional high levels of strength, stiffness, wear resistance, high temperature resistance, low coefficient of thermal expansion and good formability. In the present work, an effort is made to study the effect of heat treatment on mechanical properties of aluminum 7075 alloy reinforced with constant weight percentage of naturally occurring mineral beryl and varying weight percentage of graphene. The hybrid composites are developed with 0.5 wt. %, 1wt.%, 1.5 wt.% and 2 wt.% of graphene and 6 wt.% of beryl  by stir casting liquid metallurgy route. The cast specimens of unreinforced aluminum alloy and hybrid composite samples were prepared for heat treatment process and subjected to solutionizing treatment (T6) at a temperature of 490±5 ^oC for 8 hours in a muffle furnace followed by quenching in boiling water. The microstructure analysis of as cast and heat treated hybrid composite specimens are examined by scanning electron microscope (SEM). The tensile test and hardness test of unreinforced aluminum alloy and hybrid composites are examined. The wear behavior is examined by pin-on disc apparatus. The results of as cast specimens and heat treated specimens were compared. The heat treated Al7075-Beryl-Graphene hybrid composite had better properties and significantly improved the ultimate tensile strength, hardness and reduced wear loss when compared to aluminum alloy and  as cast hybrid composites.

Keywords: beryl, graphene, heat treatment, mechanical properties

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Authors: Waheed O. Majekodunmi

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Climate change is a real global phenomenon and an unquestionable threat to our quest for a healthy and livable planet. It is now regarded as potentially the most monumental environmental challenge people and the planet will be confronted with over the next centuries. Expectedly, climate change mitigation was one of the central themes of COP 28. Despite contributing the least to climate change, Africa is and remains the hardest hit by the negative consequences of climate change including poor growth performance. Currently, it is being hypothesized that the high level of vulnerability and exposure to climate-related disasters, low adaptive capacity against global warming and high mitigation costs of climate change across the continent could be linked to the recent abysmal economic performance of African countries, especially in oil-producing countries where greenhouse gas emissions, is potentially more prevalent. This paper examines the impact of climate change on the economic performance of selected oil-producing countries in Africa using evidence from Nigeria, Algeria and Angola. The objective of the study is to determine whether or not climate change influences the economic performance of oil-producing countries in Africa by examining the nexus between economic growth and climate-related variables. The study seeks to investigate the effect of climate change on the pace of economic growth in African oil-producing countries. To achieve the research objectives, this study utilizes a quantitative approach by using historical and current secondary data sets to determine the relationship between climate-related variables and economic growth variables in the selected countries. The study employed numbers, percentages, tables and trend graphs to explain the trends or common patterns between climate change, economic growth and determinants of economic growth: governance effectiveness, infrastructure, macroeconomic stability and regulatory efficiency. Results from the empirical analysis of data show that the trends of economic growth and climate-related variables in the selected oil-producing countries are in the opposite directions as the increasing share of renewable energy sources in total energy consumption and the reduction in greenhouse gas emissions per capita in the oil-producing countries did not translate to higher economic growth. Further findings show that annual surface temperatures in the selected countries do not share similar trends with the food imports ratio and GDP per capita annual growth rate suggesting that climate change does not impact significantly agricultural productivity and economic growth in oil-producing countries in Africa. Annual surface temperature was also found to not share a similar pattern with governance effectiveness, macroeconomic stability and regulatory efficiency reinforcing the claim that some economic growth variables are independent of climate change. The policy implication of this research is that oil-producing African countries need to focus more on improving the macroeconomic environment and streamlining governance and institutional processes to boost their economic performance before considering the adoption of climate change adaptation and mitigation strategies.

Keywords: climate change, climate vulnerability, economic growth, greenhouse gas emissions per capita, oil-producing countries, share of renewable energy in total energy consumption

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Authors: Srinivas Peri, Siva Abhishek Sirivella, Tejaswini Kallakuri, Uzair Ahmad

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Effective traffic management and infrastructure planning are crucial for the development of smart cities and intelligent transportation systems. This study addresses the challenge of data scarcity by generating realistic synthetic traffic data using the PeMS-Bay dataset, improving the accuracy and reliability of predictive modeling. Advanced synthetic data generation techniques, including TimeGAN, GaussianCopula, and PAR Synthesizer, are employed to produce synthetic data that replicates the statistical and structural characteristics of real-world traffic. Future integration of Spatial-Temporal Generative Adversarial Networks (ST-GAN) is planned to capture both spatial and temporal correlations, further improving data quality and realism. The performance of each synthetic data generation model is evaluated against real-world data to identify the best models for accurately replicating traffic patterns. Long Short-Term Memory (LSTM) networks are utilized to model and predict complex temporal dependencies within traffic patterns. This comprehensive approach aims to pinpoint areas with low vehicle counts, uncover underlying traffic issues, and inform targeted infrastructure interventions. By combining GAN-based synthetic data generation with LSTM-based traffic modeling, this study supports data-driven decision-making that enhances urban mobility, safety, and the overall efficiency of city planning initiatives.

