Search results for: 99.95% IoT data transmission savings

Authors: A. Qayed Al-Emadi, C. Schwabenland, Q. Wei, B. Czarnecka

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In 2009, the new HRM policy was implemented in Qatar for public sector organisations. The purpose of this research is to examine how Qatar’s 2009 HRM policy was significant in influencing employee retention in public organisations. The conducted study utilised quantitative methodology to analyse the data on employees’ perceptions of such HRM practices as performance çanagement, rewards and promotion, training and development associated with the HRM policy in public organisations in comparison to semi-private organisations. Employees of seven public and semi-private organisations filled in the questionnaire based on the 5-point likert scale to present quantitative results. The data was analysed with the correlation and multiple regression statistical analyses. It was found that Performance Management had the relationship with Employee Retention, and Rewards and Promotion influenced Job Satisfaction in public organisations. The relationship between Job Satisfaction and Employee Retention was also observed. However, no significant differences were observed in the role of HRM practices in public and semi-private organisations.

Keywords: performance management, rewards and promotion, training and development, job satisfaction, employee retention, SHRM, configurational perspective

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Authors: Abdulsamad Qadir Hussien

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This paper examines the impact of funders on the media industry in the Kurdistan Region Iraqi (henceforth KRI). The key objectives of the study are also looking at: how the media industry funder influences the media organization and journalists’ practices in the Kurdish community; how the media organizations attempt to utilize the available capabilities to serve the goals of the funded entities, whether they are parties, NGOs, governments, commercial companies or have individual ownership of media institutes. Further, the research project seeks to discover the influence and role of the funder on the media content and determine the prioritizing that will broadcast on the media. Furthermore, the project tries to understand to what extent the media organizations have a commitment to achieve the public interest and public affairs by following the key ethical principles. The study also attempts to explain the situation of the public service media. These variables are measured through a survey questionnaire distributed among a sample of 108 journalists and media practitioners. This research project, therefore, explores a new topic for study in the Kurdish community regarding the media industry, funding, and financial support. This article adopted surveys (n=108) as data collection tools by using a statistical method (SPSS 21). The data of the study have been tabulated, coded, and presented in a descriptive form.

Keywords: funding, journalists’ practices, Kurdish media industry, public services media

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Authors: Mustofa Mahmud Al Mamun

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Government spending, one of the major components of gross domestic product (GDP), is composed of government consumption, investment, and transfer payments. A change in government spending during recessionary periods can generate an increase in GDP greater than the increase in spending. This is called the "multiplier effect". Accurate estimation of government spending multiplier is important because fiscal policy has been used to stimulate a flagging economy. Many recent studies have focused on identifying parts of the economy that responds more to a stimulus under a variety of circumstances. This paper used the US dataset from 1966 to 2020 and local projection method assuming standard identification strategy to estimate the multipliers. The model includes important macroaggregates and controls for forecasted government spending, interest rate, consumer price index (CPI), export, import, and level of public debt. Investment multipliers are found to be positive and larger than the consumption multipliers. Consumption multipliers are either negative or not significantly different than zero. Results do not vary across the business cycle. However, the consumption multiplier estimated from pre-1980 data is positive.

Keywords: business cycle, consumption multipliers, forecasted government spending, investment multipliers, local projection method, zero lower bound

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Authors: Jose A. Diaz-Olivares, Nafise Mahdavian, Farhad Abtahi, Kaj Lindecrantz, Abdelakram Hafid, Fernando Seoane

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Despite new recommendations and guidelines for the evaluation of occupational risk assessments and their prevention, work-related musculoskeletal disorders are still one of the biggest causes of work activity disruption, productivity loss, sick leave and chronic work disability. It affects millions of workers throughout Europe, with a large-scale economic and social burden. These specific efforts have failed to produce significant results yet, probably due to the limited availability and high costs of occupational risk assessment at work, especially when the methods are complex, consume excessive resources or depend on self-evaluations and observations of poor accuracy. To overcome these limitations, a pervasive system of risk assessment tools in real time has been developed, which has the characteristics of a systematic approach, with good precision, usability and resource efficiency, essential to facilitate the prevention of musculoskeletal disorders in the long term. The system allows the combination of different wearable sensors, placed on different limbs, to be used for data collection and evaluation by a software solution, according to the needs and requirements in each individual working environment. This is done in a non-disruptive manner for both the occupational health expert and the workers. The creation of this solution allows us to attend different research activities that require, as an essential starting point, the recording of data with ergonomic value of very diverse origin, especially in real work environments. The software platform is here presented with a complimentary smart clothing system for data acquisition, comprised of a T-shirt containing inertial measurement units (IMU), a vest sensorized with textile electronics, a wireless electrocardiogram (ECG) and thoracic electrical bio-impedance (TEB) recorder and a glove sensorized with variable resistors, dependent on the angular position of the wrist. The collected data is processed in real-time through a mobile application software solution, implemented in commercially available Android-based smartphones and tablet platforms. Based on the collection of this information and its analysis, real-time risk assessment and feedback about postural improvement is possible, adapted to different contexts. The result is a tool which provides added value to ergonomists and occupational health agents, as in situ analysis of postural behavior can assist in a quantitative manner in the evaluation of work techniques and the occupational environment.

