Search results for: corporate social performance

Authors: Tahir Mehmood, Mumtaz Akhter

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The global need for conflict management is greater now in the early 21st century than ever before. According to UNESCO, half of the world’s 195 countries will have to expand their stock of educationist significantly, some by tens of thousands, if the goal development targets are desired to achieve. Socioeconomic inequities, political instability, demographic changes and crises such as the HIV/AIDs epidemic have engendered huge shortfalls in teacher supply and low teacher quality in many developing countries. Education serves as back bone in development process. Open learning and distance education programs are serving as pivotal part of development process. It is now clear that ‘bricks and mortar’ approaches to expanding teacher education may not be adequate if the current and projected shortfalls in teacher supply and low teacher quality are to be properly addressed. The study is designed to measure the perceptions of teaching learning community about conflict management with special reference to open and distance learning. It was descriptive study which targeted teachers, students, community members and experts. Data analysis was carried out by using statistical techniques served by SPSS. Findings reflected that audience perceives open and distance learning as change agent and as development tool. It is noticed that target audience has driven prominent performance by using facility of open and distance learning.

Keywords: conflict management, open and distance learning, teachers, students

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Authors: Sonia Butalia, Huong Luu, Alexis Guigue, Karen J. B. Martins, Khanh Vu, Scott W. Klarenbach

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Obesity is associated with significant personal impacts on health and has a substantial economic burden on payers due to increased healthcare use. A contemporary estimate of the healthcare costs associated with obesity at the population level are lacking. This evidence may provide further rationale for weight management strategies. Methods: Adults who underwent a medical procedure between 2012 and 2019 in Alberta, Canada were categorized into the investigational cohort (had body mass index [BMI]-defined class 2 or 3 obesity based on a procedure-associated code) and the control cohort (did not have the BMI procedure-associated code); those who had bariatric surgery were excluded. Characteristics were presented and healthcare costs ($CDN) determined over a 1-year observation period (2019/2020). Logistic regression and a generalized linear model with log link and gamma distribution were used to assess total healthcare costs (comprised of hospitalizations, emergency department visits, ambulatory care visits, physician visits, and outpatient prescription drugs); potential confounders included age, sex, region of residence, and whether the medical procedure was performed within 6-months before the observation period in the partial adjustment, and also the type of procedure performed, socioeconomic status, Charlson Comorbidity Index (CCI), and seven obesity-related health conditions in the full adjustment. Cost ratios and estimated cost differences with 95% confidence intervals (CI) were reported; incremental cost differences within the adjusted models represent referent cases. Results: The investigational cohort (n=220,190) was older (mean age: 53 standard deviation [SD]±17 vs 50 SD±17 years), had more females (71% vs 57%), lived in rural areas to a greater extent (20% vs 14%), experienced a higher overall burden of disease (CCI: 0.6 SD±1.3 vs 0.3 SD±0.9), and were less socioeconomically well-off (material/social deprivation was lower [14%/14%] in the most well-off quintile vs 20%/19%) compared with controls (n=1,955,548). Unadjusted total healthcare costs were estimated to be 1.77-times (95% CI: 1.76, 1.78) higher in the investigational versus control cohort; each healthcare resource contributed to the higher cost ratio. After adjusting for potential confounders, the total healthcare cost ratio decreased, but remained higher in the investigational versus control cohort (partial adjustment: 1.57 [95% CI: 1.57, 1.58]; full adjustment: 1.21 [95% CI: 1.20, 1.21]); each healthcare resource contributed to the higher cost ratio. Among urban-dwelling 50-year old females who previously had non-operative procedures, no procedures performed within 6-months before the observation period, a social deprivation index score of 3, a CCI score of 0.32, and no history of select obesity-related health conditions, the predicted cost difference between those living with and without obesity was $386 (95% CI: $376, $397). Conclusions: If these findings hold for the Canadian population, one would expect an estimated additional $3.0 billion per year in healthcare costs nationally related to BMI-defined obesity (based on an adult obesity rate of 26% and an estimated annual incremental cost of $386 [21%]); incremental costs are higher when obesity-related health conditions are not adjusted for. Results of this study provide additional rationale for investment in interventions that are effective in preventing and treating obesity and its complications.

Keywords: administrative data, body mass index-defined obesity, healthcare cost, real world evidence

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Authors: Ashish Kumar, Munesh Raghuraj Varma, Nisarg Joshi, Gujjula Vishwa Teja, Srikanth Sambi, Arpit Awasthi

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Autonomous driving vehicles are revolutionizing the transportation system of the 21st century. This has been possible due to intensive research put into making a robust, reliable, and intelligent program that can perceive and understand its environment and make decisions based on the understanding. It is a very data-intensive task with data coming from multiple sensors and the amount of data directly reflects on the performance of the system. Researchers have to design the preprocessing pipeline for different datasets with different sensor orientations and alignments before the dataset can be fed to the model. This paper proposes a solution that provides a method to unify all the data from different sources into a uniform format using the intrinsic and extrinsic parameters of the sensor used to capture the data allowing the same pipeline to use data from multiple sources at a time. This also means easy adoption of new datasets or In-house generated datasets. The solution also automates the complete deep learning pipeline from preprocessing to post-processing for various tasks allowing researchers to design multiple custom end-to-end pipelines. Thus, the solution takes care of the input and output data handling, saving the time and effort spent on it and allowing more time for model improvement.

