Search results for: Big Data Movement
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 25697

Search results for: Big Data Movement

19337 Evaluation of the Impact of Telematics Use on Young Drivers’ Driving Behaviour: A Naturalistic Driving Study

Authors: WonSun Chen, James Boylan, Erwin Muharemovic, Denny Meyer

Abstract:

In Australia, drivers aged between 18 and 24 remained at high risk of road fatality over the last decade. Despite the successful implementation of the Graduated Licensing System (GLS) that supports young drivers in their early phases of driving, the road fatality statistics for these drivers remains high. In response to these statistics, studies conducted in Australia prior to the start of the COVID-19 pandemic have demonstrated the benefits of using telematics devices for improving driving behaviour, However, the impact of COVID-19 lockdown on young drivers’ driving behaviour has emerged as a global concern. Therefore, this naturalistic study aimed to evaluate and compare the driving behaviour(such as acceleration, braking, speeding, etc.) of young drivers with the adoption of in-vehicle telematics devices. Forty-two drivers aged between 18 and 30 and residing in the Australian state of Victoria participated in this study during the period of May to October 2022. All participants drove with the telematics devices during the first 30-day. At the start of the second 30-day, twenty-one participants were randomised to an intervention group where they were provided with an additional telematics ray device that provided visual feedback to the drivers, especially when they committed to aggressive driving behaviour. The remaining twenty-one participants remined their driving journeys without the extra telematics ray device (control group). Such trustworthy data enabled the assessment of changes in the driving behaviour of these young drivers using a machine learning approach in Python. Results are expected to show participants from the intervention group will show improvements in their driving behaviour compared to those from the control group.Furthermore, the telematics data enable the assessment and quantification of such improvements in driving behaviour. The findings from this study are anticipated to shed some light in guiding the development of customised campaigns and interventions to further address the high road fatality among young drivers in Australia.

Keywords: driving behaviour, naturalistic study, telematics data, young drivers

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19336 Predicting Loss of Containment in Surface Pipeline using Computational Fluid Dynamics and Supervised Machine Learning Model to Improve Process Safety in Oil and Gas Operations

Authors: Muhammmad Riandhy Anindika Yudhy, Harry Patria, Ramadhani Santoso

Abstract:

Loss of containment is the primary hazard that process safety management is concerned within the oil and gas industry. Escalation to more serious consequences all begins with the loss of containment, starting with oil and gas release from leakage or spillage from primary containment resulting in pool fire, jet fire and even explosion when reacted with various ignition sources in the operations. Therefore, the heart of process safety management is avoiding loss of containment and mitigating its impact through the implementation of safeguards. The most effective safeguard for the case is an early detection system to alert Operations to take action prior to a potential case of loss of containment. The detection system value increases when applied to a long surface pipeline that is naturally difficult to monitor at all times and is exposed to multiple causes of loss of containment, from natural corrosion to illegal tapping. Based on prior researches and studies, detecting loss of containment accurately in the surface pipeline is difficult. The trade-off between cost-effectiveness and high accuracy has been the main issue when selecting the traditional detection method. The current best-performing method, Real-Time Transient Model (RTTM), requires analysis of closely positioned pressure, flow and temperature (PVT) points in the pipeline to be accurate. Having multiple adjacent PVT sensors along the pipeline is expensive, hence generally not a viable alternative from an economic standpoint.A conceptual approach to combine mathematical modeling using computational fluid dynamics and a supervised machine learning model has shown promising results to predict leakage in the pipeline. Mathematical modeling is used to generate simulation data where this data is used to train the leak detection and localization models. Mathematical models and simulation software have also been shown to provide comparable results with experimental data with very high levels of accuracy. While the supervised machine learning model requires a large training dataset for the development of accurate models, mathematical modeling has been shown to be able to generate the required datasets to justify the application of data analytics for the development of model-based leak detection systems for petroleum pipelines. This paper presents a review of key leak detection strategies for oil and gas pipelines, with a specific focus on crude oil applications, and presents the opportunities for the use of data analytics tools and mathematical modeling for the development of robust real-time leak detection and localization system for surface pipelines. A case study is also presented.

Keywords: pipeline, leakage, detection, AI

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19335 Disaster Management Using Wireless Sensor Networks

Authors: Akila Murali, Prithika Manivel

Abstract:

Disasters are defined as a serious disruption of the functioning of a community or a society, which involves widespread human, material, economic or environmental impacts. The number of people suffering food crisis as a result of natural disasters has tripled in the last thirty years. The economic losses due to natural disasters have shown an increase with a factor of eight over the past four decades, caused by the increased vulnerability of the global society, and also due to an increase in the number of weather-related disasters. Efficient disaster detection and alerting systems could reduce the loss of life and properties. In the event of a disaster, another important issue is a good search and rescue system with high levels of precision, timeliness and safety for both the victims and the rescuers. Wireless Sensor Networks technology has the capability of quick capturing, processing, and transmission of critical data in real-time with high resolution. This paper studies the capacity of sensors and a Wireless Sensor Network to collect, collate and analyze valuable and worthwhile data, in an ordered manner to help with disaster management.

