Search results for: tool comparison

Authors: Shipra Sharma, Jagat Jerath

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Human resource training is an essential element of talent management in the current era of global competitiveness and dynamic trade in the manufacturing industry. Globally, India is behind only China as the largest textile manufacturer. The major challenges faced by the Indian textile manufacturing Industry are low technology levels, growing skill gaps, unorganized structure, lower efficiencies, etc. indicating the need for constant talent up-gradation. Assessment of training needs from a strategic perspective is an essential step for the formulation of effective training. The paper established the significance of training in the Indian textile industry and to determine the training needs on various parameters as presented. 40 HR personnel/s working in the textile and apparel companies based in the industrial region of Punjab, India, were the respondents for the study. The research tool used in this case was a structured questionnaire as per five-point Likert scale. Statistical analysis through descriptive statistics and chi-square test indicated the increased need for training whenever there were technical changes in the organizations. As per the data presented in this study, most of the HR personnel/s agreed that the variables associated with organizational analysis, task analysis, and individual analysis have a statistically significant role to play in determining the need for training in an organization.

Keywords: Indian textile manufacturing industry, significance of training, training needs analysis, parameters for training needs assessment

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Authors: Sifeddine Abderrahmani, Sonia Bouafia

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The finite element method is the most practical tool for the analysis of structures, whatever the geometrical shape and behavior. It is extensively used in many high-tech industries, such as civil or military engineering, for the modeling of bridges, motor bodies, fuselages, and airplane wings. Additionally, experience demonstrates that engineers like modeling their structures using the most basic finite elements. Numerous models of finite elements may be utilized in the numerical analysis depending on the interpolation field that is selected, and it is generally known that convergence to the proper value will occur considerably more quickly with a good displacement pattern than with a poor pattern, saving computation time. The method for creating finite elements using the strain approach (S.B.A.) is presented in this presentation. When the results are compared with those provided by equivalent displacement-based elements, having the same total number of degrees of freedom, an excellent convergence can be obtained through some application and validation tests using recently developed membrane elements, plate bending elements, and flat shell elements. The effectiveness and performance of the strain-based finite elements in modeling structures are proven by the findings for deflections and stresses.

Keywords: finite elements, plate bending, strain approach, displacement formulation, shell element

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Authors: Jiangyong Liu, Xiangxiang Xu, Bote Luo, Xiaoxue Luo, Jiang Zhu, Lingzhi Yi

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To address the problems of non-linearity and high randomness of the original power load sequence causing the degradation of power load forecasting accuracy, a short-term load forecasting method is proposed. The method is based on the Least Square Support Vector Machine optimized by an Improved Sparrow Search Algorithm combined with the Variational Mode Decomposition proposed in this paper. The application of the variational mode decomposition technique decomposes the raw power load data into a series of Intrinsic Mode Functions components, which can reduce the complexity and instability of the raw data while overcoming modal confounding; the proposed improved sparrow search algorithm can solve the problem of difficult selection of learning parameters in the least Square Support Vector Machine. Finally, through comparison experiments, the results show that the method can effectively improve prediction accuracy.

Keywords: load forecasting, variational mode decomposition, improved sparrow search algorithm, least square support vector machine

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Authors: Mohamed Ahmed AbdelKawy, A. H. El-Shazly

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In this study, Nano iron-copper core-shell was synthesized by using Kinetic energy micro reactor ( K-M reactor). The reaction between nano-pure iron with copper sulphate pentahydrate (CuSO4.5H2O) beside NaCMC as a stabilizer at K-M reactor gives many advantages in comparison with the traditional chemical method for production of nano iron-Copper core-shell in batch reactor. Many factors were investigated for its effect on the process performance such as initial concentrations of nano iron and copper sulphate pentahydrate solution. Different techniques were used for investigation and characterization of the produced nano iron particles such as SEM, XRD, UV-Vis, XPS, TEM and PSD. The produced Nano iron-copper core-shell particle using micro mixer showed better characteristics than those produced using batch reactor in different aspects such as homogeneity of the produced particles, particle size distribution and size, as core diameter 10nm particle size were obtained. The results showed that 10 nm core diameter were obtained using Micro mixer as compared to 80 nm core diameter in one-fourth the time required by using traditional batch reactor and high thickness of copper shell and good stability.