Keywords: ergonomics, mobile technologies, risk assessment, smart textiles

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Authors: Robertoes K. K. Wibowo, Siswoyo Soekarno, Irma Puspitasari

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Indonesian people use trains for their transportation, especially they use economy class train transportation because it is cheaper and has a more precise schedule than any other ground transportation. Nevertheless, the economy class passenger seat raises some inconvenience issues for passengers. This is due to the design of the chair on the economic class of trains that did not adjusted to the shape of anthropometry of Indonesian people. Thus, research needs to be conducted on the design of the seats in the economic class of trains. The purpose of this research is to make the design of economy class passenger seats ergonomic. This research method uses questionnaires and anthropometry measurements. The data obtained is processed using House of Quality of Ergonomic Function Development. From the results of analysis and data processing were obtained important changes from the original design. Ergonomic chair design according to the analysis is a stainless steel frame, seat height 390 mm, with a seat width for each passenger of 400 mm and a depth of 400 mm. Design of the backrest has a height of 840 mm, width of 430 mm and length of 300 mm that can move at the angle of 105-115 degrees. The width of the footrest is 42 mm and 400 mm length. The thickness of the seat cushion is 100 mm.

Keywords: chair, ergonomics, function development, train passenger

Procedia PDF Downloads 294

Authors: R. Premasiri, W. A. H. A. Abeygunasekara, S. M. Hewavidana, T. Jananthan, R. M. S. Madawala, K. Vaheeshan

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Forecasting the potential for disastrous events such as landslides has become one of the major necessities in the current world. Most of all, the landslides occurred in Sri Lanka are found to be triggered mostly by intense rainfall events. The study area is the landslide near Gerandiella waterfall which is located by the 41st kilometer post on Nuwara Eliya-Gampala main road in Kotmale Division in Sri Lanka. The landslide endangers the entire Kotmale town beneath the slope. Geographic Information System (GIS) platform is very much useful when it comes to the need of emulating the real-world processes. The models are used in a wide array of applications ranging from simple evaluations to the levels of forecast future events. This project investigates the possibility of developing a dynamic model to map the spatial distribution of the slope stability. The model incorporates several theoretical models including the infinite slope model, Green Ampt infiltration model and Perched ground water flow model. A series of rainfall values can be fed to the model as the main input to simulate the dynamics of slope stability. Hydrological model developed using GIS is used to quantify the perched water table height, which is one of the most critical parameters affecting the slope stability. Infinite slope stability model is used to quantify the degree of slope stability in terms of factor of safety. DEM was built with the use of digitized contour data. Stratigraphy was modeled in Surfer using borehole data and resistivity images. Data available from rainfall gauges and piezometers were used in calibrating the model. During the calibration, the parameters were adjusted until a good fit between the simulated ground water levels and the piezometer readings was obtained. This model equipped with the predicted rainfall values can be used to forecast of the slope dynamics of the area of interest. Therefore it can be investigated the slope stability of rainfall induced landslides by adjusting temporal dimensions.

Keywords: factor of safety, geographic information system, hydrological model, slope stability

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Authors: Ting Lu, Ya-Ru Diao, Fei Fan, Ye Xue, Lei Shi, Xian-e Tang, Meng-jun Zhan, Zhen-hua Deng

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Accurate adult age estimation (AAE) is a significant and challenging task in forensic and archeology fields. Attempts have been made to explore optimal adult age metrics, and the rib is considered a potential age marker. The traditional way is to extract age-related features designed by experts from macroscopic or radiological images followed by classification or regression analysis. Those results still have not met the high-level requirements for practice, and the limitation of using feature design and manual extraction methods is loss of information since the features are likely not designed explicitly for extracting information relevant to age. Deep learning (DL) has recently garnered much interest in imaging learning and computer vision. It enables learning features that are important without a prior bias or hypothesis and could be supportive of AAE. This study aimed to develop DL models for AAE based on CT images and compare their performance to the manual visual scoring method. Chest CT data were reconstructed using volume rendering (VR). Retrospective data of 2500 patients aged 20.00-69.99 years were obtained between December 2019 and September 2021. Five-fold cross-validation was performed, and datasets were randomly split into training and validation sets in a 4:1 ratio for each fold. Before feeding the inputs into networks, all images were augmented with random rotation and vertical flip, normalized, and resized to 224×224 pixels. ResNeXt was chosen as the DL baseline due to its advantages of higher efficiency and accuracy in image classification. Mean absolute error (MAE) was the primary parameter. Independent data from 100 patients acquired between March and April 2022 were used as a test set. The manual method completely followed the prior study, which reported the lowest MAEs (5.31 in males and 6.72 in females) among similar studies. CT data and VR images were used. The radiation density of the first costal cartilage was recorded using CT data on the workstation. The osseous and calcified projections of the 1 to 7 costal cartilages were scored based on VR images using an eight-stage staging technique. According to the results of the prior study, the optimal models were the decision tree regression model in males and the stepwise multiple linear regression equation in females. Predicted ages of the test set were calculated separately using different models by sex. A total of 2600 patients (training and validation sets, mean age=45.19 years±14.20 [SD]; test set, mean age=46.57±9.66) were evaluated in this study. Of ResNeXt model training, MAEs were obtained with 3.95 in males and 3.65 in females. Based on the test set, DL achieved MAEs of 4.05 in males and 4.54 in females, which were far better than the MAEs of 8.90 and 6.42 respectively, for the manual method. Those results showed that the DL of the ResNeXt model outperformed the manual method in AAE based on CT reconstruction of the costal cartilage and the developed system may be a supportive tool for AAE.

