Search results for: data analyses

Authors: S. Adjiri-Bailiche, S. M. Boudia, H. Daaou, S. Hadouche, A. Benzaoui

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In this work the study of changes in the wind speed depending on the altitude is calculated and described by the model of the neural networks, the use of measured data, the speed and direction of wind, temperature and the humidity at 10 m are used as input data and as data targets at 50m above sea level. Comparing predict wind speeds and extrapolated at 50 m above sea level is performed. The results show that the prediction by the method of artificial neural networks is very accurate.

Keywords: MATLAB, neural network, power low, vertical extrapolation, wind energy, wind speed

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Authors: Ahmad Badawi Saluy, Novawiguna Kemalasari

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This study aims to examine, analyze and explain the impacts of compensation, career development and employee engagement to employee’s performance partially and simultaneously (Case Study at PT Bank XYZ). The research design used is quantitative descriptive research causality involving 30 respondents. Sources of data are from primary and secondary data, primary data obtained from questionnaires distribution and secondary data obtained from journals and books. Data analysis used model test using smart application PLS 3 that consists of test outer model and inner model. The results showed that compensation, career development and employee engagement partially have a positive impact on employee performance, while they have a positive and significant impact on employee performance simultaneously. The independent variable has the greatest impact is the employee engagement.

Keywords: compensation, career development, employee engagement, employee performance

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Authors: Thomas L. McCullough, John D. Hague, Marylesa M. Howard, Matthew K. Kiser, Michael A. Mazur, Lance K. McLean, Johanna L. Turk

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Radiological search and mapping depends on the successful recognition of anomalies in large data sets which contain varied and dynamic backgrounds. We present a new algorithmic approach for real-time anomaly detection which is resistant to common detector imperfections, avoids the limitations of a source template library and provides immediate, and easily interpretable, user feedback. This algorithm is based on a continuous wavelet transform for variance reduction and evaluates the deviation between a foreground measurement and a local background expectation using methods from linear algebra. We also present a technique for recognizing and visualizing spectrally similar clusters of data. This technique uses Laplacian Eigenmap Manifold Learning to perform dimensional reduction which preserves the geometric "closeness" of the data while maintaining sensitivity to outlying data. We illustrate the utility of both techniques on real-world data sets.

Keywords: radiological search, radiological mapping, radioactivity, radiation protection

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Authors: Teresa Sarmento de Beires, Sofia Padilha, Pedro Arantes, Joana Ribeiro, Andreia Eiras

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Background: Trichotillomania is a psychiatric condition that is very challenging to treat, with no first-line medications approved by any medical agency. It is defined as a recurrent compulsive habit of pulling out one's own hair, usually from the scalp and eyebrows area, but it can also affect eyelashes or any other hair-bearing area. N-acetylcysteine, a glutamate modulator, has been studied as a possible treatment for several psychiatric and neurological disorders, considering its role in attenuating pathophysiological processes responsible for compulsive behaviors and, therefore, trichotillomania. Objective: This study aims to determine the efficacy of N-acetylcysteine in the treatment of adults with trichotillomania. Methodology: The authors researched guidelines, standards of clinical guidance, systematic reviews, meta-analyses, and randomized clinical trials, published in the last 20 years using the MeSH terms: "Trichotillomania” and “N-acetylcysteine” in the following databases: PubMed, Cochrane library, National Guideline Clearing House, National Institute of Health and Care Excellence (NICE), Canadian Medical Association Practice Guidelines and Database of Abstracts of Reviews of Effectiveness (DARE). The Strength of Recommendation Taxonomy (SORT) Scale, from the American Family Physician, was used to evaluate the level of evidence and assign the strength of recommendation. Results: The research found fifteen articles, among which only three were eligible according to the inclusion criteria: 1. systematic review and 2. meta-analyses. There was evidence of a probable beneficial effect of N-acetylcysteine on treatment response and reduction of trichotillomania symptom severity in adults, with moderate certainty in the effect estimate. There was no evidence of effectiveness with the use of inositol, antioxidants, naltrexone, or selective serotonin reuptake inhibitors (SSRIs) in the treatment of adults with trichotillomania. Clomipramine and Olanzapine showed potential treatment benefits, with low certainty. N-acetylcysteine had the least severe side effect profile in adults compared with the other potentially beneficial pharmacological treatments. Conclusion: Evidence points towards the effectiveness of N-acetylcysteine in the treatment of adults with trichotillomania, which exhibits a good tolerability profile with minimal adverse effects. Therefore, the authors attribute a level of evidence 2, the strength of recommendation B, to the prescription of N-acetylcysteine in the treatment of adults suffering from trichotillomania (SORT analysis). Further investigation is needed in order to extract high-quality conclusions from the meta-analysis.