Keywords: augmentation, autonomous driving, camera, custom end-to-end pipeline, data unification, lidar, post-processing, preprocessing

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Authors: Tabiti S. Tabiti, A. M. Jinadu, Daramola Japheth

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Urban insecurity is among the challenges militating against sustainable urban governance; in the first place it distorts the peace of urban areas making them unsafe. On the other hand it hinders the effective performance of urban functions. Urban security challenges manifest in different forms such as, street violence, theft and robbery, accidents of different types kidnapping, killings etc.. Efforts to address urban security challenges in Nigeria have been concentrated in legislative, law enforcement and the use of community vigilante groups. However in this study, the place of physical planning strategy through effective neighbourhood renewal as practiced in Mokola is presented as an effective complementary approach for addressing urban insecurity. On this backdrop, the paper recommends the need for gradual rehabilitation of urban slum neighborhoods by the state government in collaboration with World Bank and other development financiers. The local governments should be made autonomy in Nigeria so as to make them more responsible to the people. Other recommendations suggested in the paper include creating enabling environment that will promote economic empowerment and public enlightment on personal and community sanitation. It is certain that if these recommendations are adopted the challenge of urban insecurity will reduce significantly in Nigerian cities.

Keywords: neighbourhood renewal, pilot project, slum upgrading, urban security

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Authors: Yan Cheng, Yijun Shao, James Rudolph, Charlene R. Weir, Beth Sahlmann, Qing Zeng-Treitler

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Supervised predictive models require labeled data for training purposes. Complete and accurate labeled data, i.e., a ‘gold standard’, is not always available, and imperfectly labeled data may need to serve as an alternative. An important question is if the accuracy of the labeled data creates a performance ceiling for the trained model. In this study, we trained several models to recognize the presence of delirium in clinical documents using data with annotations that are not completely accurate (i.e., weakly-supervised learning). In the external evaluation, the support vector machine model with a linear kernel performed best, achieving an area under the curve of 89.3% and accuracy of 88%, surpassing the 80% accuracy of the training sample. We then generated a set of simulated data and carried out a series of experiments which demonstrated that models trained on imperfect data can (but do not always) outperform the accuracy of the training data, e.g., the area under the curve for some models is higher than 80% when trained on the data with an error rate of 40%. Our experiments also showed that the error resistance of linear modeling is associated with larger sample size, error type, and linearity of the data (all p-values < 0.001). In conclusion, this study sheds light on the usefulness of imperfect data in clinical research via weakly-supervised learning.

Keywords: weakly-supervised learning, support vector machine, prediction, delirium, simulation

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Authors: Chechen Liao, Hung Wen Shaw

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Recently, online impulse buying has been growing rapidly. It has become a major issue of concern and provided a lot of opportunities for online businesses. This study examines the effect of hedonic shopping values on hedonic motivations, and in turn affecting the urge of impulse buying. The study also explores the effects of website quality and the individual characteristics of impulsiveness on the urge of impulse buying. A total of 459 valid questionnaires were collected. Structural equation modelling was used to test the research hypothesis. This study found that adventure shopping, value shopping, and social shopping have a positive effect on hedonic motivations, which in turn positively affect the urge of impulse buying. Website quality and the individual characteristics of impulsiveness have a positive effect on the urge of impulse buying. The result of this study validates the phenomenon of online impulse buying behavior. This study also suggests that having a good website quality is the most important factor for increasing the likelihood of consumer impulse purchase. The study could serve as a basis for future research regarding online impulse buying behavior.

Keywords: hedonic motivation, hedonic shopping value, impulse buying, impulsiveness, website quality

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Authors: Murray Olowa

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This article examines the studies investigating the Mathematical Knowledge for Teaching (MKT) of secondary preservice teachers in Papua New Guinea based on probabilities. This research was conducted due to the continuous issues faced in the country in both primary and secondary education, like changes in curriculum, emphasis on mathematics and science education, and a decline in mathematics performance. Moreover, the mathematics curriculum doesn’t capture Pedagogical Content Knowledge (PCK) or Subject Matter Knowledge (SMK). The two main domains that have been identified are SMK and PCK, which have been further sub-divided into Common Content Knowledge (CCK), Specialised Content Knowledge (SCK) and Horizon Content Knowledge (HCK), and Knowledge of Content and Students (KCS), Knowledge of Content and Teaching (KCT) and Knowledge of Content and Curriculum (KCC), respectively. The data collected from 15-_year-_ ones and 15-_year-_fours conducted at St Peter Chanel Secondary Teachers College revealed that there is no significant difference in subject matter knowledge between year one and year four since the P-value of 0.22>0.05. However, it was revealed that year fours have higher pedagogical content knowledge than year one since P-value was 0.007<0.05. Finally, the research has proven that year fours have higher MKT than year one. This difference occurred due to final year preservice teachers’ hard work and engagement in mathematics curriculum and teaching practice.