Keywords: GAN, long short-term memory, synthetic data generation, traffic management

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Authors: Yonas Shuke Kitawa

Abstract:

Background: Although malaria incidence has substantially fallen sharply over the past few years, the rate of decline varies by district, time, and malaria type. Despite this turn-down, malaria remains a major public health threat in various districts of Ethiopia. Consequently, the present study is aimed at developing a predictive model that helps to identify the spatio-temporal variation in malaria risk by multiple plasmodium species. Methods: We propose a multivariate spatio-temporal Bayesian model to obtain a more coherent picture of the temporally varying spatial variation in disease risk. The spatial autocorrelation in such a data set is typically modeled by a set of random effects that assign a conditional autoregressive prior distribution. However, the autocorrelation considered in such cases depends on a binary neighborhood matrix specified through the border-sharing rule. Over here, we propose a graph-based optimization algorithm for estimating the neighborhood matrix that merely represents the spatial correlation by exploring the areal units as the vertices of a graph and the neighbor relations as the series of edges. Furthermore, we used aggregated malaria count in southern Ethiopia from August 2013 to May 2019. Results: We recognized that precipitation, temperature, and humidity are positively associated with the malaria threat in the area. On the other hand, enhanced vegetation index, nighttime light (NTL), and distance from coastal areas are negatively associated. Moreover, nonlinear relationships were observed between malaria incidence and precipitation, temperature, and NTL. Additionally, lagged effects of temperature and humidity have a significant effect on malaria risk by either species. More elevated risk of P. falciparum was observed following the rainy season, and unstable transmission of P. vivax was observed in the area. Finally, P. vivax risks are less sensitive to environmental factors than those of P. falciparum. Conclusion: The improved inference was gained by employing the proposed approach in comparison to the commonly used border-sharing rule. Additionally, different covariates are identified, including delayed effects, and elevated risks of either of the cases were observed in districts found in the central and western regions. As malaria transmission operates in a spatially continuous manner, a spatially continuous model should be employed when it is computationally feasible.

Keywords: disease mapping, MSTCAR, graph-based optimization algorithm, P. falciparum, P. vivax, waiting matrix

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Authors: Arfanara Najnin, Michael W. Roach, Jr., Dr. Jianhong Cecilia Xia

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The SkyCar Rapid Transit System (SRT) is an innovative intelligent transport system for the sustainable urban transport system. This system will increase the urban area network connectivity and decrease urban area traffic congestion. The SRT system is designed as a suspended Personal Rapid Transit (PRT) system that travels under a guideway 5m above the ground. A driver-less passenger is via pod-cars that hang from slender beams supported by columns that replace existing lamp posts. The beams are setup in a series of interconnecting loops providing non-stop travel from beginning to end to assure journey time. The SRT forward movement is effected by magnetic motors built into the guideway. Passenger stops are at either at line level 5m above the ground or ground level via a spur guideway that curves off the main thoroughfare. The main objective of this paper is to propose an integrated Automated Transit Network (ATN) technology for the future intelligent transport system in the urban built environment. To fulfil the objective a 4D simulated model in the urban built environment has been proposed by using the concept of SRT-ATN system. The methodology for the design, construction and testing parameters of a Technology Demonstrator (TD) for proof of concept and a Simulator (S) has been demonstrated. The completed TD and S will provide an excellent proving ground for the next development stage, the SRT Prototype (PT) and Pilot System (PS). This paper covered by a 4D simulated model in the virtual built environment is to effectively show how the SRT-ATN system works. OpenSim software has been used to develop the model in a virtual environment, and the scenario has been simulated to understand and visualize the proposed SkyCar Rapid Transit Network model. The SkyCar system will be fabricated in a modular form which is easily transported. The system would be installed in increasingly congested city centers throughout the world, as well as in airports, tourist resorts, race tracks and other special purpose for the urban community. This paper shares the lessons learnt from the proposed innovation and provides recommendations on how to improve the future transport system in urban built environment. Safety and security of passengers are prime factors to be considered for this transit system. Design requirements to meet the safety needs to be part of the research and development phase of the project. Operational safety aspects would also be developed during this period. The vehicles, the track and beam systems and stations are the main components that need to be examined in detail for safety and security of patrons. Measures will also be required to protect columns adjoining intersections from errant vehicles in vehicular traffic collisions. The SkyCar Rapid Transit takes advantage of all current disruptive technologies; batteries, sensors and 4G/5G communication and solar energy technologies which will continue to reduce the costs and make the systems more profitable. SkyCar's energy consumption is extremely low compared to other transport systems.

Keywords: SkyCar, rapid transit, Intelligent Transport System (ITS), Automated Transit Network (ATN), urban built environment, 4D Visualization, smart city

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