Keywords: trichotillomania, hair pulling, treatment, n-acetylcysteine

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Authors: Rhaed Khiati, Muhammad Hanif

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In the past decade, smart healthcare systems have been on an ascendant drift, especially with the evolution of hospitals and their increasing reliance on bioinformatics and software specializing in healthcare. Doctors have become reliant on technology more than ever, something that in the past would have been looked down upon, as technology has become imperative in reducing overall costs and improving the quality of patient care. With patient-doctor interactions becoming more necessary and more complicated than ever, systems must be developed while taking into account costs, patient comfort, and patient data, among other things. In this work, we proposed a smart hospital bed, which mixes the complexity and big data usage of traditional healthcare systems with the comfort found in soft beds while taking certain concerns like data confidentiality, security, and maintaining SLA agreements, etc. into account. This research work potentially provides users, namely patients and doctors, with a seamless interaction with to their respective nurses, as well as faster access to up-to-date personal data, including prescriptions and severity of the condition in contrast to the previous research in the area where there is lack of consideration of such provisions.

Keywords: big data, smart healthcare, distributed systems, bioinformatics

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Authors: Tero Huhtala, Minna Pikkarainen, Saila Saraniemi

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Information technology has long been used as an enabler of exchange for goods and services. Services are evolving from generic to personalized, and the reverse use of customer data has been discussed in both academia and industry for the past few years. This article presents the results of an empirical case study in the area of preventive health care services. The primary data were gathered in workshops, in which future personal data-based services were conceptualized by analyzing future scenarios from a business perspective. The aim of this study is to understand business model transformation in emerging personal data ecosystems. The work was done as a case study in the context of occupational healthcare. The results have implications to theory and practice, indicating that adopting personal data management principles requires transformation of the business model, which, if successfully managed, may provide access to more resources, potential to offer better value, and additional customer channels. These advantages correlate with the broadening of the business ecosystem. Expanding the scope of this study to include more actors would improve the validity of the research. The results draw from existing literature and are based on findings from a case study and the economic properties of the healthcare industry in Finland.

Keywords: ecosystem, business model, personal data, preventive healthcare

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Authors: Merav Ben Natan, May Revach, Or Sade, Yaniv Yonay, Yaron Berkovich

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Background: The inclusion of nurse practitioners (NPs) specializing in orthopedics holds promise for enhancing the quality of care for orthopedic patients. Understanding patients’ perspectives on this role is crucial for evaluating the feasibility and acceptance of integrating NPs into orthopedic settings. This study aims to explore the receptiveness of orthopedic patients to treatment by orthopedic NPs and examines potential associations between patients’ willingness to engage with NPs, their familiarity with the NP role, perceptions of nursing, and satisfaction with orthopedic nursing care. Methods: This cross-sectional study involved patients admitted to an orthopedic department at a central Israeli hospital between January and February 2023. Data was collected using a validated questionnaire consisting of five sections, reviewed by content experts. Statistical analyses were conducted using SPSS and included descriptive statistics, independent samples t-tests, Pearson correlations, and linear regression. Results: Participants in the study showed a moderate willingness to receive treatment from orthopedic NPs, with more than two-thirds expressing strong openness. Patients were generally receptive to NPs performing various clinical tasks, though there was less enthusiasm for NPs’ involvement in medication management and preoperative evaluations. Positive attitudes towards nurses and familiarity with the NP role were significant predictors of patient receptiveness to NP treatment. Conclusion: Patient acceptance of orthopedic NPs varies across different aspects of care. While there is a general willingness to receive care from NPs, these nuanced preferences must be considered when implementing NPs in orthopedic settings. Awareness and positive perceptions of the NP role play crucial roles in shaping patients’ willingness to engage with NPs.

Keywords: orthopedic nurse practitioners, patient receptiveness, perceptions of nursing, clinical tasks

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Authors: Syed Nauman Bin Asghar Bukhari, Mohtashim Mansoor, Mohammad Nouman

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Engine test-Bed system is a fundamental tool to measure dynamic parameters, economic performance, and reliability of an aircraft Engine, and its automation and accuracy directly influences the precision of acquired and analysed data. In this paper, we present the design of digital Data Acquisition (DAQ) system for a vintage aircraft engine test bed that lacks the capability of displaying all the analyzed parameters at one convenient location (one panel-one screen). Recording such measurements in the vintage test bed is not only time consuming but also prone to human errors. Digitizing such measurement system requires a Data Acquisition (DAQ) system capable of recording these parameters and displaying them on one screen-one panel monitor. The challenge in designing upgrade to the vintage systems arises with a need to build and integrate digital measurement system from scratch with a minimal budget and modifications to the existing vintage system. The proposed design not only displays all the key performance / maintenance parameters of the gas turbine engines for operator as well as quality inspector on separate screens but also records the data for further processing / archiving.