Keywords: forensic anthropology, age determination by the skeleton, costal cartilage, CT, deep learning

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Authors: Hossein Shabanali Fami, Omid Sharifi, Javad Ghasemi, Mahtab Pouratashi, Mona Sadat Moghadasian

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The main purpose of this study was to investigate perception of greenhouse vegetable growers regarding use of biological control practices during the growing season. The statistical population of the study included greenhouse vegetable growers in Jiroft county (N=1862). A sample of 137 vegetable growers was selected, using random sampling method. Data were collected via a questionnaire. The validity of the instrument was obtained by the faculty members of the Department of Agricultural Development and Management in the University of Tehran. Cronbach’s alpha was applied to estimate the reliability which showed a high reliability for the instrument. Data was analyzed using SPSS/Windows 13.5. The results revealed that greenhouse vegetable growers had moderate level of perception regarding biological control practices. Levels of vegetable growers’ perceptions regarding biological control practices were different on the basis of their academic qualifications as well as educational level and job. In addition, the results indicated that about 54.1% of variations in vegetable growers’ perceptions could be explained by variables such as awareness of biological control practices, knowledge on pests, annual production and age.

Keywords: greenhouse, biological control, biological agents, perception, vegetable grower

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Authors: Cahya Wimar Wicaksono, Reynara Davin Chen, Alvian Kristianto Santoso

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Grasberg Cu-Au ore deposit as one of the biggest porphyry deposits located in Papua Province, Indonesia produced by several intrusion that restricted by Heavy Sulphide Zone (HSZ) in peripheral. HSZ is the rock that becomes the contact between Grassberg Igneous Complex (GIC) with sedimentary and igneous rock outside, which is rich in sulphide minerals such as pyrite ± pyrrhotite. This research is to obtain the characteristic of HSZ based on geotechnical, geochemical and mineralogy aspect and those implication for daily mining operational activities. Method used in this research are geological and alteration mapping, core logging, FAA (Fire Assay Analysis), AAS (Atomic absorption spectroscopy), RQD (Rock Quality Designation) and rock water content. Data generated from methods among RQD data, mineral composition and grade, lithological and structural geology distribution in research area. The mapping data show that HSZ material characteristics divided into three type based on rocks association, there are near igneous rocks, sedimentary rocks and on HSZ area. And also divided based on its location, north and south part of research area. HSZ material characteristic consist of rock which rich of pyrite ± pyrrhotite, and RQD range valued about 25%-100%. Pyrite ± pyrrhotite which outcropped will react with H₂O and O₂ resulting acid that generates corrosive effect on steel wire and rockbolt. Whereas, pyrite precipitation proses in HSZ forming combustible H₂S gas which is harmful during blasting activities. Furthermore, the impact of H₂S gas in blasting activities is forming poison gas SO₂. Although HSZ high grade Cu-Au, however those high grade Cu-Au rich in sulphide components which is affected in flotation milling process. Pyrite ± pyrrhotite in HSZ will chemically react with Cu-Au that will settle in milling process instead of floating.

Keywords: combustible, corrosive, heavy sulphide zone, pyrite ± pyrrhotite

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Authors: Tarun Kumar Dalakoti, Debajyoti Majumder, Aditya Prasad Das, Samir Chandra Saxena

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India’s ambitious target to achieve a 50 percent share of energy from non-fossil fuels and the 500-gigawatt (GW) renewable energy capacity before the deadline of 2030, coupled with the global pursuit of sustainable development, will compel the nation to embark on a rapid clean energy transition. As a result, electricity market reforms will emerge as critical policy instruments to facilitate this transition and achieve ambitious environmental targets. This paper will present a comprehensive analysis of the various electricity market reforms to be introduced in the Indian Electricity sector to facilitate the integration of clean energy sources and will assess their impact on the overall energy landscape. The first section of this paper will delve into the policy mechanisms to be introduced by the Government of India and the Central Electricity Regulatory Commission to promote clean energy deployment. These mechanisms include extensive provisions for the integration of renewables in the Indian Electricity Grid Code, 2023. The section will also cover the projection of RE Generation as highlighted in the National Electricity Plan, 2023. It will discuss the introduction of Green Energy Market segments, the waiver of Inter-State Transmission System (ISTS) charges for inter-state sale of solar and wind power, the notification of Promoting Renewable Energy through Green Energy Open Access Rules, and the bundling of conventional generating stations with renewable energy sources. The second section will evaluate the tangible impact of these electricity market reforms. By drawing on empirical studies and real-world case examples, the paper will assess the penetration rate of renewable energy sources in India’s electricity markets, the decline of conventional fuel-based generation, and the consequent reduction in carbon emissions. Furthermore, it will explore the influence of these reforms on electricity prices, the impact on various market segments due to the introduction of green contracts, and grid stability. The paper will also discuss the operational challenges to be faced due to the surge of RE Generation sources as a result of the implementation of the above-mentioned electricity market reforms, including grid integration issues, intermittency concerns with renewable energy sources, and the need for increasing grid resilience for future high RE in generation mix scenarios. In conclusion, this paper will emphasize that electricity market reforms will be pivotal in accelerating the global transition towards clean energy systems. It will underscore the importance of a holistic approach that combines effective policy design, robust regulatory frameworks, and active participation from market actors. Through a comprehensive examination of the impact of these reforms, the paper will shed light on the significance of India’s sustained commitment to a cleaner, more sustainable energy future.