Keywords: mathematical knowledge for teaching, subject matter knowledge, pedagogical content knowledge, Papua New Guinea, preservice teachers, probability

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Authors: Aishwarya Ravindra Fursule, Shruti Kshirsagar

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In the intersection of artificial intelligence and human-centered computing, this paper delves into speech emotion recognition (SER). It presents a comparative analysis of machine learning models such as K-Nearest Neighbors (KNN),logistic regression, support vector machines (SVM), decision trees, ensemble classifiers, and random forests, applied to SER. The research employs four datasets: Crema D, SAVEE, TESS, and RAVDESS. It focuses on extracting salient audio signal features like Zero Crossing Rate (ZCR), Chroma_stft, Mel Frequency Cepstral Coefficients (MFCC), root mean square (RMS) value, and MelSpectogram. These features are used to train and evaluate the models’ ability to recognize eight types of emotions from speech: happy, sad, neutral, angry, calm, disgust, fear, and surprise. Among the models, the Random Forest algorithm demonstrated superior performance, achieving approximately 79% accuracy. This suggests its suitability for SER within the parameters of this study. The research contributes to SER by showcasing the effectiveness of various machine learning algorithms and feature extraction techniques. The findings hold promise for the development of more precise emotion recognition systems in the future. This abstract provides a succinct overview of the paper’s content, methods, and results.

Keywords: comparison, ML classifiers, KNN, decision tree, SVM, random forest, logistic regression, ensemble classifiers

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Authors: Pedro Paulo Galindo Francisco, Eli Dhadad Junior

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This study addresses the Meese-Rogoff Puzzle by introducing the latest machine learning techniques as alternatives for predicting the exchange rates. Using RMSE as a comparison metric, Meese and Rogoff discovered that economic models are unable to outperform the random walk model as short-term exchange rate predictors. Decades after this study, no statistical prediction technique has proven effective in overcoming this obstacle; although there were positive results, they did not apply to all currencies and defined periods. Recent advancements in artificial intelligence technologies have paved the way for a new approach to exchange rate prediction. Leveraging this technology, we applied five machine learning techniques to attempt to overcome the Meese-Rogoff puzzle. We considered daily data for the real, yen, British pound, euro, and Chinese yuan against the US dollar over a time horizon from 2010 to 2023. Our results showed that none of the presented techniques were able to produce an RMSE lower than the Random Walk model. However, the performance of some models, particularly LSTM and N-BEATS were able to outperform the ARIMA model. The results also suggest that machine learning models have untapped potential and could represent an effective long-term possibility for overcoming the Meese-Rogoff puzzle.

Keywords: exchage rate, prediction, machine learning, deep learning

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Authors: Joon-Yeop Na, Sang-Keun Baik, Kyu-Soo Chong

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Road sign sizes are related to their support and foundation, and the large-scale support that is generally installed at roadsides can cause inconvenience to pedestrians and damage the urban landscape. The most influential factor in determining the support and foundation of road signs is the wind load. In this study, we introduce a hole-type road sign to analyze its effects on reducing wind load. A hole-type road sign reduces the drag coefficient that is applied when considering the air and fluid resistance of a plate when the wind pressure is calculated, thus serving as an effective option for lightening the weights of road sign structures. A hole-type road sign is punctured with a perforator. Furthermore, the size of the holes and their distance is determined considering the damage to characters, the poor performance of reflective sheets, and legibility. For the calculation of the optimal specification of a hole-type road sign, we undertook a theoretical examination for reducing the wind loads on hole-type road signs, and analyzed the bending and reflectivity of sample road sign plates. The analytic results confirmed that a hole-type road sign sample that contains holes of 6 mm in diameter with a distance of 18 mm between the holes shows reflectivity closest to that of existing road signs; moreover, the average bending moment resulted in a reduction of 4.24%, and the support’s diameter is reduced by 40.2%.

Keywords: hole type, road sign, weight lightening, wind load

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Authors: Ahmed A. D. Sarhan, M. Sayuti, M. Hamdi

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Due to rapid consumption of world's fossil fuel resources and impracticality of large-scale application and production of renewable energy, the significance of energy efficiency improvement of current available energy modes has been widely realized by both industry and academia. In the CNC machining field, the key solution for this issue is by increasing the effectiveness of the existing lubrication systems as it could reduce the power required to overcome the friction component in machining process. For more improvement, introducing the nanolubrication could produce much less power consumption as the rolling action of billions units of nanoparticle in the tool chip interface could reduce the cutting forces significantly. In this research, the possibility of using carbon onion nanolubrication with DLC cutting tool is investigated to reduce the machining power consumption. Carbon onion nanolubrication has been successfully developed with high tribology performance and mixed with ordinary mineral oil. The proper sonification method is used to provide a way to mix and suspend the particles thoroughly and efficiently. Furthermore, Diamond-Like Carbon (DLC) cutting tool is used and expected to play significant role in reducing friction and cutting forces and increasing abrasion resistance. The results showed significant reduction of the cutting force and the working power compared with the other conditions of using carbon black and normal lubrication systems.