Keywords: Gas turbine engine, engine test cell, data acquisition, instrumentation

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Authors: Mohammed Mesrar, Hamza El Malki, Hamza Mesrar

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In this study, ceramics of (1-x)(Na0.5Bi0.5)TiO3 x(K0.5 Bi0.5)TiO3 were synthesized through a conventional calcination process (solid-state method) at 1000°C for 4 hours, with x(%) values ranging from 0.0 to 100. Room temperature XRD patterns confirmed the phase formation of the samples. The Rietveld refinement method was employed to verify the morphotropic phase boundary (MPB) at x(%)=16-20. We investigated the average crystallite size and lattice strain using Scherrer's formula and Williamson-Hall (W-H) analysis. SEM image analyses provided additional evidence of the impact of doping on structural growth under low temperatures. Relaxation time extracted from Z″(f) and M″(f) spectra for x(%) = 0.0, 12, 16, 20, and 30 followed the Arrhenius law, revealing the presence of three distinct relaxation mechanisms with varying activation energies. The shoulder response in M″(f) indirectly indicated the existence of highly polarizable entities in the samples, serving as a signature of polar nanoregions (PNRs) within the grains.In this study, ceramics of (1-x)(Na0.5Bi0.5)TiO3 x(K0.5 Bi0.5)TiO3 were synthesized through a conventional calcination process (solid-state method) at 1000°C for 4 hours, with x(%) values ranging from 0.0 to 100. Room temperature XRD patterns confirmed the phase formation of the samples. The Rietveld refinement method was employed to verify the morphotropic phase boundary (MPB) at x(%)=16-20. We investigated the average crystallite size and lattice strain using Scherrer's formula and Williamson-Hall (W-H) analysis. SEM image analyses provided additional evidence of the impact of doping on structural growth under low temperatures. Relaxation time extracted from Z″(f) and M″(f) spectra for x(%) = 0.0, 12, 16, 20, and 30 followed the Arrhenius law, revealing the presence of three distinct relaxation mechanisms with varying activation energies. The shoulder response in M″(f) indirectly indicated the existence of highly polarizable entities in the samples, serving as a signature of polar nanoregions (PNRs) within the grains.

Keywords: (1-x)(Na0.5Bi0.5)TiO3 x(K0.5 Bi0.5)TiO3, Rietveld refinement, Scanning electron microscopy (SEM), Williamson-Hall plots, charge density distribution, dielectric properties

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Authors: Evangelos G. Ilias, Panagiotis G. Ilias, Vasileios T. Popotas

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The United Kingdom has one of the oldest railway networks in the world dating back to 1825 when the world’s first passenger railway was opened. The network has some 40,000 bridges of various construction types using a wide range of materials including masonry, steel, cast iron, wrought iron, concrete and timber. It is commonly accepted that the successful operation of the network is vital for the economy of the United Kingdom, consequently the cost effective maintenance of the existing infrastructure is a high priority to maintain the operability of the network, prevent deterioration and to extend the life of the assets. Every bridge on the railway network is required to be assessed every eighteen years and a structured approach to assessments is adopted with three main types of progressively more detailed assessments used. These assessment types include Level 0 (standardized spreadsheet assessment tools), Level 1 (analytical hand calculations) and Level 2 (generally finite element analyses). There is a degree of conservatism in the first two types of assessment dictated to some extent by the relevant standards which can lead to some structures not achieving the required load rating. In these situations, a Level 2 Assessment is often carried out using finite element analysis to uncover ‘latent strength’ and improve the load rating. If successful, the more sophisticated analysis can save on costly strengthening or replacement works and avoid disruption to the operational railway. This paper presents the ‘strengthening by assessment’ achieved by Level 2 analyses. The use of more accurate analysis assumptions and the implementation of non-linear modelling and functions (material, geometric and support) to better understand buckling modes and the structural behaviour of historic construction details that are not specifically covered by assessment codes are outlined. Metallic bridges which are susceptible to loss of section size through corrosion have largest scope for improvement by the Level 2 Assessment methodology. Three case studies are presented, demonstrating the effectiveness of the sophisticated Level 2 Assessment methodology using finite element analysis against the conservative approaches employed for Level 0 and Level 1 Assessments. One rail overbridge and two rail underbridges that did not achieve the required load rating by means of a Level 1 Assessment due to the inadequate restraint provided by U-Frame action are examined and the increase in assessed capacity given by the Level 2 Assessment is outlined.

Keywords: assessment, bridges, buckling, finite element analysis, non-linear modelling, strengthening

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Authors: Parmeet Kaur, Nighat Yaseen Sofi, Shakti Kumar Gupta, Veena Pandey, Rajvaedhan Azad

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Nutritional status and prevailing blood glucose level trends amongst hospitalized patients has been linked to clinical outcome. Therefore, the present study was undertaken to assess hospitalized Diabetic Eye Disease (DED) patients' anthropometric and dietary intake trends. DED patients with type 1 or 2 diabetes > 20 years were enrolled. Actual food intake was determined by weighed food record method. Mifflin St Joer predictive equation multiplied by a combined stress and activity factor of 1.3 was applied to estimate caloric needs. A questionnaire was further administered to obtain reasons of inadequate dietary intake. Results indicated validity of joint analyses of body mass index in combination with waist circumference for clinical risk prediction. Dietary data showed a significant difference (p < 0.0005) between average daily caloric and carbohydrate intake and actual daily caloric and carbohydrate needs. Mean fasting and post-prandial plasma glucose levels were 150.71 ± 72.200 mg/dL and 219.76 ± 97.365 mg/dL, respectively. Improvement in food delivery systems and nutrition educations were indicated for reducing plate waste and to enable better understanding of dietary aspects of diabetes management. A team approach of nurses, physicians and other health care providers is required besides the expertise of dietetics professional. To conclude, findings of the present study will be useful in planning nutritional care process (NCP) for optimizing glucose control as a component of quality medical nutrition therapy (MNT) in hospitalized DED patients.