Keywords: renewables, Indian electricity grid code, national electricity plan, green energy market

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Authors: Ranadhir Roy

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Inverse problems arise in medical (molecular) imaging. These problems are characterized by large in three dimensions, and by the diffusion equation which models the physical phenomena within the media. The inverse problems are posed as a nonlinear optimization where the unknown parameters are found by minimizing the difference between the predicted data and the measured data. To obtain a unique and stable solution to an ill-posed inverse problem, a priori information must be used. Mathematical conditions to obtain stable solutions are established in Tikhonov’s regularization method, where the a priori information is introduced via a stabilizing functional, which may be designed to incorporate some relevant information of an inverse problem. Effective determination of the Tikhonov regularization parameter requires knowledge of the true solution, or in the case of optical imaging, the true image. Yet, in, clinically-based imaging, true image is not known. To alleviate these difficulties we have applied the penalty/modified barrier function (PMBF) method instead of Tikhonov regularization technique to make the inverse problems well-posed. Unlike the Tikhonov regularization method, the constrained optimization technique, which is based on simple bounds of the optical parameter properties of the tissue, can easily be implemented in the PMBF method. Imposing the constraints on the optical properties of the tissue explicitly restricts solution sets and can restore uniqueness. Like the Tikhonov regularization method, the PMBF method limits the size of the condition number of the Hessian matrix of the given objective function. The accuracy and the rapid convergence of the PMBF method require a good initial guess of the Lagrange multipliers. To obtain the initial guess of the multipliers, we use a least square unconstrained minimization problem. Three-dimensional images of fluorescence absorption coefficients and lifetimes were reconstructed from contact and noncontact experimentally measured data.

Keywords: constrained minimization, ill-conditioned inverse problems, Tikhonov regularization method, penalty modified barrier function method

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Authors: África Vicario, Fernando J. Álvarez, Felipe Parralejo, Fernando Aranda

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The irrigation systems of traditional agriculture, such as gravity-fed irrigation, produce a great waste of water because, generally, there is no control over the amount of water supplied in relation to the water needed. The AIRON Project tries to solve this problem by implementing an IoT-based system to sensor the irrigation plots so that the state of the crops and the amount of water used for irrigation can be known remotely. The IoT system consists of a sensor network that measures the humidity of the soil, the weather conditions (temperature, relative humidity, wind and solar radiation) and the irrigation water flow. The communication between this network and a central gateway is conducted by means of long-range wireless communication that depends on the characteristics of the irrigation plot. The main objective of the AIRON project is to deploy an IoT sensor network in two different plots of the irrigation community of Aranjuez in the Spanish region of Madrid. The first plot is 2 km away from the central gateway, so LoRa has been used as the base communication technology. The problem with this plot is the absence of mains electric power, so devices with energy-saving modes have had to be used to maximize the external batteries' use time. An ESP32 SOC board with a LoRa module is employed in this case to gather data from the sensor network and send them to a gateway consisting of a Raspberry Pi with a LoRa hat. The second plot is located 18 km away from the gateway, a range that hampers the use of LoRa technology. In order to establish reliable communication in this case, the long-term evolution (LTE) standard is used, which makes it possible to reach much greater distances by using the cellular network. As mains electric power is available in this plot, a Raspberry Pi has been used instead of the ESP32 board to collect sensor data. All data received from the two plots are stored on a proprietary server located at the irrigation management company's headquarters. The analysis of these data by means of machine learning algorithms that are currently under development should allow a short-term prediction of the irrigation water demand that would significantly reduce the waste of this increasingly valuable natural resource. The major finding of this work is the real possibility of deploying a remote sensing system for irrigated plots by using Commercial-Off-The-Shelf (COTS) devices, easily scalable and adaptable to design requirements such as the distance to the control center or the availability of mains electrical power at the site.

Keywords: internet of things, irrigation water control, LoRa, LTE, smart farming

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Authors: Sushil Kumar Saraswat, K. K. Pant

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Co metal supported on SiO2 and Al2O3 catalysts with a metal loading varied from 30 of 70 wt.% were evaluated for decomposition of methane to CO/CO2 free hydrogen and carbon nano materials. The catalytic runs were carried out from 550-800 oC under atmospheric pressure using fixed bed vertical flow reactor. The fresh and spent catalysts were characterized by BET surface area analyzer, TPR, XRD, SEM, TEM, and TG analysis. The data showed that 50% Co/Al2O3 catalyst exhibited remarkable higher activity and stability up to 10 h time-on-stream at 750 oC with respect to H2 production compared to rest of the catalysts. However, the catalytic activity and durability was greatly declined at a higher temperature. The main reason for the catalytic inhibition of Co containing SiO2 catalysts is the higher reduction temperature of Co2SiO4. TEM images illustrate that the carbon materials with various morphologies, carbon nanofibers (CNFs), helical-shaped CNFs, and branched CNFs depending on the catalyst composition and reaction temperature, were obtained. The TG data showed that a higher yield of MWCNTs was achieved over 50% Co/Al2O3 catalyst compared to other catalysts.