Keywords: nano iron, core-shell, reduction reaction, K-M reactor

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Authors: Ennus Tajuddin Tamboli, Madhukar Garg, Mohd. Mujeeb, Sayeed Ahmad

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An efficient protocol for simultaneous production of forskolin and rosmarinic acid in in vitro callus derived from the leaves of Coleus forskohlii Briq. has been developed. MS media was used for the establishment of cultures and NAA + 6-BA (1.0 ppm) was found best for callus growth. The callus was further subjected to treatment with various elicitor/precursors viz. chitosan, thidiazuron and methyl jasmonate to observe their effect on production of biomass and accumulation of secondary metabolites. The content of forskolin and rosmarinic acid were estimated by HPTLC, in comparison to natural explant which showed 2 fold and 10 fold rise in forskolin and rosmarinic acid content, respectively. Methy1 jasmonate 50 µM was found best for production of forskolin, whereas thidiazuron showed best results in the yield of rosmarinic acid, separately in static culture. However, combined treatment in suspension culture showed moderated effect for increase in secondary metabolites but the biomass increased significantly as compared to static culture.

Keywords: plant tissue culture, secondary metabolites, coleus, forskolin, rosmarinic acid, HPTLC

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Authors: Kaouka Alaeddine, K. Benarous

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This study aims to obtain a surface of pure titanium and titanium alloy Ti-64Al with high performance by the diffusion process. Two agents metal alloy have been used in this treatment, niobium (Nb) and molybdenum (Mo), spread on elemental titanium and Ti-64Al alloy. Nb and Mo are used as powder form to increase the contact surface and to improve the distribution. Both Mo and Nb are distributed on samples of Ti and Ti-64Al at 1100 °C and 1200 °C for 3 h. They were performed to effect different experiments objectives. This work was achieved to improve some properties and microstructure of Ti and Ti-64Al surface, using optical microscopy and SEM and study some mechanical properties. The effects of temperature and the powder contents on the microstructure of Ti and Ti-64Al alloy, different phases and hardness value of Ti and Ti-64Al alloy were determined. Experimental results indicate that increasing the powder contents and/or the temperature, the α + β phases change to the equiaxed β lamellar structure. In particular, experiments in 1200 °C were created by diffusion α + β phases both equiaxed β phase laminar and α + β phase, thus meeting the objectives were established in the work. In addition, simulation results are used for comparison with the experimental results by DICTRA software.

Keywords: diffusion, powder metallurgy, titanium alloy, molybdenum, niobium

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Authors: Esmaeil Kouhgardi, Saeedeh Dashti, Hakimeh Fekrandish

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This research has been conducted to study the method of culture and comparing growth and biomass of Gracilariacorticata cultured on rope and net for 50 days through two treatments (first treatment: culture of alga on net and the second treatment: culture of alga on rope and each treatment was repeated by four cases). During culture period, the water of aquariums was replaced once every two days for 40-50%. Also, 0.3-0.5 grams of Urea fertilizer was added to the culture environment for fertilization. Moreover, some of the environmental factors such as pH, salinity and temperature of the environment were measured on a daily basis. During the culture period, extent of longitudinal growth of the species of both treatments was equal. The said length was reached from 8-10 cm to 10.5-13 cm accordingly. The resulted weight in repetitions of the first treatment was higher than that of the second treatment in such a way as in the first treatment, its weight reached from 10 grams to 21.119 grams and in the second treatment, its weight reached from 10 grams to 17.663 grams. On a whole, it may be stated that that kind of alga being studied has a considerable growth with respect to its volume. The results have revealed that the percentage of daily growth and wet weight at the end of the first treatment was higher than that of the second treatment and it was registered as 0.934, 6.072 and 811.432 in the first treatment and 0.797, 4.990 and 758.071 in the second treatment respectively. This difference is significant (P < 0.05). Growth and biomass of G. corticata through culture on net was more emphasizing on numerous branches due to wider bed. Moreover, higher level of the species in this method was exposed to sunlight and this increased biosynthesis and eventually increases of growth and biomass.

Keywords: red alga, growth, biomass, culture, net, rope

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Authors: Abdulaziz Afandi

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Minimizing the inventory cost, optimizing the inventory quantities, and increasing system operational availability are the main motivations to enhance forecasting demand of spare parts in a major power utility company in Medina. This paper reports in an effort made to optimize the orders quantities of spare parts by improving the method of forecasting the demand. The study focuses on equipment that has frequent spare parts purchase orders with uncertain demand. The pattern of the demand considers a lumpy pattern which makes conventional forecasting methods less effective. A comparison was made by benchmarking various methods of forecasting based on experts’ criteria to select the most suitable method for the case study. Three actual data sets were used to make the forecast in this case study. Two neural networks (NN) approaches were utilized and compared, namely long short-term memory (LSTM) and multilayer perceptron (MLP). The results as expected, showed that the NN models gave better results than traditional forecasting method (judgmental method). In addition, the LSTM model had a higher predictive accuracy than the MLP model.