Keywords: nutritional status, diabetic eye disease, nutrition care process, medical nutrition therapy

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Authors: Yushinta Fujaya, Andi Ivo Asphama, Andi Parenrengi, Andi Tenriulo

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Blue Swimming crab (Portunus pelagicus) is an important commercial species throughout the subtropical waters and as such constitutes part of the fisheries resources. Data are lacking on the morphological variations of selected fast-growing crabs reared in a pond. This study aimed to analyze the morphological and molecular character of a selected fast-growing crab reared in ponds in South of Sulawesi. The crab seeds were obtained from local fish-trap and hatchery. A study on the growth was carried out in the population of crabs. The dimensions analyzed were carapace width (CW) measured after 3 months of grow out. Morphological character states were examined based on the pattern of spots on the carapace. Molecular analysis was performed using RAPD (Random Amplified Polymorphic DNA). Genetic distance was analysed using TFPGA (Tools for Population Genetic Analyses) version 1.3. The results showed that there were variations in the growth of crabs. These crabs clustered morphologically into three quite distinct groups. The crab with white spots irregularly spread over its carapace was the largest size while the crab with large white spots scattered over the carapace was the smaller size (3%). The crab with small white spots scattered over the carapace was the smallest size found in this study. Molecular analysis showed that there are morphologically and genetically different between groups of crabs. Genetic distances among crabs ranged from 0.1527 to 0.5856. Thus, this study provides information the use of white spots pattern over carapace as indicators to identify the type of blue swimming crabs.

Keywords: crab, portunus pelagicus, morphology, RAPD, Carapace

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Authors: Jureerat Kilsomporn, Chularat Howharn

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The aim of this qualitative study was to describe the meaning of leisure and the role of leisure among elderly people aged more than 80. Participants were purposive selected. Inclusion criteria were age more than 80 year, has no disease, and independent for daily life activities. Data were collected by in-depth interview. Each participant was interviewed two times and 45-60 minutes in each time of interview. Content analyses were conducted to describe the findings. The findings were as followed. Ten active aging participated in this study. All of them are Buddhist with age between 83-89 years old. Most of them completed the primary school. All of them were active members of community club such as elderly club, women club, and funeral association. Active aging described leisure as activities that connected them with their communities. Leisure could be categorized into three groups which were religious activities, entertainment activities, and hobbies. Examples of religious activities were ordination, house-blessing ceremony, and wedding ceremony. Examples of entertainment activities were Thai dance, beat a drum, and sang local songs. Participants described more that they joined and did in leisure for a sake of pleasure. These leisure played significant roles; significantly affect were their minds and their spiritual. Religious activities play a significant role in spiritual well-being while entertainment activities play a significant role in maintaining good status of mental health. Effect of hobby activities which most of these were payable activities were increased their self-valued. Although it was not high incomes but they can use their own money as they designed. Moreover, participants describe that they have a feeling of use their time wisely since they can earn the money, they can have an exercise, and they can share the time with their neighborhood with these activities. Suggestions from this study were that authorized personnel should promote leisure for aging regularly and continuously. Any facilities that meet with their need and their desired should be promoted since these can facilitate aging to maintain their good health status.

Keywords: active aging, activities, elderly, leisure

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Authors: Khoi A. Nguyen, Rodney A. Stewart, Hong Zhang

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‘Water-related energy’ is energy use which is directly or indirectly influenced by changes to water use. Informatics applying a range of mathematical, statistical and rule-based approaches can be used to reveal important information on demand from the available data provided at second, minute or hourly intervals. This study aims to combine these two concepts to improve the current water end use disaggregation problem through applying a wide range of most advanced pattern recognition techniques to analyse the concurrent high-resolution water-energy consumption data. The obtained results have shown that recognition accuracies of all end-uses have significantly increased, especially for mechanised categories, including clothes washer, dishwasher and evaporative air cooler where over 95% of events were correctly classified.

Keywords: deep learning network, smart metering, water end use, water-energy data

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Authors: Julius Adebayo John

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The objective of this study is to compare the use of medicinal plants and Conventional medicine intervention in the management of HBV among Ibadan populace. A purposive sampling technique was used to administer questionnaires at 2 places, namely, the University College Hospital and Total Healthcare Diagnostic Centre, Ibadan, where viral loads are carried out. A EuroQol (EQ – 5D) was adopted to collect data. Descriptive and inferential analyses were performed. Also, ANOVA, Correlation, charts, and tables were used. Findings revealed a high prevalence of HBV among female respondents and sample between ages 26years to 50years. Results showed that the majority discovered their health status through free HBV tests. Analysis indicated that the use of medicinal plant extract is cost-effective in 73% of cases. Rank order utility derived from medicinal plants is higher than other interventions. Correlation analysis performed for the current health status of respondents were significant at P<0.01 against the intervention management adopted (0.046), cost of treatment (0.549), utility (0.407) at P<0.00, duration of the treatment (0.604) at P<0.01; viral load before treatment (-0.142) not significant at P<0.01, the R2 (72.2%) showed the statistical variance in respondents current health status as explained by the independent variables. Respondents gained quality-adjusted life-years (QALYs) of between 1year to 3years. Suggestions were made for a public-private partnership effort against HBV with emphasis on periodic screening, viral load test subsidy, and free vaccination of people with –HBV status. Promoting phytomedicine through intensive research with strong regulation of herbal practitioners will go a long way in alleviating the burdens of the disease in society.