Keywords: carbon nanotubes, cobalt, hydrogen production, methane decomposition

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Authors: Soma Chatterjee, I. Das

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In the present study, we have investigated the structural, electrical and magneto-transport properties of polycrystalline and nanocrystalline Gd0.5Sr0.5MnO3 compounds. The variation of transport properties is modified by tuning the grain size of the material. In the high-temperature semiconducting region, temperature-dependent resistivity data can be well explained by the non-adiabatic small polaron hopping (SPH) mechanism. In addition, the resistivity data for all compounds in the low-temperature paramagnetic region can also be well explained by the variable range hopping (VRH) model. The parameters obtained from SPH and VRH mechanisms are found to be reasonable. In the case of nanocrystalline compounds, there is an overlapping temperature range where both SPH and VRH models are valid simultaneously, and a new conduction mechanism - variable range hopping of small polaron s(VR-SPH) is satisfactorily valid for the whole temperature range of these compounds. However, for the polycrystalline compound, the overlapping temperature region between VRH and SPH models does not exist and the VR-SPH mechanism is not valid here. Thus, polarons play a leading role in selecting different conduction mechanisms in different temperature ranges.

Keywords: electrical resistivity, manganite, small polaron hopping, variable range hopping, variable range of small polaron hopping

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Authors: T. Wejrzanowski, M. Grybczuk, E. Tymicki, K. J. Kurzydlowski

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In the present study numerical simulations silicon carbide single crystal growth process in Physical Vapor Transport reactor are addressed. Silicon Carbide is a perspective material for many applications in modern electronics. One of the main challenges for wider applications of SiC is high price of high quality mono crystals. Improvement of silicon carbide manufacturing process has a significant influence on the product price. Better understanding of crystal growth allows for optimization of the process, and it can be achieved by numerical simulations. In this work Virtual Reactor software was used to simulate the process. Predicted geometrical properties of the final product and information about phenomena occurring inside process reactor were obtained. The latter is especially valuable because reactor chamber is inaccessible during the process due to high temperature inside the reactor (over 2000˚C). Obtained data was used for improvement of the process and reactor geometry. Resultant crystal quality was also predicted basing on crystallization front shape evolution and threading dislocation paths. Obtained results were confronted with experimental data and the results are in good agreement.

Keywords: Finite Volume Method, semiconductors, Physical Vapor Transport, silicon carbide

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Authors: Ejoh Nonso Francis

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: Irrigation scheduling is a critical aspect of sustainable agriculture as it ensures optimal use of water resources, reduces water waste, and enhances crop yields. This paper presents a case study of a farm in Onitsha, Anambra State, Nigeria, where irrigation scheduling was optimized using a combination of soil moisture sensors and weather data. The study aimed to evaluate the effectiveness of this approach in improving water use efficiency and crop productivity. The results showed that the optimized irrigation scheduling approach led to a 30% reduction in water use while increasing crop yield by 20%. The study demonstrates the potential of technology-based irrigation scheduling to enhance sustainable agriculture in Nigeria and beyond.

Keywords: irrigation scheduling, sustainable agriculture, soil moisture sensors, weather data, water use efficiency, crop productivity, nigeria, onitsha, anambra state, technology-based irrigation scheduling, water resources, environmental degradation, crop water requirements, overwatering, water waste, farming systems, scalability

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Authors: Oktavian Prasetia Wardana, Martono Tri Utomo, Risa Etika, Kartika Darma Handayani, Dina Angelika, Wurry Ayuningtyas

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Background: Critically ill neonates are newborn babies with high-risk factors that potentially cause disability and/or death. Scoring systems for determining the severity of the disease have been widely developed as well as some designs for use in neonates. The SNAPPE-II method, which has been used as a mortality predictor scoring system in several referral centers, was found to be slow in assessing the outcome of critically ill neonates in the Neonatal Intensive Care Unit (NICU). Objective: To analyze the predictive value of MSNS on the outcome of critically ill neonates at the time of arrival up to 24 hours after being admitted to the NICU. Methods: A longitudinal observational analytic study based on medical record data was conducted from January to August 2022. Each sample was recorded from medical record data, including data on gestational age, mode of delivery, APGAR score at birth, resuscitation measures at birth, duration of resuscitation, post-resuscitation ventilation, physical examination at birth (including vital signs and any congenital abnormalities), the results of routine laboratory examinations, as well as the neonatal outcomes. Results: This study involved 105 critically ill neonates who were admitted to the NICU. The outcome of critically ill neonates was 50 (47.6%) neonates died, and 55 (52.4%) neonates lived. There were more males than females (61% vs. 39%). The mean gestational age of the subjects in this study was 33.8 ± 4.28 weeks, with the mean birth weight of the subjects being 1820.31 ± 33.18 g. The mean MSNS score of neonates with a deadly outcome was lower than that of the lived outcome. ROC curve with a cut point MSNS score <10.5 obtained an AUC of 93.5% (95% CI: 88.3-98.6) with a sensitivity value of 84% (95% CI: 80.5-94.9), specificity 80 % (CI 95%: 88.3-98.6), Positive Predictive Value (PPV) 79.2%, Negative Predictive Value (NPV) 84.6%, Risk Ratio (RR) 5.14 with Hosmer & Lemeshow test results p>0.05. Conclusion: The MSNS score has a good predictive value and good calibration of the outcomes of critically ill neonates admitted to the NICU.