Keywords: neural network, LSTM, MLP, forecasting demand, inventory management

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Authors: M. M. Qasaymeh, M. A. Khodeir

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Subspace channel estimation methods have been studied widely. It depends on subspace decomposition of the covariance matrix to separate signal subspace from noise subspace. The decomposition normally is done by either Eigenvalue Decomposition (EVD) or Singular Value Decomposition (SVD) of the Auto-Correlation matrix (ACM). However, the subspace decomposition process is computationally expensive. In this paper, the multipath channel estimation problem for a Slow Frequency Hopping (SFH) system using noise space based method is considered. An efficient method to estimate multipath the time delays basically is proposed, by applying MUltiple Signal Classification (MUSIC) algorithm which used the null space extracted by the Rank Revealing LU factorization (RRLU). The RRLU provides accurate information about the rank and the numerical null space which make it a valuable tool in numerical linear algebra. The proposed novel method decreases the computational complexity approximately to the half compared with RRQR methods keeping the same performance. Computer simulations are also included to demonstrate the effectiveness of the proposed scheme.

Keywords: frequency hopping, channel model, time delay estimation, RRLU, RRQR, MUSIC, LS-ESPRIT

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Authors: Khashane Stephen Malatji, Makwalete Johanna Malatji

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Student evaluation of teaching (SET) is the common way of assessing teaching quality at universities and tracing the professional growth of lecturers. The aim of this study was to investigate the role played by student evaluation in the teaching and learning agenda at one South African University. The researchers used a qualitative approach and a case study research design. With regards to data collection, document analysis was used. Evaluation reports were reviewed to monitor the growth of lecturers who were evaluated during the academic years 2020 and 2021 in one faculty. The results of the study reveal that student evaluation remains the most relevant tool to inform the teaching agenda at a university. Lecturers who were evaluated were found to grow academically. All lecturers evaluated during 2020 have shown great improvement when evaluated repeatedly during 2021. Therefore, it can be concluded that student evaluation helps to improve the pedagogical and professional proficiency of lecturers. The study therefore, recommends that lecturers conduct an evaluation for each module they teach every semester or annually in case of year modules. The study also recommends that lecturers attend to all areas that draw negative comments from students in order to improve.

Keywords: students’ voices, teaching agenda, evaluation, feedback, responses

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Authors: Mehvish Bilal, Navneet Singh, Jasir Mushtaq

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Water pollution puts people's health at risk, and it can also impact the ecology. For practitioners of integrated water resources management (IWRM), water quality modelling may be useful for informing decisions about pollution control (such as discharge permitting) or demand management (such as abstraction permitting). To comprehend the current pollutant load, movement of effective load movement of contaminants generates effective relation between pollutants, mathematical simulation, source, and water quality is regarded as one of the best estimating tools. The current study involves the Qual2k model, which includes manual simulation of the various physiochemical characteristics of water. To this end, various sensors could be installed for the automatic simulation of various physiochemical characteristics of water. An artificial intelligence model has been proposed for the automatic simulation of water quality parameters. Models of water quality have become an effective tool for identifying worldwide water contamination, as well as the ultimate fate and behavior of contaminants in the water environment. Water quality model research is primarily conducted in Europe and other industrialized countries in the first world, where theoretical underpinnings and practical research are prioritized.

Keywords: artificial intelligence, QUAL2K, simulation, physiochemical parameters

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Authors: Shafieeh Mansoori, Fatemeh Yazdian, Ashrafsadat Hatamian, Majid Azizi

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Monascus purpureus, which has a special metabolite with many therapeutic and medicinal properties including antioxidant, antibiotic, anti-hypercholesterolemia, and immunosuppressive properties, is a traditional Chinese fermentation fungus and is used as a natural dietary supplement. Production of desired metabolites actually determined by optimized growth which is supported by some factors such as substrates and Monascus strains type, moisture content of the fermentation mixture, aeration, and control of contamination issues. In this experiment, M. purpureus PTCC5305 was cultured in both the liquid and solid culture medium. The former medium contain YMP (yeast extract, maltose and peptone), PGC (peptone, glucose complex), and GYP (glucose, yeast extract and peptone) medium. After 8 days, the best medium for the cell production was PGC agar medium on solid culture with 0.28 g dry weight of cell mass whereas the best liquid culture was GYP medium with 3.5 g/l dry weight of cell mass. The lowest cell production was on YMP agar with 0.1 g dry weight of cell mass and then YMP medium with 2.5 g/l dry cell weight.