Keywords: alerting systems, disaster detection, Ad Hoc network, WSN technology

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19334 Automated Transformation of 3D Point Cloud to BIM Model: Leveraging Algorithmic Modeling for Efficient Reconstruction

Authors: Radul Shishkov, Orlin Davchev

Abstract:

The digital era has revolutionized architectural practices, with building information modeling (BIM) emerging as a pivotal tool for architects, engineers, and construction professionals. However, the transition from traditional methods to BIM-centric approaches poses significant challenges, particularly in the context of existing structures. This research introduces a technical approach to bridge this gap through the development of algorithms that facilitate the automated transformation of 3D point cloud data into detailed BIM models. The core of this research lies in the application of algorithmic modeling and computational design methods to interpret and reconstruct point cloud data -a collection of data points in space, typically produced by 3D scanners- into comprehensive BIM models. This process involves complex stages of data cleaning, feature extraction, and geometric reconstruction, which are traditionally time-consuming and prone to human error. By automating these stages, our approach significantly enhances the efficiency and accuracy of creating BIM models for existing buildings. The proposed algorithms are designed to identify key architectural elements within point clouds, such as walls, windows, doors, and other structural components, and to translate these elements into their corresponding BIM representations. This includes the integration of parametric modeling techniques to ensure that the generated BIM models are not only geometrically accurate but also embedded with essential architectural and structural information. Our methodology has been tested on several real-world case studies, demonstrating its capability to handle diverse architectural styles and complexities. The results showcase a substantial reduction in time and resources required for BIM model generation while maintaining high levels of accuracy and detail. This research contributes significantly to the field of architectural technology by providing a scalable and efficient solution for the integration of existing structures into the BIM framework. It paves the way for more seamless and integrated workflows in renovation and heritage conservation projects, where the accuracy of existing conditions plays a critical role. The implications of this study extend beyond architectural practices, offering potential benefits in urban planning, facility management, and historic preservation.

Keywords: BIM, 3D point cloud, algorithmic modeling, computational design, architectural reconstruction

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19333 Challenges in the Management of Her2 Neu Positive Breast Cancer Patients: Real World Data from India

Authors: Praveen Adusumilli, Meher Lakshmi Konatam, Sadashivudu Gundeti, Stalin Bala

Abstract:

The invention of trastuzumab has changed the treatment of breast cancer and lives of many patients all over the world. Despite many patients getting benefitted from the drug, it is out of reach for most of the patients. There is very limited real world data regarding the epidemiology and clinical outcome of Her2neu positive breast cancer patients. Materials and Methods: This is a retrospective analysis of breast cancer patients presenting to a tertiary care cancer centre in Southern India from 2007 to2013. All early and locally advanced breast cancer patients, who were Her2neu 3+ on IHC are included in the study and evaluated in terms of epidemiology, 3-year disease free survival (DFS)and 5-year overall survival(OS). Chemotherapy regimens used were-FAC 6 cycles or AC 4 cycles followed by 12 cycles of weekly paclitaxel . Trastuzumab was given after 6 cycles of FAC or weekly with paclitaxel followed by 3weekly maintenance until 1 year. Results: Over the period of this study there were 885 newly diagnosed cases of carcinoma breast, of which 242 (27%) were Her2neu positive, 360(40%) were hormone receptor positive, and 212(24%) were triple negative. A total of 71(8%) were Her2neu equivocal of which only 10 patients got FISH test done. Of the 212 newly diagnosed patients, only 74 (29%) opted to have standard of care therapy with trastuzumab at our centre, out of which 52(24%), 8(3%), received under insurance, paying basis respectively. 14(9%) patients received the care as part of clinical trial program (ALTTO trial). 7 (9.72%) patients developed decrease of ejection fraction by greater than 10%, requiring stoppage of trastuzumab out of which 5 were restarted in 2 months. Patients receiving trastuzumab along with chemotherapy had longer 3year DFS 92% vs. 60% (p value<0.0001) when compared to chemotherapy alone. 5 year OS was 87% vs 44% (p-value <0.0001) compared to chemotherapy alone. Conclusion: Trastuzumab with chemotherapy improves the DFS and OS in Her2neu positive patients. The biggest constraint is the cost of the treatment and absence of universal health security net to treat all patients with this diagnosis.