Keywords: critically ill neonate, outcome, MSNS, NICU, predictive value

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Authors: Eylem G. Cengiz, Ersin Çilek, Gözde Başkaya, Havva Nur Taş

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It is possible to define the abuse and neglect of the child as a social problem. Such adverse experiences of the child are witnessed by wider social circles as well as his or her immediate environment. The most effective institution among these social circles is the school. The awareness of teachers, administrators, and even auxiliary personnel on this issue can act as a protective and preventive buffer because teachers have the opportunity to be with children every day and constantly observe them; therefore, they can notice the physical and mental changes in students. Furthermore, school administrators have an undeniable role in recognizing and responding to the risk of neglect and abuse. This study aims to evaluate the awareness of school administrators on the risk factors, clues, and ways of intervention towards abuse and neglect through the scenarios given to them. Data were collected from 37 primary, secondary, and high school administrators working in various provinces of Turkey through descriptive and scenario-based questions to determine their general knowledge of the concepts of neglect and abuse and their general tendencies towards practice. Descriptive questions were evaluated with content analysis, and scenario-based questions were evaluated with numerical qualitative data analysis. Concepts and themes were tried to be reached by content analysis from the descriptive data collected. When the results are evaluated in general, it is striking that the concept of child abuse means only sexual abuse for some school administrators. There is an important uncertainty for school administrators in the content of the idea of neglect. When the views on the causes of neglect and abuse are examined, the family factor was seen as the primary source of both neglect and abuse. In addition, among the prevention strategies applied by school administrators, intervention for the family -interviewing and informing- was recommended by only 9 (29%) out of 31 administrators. When the responses to the physical, emotional, and sexual abuse scenarios are examined, it is revealed that the administrators generally realize the abuse but fail to develop an appropriate/whole intervention method. The research results show that school administrators' awareness should be increased. Although administrators have sensitivity towards children, they should be empowered to recognize all types of neglect and abuse and develop appropriate intervention tools.

Keywords: assessment child abuse and neglect, child abuse, child neglect, school administrators

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Authors: Marjan Golmaryami, Marzieh Behzadi

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Recent developments in stock exchange highlight the need for an efficient and accurate method that helps stockholders make better decision. Since stock markets have lots of fluctuations during the time and different effective parameters, it is difficult to make good decisions. The purpose of this study is to employ artificial neural network (ANN) which can deal with time series data and nonlinear relation among variables to forecast next day stock price. Unlike other evolutionary algorithms which were utilized in stock exchange prediction, we trained our proposed neural network with metaheuristic bat algorithm, with fast and powerful convergence and applied it in stock price prediction for the first time. In order to prove the performance of the proposed method, this research selected a 7 year dataset from Parsian Bank stocks and after imposing data preprocessing, used 3 types of ANN (back propagation-ANN, particle swarm optimization-ANN and bat-ANN) to predict the closed price of stocks. Afterwards, this study engaged MATLAB to simulate 3 types of ANN, with the scoring target of mean absolute percentage error (MAPE). The results may be adapted to other companies stocks too.

Keywords: artificial neural network (ANN), bat algorithm, particle swarm optimization algorithm (PSO), stock exchange

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Authors: J. Julius Adebayo

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The objective of this paper is to assess the agro-climatic condition of Ibadan in the rain forest ecological zone of Nigeria, using rainfall pattern and temperature between 1978-2018. Data on rainfall and temperature in Ibadan, Oyo State for a period of 40 years were obtained from Meteorological Section of Forestry Research Institute of Nigeria, Ibadan and Oyo State Meteorology Centre. Time series analysis was employed to analyze the data. The trend revealed that rainfall is decreasing slowly and temperature is averagely increasing year after year. The model for rainfall and temperature are Yₜ = 1454.11-8*t and Yₜ = 31.5995 + 2.54 E-02*t respectively, where t is the time. On this basis, a forecast of 20 years (2019-2038) was generated, and the results showed a further downward trend on rainfall and upward trend in temperature, this indicates persistence rainfall shortage and very hot weather for agricultural practices in the southwest rain forest ecological zone. Suggestions on possible solutions to avert climate change crisis and also promote climate-smart agriculture for sustainable food and nutrition security were also discussed.

Keywords: climate change, rainfall pattern, temperature, time series analysis, food and nutrition security

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Authors: Satish Kumar Pappu

Abstract:

The most common questions which are frequently asked in oil and gas industry are how much is the current production rate from a particular well and what is the approximate predicted life of that well. These questions can be answered through forecasting of important realistic data like flowing tubing hole pressures FTHP, Production decline curves which are used predict the future performance of a well in a reservoir. With the advent of directional drilling, cluster well drilling has gained much importance and in-fact has even revolutionized the whole world of oil and gas industry. An oil or gas reservoir can generally be described as a collection of several overlying, producing and potentially producing sands in to which a number of wells are drilled depending upon the in-place volume and several other important factors both technical and economical in nature, in some sands only one well is drilled and in some, more than one. The aim of this study is to derive important information from the data collected over a period of time at regular intervals on a depleted well in a reservoir sand and apply this information to predict the performance of other wells in that reservoir sand. The depleted wells are the most common observations when an oil or gas field is being visited, w the application of this study more realistic in nature.