Keywords: Monascus purpureus, solid state fermentation, submerged culture, Chinese fermentation fungus

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Authors: Muhammad Asghar, Aamer Iqbal Bhatti, Qadeer Ahmed, Tahir Izhar

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Three wheeler auto Rickshaw, often termed as ‘auto rickshaw’ is very common in Pakistan and is considered as the most affordable means of transportation to the local people. Problems caused by the gasoline engine on the environment and people, the researchers and the automotive industry have turned to the hybrid electric vehicles and electrical powered vehicle. The research in this paper explains the design of energy efficient Electric auto Rickshaw. An electric auto rickshaw is being developed at Center for Energy Research and Development, (Lahore), which is running on the roads of Lahore city. Energy storage capacity of batteries is at least 25 times heavier than fossil fuel and having volume 10 times in comparison to fuel, resulting an increase of the Rickshaw weight. A set of specifications is derived according to the mobility requirements of the electric auto rickshaw. The design choices considering the power-train and component selection are explained in detail. It was concluded that electric auto rickshaw has many advantages and benefits over the conventional auto rickshaw. It is cleaner and much more energy efficient but limited to the distance it can travel before recharging of battery. In addition, a brief future view of the battery technology is given.

Keywords: conventional auto rickshaw, energy efficiency, electric auto rickshaw, internal combustion engine, environment

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Authors: Allison Futter

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Lifetime use of electronic cigarettes (EC) in college students has been estimated at around 50%; recent research shows Mobile Health (mHealth) technology is a promising tool to help address this public health issue, yet the majority of EC cessation mHealth tools found on smartphone app stores lack empirical support of their effectiveness. The Smiling Instead of Smoking (SiS) app is a positive psychology-based smartphone app for nondaily smokers. Due to previous success with brief, self-administered positive psychology exercises for cigarette cessation, this study examined the SiS App’s feasibility and effectiveness for EC cessation. Sixteen undergraduates used the SiS app for 3 weeks: one week before their quit date and 2 weeks after. As hypothesized, participants had significant declines in their craving and maintained pre-cessation levels of positive affect. There were no significant changes in dependency or self-efficacy. In the one-month follow-up survey, 38% of participants reported being abstinent. The app had an almost 4-star rating for its features (e.g., functionality, aesthetics, information, etc.) and participants reported moderate satisfaction with its use. Participants used the app, on average, 10 out of the 21 days of the prescribed app use. This study highlights the promise of mHealth support and positive psychology for EC cessation, adding to the understanding of possible ways to support EC quit attempts.

Keywords: e-cigarette cessation, mHealth, positive psychology, smartphone app

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Authors: Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

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A database that records average traffic speeds measured at five-minute intervals for all the links in the traffic network of a metropolitan city. While learning from this data the models that can predict future traffic speed would be beneficial for the applications such as the car navigation system, building predictive models for every link becomes a nontrivial job if the number of links in a given network is huge. An advantage of adopting k-nearest neighbor (k-NN) as predictive models is that it does not require any explicit model building. Instead, k-NN takes a long time to make a prediction because it needs to search for the k-nearest neighbors in the database at prediction time. In this paper, we investigate how much we can speed up k-NN in making traffic speed predictions by reducing the amount of data to be searched for without a significant sacrifice of prediction accuracy. The rationale behind this is that we had a better look at only the recent data because the traffic patterns not only repeat daily or weekly but also change over time. In our experiments, we build several different k-NN models employing different sets of features which are the current and past traffic speeds of the target link and the neighbor links in its up/down-stream. The performances of these models are compared by measuring the average prediction accuracy and the average time taken to make a prediction using various amounts of data.

Keywords: big data, k-NN, machine learning, traffic speed prediction

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Authors: Anderson Ngowa Chembe, John Olukuru

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Greenhouse emissions by human activities are known to irreversibly increase global temperatures through the greenhouse effect. This study seeks to propose a mortality model with sensitivity to heat-change effects as one of the underlying parameters in the model. As such, the study sought to establish the relationship between greenhouse emissions and mortality indices in five OECD countries (USA, UK, Japan, Canada & Germany). Upon the establishment of the relationship using correlation analysis, an additional parameter that accounts for the sensitivity of heat-changes to mortality rates was incorporated in the Lee-Carter model. Based on the proposed model, new parameter estimates were calculated using iterative algorithms for optimization. Finally, the goodness of fit for the original Lee-Carter model and the proposed model were compared using deviance comparison. The proposed model provides a better fit to mortality rates especially in USA, UK and Germany where the mortality indices have a strong positive correlation with the level of greenhouse emissions. The results of this study are of particular importance to actuaries, demographers and climate-risk experts who seek to use better mortality-modeling techniques in the wake of heat effects caused by increased greenhouse emissions.