Keywords: carbon onion, nanolubrication, machining power consumption, DLC cutting tool

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Authors: Youn Young Shim, Ji Hye Kim, Jae Youl Cho, Martin JT Reaney

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Flaxseed (Linumusitatissimum L.) is gaining popularity in the food industry as a superfood due to its health-promoting properties. Linusorbs (LOs, a.k.a. Cyclolinopeptide) are bioactive compounds present in flaxseed exhibiting potential health effects. The study focused on the effects of processing and storage on the stability of flaxseed-derived LOs added to various bakery products. The flaxseed meal fortified gluten-free (GF) bakery bread was prepared, and the changes of LOs during the bread-making process (meal, fortified flour, dough, and bread) and storage (0, 1, 2, and 4 weeks) at different temperatures (−18 °C, 4 °C, and 22−23 °C) were analyzed by high-performance liquid chromatography-diode array detection. The total oxidative LOs and LO1OB2 were almost kept stable in flaxseed meals at storage temperatures of 22−23 °C, −18 °C, and 4 °C for up to four weeks. Processing steps during GF-bread production resulted in the oxidation of LOs. Interestingly, no LOs were detected in the dough sample; however, LOs appeared when the dough was stored at −18 °C for one week, suggesting that freezing destroyed the sticky structure of the dough and resulted in the release of LOs. The final product, flaxseed meal fortified bread, could be stored for up to four weeks at −18 °C and 4 °C, and for one week at 22−23 °C. All these results suggested that LOs may change during processing and storage and that flaxseed flour-fortified bread should be stored at low temperatures to preserve effective LOs components.

Keywords: linum usitatissimum L., flaxseed, linusorb, stability, gluten-free, peptides, cyclolinopeptide

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Authors: Saleh B. Mohamed, Mohamed H. Elhsnawi, Mesbah M. Salem

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Current and future applications of small gas turbine engines annular type combustors have requirements presenting difficult disputes to the combustor designer. Reduced cost and fuel consumption and improved durability and reliability as well as higher temperatures and pressures for such application are forecast. Coupled with these performance requirements, irrespective of the engine size, is the demand to control the pollutant emissions, namely the oxides of nitrogen, carbon monoxide, smoke and unburned hydrocarbons. These technical and environmental challenges have made the design of small size combustion system a very hard task. Thus, the main target of this work is to generalize a calculation method of annular type combustors for small gas turbine engines that enables to understand the fundamental concepts of the coupled processes and to identify the proper procedure that formulates and solves the problems in combustion fields in as much simplified and accurate manner as possible. The combustion chamber in task is designed with central vaporizing unit and to deliver 516.3 KW of power. The geometrical constraints are 142 mm & 140 mm overall length and casing diameter, respectively, while the airflow rate is 0.8 kg/sec and the fuel flow rate is 0.012 kg/sec. The relevant design equations are programmed by using MathCAD language for ease and speed up of the calculation process.

Keywords: design of gas turbine, small engine design, annular type combustors, mechanical engineering

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Authors: Reza Vakili

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This experiment was conducted to investigate the effect of duration water restriction of drinking water and salinity level on production performance, egg quality and biochemical and hematological blood indices of laying hens. A total of 240 Hy-Line laying hens were used in a completely randomized design with a 2 × 2 factorial arrangement of treatments. Experimental treatments were: 1) free access to drinking water and a low level of salinity (TDS below 500 mg/L) (FAW+LS), 2) free access to water and a high level of salinity (TDS above 1500 mg/L), (FAW+HS), 3) 12 h nightly water restriction and a low level of salinity (LAW+LS), and 4) 12 h water restriction and a high level of salinity (LAW+HS). Intake of feed, percentage of egg production and egg weight and mass were not affected by water restriction or salinity level (P > 0.05), however, a trend (P < 0.01) for lower water consumption was detected in water-restricted hens, regardless of salinity level (213 vs 187). A tendency for lower eggshell and yolk weights was observed in hens that had limited access to water with high salinity compared to those had free access to high saline water (P = 0.08). Serum total protein and glucose concentrations significantly reduced (P < 0.05) in hens drank high salinity water, regardless of water restriction. Moreover, saline water increased the concentration of uric acid, creatinine, and cholesterol when compared to low salinity drank-hens (P < 0.05). The concentrations of ALT and AST increased with salinity level (P < 0.05) and water restriction caused an increment in AST content (P < 0.05). In conclusion, Hy-Line laying hens could withstand water restriction, whilst could not tolerate water salinity of about 1500 mg/L.