Keywords: medicinal plant, HBV management interventions, utility, QALYs, ibadan metropolis

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Authors: Maryam Jaberi, Siavosh Shayan, Mojtaba Yamani

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Habble-Rud River basin (HR), up to 100 km length, one of the largest watersheds which drain into deserts to the north of Central Iran (Dasht-e Kavir). This stream is oblique with the NE-SW trending, flow in the southern range of central Alborz Mountains and the northern border of Central Iran. The end of the ~17 km suddenly change direction and with the southern trending to have a morphology which meanders passes through the Alborz Mountain ridge and flows into the Garmsar plain where it forms one of the largest alluvial fans in Iran, i.e. the vast Garmsar alluvial fan with an area of 476 km2. This study was carried out through morphometric analyses, longitudinal river profiles, and study of geomorpholic evidence such as fluvial terraces, gypsum-salt domes, seismic data, and satellite images. This study aimed to investigate the changes in the pattern of rivers in the southern part of the HR river basin. The southern part of HR river basin located at the southern foothills of the Central Alborz is characterized the thrust faults (Sorkheh-Kalut and Garmsar faults), folds,diapirs and arid climate. The activity of more than 10 salt domes that belong to the Oligocene-Miocene period has considerably influenced the pattern of streams in this region. Dissolution of these domes has not only reduced the quality of water and soil resources, but also has led to the formation of badlands and gullies.Our results indicated that the pattern of rivers in the southern part of HR river basin was influenced by discharge of the HR river in Quaternary, geological structure, subsidence of Central Iran and vertical uplift of Alborz mountain. These agents caused the formation meanders in the southern part of the HR River and evaluation of the seasonal rivers like Shoor-Darre and Garmabsar.

Keywords: geomorphologic evaluation, rivers pattern, Habble-Rud River basin, seasonal rivers

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Authors: Aminah Muchdar, Nuraeni, Eddy

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The aims of the research are: (1) to verify the cropsyst plant model of experimental data in the field of soybean plants and (2) to predict planting time and potential yield soybean plant with the use of cropsyst model. This research is divided into several stages: (1) first calibration stage which conducted in the field from June until September 2015.(2) application models stage, where the data obtained from calibration in the field will be included in cropsyst models. The required data models are climate data, ground data/soil data,also crop genetic data. The relationship between the obtained result in field with simulation cropsyst model indicated by Efficiency Index (EF) which the value is 0,939.That is showing that cropsyst model is well used. From the calculation result RRMSE which the value is 1,922%.That is showing that comparative fault prediction results from simulation with result obtained in the field is 1,92%. The conclusion has obtained that the prediction of soybean planting time cropsyst based models that have been made valid for use. and the appropriate planting time for planting soybeans mainly on rain-fed land is at the end of the rainy season, in which the above study first planting time (June 2, 2015) which gives the highest production, because at that time there was still some rain. Tanggamus varieties more resistant to slow planting time cause the percentage decrease in the yield of each decade is lower than the average of all varieties.

Keywords: soybean, Cropsyst, calibration, efficiency Index, RRMSE

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Authors: Seyedeh Belin Tavakoly Sany, Rosli Hashim, Majid Rezayi, Aishah Salleh

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The primary objectives of this study were to investigate the distribution and composition of the macrobenthic community and their response to environmental parameters in the North Port, west coastal waters of Malaysia. A total of 25 species were identified, including 13 bivalvia, 4 gastropoda, and 3 crustacea. The other taxa were less diversified. There were no temporal changes in the macrobenthic community composition, but significant effects (p < 0.05) on the benthic community composition were found on a spatial scale. The correlation analyses and similarity tests were in good agreement, confirming the significant response of macrobenthic community composition to variations of environmental parameters.