Keywords: climate risk, greenhouse emissions, Lee-Carter model, OECD

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Authors: Asma Osivand, Hossein Mardani, Hiroshi Araya, Yoshiharu Fujii

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Wild mushrooms have always been considered as valuable source of bioactive compounds, while edible mushrooms have been known for their importance as food source. However, their interaction with plants through chemicals that could lead to find new biochemical have not been well undertaken. A special bioassay method (Sandwich method) was applied to compare eight common edible mushrooms (Pleurotus eryngii, Pleurotus citrinopileatus, Pleurotus ostreatus, Lentinula edodes, Grifola frondosa, Flammulina velutipes, Hypsizygus tessellatus and Pholiota namako) with some wild species (Ganoderma appelanatum, Amanita pantherina, Artomyces pyxidatus, Morchella conica, Tricholosporum porphyrophyllum, Trametes hirsuta) for their phytotoxicity against lettuce. Among all tested edible mushrooms, application of 5 mg of P. ostreatus showed stronger allelopathic activity by inhibiting the growth of radicle and hypocotyl of lettuce by 84% and 63% respectively. Moreover, same amount of T. porphyrophyllum exerted 77% and 67% growth inhibition on radicle and hypocotyl of lettuce. In general, biochemicals contributed in tested mushrooms could be the main cause for their inhibitory activity and could lead to find new allelochemicals.

Keywords: allelopathy, interaction, mushroom, phytotoxicity, Pleurotus sp., sandwich method

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Authors: Anshul Ashu

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Computers are applied to the vehicle aerodynamics in two ways. One of two is Computational Fluid Dynamics (CFD) and other is Computer Aided Flow Visualization (CAFV). Out of two CFD is chosen because it shows the result with computer graphics. The simulation of flow field around the vehicle is one of the important CFD applications. The flow field can be solved numerically using panel methods, k-ε method, and direct simulation methods. The spoiler is the tool in vehicle aerodynamics used to minimize unfavorable aerodynamic effects around the vehicle and the parallel spoiler is set of two spoilers which are designed in such a manner that it could effectively reduce the drag. In this study, the standard k-ε model of the simplified version of Bugatti Veyron, Audi R8 and Porsche 911 are used to simulate the external flow field. Flow simulation is done for variable Reynolds number. The flow simulation consists of three different levels, first over the model without a rear spoiler, second for over model with single rear spoiler, and third over the model with parallel rear-spoiler. The second and third level has following parameter: the shape of the spoiler, the angle of attack and attachment position. A thorough analysis of simulations results has been found. And a new parallel spoiler is designed. It shows a little improvement in vehicle aerodynamics with a decrease in vehicle aerodynamic drag and lift. Hence, it leads to good fuel economy and traction force of the model.

Keywords: drag, lift, flow simulation, spoiler

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Authors: Robert Jacobsen

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Flood inundation maps (FIMs) are an essential tool in communicating flood threat scenarios to the public as well as in floodplain governance. With an increasing demand for online raster FIMs, the FIM State-of-the-Practice (SOP) is rapidly advancing to meet the dual requirements for high-resolution and high-accuracy—or High-Definition. Importantly, today’s technology also enables the resolution of problems of local—neighborhood-scale—bias errors that often occur in FIMs, even with the use of SOP two-dimensional flood modeling. To facilitate the development of HD-FIMs, a new GIS method--Raster Adjustment with Scenario Profiles, RASPTM—is described for adjusting kernel raster FIMs to match refined scenario profiles. With RASPTM, flood professionals can prepare HD-FIMs for a wide range of scenarios with available kernel rasters, including kernel rasters prepared from vector FIMs. The paper provides detailed procedures for RASPTM, along with an example of applying RASPTM to prepare an HD-FIM for the August 2016 Flood in Louisiana using both an SOP kernel raster and a kernel raster derived from an older vector-based flood insurance rate map. The accuracy of the HD-FIMs achieved with the application of RASPTM to the two kernel rasters is evaluated.

Keywords: hydrology, mapping, high-definition, inundation

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Authors: Ajay Kumar

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Using data from census of India, sample registration system and national family health survey (NFHS-3), this paper traces spatial pattern, trends and the factors which have played their role differently in fertility transition in Uttar Pradesh and Tamil Nadu. For the purpose spatial variation analysis, trend line and binary logistic regression analysis has been carried out. There exist considerable regional disparities in terms of fertility decline in northern and southern states. The pace of fertility decline has been faster in southern and coastal regions, and at a slow pace in backward northern state. In Tamil Nadu fertility declined substantially among the women of lower and higher age groups in comparison to Uttar Pradesh characterized by low literacy, low female age at marriage, poor health infrastructure and low status of women. The Study shows that Fertility rates have been higher among the most vulnerable and deprived sections of the society like Illiterate women, women belong to scheduled caste, scheduled tribe and women residing in rural areas.