Keywords: chemical pollutants, eggs, laying hens, salinity, water quality

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Authors: Savvas Rogotis, Nikolaos Kalatzis, Stergios Dimou-Sakellariou, Nikolaos Marianos

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As precision holds the key for the introduction of distinct benefits in agriculture (e.g., energy savings, reduced labor costs, optimal application of inputs, improved products, and yields), it steadily becomes evident that new initiatives should focus on rendering Precision Agriculture (PA) more accessible to the average farmer. PA leverages on technologies such as the Internet of Things (IoT), earth observation, robotics and positioning systems (e.g., the Global Navigation Satellite System – GNSS - as well as individual positioning systems like GPS, Glonass, Galileo) that allow: from simple data georeferencing to optimal navigation of agricultural machinery to even more complex tasks like Variable Rate Applications. An identified customer pain point is that, from one hand, typical triangulation-based positioning systems are not accurate enough (with errors up to several meters), while on the other hand, high precision positioning systems reaching centimeter-level accuracy, are very costly (up to thousands of euros). Within this paper, a Ground-Based Augmentation System (GBAS) is introduced, that can be adapted to any existing IoT field-sensing station infrastructure. The latter should cover a minimum set of requirements, and in particular, each station should operate as a fixed, obstruction-free towards the sky, energy supplying unit. Station augmentation will allow them to function in pairs with GNSS rovers following the differential GNSS base-rover paradigm. This constitutes a key innovation element for the proposed solution that encompasses differential GNSS capabilities into an IoT field-sensing infrastructure. Integrating this kind of information supports the provision of several additional PA beneficial services such as spatial mapping, route planning, and automatic field navigation of unmanned vehicles (UVs). Right at the heart of the designed system, there is a high-end GNSS toolkit with base-rover variants and Real-Time Kinematic (RTK) capabilities. The GNSS toolkit had to tackle all availability, performance, interfacing, and energy-related challenges that are faced for a real-time, low-power, and reliable in the field operation. Specifically, in terms of performance, preliminary findings exhibit a high rover positioning precision that can even reach less than 10-centimeters. As this precision is propagated to the full dataset collection, it enables tractors, UVs, Android-powered devices, and measuring units to deal with challenging real-world scenarios. The system is validated with the help of Gaiatrons, a mature network of agro-climatic telemetry stations with presence all over Greece and beyond ( > 60.000ha of agricultural land covered) that constitutes part of “gaiasense” (www.gaiasense.gr) smart farming (SF) solution. Gaiatrons constantly monitor atmospheric and soil parameters, thus, providing exact fit to operational requirements asked from modern SF infrastructures. Gaiatrons are ultra-low-cost, compact, and energy-autonomous stations with a modular design that enables the integration of advanced GNSS base station capabilities on top of them. A set of demanding pilot demonstrations has been initiated in Stimagka, Greece, an area with a diverse geomorphological landscape where grape cultivation is particularly popular. Pilot demonstrations are in the course of validating the preliminary system findings in its intended environment, tackle all technical challenges, and effectively highlight the added-value offered by the system in action.

Keywords: GNSS, GBAS, precision agriculture, RTK, smart farming

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Authors: Muzaffar Hussain

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Requests strategies are considered as a part of the speech acts, which are frequently used in everyday communication. Each language provides speech acts to the speakers; therefore, the selection of appropriate form seems more culture-specific rather than language. The present paper investigates the gender-based difference in the use of request strategies by native speakers of Urdu/Punjabi male and female who are learning English as a second language. The data for the present study were collected from 68 graduate students, who are learning English as an L2 in Pakistan. They were given an online close-ended questionnaire, based on Discourse Completion Test (DCT). After analyzing the data, it was found that the L1 male Urdu/Punjabi speakers were inclined to use more direct request strategies while the female Urdu/Punjabi speakers used indirect request strategies. This paper also found that in some situations female participants used more direct strategies than male participants. The present study concludes that the use of request strategies is influenced by culture, social status, and power distribution in a society.

Keywords: gender variation, request strategies, face-threatening, second language pragmatics, language competence

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Authors: Naragain Phumchusri, Kittitach Pongpairoj

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Overbooking is a very useful revenue management technique that could help reduce costs caused by either undersales or oversales. In this paper, we propose an overbooking model for two types of cars that can minimize the total cost for car rental service. With two types of cars, there is an upgrade possibility for lower type to upper type. This makes the model more complex than one type of cars scenario. We have found that convexity can be proved in this case. Sensitivity analysis of the parameters is conducted to observe the effects of relevant parameters on the optimal solution. Model simplification is proposed using multiple linear regression analysis, which can help estimate the optimal overbooking level using appropriate independent variables. The results show that the overbooking level from multiple linear regression model is relatively close to the optimal solution (with the adjusted R-squared value of at least 72.8%). To evaluate the performance of the proposed model, the total cost was compared with the case where the decision maker uses a naïve method for the overbooking level. It was found that the total cost from optimal solution is only 0.5 to 1 percent (on average) lower than the cost from regression model, while it is approximately 67% lower than the cost obtained by the naïve method. It indicates that our proposed simplification method using regression analysis can effectively perform in estimating the overbooking level.