Keywords: decline curve analysis, estimation of future gas reserves, reservoir sands, reservoir risk profile

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Authors: Christopher J. Johnston

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This paper presents the finding of a research study in which novice (first and second year) elementary teachers (grades Kindergarten – six) evaluated various mathematics Virtual Manipulatives, websites, and Applets (tools) for use in mathematics instruction. Participants identified the criteria they used for evaluating these types of resources and provided recommendations for or against five pre-selected tools. During the study, participants participated in three data collection activities: (1) A brief Likert-scale survey which gathered information about their attitudes toward technology use; (2) An identification of criteria for evaluating technology tools; and (3) A review of five pre-selected technology tools in light of their self-identified criteria. Data were analyzed qualitatively using four theoretical categories (codes): Software Features (41%), Mathematics (26%), Learning (22%), and Motivation (11%). These four theoretical categories were then grouped into two broad categories: Content and Instruction (Mathematics and Learning), and Surface Features (Software Features and Motivation). These combined, broad categories suggest novice teachers place roughly the same weight on pedagogical features as they do technological features. Implications for mathematics teacher educators are discussed, and suggestions for future research are provided.

Keywords: mathematics education, novice teachers, technology, virtual manipulatives

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Authors: Hsin-Yang Wang, K. M. A. Salam, Ying-Jia Lin, Daniel Tan, Tzu-Hsuan Chou, Hung-Yu Kao

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Detecting user intent from natural language expression has a wide variety of use cases in different natural language processing applications. Recently few-shot training has a spike of usage on commercial domains. Due to the lack of significant sample features, the downstream task performance has been limited or leads to an unstable result across different domains. As a state-of-the-art method, the pre-trained BERT model gathering the sentence-level information from a large text corpus shows improvement on several NLP benchmarks. In this research, we are proposing a method to change multi-class classification tasks into binary classification tasks, then use the confidence score to rank the results. As a language model, BERT performs well on sequence data. In our experiment, we change the objective from predicting labels into finding the relations between words in sequence data. Our proposed method achieved 71.0% accuracy in the internal intent detection dataset and 63.9% accuracy in the HuffPost dataset. Acknowledgment: This work was supported by NCKU-B109-K003, which is the collaboration between National Cheng Kung University, Taiwan, and SoftBank Corp., Tokyo.

Keywords: OSML, BERT, text classification, one shot

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Authors: Ioanna Pagoni, Annitsa Koumoutsidi

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The aim of this paper is to estimate the efficiency of airports that are located in touristic regions. It focuses on the regional airports of Greece, which are located at the mainland and the islands that constitute touristic destinations. Most of these airports share the following characteristics. They operate at levels below capacity with a high level of seasonality to their traffic. In addition, in such airports, the operation of charter and low-cost airlines is significant. The efficiency of the study airports is calculated by using the non-parametric data envelopment analysis during the period of 2010-2016. The selected inputs include several airport infrastructure measures such as passenger terminal size, aircraft parking area, runway length, and the number of check-in counters, while the number of employees in each airport is also used. The number of passengers and aircraft movements are selected as outputs. The effect of seasonality, as well as the operation of charter airlines and low-cost carriers on airport efficiency, is estimated by running proper regression models. Preliminary findings indicate that low-cost and charter airlines contribute to increasing airport efficiency for most of the study airports. The results of this research could be useful for airlines, airport operators, hotel businesses, and other tourism-related operators.

Keywords: airport efficiency, data envelopment analysis, low-cost carriers, charter airlines, seasonality

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Authors: Guerrero Ramírez Sandra, Ramos Salinas Norma Maricela, Muriel Amezcua Vanesa

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This article presents the beginning of a wider study that intends to demonstrate how within organizations of the automotive industry from the city of Querétaro. Knowledge management and technological management are required, as well as people’s initiative and the interaction embedded at the interior of it, with the appropriate environment that facilitates information conversion with wide information technologies management (ITM) range. A company was identified for the pilot study of this research, where descriptive and inferential research information was obtained. The results of the pilot suggest that some respondents did noted entity the knowledge management topic, even if staffs have access to information technology (IT) that serve to enhance access to knowledge (through internet, email, databases, external and internal company personnel, suppliers, customers and competitors) data, this implicates that there are Knowledge Management (KM) problems. The data shows that academically well-prepared organizations normally do not recognize the importance of knowledge in the business, nor in the implementation of it, which at the end is a great influence on how to manage it, so that it should guide the company to greater in sight towards a competitive strategy search, given that the company has an excellent technological infrastructure and KM was not exploited. Cultural diversity is another factor that was observed by the staff.

Keywords: Knowledge Management (KM), Technological Knowledge Management (TKM), Technology Information Management (TI), access to knowledge

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Authors: Aiman Mazhar Qureshi, Ahmed Rachid

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Extreme heat events are emerging human environmental health concerns in dense urban areas due to anthropogenic activities. High spatial and temporal resolution heat maps are important for urban heat adaptation and mitigation, helping to indicate hotspots that are required for the attention of city planners. The Heat Vulnerability Index (HVI) is the important approach used by decision-makers and urban planners to identify heat-vulnerable communities and areas that require heat stress mitigation strategies. Amiens is a medium-sized French city, where the average temperature has been increasing since the year 2000 by +1°C. Extreme heat events are recorded in the month of July for the last three consecutive years, 2018, 2019 and 2020. Poor air quality, especially ground-level ozone, has been observed mainly during the same hot period. In this study, we evaluated the HVI in Amiens during extreme heat days recorded last three years (2018,2019,2020). The Principal Component Analysis (PCA) technique is used for fine-scale vulnerability mapping. The main data we considered for this study to develop the HVI model are (a) socio-economic and demographic data; (b) Air pollution; (c) Land use and cover; (d) Elderly heat-illness; (e) socially vulnerable; (f) Remote sensing data (Land surface temperature (LST), mean elevation, NDVI and NDWI). The output maps identified the hot zones through comprehensive GIS analysis. The resultant map shows that high HVI exists in three typical areas: (1) where the population density is quite high and the vegetation cover is small (2) the artificial surfaces (built-in areas) (3) industrial zones that release thermal energy and ground-level ozone while those with low HVI are located in natural landscapes such as rivers and grasslands. The study also illustrates the system theory with a causal diagram after data analysis where anthropogenic activities and air pollution appear in correspondence with extreme heat events in the city. Our suggested index can be a useful tool to guide urban planners and municipalities, decision-makers and public health professionals in targeting areas at high risk of extreme heat and air pollution for future interventions adaptation and mitigation measures.