Keywords: age specific fertility rate, fertility transition, replacement level, total fertility rate

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Authors: Mohammed Bakhit Kashoob, Mohammed Salim Al-Maashani, Ahmed Abdullah Al-Marhoon

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Fatalities of Road Traffic Crashes (RTCs) on rural roads are usually higher than that on urban roads. The likelihood of traffic accidents may increase with the presence of factors that are associated with the rural type of community such as long-distance, road type, road geometry (e.g., curves and steepens), poor lighting, terrain, obstacles (e.g., animals crossing, boulders or tree branches), heavy truck traffic, weather conditions, and road flaws. Most of these factors are present on the rural roads of Oman. As many cities in Oman are surrounded by mountains and connected by rural roads, this is of great concern. In this paper, the causes of traffic crashes on rural roads in Oman are analyzed. The fatality rate of traffic deaths on rural roads is compared with the fatality rate on urban roads for different regions in Oman. Statistical data and police reports show that the leading cause of RTCs and deaths on rural roads is vehicle speeding, especially on long-distance roads. It is shown that crashes on rural roads result in higher fatalities than crashes on urban roads. In comparison to speed, the numbers of RTCs and deaths that resulted from other causes are small.

Keywords: causes of traffic crashes, road safety, road traffic crash, rural roads

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Authors: Nipon Sasithornsaowapa

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The purposes of this research was to study the female management career success of the primary education department of Thailand. The independent variable was human capital which included three factors: family status, personality, and knowledge-skill-experience, while the important dependent variable was the career success. The population of this study included 2,179 female management officials in the department of primary education. A total of 400 female managers were interviewed and utilized as a sample group. A questionnaire was developed and used as a main tool for collecting data. Content analysis was performed to get the quantitative data. Descriptive statistics in this research was done by SPSS program. The findings revealed that family and personality factors had a high influence on the human capital and, in turn, influenced the career success of female managers. On the other hand, knowledge-skill-experience had an insignificant influence to the human capital and the female career success. In addition, the findings from the in-depth interview revealed that the majority of respondents defined career success as the satisfaction in job duties, not money and position.

Keywords: career, female managers, primary education

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Authors: Tsafi Timor

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The research focuses on the exploration of the unique journey that novice teachers experience in their first year of teaching, among graduates of re-training programs into teaching. The study explores the experiences of success and failure and the factors that underpin positive experiences, as well as the journey (process) of this year with reference to the comparison between novice teachers and new immigrants. The content analysis that was adopted in the study was conducted on texts that were written by the teachers and detailed their first year of teaching. The findings indicate that experiences of success are featured by personal satisfaction, constant need of feedback, high motivation in challenging situations, and emotions. Failure experiences are featured by frustration, helplessness, sense of humiliation, feeling of rejection, and lack of efficacy. Factors that promote and inhibit positive experiences relate to personal, personality, professional and organizational levels. Most teachers reported feeling like new immigrants, and demonstrated different models of the process of the first year of teaching. Further research is recommended on the factors that promote and inhibit positive experiences, and on 'The Missing Link' of the relationship between Teacher Education Programs and the practices in schools.

Keywords: first-year teaching, novice teachers, school practice, teacher education programs

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Authors: José Dinis-Carvalho, Levi Guimarães, Celina Leão, Rui Sousa, Rosa Eliza Vieira, Larissa Thomaz, Kelliane Guerreiro

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This research paper investigates the efficacy of waste identification diagrams (WIDs) as a tool for waste reduction and management within the Manaus Industrial Pole. The study focuses on assessing the practical application and effectiveness of WIDs in identifying, categorizing, and mitigating various forms of waste generated across industrial processes. Employing a mixed-methods approach, including a qualitative questionnaire applied to 5 companies and quantitative data analysis with SPSS statistical software, the research evaluates the implementation and impact of WIDs on waste reduction practices in select industries within the Manaus Industrial Pole. The findings contribute to understanding the utility of WIDs as a proactive strategy for waste management, offering insights into their potential for fostering sustainable practices and promoting environmental stewardship in industrial settings. The study also discusses challenges, best practices, and recommendations for optimizing the utilization of WIDs in industrial waste management, thereby addressing the broader implications for sustainable industrial development.