Keywords: overbooking, car rental industry, revenue management, stochastic model

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Authors: Sirine Sayed, Mostapha Tarfaoui, Abdelmalek Toumi, Youssef Qarssis, Mohamed Daly, Chokri Bouraoui

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This paper delves into the combination of additive manufacturing (AM) and artificial intelligence (AI) to solve challenges related to the mechanical behavior of AM-produced parts. The article highlights the fundamentals and benefits of additive manufacturing, including creating complex geometries, optimizing material use, and streamlining manufacturing processes. The paper also addresses the challenges associated with additive manufacturing, such as ensuring stable mechanical performance and material properties. The role of AI in improving the static behavior of AM-produced parts, including machine learning, especially the neural network, is to make regression models to analyze the large amounts of data generated during experimental tests. It investigates the potential synergies between AM and AI to achieve enhanced functions and personalized mechanical properties. The mechanical behavior of parts produced using additive manufacturing methods can be further improved using design optimization, structural analysis, and AI-based adaptive manufacturing. The article concludes by emphasizing the importance of integrating AM and AI to enhance mechanical operations, increase reliability, and perform advanced functions, paving the way for innovative applications in different fields.

Keywords: additive manufacturing, mechanical behavior, artificial intelligence, machine learning, neural networks, reliability, advanced functionalities

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Authors: Abdoulaye Diop, Nahid Emad, Thierry Winter, Mohamed Hilia

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Data assets protection is a crucial issue in the cybersecurity field. Companies use logical access control tools to vault their information assets and protect them against external threats, but they lack solutions to counter insider threats. Nowadays, insider threats are the most significant concern of security analysts. They are mainly individuals with legitimate access to companies information systems, which use their rights with malicious intents. In several fields, behavior anomaly detection is the method used by cyber specialists to counter the threats of user malicious activities effectively. In this paper, we present the step toward the construction of a user and entity behavior analysis framework by proposing a behavior anomaly detection model. This model combines machine learning classification techniques and graph-based methods, relying on linear algebra and parallel computing techniques. We show the utility of an ensemble learning approach in this context. We present some detection methods tests results on an representative access control dataset. The use of some explored classifiers gives results up to 99% of accuracy.

Keywords: cybersecurity, data protection, access control, insider threat, user behavior analysis, ensemble learning, high performance computing

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Authors: Ali Mohammadi

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This study explored the root causes of women's lack of writing in literature by digging into Virginia Woolf's A Room of One’s Own. Virginia Woolf was the pioneer of feminist literary criticism in the 20th century. She was hugely preoccupied, throughout her writing life, with the role of women in history and with the relationship between women and fiction. Besides, she wrote continuously about the difficulties of women's writing and of writing as a woman. This research aims to mirror a number of key arguments concerning women’s issues: the social and economic conditions necessary for writing; the problem of a tradition of women's writing; the concept of a 'female sentence' articulating women's voices and values and the idea of the androgynous aesthetic in which an author would be able to write free from an awareness of their sex as male or female. Woolf was very wary of making any definitive assertions about women's writing, or at least in terms of its style or form. Indeed, much of the essay is taken up with her reflections on the lack of women's writing over the history of English literature. It was concluded that the reason for this absence of female writing does not just spring from the deficiency of genius, but of material circumstances and facilities. Additionally, the demands of the domestic household, the poverty of education available to women, and the laws that denied married women’s ownership of funds or property made it virtually impossible for women to take up writing as a profession.

Keywords: autonomy, facilities, genius, literature, women

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Authors: Zerzouri Nora, Benalia Nadia, Bensiali Nadia

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This paper presents a grid-connected wind power generation scheme using Doubly Fed Induction Generator (DFIG). This can supply power at constant voltage and constant frequency with the rotor speed varying. This makes it suitable for variable speed wind energy application. The DFIG system consists of wind turbine, asynchronous wound rotor induction generator, and inverter with Space Vector Modulation (SVM) controller. In which the stator is connected directly to the grid and the rotor winding is in interface with rotor converter and grid converter. The use of back-to-back SVM converter in the rotor circuit results in low distortion current, reactive power control and operate at variable speed. Mathematical modeling of the DFIG is done in order to analyze the performance of the systems and they are simulated using MATLAB. The simulation results for the system are obtained and hence it shows that the system can operate at variable speed with low harmonic current distortion. The objective is to track and extract maximum power from the wind energy system and transfer it to the grid for useful work.

Keywords: Doubly Fed Induction Generator, Wind Energy Conversion Systems, Space Vector Modulation, distortion harmonics

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Authors: Mona Mahmoud Abou Samra, Alaa Hamed Salama, Ghada Awad, Soheir Said Mansy

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Proniosomes are well documented for topical drug delivery and preferred over other vesicular systems because they are biodegradable, biocompatible, non-toxic, possess skin penetration ability and prolong the release of drugs by acting as depot in deeper layers of skin. Proniosome drug delivery was preferred due to improved stability of the system than niosomes. The present investigation aimed at formulation development and performance evaluation of proniosomal gel as a vesicular drug carrier system for antifungal drug tolnaftate. Proniosomes was developed using different nonionic surfactants such as span 60 and span 65 with cholesterol in different molar ratios by the Coacervation phase separation method in presence or absence of either lecithin or phospholipon 80 H. Proniosomal gel formulations of tolnaftate were characterized for vesicular shape & size, entrapment efficiency, rheological properties and release study. The effect of surfactants and additives on the entrapment efficiency, particle size and percent of drug released was studied. The selected proniosomal formulations for topical delivery of tolnaftate was subjected to a microbiological study in male rats infected with Trichophyton rubrum; the main cause of Tinea Pedis compared to the free drug and a market product and the results was recorded.