Keywords: distribution, macrobenthic community, diversity, North Port, Malaysia

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Authors: Chimuanya Osuji, Kido Uyamasi, Morgan Bradley

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Introduction: Obesity is a major risk factor for many chronic diseases, with higher rates occurring among certain populations. Even though disparities in obesity rates exist for those with disabilities, few studies have assessed the association between disability and obesity status. This study aims to examine the association between type of disability and obesity status among US adults during the Covid-19 pandemic (2019-2021). Methods: Data for this cross-sectional study was obtained from the 2019, 2020 and 2021 NHIS. Multinomial logistic regressions were used to assess the relationship between each type of disability and obesity status (reference= normal/underweight). Each model adjusted for demographic, health status and health-related quality of life variables. Statistical analyses were conducted using SAS version 9.4. Results: Of the 82,632 US adults who completed the NHIS in 2019, 2020, and 2021. 8.9% (n= 7,354) reported at least 1 disability-related condition. Respondents reported having a disability across vision (1.5%), hearing (1.5%), mobility (5.3%), communication (0.8%), cognition (2.4%) and self-care (1.1%) domains. After adjusting for covariates, adults with at least 1 disability-related condition were about 30% more likely to have moderate-severe obesity (AOR=1.3; 95% CI=1.11, 1.53). Mobility was the only disability category positively associated with mild obesity (AOR=1.16; 95% CI=1.01, 1.35) and moderate/severe obesity (AOR=1.6; 95% CI=1.35, 1.89). Individuals with vision disability were about 35% less likely to have mild obesity (AOR=0.66; 95% CI=0.51, 0.86) and moderate-severe obesity (AOR=0.66; 95% CI= 0.48, 0.9). Individuals with hearing disability were 28% less likely to have mild obesity (AOR=0.72; 95% CI= 0.56, 0.94). Individuals with communication disability were about 30% less likely to be overweight (AOR=0.66; 95% CI=0.47, 0.93) and 50% less likely to have mild obesity (AOR=0.45; 95% CI= 0.29, 0.71). Individuals with cognitive disability were about 25% less likely to have mild obesity and about 35% less likely to have moderate-severe obesity. Individuals with self-care disability were about 30% less likely to be overweight. Conclusion: Mobility-related disabilities are significantly associated with obesity status among adults residing in the United States. Researchers and policy makers should implement obesity intervention methods that can address the gap in obesity prevalence rates among those with and without disabilities.

Keywords: cognition, disability, mobility, obesity

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Authors: Min Woo Lee, Kyoung Seok Kim

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We made an effort to resolve a research question, which is about the relationship between employees’ corporate social responsibility (CSR) participation and their organizational citizenship behavior (OCB), and an effect of profiles of job characteristics. To test the question, we divided sample into two groups that have the profiles of each job characteristic. One group had high level on the five dimensions of job characteristic (D group), whereas another group had low level on the dimensions (R group). As a result, regression analyses showed that the relationship between CSR participation and OCB is positive in the D group, but the relationship is not significant in the R group. The results raise a question to the argument of recent studies showing that there is positive relationship between the CSR and the OCB. Implications and limitations are demonstrated in the conclusion.

Keywords: CSR, OCB, job characteristics, cluster analysis

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Authors: Reza Safdari, Goli Arji, Robab Abdolkhani Maryam zahmatkeshan

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Background and purpose: Cardiovascular diseases are among the most common diseases in all societies. The most important step in minimizing myocardial infarction and its complications is to minimize its risk factors. The amount of medical data is increasingly growing. Medical data mining has a great potential for transforming these data into information. Using data mining techniques to generate predictive models for identifying those at risk for reducing the effects of the disease is very helpful. The present study aimed to collect data related to risk factors of heart infarction from patients’ medical record and developed predicting models using data mining algorithm. Methods: The present work was an analytical study conducted on a database containing 350 records. Data were related to patients admitted to Shahid Rajaei specialized cardiovascular hospital, Iran, in 2011. Data were collected using a four-sectioned data collection form. Data analysis was performed using SPSS and Clementine version 12. Seven predictive algorithms and one algorithm-based model for predicting association rules were applied to the data. Accuracy, precision, sensitivity, specificity, as well as positive and negative predictive values were determined and the final model was obtained. Results: five parameters, including hypertension, DLP, tobacco smoking, diabetes, and A+ blood group, were the most critical risk factors of myocardial infarction. Among the models, the neural network model was found to have the highest sensitivity, indicating its ability to successfully diagnose the disease. Conclusion: Risk prediction models have great potentials in facilitating the management of a patient with a specific disease. Therefore, health interventions or change in their life style can be conducted based on these models for improving the health conditions of the individuals at risk.

Keywords: decision trees, neural network, myocardial infarction, Data Mining

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Authors: V. M. Mmbengwa, J. R. M. Mabuso, C. P. Du Plooy, S. Laurrie, H. D. van Schalkwyk

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Sweet potato products are necessary for the provision of essential nutrients in every household, regardless of their poverty status. Their consumption appears to be highly influenced by socio-economic factors, such as malnutrition, food insecurity and unemployment. Therefore, market availability is crucial for these cultivars to resolve some of the socio-economic factors. The aim of the study was to investigate market availability of sweet potato cultivars in the North West Province. In this study, both qualitative and quantitative research methodologies were used. Qualitative methodology was used to explain the quantitative outcomes of the variables. On the other hand, quantitative results were used to test the hypothesis. The study used SPSS software to analyse the data. Cross-tabulation and Chi-square statistics were used to obtain the descriptive and inferential analyses, respectively. The study found that the Blesbok cultivar is dominating the markets of the North West Province, with the Monate cultivar dominating in the Bojanala Platinum (75 %) and Dr Ruth Segomotsi Mompati (25 %) districts. It is also found that a unit increase in the supply of sweet potato cultivars in both local and district municipal markets is accompanied by a reduced demand of 28 % and 33 % at district and local markets, respectively. All these results were found to be significant at p<0.05. The results further revealed that in four out of nine local municipality markets, the Blesbok cultivar seems to be solely available in those four local municipal markets of North West Province. It can be concluded that Blesbok, relative to other cultivars, is the most commercialised sweet potato variety and that consumers across this Province are highly aware of it. For other cultivars to assume market prominence in this Province, a well-designed marketing campaign for creating awareness may be required. This campaign may be based on nutritional advantages of different cultivars, of which Blesbok is relatively inferior, compared to orange-fleshed sweet potato varieties.