Keywords: waste identification diagram, value stream mapping, overall equipment effectiveness, lean manufacturing

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Authors: Hsin-Yu Lee, Ming-Zhong Li, Wen-Hsi Chiu, Su-Fen Cheng, Shwu-Wen Lin

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Background: The use of medical terminology is essential to professional nurses on clinical practice. However, most nursing students consider traditional lecture-based teaching of medical terminology as boring and overly conceptual and lack motivation to learn. It is thus an issue to be discussed on how to enhance nursing students’ self-directed learning and improve learning outcomes of medical terminology. Digital game-based learning is a learner-centered way of learning. Past literature showed that the most common game-based learning for language education has been immersive games and teaching games. Thus, this study selected role-playing games (RPG) and digital puzzle games for observation and comparison. It is interesting to explore whether digital game-based learning has positive impact on nursing students’ learning of medical terminology and whether students can adapt well on this type of learning. Results can be used to provide references for institutes and teachers on teaching medical terminology. These instructions give you guidelines for preparing papers for the conference. Use this document as a template if you are using Microsoft Word. Otherwise, use this document as an instruction set. The electronic file of your paper will be formatted further at WASET. Define all symbols used in the abstract. Do not cite references in the abstract. Do not delete the blank line immediately above the abstract; it sets the footnote at the bottom of this column. Page margins are 1,78 cm top and down; 1,65 cm left and right. Each column width is 8,89 cm and the separation between the columns is 0,51 cm. Objective: The purpose of this research is to explore respectively the impact of RPG and puzzle game on nursing students’ self-directed learning and technology acceptance. The study further discusses whether different game types bring about different influences on students’ self-directed learning and technology acceptance. Methods: A quasi-experimental design was adopted in this study so that repeated measures between two groups could be conveniently conducted. 103 nursing students from a nursing college in Northern Taiwan participated in the study. For three weeks of experiment, the experiment group (n=52) received “traditional teaching + RPG” while the control group (n=51) received “traditional teaching + puzzle games”. Results: 1. On self-directed learning: For each game type, there were significant differences for the delayed tests of both groups as compared to the pre and post-tests of each group. However, there were no significant differences between the two game types. 2. On technology acceptance: For the experiment group, after the intervention of RPG, there were no significant differences concerning technology acceptance. For the control group, after the intervention of puzzle games, there were significant differences regarding technology acceptance. Pearson-correlation coefficient and path analysis conducted on the results of the two groups revealed that the dimension were highly correlated and reached statistical significance. Yet, the comparison of technology acceptance between the two game types did not reach statistical significance. Conclusion and Recommend: This study found that through using different digital games on learning, nursing students have effectively improved their self-directed learning. Students’ technology acceptances were also high for the two different digital game types and each dimension was significantly correlated. The results of the experimental group showed that through the scenarios of RPG, students had a deeper understanding of medical terminology, which reached the ‘Understand’ dimension of Bloom’s taxonomy. The results of the control group indicated that digital puzzle games could help students memorize and review medical terminology, which reached the ‘Remember’ dimension of Bloom’s taxonomy. The findings suggest that teachers of medical terminology could use digital games to assist their teaching according to their goals on cognitive learning. Adequate use of those games could help improve students’ self-directed learning and further enhance their learning outcome on medical terminology.

Keywords: digital game-based learning, medical terminology, nursing education, self-directed learning, technology acceptance model

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Authors: Rodrigo Buaiz Boabaid

Abstract:

Tokenization of Blue Bonds is an emerging Green Finance tool that has the potential to scale Blue Carbon Projects to fight climate change. This innovative solution has a huge potential to democratize the green finance market and catalyze innovations in the climate change finance sector. Switzerland has emerged as a leader in the Green Finance space and is well-positioned to drive the adoption of Tokenization of Blue & Green Bonds. This unique approach has the potential to unlock new sources of capital and enable global investors to participate in the financing of sustainable blue carbon projects. By leveraging the power of blockchain technology, Tokenization of Blue Bonds can provide greater transparency, efficiency, and security in the investment process while also reducing transaction costs. Investments are in line with the highest regulations and designed according to the stringent legal framework and compliance standards set by Switzerland. The potential benefits of Tokenization of Blue Bonds are significant and could transform the way that sustainable projects are financed. By unlocking new sources of capital, this approach has the potential to accelerate the deployment of Blue Carbon projects and create new opportunities for investors to participate in the fight against climate change.