Keywords: fungal infection, proniosome, tolnaftate, trichophyton rubrum

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Authors: Madhurima S. Waghmare, Shaleen Singhal

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The concept of smartness, inclusion, sustainability is multidisciplinary and fuzzy, rooted in economic and social development theories and policies which get reflected in the spatial development of the cities. It is a challenge to convert these concepts from aspirations to transforming actions. There is a dearth of assessment and planning tools to support the city planners and administrators in developing smart, inclusive, and sustainable cities. To address this gap, this study develops an inclusive cities decision matrix based on an exploratory approach and using mixed methods. The matrix is soundly based on a review of multidisciplinary urban sector literature and refined and finalized based on inputs from experts and insights from case studies. The application of the decision matric on the case study cities in India suggests that the contemporary planning tools for cities need to be multidisciplinary and flexible to respond to the unique needs of the diverse contexts. The paper suggests that a multidimensional and inclusive approach to city planning can play an important role in building sustainable smart cities.

Keywords: inclusive-cities decision matrix, smart cities in India, city planning tools, sustainable cities

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Authors: Han Yan, Jieren Luo, Qiuhui Yan, Xiaoqing Li

Abstract:

The thermal conductivity of porous materials is closely related to the thermal and moisture environment and the overall energy consumption of the building. The study of thermal conductivity of porous materials has great significance for the realization of low energy consumption building and economic construction building. Based on the study of effective thermal conductivity of porous materials at home and abroad, the thermal conductivity under a variety of different density of polystyrene board (EPS), plastic extruded board (XPS) and polyurethane (PU) and phenolic resin (PF) in wet state through theoretical analysis and experimental research has been studied. Initially, the moisture absorption and desorption properties of specimens had been discussed under different density, which led a result indicates the moisture absorption of four porous materials all have three stages, fast, stable and gentle. For the moisture desorption, there are two types. One is the existence of the rapid phase of the stage, such as XPS board, PU board. The other one does not have the fast desorption, instead, it is more stabilized, such as XPS board, PF board. Furthermore, the relationship between water content and thermal conductivity of porous materials had been studied and fitted, which figured out that in the wake of the increasing water content, the thermal conductivity of porous material is continually improving. At the same time, this result also shows, in different density, when the same kind of materials decreases, the saturated moisture content increases. Finally, the moisture absorption and desorption properties of the four kinds of materials are compared comprehensively, and it turned out that the heat preservation performance of PU board is the best, followed by EPS board, XPS board, PF board.

Keywords: porous materials, thermal conductivity, moisture content, transient hot-wire method

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Authors: Ahmad Javid Habib, Tetsuo Kidokoro

Abstract:

There is an increasing demand for developing urban land to provide better living conditions for all citizens in Afghanistan. Most of the development will involve the acquisition of land. And the current land acquisition method practiced by central government is expropriation, which is a cash-based transaction method that imposes heavy fiscal burden on local municipalities and central government, and it does not protect ownership rights and social equity of landowners besides it relocates the urban poor to remote areas with limited access to jobs and public services. The questionnaire analysis, backed by observations of different case studies in countries where land readjustment is used as a collaborative land development tool indicates that the method plays a key role in valuing landowners’ rights, giving other community members and stakeholders the opportunity to collaboratively implement urban development projects. The practice of the method is reducing the heavy fiscal burden on the local and central governments and is a better option to deal with the current development challenges in Afghanistan.

Keywords: collaboration, land readjustment, master plan, expropriation

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Authors: Waleed Basuliman

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Anthropometric dimensions are considered one of the important factors when designing human-machine systems. In this study, the estimation of anthropometric dimensions has been improved by using Artificial Neural Network (ANN) model that is able to predict the anthropometric measurements of Saudi males in Riyadh City. A total of 1427 Saudi males aged 6 to 60 years participated in measuring 20 anthropometric dimensions. These anthropometric measurements are considered important for designing the work and life applications in Saudi Arabia. The data were collected during eight months from different locations in Riyadh City. Five of these dimensions were used as predictors variables (inputs) of the model, and the remaining 15 dimensions were set to be the measured variables (Model’s outcomes). The hidden layers varied during the structuring stage, and the best performance was achieved with the network structure 6-25-15. The results showed that the developed Neural Network model was able to estimate the body dimensions of Saudi male population in Riyadh City. The network's mean absolute percentage error (MAPE) and the root mean squared error (RMSE) were found to be 0.0348 and 3.225, respectively. These results were found less, and then better, than the errors found in the literature. Finally, the accuracy of the developed neural network was evaluated by comparing the predicted outcomes with regression model. The ANN model showed higher coefficient of determination (R2) between the predicted and actual dimensions than the regression model.