Keywords: cultivar, malnutrition, markets, sweet potato

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Authors: Fuad Noman, Sh-Hussain Salleh, Chee-Ming Ting, Hadri Hussain, Syed Rasul

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In this paper, a data-driven dictionary approach is proposed for the automatic detection and classification of cardiovascular abnormalities. Electrocardiography (ECG) signal is represented by the trained complete dictionaries that contain prototypes or atoms to avoid the limitations of pre-defined dictionaries. The data-driven trained dictionaries simply take the ECG signal as input rather than extracting features to study the set of parameters that yield the most descriptive dictionary. The approach inherently learns the complicated morphological changes in ECG waveform, which is then used to improve the classification. The classification performance was evaluated with ECG data under two different preprocessing environments. In the first category, QT-database is baseline drift corrected with notch filter and it filters the 60 Hz power line noise. In the second category, the data are further filtered using fast moving average smoother. The experimental results on QT database confirm that our proposed algorithm shows a classification accuracy of 92%.

Keywords: electrocardiogram, dictionary learning, sparse coding, classification

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Authors: Chi-Hsuan Cheng

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This research aims to evaluate public-private partnerships against cyberattacks by comparing the UK and Taiwan. First, the study analyses major cyberattacks and factors influencing cybersecurity in both countries. Second, it assesses the effectiveness of current cyber defence strategies in combating cyberattacks by comparing the approaches taken in the UK and Taiwan, while also evaluating the cyber resilience of both nations. Lastly, the research evaluates existing public-private partnerships by comparing those in the UK and Taiwan, and proposes recommendations for enhancing cooperation and collaboration mechanisms in tackling cyberattacks. Grounded theory serves as the core research method. Theoretical sampling is used to recruit participants in both the UK and Taiwan, including investigators, police officers, and professionals from cybersecurity firms. Semi-structured interviews are conducted in English in the UK and Mandarin in Taiwan, recorded with consent, and pseudonymised for privacy. Data analysis involves open coding, grouping excerpts into codes, and categorising codes. Axial coding connects codes into categories, leading to the development of a codebook. The process continues iteratively until theoretical saturation is reached. Finally, selective coding identifies the core topic, evaluating public-private cooperation against cyberattacks and its implications for social and policing strategies in the UK and Taiwan, which highlights the current status of the cybersecurity industry, governmental plans for cybersecurity, and contributions to cybersecurity from both government sectors and cybersecurity firms, with a particular focus on public-private partnerships. In summary, this research aims to offer practical recommendations to law enforcement, private sectors, and academia for reflecting on current strategies and tailoring future approaches in cybersecurity

Keywords: cybersecurity, cybercrime, public private partnerships, cyberattack

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Authors: Qiuxiao Chen, Yan Hou, Ning Wu

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As there are deficiencies of the classic Douglas-Peucker Algorithm (DPA), such as high risks of deleting key nodes by mistake, high complexity, time consumption and relatively slow execution speed, a new Deletion-Cost Based Compression Algorithm (DCA) for linear vector data was proposed. For each curve — the basic element of linear vector data, all the deletion costs of its middle nodes were calculated, and the minimum deletion cost was compared with the pre-defined threshold. If the former was greater than or equal to the latter, all remaining nodes were reserved and the curve’s compression process was finished. Otherwise, the node with the minimal deletion cost was deleted, its two neighbors' deletion costs were updated, and the same loop on the compressed curve was repeated till the termination. By several comparative experiments using different types of linear vector data, the comparison between DPA and DCA was performed from the aspects of compression quality and computing efficiency. Experiment results showed that DCA outperformed DPA in compression accuracy and execution efficiency as well.