Keywords: blue bonds, blue carbon, tokenization, green finance

Procedia PDF Downloads 82

Authors: Wen Xu

Abstract:

The expansion of Confucius institutes and Chinese as a Foreign Language (CFL) education is often considered as cultural invasion and part of much bigger, if not ambitious, Chinese central government agenda among Western public opinion. The CFL knowledge and teaching practice inherent in textbooks are also harshly critiqued as failing to align with Western educational principles. This paper takes up these concerns and attempts to articulate that Confucius’s idea of ‘education without discrimination’ appears to have become synonymous with social justice touted in contemporary Australian education and policy discourses. To do so, it capitalises on Bernstein's conceptualization of classification and pedagogic rights to articulate CFL curriculum's potential of drawing in and drawing out curriculum boundaries to achieve educational justice. In this way, the potential useful knowledge of CFL constitutes a worthwhile tool to engage in a peripheral Western country’s education issues, as well as to include disenfranchised students in the multicultural Australian society. It opens spaces for critically theorising CFL curricular justice in Australian educational contexts, and makes an original contribution to scholarly argumentation that CFL curriculum has the potential of including socially and economically disenfranchised students in schooling.

Keywords: curriculum justice, Chinese as a Foreign Language curriculum, Bernstein, equity

Procedia PDF Downloads 141

Authors: G. Peker, Tolga N. Aynur, E. Tinar

Abstract:

In order to determine the energy consumption level and cooling characteristics of a domestic refrigerator controlled with various cooling system algorithms, a side by side type (SBS) refrigerator was tested in temperature and humidity controlled chamber conditions. Two different control algorithms; so-called drop-in and frequency controlled variable capacity compressor algorithms, were tested on the same refrigerator. Refrigerator cooling characteristics were investigated for both cases and results were compared with each other. The most important comparison parameters between the two algorithms were taken as; temperature distribution, energy consumption, evaporation and condensation temperatures, and refrigerator run times. Standard energy consumption tests were carried out on the same appliance and resulted in almost the same energy consumption levels, with a difference of %1,5. By using these two different control algorithms, the power consumptions character/profile of the refrigerator was found to be similar. By following the associated energy measurement standard, the temperature values of the test packages were measured to be slightly higher for the frequency controlled algorithm compared to the drop-in algorithm. This paper contains the details of this experimental study conducted with different cooling control algorithms and compares the findings based on the same standard conditions.

Keywords: control algorithm, cooling, energy consumption, refrigerator

Procedia PDF Downloads 367

Authors: M. Fertouna Bellakhal, M. Bellakhal, A. Dhib, A. Fathalli, S. Turki, L. Aleya

Abstract:

Study of dinoflagellate cysts is a precious tool to get information about environment and water quality in many aquatic ecosystems. The distribution of Alexandrium pacificum cysts, in Bizerta lagoon located in North of Tunisia, was made based on sediment samples analysis from 123 equidistant stations delimiting 125 km² surfaces. Sediment characteristics such as percentage of water, organic matter, and particle size were analyzed to determine the factors that influence the distribution of this dinoflagellate. In addition, morphological examination and ribotyping of vegetative forms from microalgal cultures made from cyst germination confirmed the identity of the species attributed to A. pacificum. A correlation between the abundance of A. pacificum cysts and the percentage of water and sediment organic matter was recorded. In addition, the sedimentary fraction < 63μm was found to be potentially favorable for the installation and initiation of the Alexandrium pacificum efflorescence at the Bizerte lagoon. The mapping of cysts in this aquatic ecosystem has also allowed us to define distinct areas with specific abundance with closed relationship with shellfish aquaculture stations located within the lagoon.

Keywords: Alexandrium pacificum, cysts, Dinoflagellate, microalgal culture

Procedia PDF Downloads 148

Authors: Kashika P. H.

Abstract:

The development of computer vision systems has been greatly aided by the efficient and precise detection of images and videos. Although the ability to recognize and comprehend images is a strength of the human brain, employing technology to tackle this issue is exceedingly challenging. In the past few years, the use of Deep Learning algorithms to treat object detection has dramatically expanded. One of the key issues in the realm of image recognition is the recognition and detection of certain notable people from randomly acquired photographs. Face recognition uses a way to identify, assess, and compare faces for a variety of purposes, including user identification, user counting, and classification. With the aid of an accessible deep learning-based API, this article intends to recognize various faces of people and their facial descriptors more accurately. The purpose of this study is to locate suitable individuals and deliver accurate information about them by using the Amazon Rekognition system to identify a specific human from a vast image dataset. We have chosen the Amazon Rekognition system, which allows for more accurate face analysis, face comparison, and face search, to tackle this difficulty.

Keywords: Amazon rekognition, API, deep learning, computer vision, face detection, text detection

Procedia PDF Downloads 101