Keywords: artificial neural network, anthropometric measurements, back-propagation

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Authors: Subzar Ahmad Bhat, Saraswati Setia, V. K.Sehgal

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During the past earthquakes, open ground storey buildings have performed poorly due to the soft storey defect. Indian Standard IS 1893:2002 allows analysis of open ground storey buildings without considering infill stiffness but with a multiplication factor 2.5 in compensation for the stiffness discontinuity. Therefore, the aim of this paper is to check the applicability of the multiplication factor of 2.5 and study behaviour of the structure after the application of the multiplication factor. For this purpose, study is performed on models considering infill stiffness using SAP 2000 (Version 14) by linear static analysis and response spectrum analysis. Total seven models are analysed and designed for the range of multiplication factor ranging from 1.25 to 2.5. The value of multiplication factor equal to 2.5 has been found on the higher side, resulting in increased dimension and percentage of reinforcement without significant enhancement beyond a certain multiplication factor. When the building with OGS is designed for values of MF higher than 1.25 considering infill stiffness soft storey effect shifts from ground storey to first storey. For the analysis of the OGS structure best way to analysis the structure is to analyse it as the frame with stiffness and strength of the infill taken into account. The provision of infill walls in the upper storeys enhances the performance of the structure in terms of displacement and storey drift controls.

Keywords: open ground storey, multiplication factor, IS 1893:2002 provisions, static analysis, response spectrum analysis, infill stiffness, equivalent strut

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Authors: Ruobing Liang, Jili Zhang, Chao Zhou

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A solar-heating-and-cooling (SHC) system, consisting of a hybrid photovoltaic/ thermal collector array, a hot water storage tank, and an absorption chiller unit is designed and modeled to satisfy thermal loads (space heating, domestic hot water, and space cooling). The system is applied for Dalian, China, a location with cold climate conditions, where cooling demand is moderate, while space heating demand is slightly high. The study investigates the potential of a solar system installed and operated onsite in a detached single-family household to satisfy all necessary thermal loads. The hot water storage tank is also connected to an auxiliary heater (electric boiler) to supplement solar heating, when needed. The main purpose of the study is to model the overall system and contact a parametric study that will determine the optimum economic system performance in terms of design parameters. The system is compared, through a cost analysis, to an electric heat pump (EHP) system. This paper will give the optimum system combination of solar collector area and volumetric capacity of the hot water storage tank, respectively.

Keywords: absorption chiller, solar PVT collector, solar heating and cooling, solar air-conditioning, parametric study, cost analysis

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Authors: Jean C. G. Silva, Kaline N. Ferreira, Rennio F. Sena, Flavio L. H. Silva

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The Prosopis juliflora (called algaroba in Northeastern Region of Brazil) is a species of medium to large size that can reach 18 meters high, being typical of arid and semi-arid regions by to requirement less water to survive; this is a fundamental attribute from its adaptation. It's considered of multiple uses, because the trunk, the fruit, and the algaroba pods are utilized for several purposes, among them, the production of wood from lumber mill, charcoal, alcohol, animal and human consumption, being hence, a culture of economic and social value. The use of waste Prosopis juliflora can be carried out for like pyrolysis and gasification processes, in order to energy production in those regions where it is grown. Thus this study aims to characterize the residue of the algaroba pods and evaluate the kinetic parameters, activation energy (Ea) and pre-exponential factor (k0), the devolatilization process through the data obtained from TG/DTG curves with different levels of heating rates. At work was used the heating rates of 5 K.min-1, 10 K.min-1, 15 K.min-1, 20 K.min-1 and 30 K.min-1, in inert nitrogen atmosphere (99.997%) under a flow of 40 ml.min-1. The kinetic parameters were obtained using the methods of Friedman and Ozawa-Flynn-Wall.

Keywords: activation energy, devolatilization, kinetic parameters, waste

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Authors: Shaker Aladwan, Paul Forrester

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This paper explores the challenges that face leaders when implementing business excellence programmes in the Jordanian public sector. The study adopted a content analysis approach to analyse the excellence assessment reports that have been produced by the King Abdullah II Centre for Excellence (KACE). The sample comprises ten public organisations which have participated in the King Abdullah Award for Excellence (KAA) more than once and acknowledge in their reports that they have failed to achieve satisfactory results. The key challenges to the implementation of leadership criteria in the public sector in Jordan were found to be poor strategic planning, lack of employee empowerment, weaknesses in benchmarking performance, a lack of financial resources, poor integration and coordination, and poor measurement system: This study proposes a conceptual model for the as assessment of challenges that face managers when seeking to implement excellence in leadership in the Jordanian public sector. Theoretically, this paper fills context gaps in the excellence literature in general and organisational excellence in the public sector in particular. Leadership challenges in the public sector are generally widely studied, but it is important to gain a better understanding of how these challenges can be overcome. In comparison to many existing studies, this research has provided specific and detailed insights these organisational excellence challenges in the public sector and provides a conceptual model for use by other researchers into the future.

Keywords: leadership criterion, organisational excellence, challenges, quality awards, public sector, Jordan

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