Keywords: Douglas-Peucker algorithm, linear vector data, compression, deletion cost

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Authors: Janusz Bobulski, Mariusz Kubanek

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The main goal of the research is to develop a multimedia container structure containing three types of images: RGB, lidar and infrared, properly calibrated to each other. An additional goal is to develop program libraries for creating and saving this type of file and for restoring it. It will also be necessary to develop a method of data synchronization from lidar and RGB cameras as well as infrared. This type of file could be used in autonomous vehicles, which would certainly facilitate data processing by the intelligent autonomous vehicle management system. Autonomous cars are increasingly breaking into our consciousness. No one seems to have any doubts that self-driving cars are the future of motoring. Manufacturers promise that moving the first of them to showrooms is the prospect of the next few years. Many experts believe that creating a network of communicating autonomous cars will be able to completely eliminate accidents. However, to make this possible, it is necessary to develop effective methods of detection of objects around the moving vehicle. In bad weather conditions, this task is difficult on the basis of the RGB(red, green, blue) image. Therefore, in such situations, you should be supported by information from other sources, such as lidar or infrared cameras. The problem is the different data formats that individual types of devices return. In addition to these differences, there is a problem with the synchronization of these data and the formatting of this data. The goal of the project is to develop a file structure that could be containing a different type of data. This type of file is calling a multimedia container. A multimedia container is a container that contains many data streams, which allows you to store complete multimedia material in one file. Among the data streams located in such a container should be indicated streams of images, films, sounds, subtitles, as well as additional information, i.e., metadata. This type of file could be used in autonomous vehicles, which would certainly facilitate data processing by the intelligent autonomous vehicle management system. As shown by preliminary studies, the use of combining RGB and InfraRed images with Lidar data allows for easier data analysis. Thanks to this application, it will be possible to display the distance to the object in a color photo. Such information can be very useful for drivers and for systems in autonomous cars.

Keywords: an autonomous car, image processing, lidar, obstacle detection

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Authors: M. Regis, E. Marin, S. Fusi, M. Pressacco, L. Fedrizzi

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Electron Beam Melting (EBM) process was used to prepare porous scaffolds with controlled porosity to ensure optimal levels of osteointegration for different trabeculae sizes. Morphological characterization by means of SEM analyses was carried out to assess pore dimensions; tensile, compression and adhesion tests have been carried out to determine the mechanical behavior. The results indicate that EBM process allows the creation of regular and repeatable porous scaffolds. Mechanical properties greatly depend on pore dimension and on bulk-pore ratio. Adhesion resistance meets the normative requirements, and the overall performance of the produced structures is compatible with potential orthopaedic applications.

Keywords: additive manufacturing, orthopaedic implants, osteointegration, trabecular structures

Procedia PDF Downloads 321

Authors: Monojit Manna, Arpan Adhikary

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In Mobile cloud sensing across the globe, an emerging paradigm is selected by the user to compute sensing tasks. In urban cities current days, Mobile vehicles are adapted to perform the task of data sensing and data collection for universality and mobility. In this work, we focused on the optimality and mobile nodes that can be selected in order to collect the maximum amount of data from urban areas and fulfill the required data in the future period within a couple of minutes. We map out the requirement of the vehicle to configure the maximum data optimization problem and budget. The Application implementation is basically set up to generalize a realistic online platform in which real-time vehicles are moving apparently in a continuous manner. The data center has the authority to select a set of vehicles immediately. A deep learning-based scheme with the help of mobile vehicles (DLMV) will be proposed to collect sensing data from the urban environment. From the future time perspective, this work proposed a deep learning-based offline algorithm to predict mobility. Therefore, we proposed a greedy approach applying an online algorithm step into a subset of vehicles for an NP-complete problem with a limited budget. Real dataset experimental extensive evaluations are conducted for the real mobility dataset in Rome. The result of the experiment not only fulfills the efficiency of our proposed solution but also proves the validity of DLMV and improves the quantity of collecting the sensing data compared with other algorithms.

Keywords: mobile crowdsensing, deep learning, vehicle recruitment, sensing coverage, data collection

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Authors: Chiahi Nadia

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The aim of our work is to monitor the behavior of soft wheat on a morpho-physiological and agronomic scale under the influence of treated wastewater. Physico-chemical analyses of the treated sewage were also carried out, and our tests were carried out on two varieties of common wheat (Triticum aestivum L), HD1220 and ARZ. For this, a seedling was made, and two different irrigations were chosen, one using treated wastewater from the Sedrata (Wilaya of Souk ahras - Algeria) WWTP and the other stormwater as a control. The tests focused on soil and soft wheat parameters, and based on our results, the soft wheat development, physiological and yield parameters appear to respond favorably to the use of these waters.

Keywords: common wheat (Triticum aestivum L.), purified wastewater, irrigation, morph physiological and agronomic parameters

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Authors: German Ricci, Horacio Divito

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This article analyses the ethical dimension of the IMF in its relationship with Argentina from the Standby Agreement sanctioned in 2018 to the Extended Fund Facilities of 2023. From the analysis of the statements of the IMF, the appeal of the Agency to an ethic is evidenced and supposedly shared with the borrowing country, in addition to the well-known technical-economic evaluations. The Fund "vindicates" and "punishes" the borrowing country through moral judgment. In the Fund's narratives, the "effort," "commitment," and "work" of the local elite are rewarded. On the other hand, there is a repeated discursive emphasis of the IMF on its permanent intention to "help" Argentina through its collaborative nature. Finally, the emergence of moral prescriptions that question the very being of the debtor country and its representatives is detected when the relationship between local authorities and the IMF is tense.

Keywords: IMF, Argentina, ethics, moral, dependency routine, symbolic power

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