Keywords: heat vulnerability index, heat mapping, heat health-illness, remote sensing, urban heat mitigation

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Authors: Bojan Najdenov, Danco Davcev

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Reduction of traffic congestions and the effects of pollution and waste of resources that come with them has been a big challenge in the past decades. Having reliable systems to facilitate the process of modeling and prediction of traffic conditions would not only reduce the environmental pollution, but will also save people time and money. Social networks play big role of people’s lives nowadays providing them means of communicating and sharing thoughts and ideas, that way generating huge knowledge bases by crowdsourcing. In addition to that, crowdsourcing as a concept provides mechanisms for fast and relatively reliable data generation and also many services are being used on regular basis because they are mainly powered by the public as main content providers. In this paper we present the Social-NETS-Traffic-Control System (SNTCS) that should serve as a facilitator in the process of modeling and prediction of traffic congestions. The main contribution of our system is to integrate data from social networks as Twitter and also implements a custom created crowdsourcing subsystem with which users report traffic conditions using an android application. Our first experience of the usage of the system confirms that the integrated approach allows easy extension of the system with other social networks and represents a very useful tool for traffic control.

Keywords: traffic, congestion reduction, crowdsource, social networks, twitter, android

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Authors: Elisa Bertagna

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A frame analysis of the work done by various energy multinational companies concerning diversity issues and gender equality is presented. Documents of four multinational companies - two from Finland and two from Italy - have been studied. The array of companies’ documents includes data from their websites, policies and so on. The Finnish and Italian contexts have been chosen as a sample of North and South Europe, of 'advanced' and 'less advanced'. The aim of the analysis is to understand if and how human resource and diversity management in Finnish and Italian multinational energy companies communicate their activity towards the employees. Attention is given on how employees are reacting in their role and on the consequences of its social positioning. The findings of this essay are crucially important. They show how the companies in object tend to focus on the HR and DM positive actions towards female employees’ struggles since the industry is characterized by multinationals with male-dominated employees. In this way, other categories, which are also depicted as sensitive such as young and elderly people or foreigners, do not receive the same amount of attention. Consequently, power hierarchies can be found: 'women' as a social category are given more importance and space in the companies’ data than others. Consequently, the present work analysis reflects on possible struggles that such companies might be facing concerning gender biases and further diverse issues.

Keywords: energy, diversity, gender, multinationals, power hierarchies

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Authors: Chen-Yuan Hsu

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Introduction Elderly is growing and results to live in the long-term care (LTC) and then due to the routine of the facilities in Taiwan, also resulted to losing of those people with environment interaction, so, the self-reliance support (SRS) for those people to experience environment interaction is an essential. Methods This study was recruited samples of a LTC in the central of Taiwan. There was a following research on the SRS group with 20 samples collected and routine care group with 20 samples. A structured questionnaire as the Environment Interaction Dimension, as data collection included demographic information and the dimensions of environment interaction. Data analysis used SPSS 22.0 for Window 2000 to report the finding. Results The Environment Interaction Dimension for Taiwanese is a Chinese version of the containing 8 items. The result of t-test analysis found that environment interaction showed a significant difference between groups (p＜.05), the result recommended that there was a higher score of environment interaction dimension on the SRS group (29.90±5.56) comparing with the routine care group (22.1±5.53). Conclusion This study showed that the SRS group was higher than the routine care group on the environment interaction dimension for Taiwanese elderly living in the LTC. The results can also provide the reference for LTC, to encourage those people to participate in SRS in LTC, and therefore also improving their environment interaction.

Keywords: self-reliance support, environment interaction, long-term care, elderly

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Authors: Cuong V Nguyen, Ralph Horne, John Fien, France Cheong

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Social vulnerability to climate change is increasingly being acknowledged, and proposals to measure and manage it are emerging. Building upon this work, this paper proposes an approach to social vulnerability assessment using a new mechanism to aggregate and account for causal relationships among components of a Social Vulnerability Index (SVI). To operationalize this index, the authors propose a means to develop an appropriate primary dataset, through application of a specifically-designed household survey questionnaire. The data collection and analysis, including calibration and calculation of the SVI is demonstrated through application in case study city in central coastal Vietnam. The calculation of SVI at the fine-grained local neighbourhood scale provides high resolution in vulnerability assessment, and also obviates the need for secondary data, which may be unavailable or problematic, particularly at the local scale in developing countries. The SVI household survey is underpinned by the results of a Delphi survey, an in-depth interview and focus group discussions with local environmental professionals and community members. The research reveals inherent limitations of existing SVIs but also indicates the potential for their use in assessing social vulnerability and making decisions associated with responding to climate change at the local scale.

Keywords: climate change, local scale, social vulnerability, social vulnerability index

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