Keywords: breast cancer, Her 2 neu positive, real world data, Trastuzumab

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19332 Investigation of the Field Trip Method’s Effectiveness: As a Way of Improving Pre-Service Teachers’ Views on Environmental Education

Authors: Abuzer Akgün, Ümit Duruk

Abstract:

This study was carried out in a period of four weeks thanks to voluntarily participation of twenty eight pre-service teachers enrolled diverse departments in Faculty of Education. The purpose of the study was to point out how pre-service teachers views on environmental education were affected by field trips. Prior to data collection, four open-ended questions were prepared and administered to all pre-service teachers in the working group. Data gathered at first and final week of the field trip were compared in a qualitative approach using content analysis. In conclusion, it is obvious that most of the participants don’t feel themselves quiet enough about environmental education and state this reason as a providing justification to participate voluntarily in the study. In the secondary school teaching context, they mostly emphasize on the vital importance of the environmental awareness level of the pupils in the schools. They also seem to think that they get a detailed knowledge of environmental education and claim that they will use this knowledge in order to bring up next generations in their professional career as teachers. Lastly, they state that observing the deteriorating materials directly in their own settings, might be more effective as regards improving environmental awareness.

Keywords: science education, environmental education, environmental issues, field trip method

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19331 Iraqi Short Term Electrical Load Forecasting Based on Interval Type-2 Fuzzy Logic

Authors: Firas M. Tuaimah, Huda M. Abdul Abbas

Abstract:

Accurate Short Term Load Forecasting (STLF) is essential for a variety of decision making processes. However, forecasting accuracy can drop due to the presence of uncertainty in the operation of energy systems or unexpected behavior of exogenous variables. Interval Type 2 Fuzzy Logic System (IT2 FLS), with additional degrees of freedom, gives an excellent tool for handling uncertainties and it improved the prediction accuracy. The training data used in this study covers the period from January 1, 2012 to February 1, 2012 for winter season and the period from July 1, 2012 to August 1, 2012 for summer season. The actual load forecasting period starts from January 22, till 28, 2012 for winter model and from July 22 till 28, 2012 for summer model. The real data for Iraqi power system which belongs to the Ministry of Electricity.

Keywords: short term load forecasting, prediction interval, type 2 fuzzy logic systems, electric, computer systems engineering

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19330 Knowledge, Attitudes and Readiness of Students towards Higher Order Thinking Skills

Authors: Mohd Aderi Che Noh, Tuan Rahayu Tuan Lasan

Abstract:

Higher order thinking skills (HOTS) is an important skill in the Malaysian education system to produce a knowledgeable generation, able to think critically and creatively in order to face the challenges in the future. Educational challenges of the 21st century require that all students to have the HOTS. Therefore, this study aims to identify the level of knowledge, attitude and readiness of students towards HOTS. The respondents were 127 form four students from schools in the Federal Territory of Putrajaya. This study is quantitative survey using a questionnaire to collect data. Data were analyzed using Statistical Package for the Social Sciences (SPSS) 23.0. The results showed that knowledge, attitudes and readiness of students towards HOTS lam were at a high level. Inferential analysis showed that there was a significant relationship between knowledge with attitude and readiness towards HOTS. This study provides information to the schools and teachers to improve the teaching and learning to increase students HOTS and fulfilling the hope of Ministry of Education to produce human capital who can be globally competitive.

Keywords: high order thinking skills, teaching, education, Malaysia

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19329 Correlation between Body Mass Index and Blood Sugar/Serum Lipid Levels in Fourth-Grade Boys in Japan

Authors: Kotomi Yamashita, Hiromi Kawasaki, Satoko Yamasaki, Susumu Fukita, Risako Sakai

Abstract:

Lifestyle-related diseases develop from the long-term accumulation of health consequences from a poor lifestyle. Thus, schoolchildren, who have not accumulated long-term lifestyle habits, are believed to be at a lower risk for lifestyle-related diseases. However, schoolchildren rarely receive blood tests unless they are under treatment for a serious disease; without such data on their blood, the impacts of their young lifestyle could not be known. Blood data from physical measurements can help in the implementation of more effective health education. Therefore, we examined the correlation between body mass index (BMI) and blood sugar/serum lipid (BS/SL) levels. From 2014 to 2016, we measured the blood data of fourth-grade students living in a city in Japan. The present study reported on the results of 281 fourth-grade boys only (80.3% of total). We analyzed their BS/SL levels by comparing the blood data against the criteria of the National Center for Child Health and Development in Japan. Next, we examined the correlation between BMI and BS/SL levels. IBM SPSS Statistics for Windows, Version 25 was used for analysis. A total of 69 boys (24.6%) were within the normal range for BMI (18.5–24), whereas 193 (71.5%) and 8 boys (2.8%) had lower and higher BMI, respectively. Regarding BS levels, 280 boys were within the normal range (70–90 mg/dl); 1 boy reported a higher value. All the boys were within the normal range for glycated Hemoglobin (HbA1c) (4.6–6.2%). Regarding SL levels, 271 boys were within the normal range (125–230 mg/dl) for total cholesterol (TC), whereas 5 boys (1.8%) had lower and 5 boys (1.8%) had higher levels. A total of 243 boys (92.7%) were within the normal range (36-138mg/dL) for triglycerides (TG), whereas 19 boys (7.3%) had lower and 19 boys (7.3%) had higher levels. Regarding high-density lipoprotein cholesterol (HDL-C), 276 boys (98.2%) were within the normal range (40-mg/dl), whereas 5 boys (1.8%) reported lower values. All but one boy (280, 99.6%) were within the normal range (-170 mg/dl) for low-density lipoprotein cholesterol (LDL-C); the exception (0.4%) had a higher level. BMI and BS didn’t show a correlation. BMI and HbA1c were moderately positively correlated (r = 0.139, p=0.019). We also observed moderate positive correlations between BMI and TG (r = 0.328, p < 0.01), TC (r=0.239, p< 0.01), LDL-C (r = 0.324, p < 0.01), respectively. BMI and HDL-C were low correlated (r = -0.185, p = 0.002). Most of the boys were within the normal range for BS/SL levels. However, some boys exceeded the normal TG range. Fourth graders with a high TG may develop a lifestyle-related disease in the future. Given its relation to TG, food habits should be improved in this group. Our findings suggested a positive correlation between BMI and BS/SL levels. Fourth-grade schoolboys with a high BMI may be at high risk for developing lifestyle-related diseases. Lifestyle improvement may be recommended to lower the BS/SL levels in this group.

Keywords: blood sugar level, lifestyle-related diseases, school students, serum lipid level

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19328 Gas-Liquid Flow Void Fraction Identification Using Slippage Number Froud Mixture Number Relation in Bubbly Flow

Authors: Jaber Masoud Alyami, Abdelsalam H. Alsrkhi

Abstract:

Characterizing and modeling multi-phase flow is a complicated scientific and technical phenomenon represented by a variety of interrelated elements. Yet, the introduction of dimensionless numbers used to grasp gas-liquid flow is a significant step in controlling and improving the multi-phase flow area. SL (Slippage number), for instance is a strong dimensionless number defined as a the ratio of the difference in gravitational forces between slip and no-slip conditions to the inertial force of the gas. The fact that plotting SL versus Frm provides a single acceptable curve for all of the data provided proves that SL may be used to realize the behavior of gas-liquid flow. This paper creates a numerical link between SL and Froud mixing number using vertical gas-liquid flow and then utilizes that relationship to validate its reliability in practice. An improved correlation in drift flux model generated from the experimental data and its rationality has been verified. The method in this paper is to approach for predicting the void fraction in bubbly flow through SL/Frm relation and the limitations of this method, as well as areas for development, are stated.

Keywords: multiphase flow, gas-liquid flow, slippage, void farction

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19327 Healthcare Seeking Behaviors of Parents Who Have Children with Disabilities: A Case Study at the Effutu Municipality, Winneba-Central Region, Ghana-West Africa

Authors: Priscilla Deede Hammond

Abstract:

Healthcare seeking behaviour has emerged as a tool to tackle perceived ill-health by taking remedial actions. And currently, efforts are being directed towards encouraging people (especially parents) to learn and use health-promoting behaviours in seeking their children’s healthcare. Regardless of these efforts, most parents encounter challenges with raising a child with a disability. The purpose of the study was to explore the healthcare-seeking behaviours of parents of children with disabilities. In order to achieve the purpose of the study, a case study design was employed where the researcher used a qualitative approach such as semi-structured interview to gather the required data. Data from participants were analysed using a thematic analysis approach. It was revealed from the findings of the study that, some of the parents after the first diagnosis by health professionals consulted a spiritualist or a herbalist for help. Also, some parents stated that their response to their children’s healthcare depended on the severity of the sickness. The study recommends the Ministry of Gender, Children and Social Protection and other social agencies such as the Social Welfare Department to provide health assessment and financial support to families of children with disabilities.

Keywords: healthcare, health, parents, disabilities

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19326 A Novel Approach to 3D Thrust Vectoring CFD via Mesh Morphing

Authors: Umut Yıldız, Berkin Kurtuluş, Yunus Emre Muslubaş

Abstract:

Thrust vectoring, especially in military aviation, is a concept that sees much use to improve maneuverability in already agile aircraft. As this concept is fairly new and cost intensive to design and test, computational methods are useful in easing the preliminary design process. Computational Fluid Dynamics (CFD) can be utilized in many forms to simulate nozzle flow, and there exist various CFD studies in both 2D mechanical and 3D injection based thrust vectoring, and yet, 3D mechanical thrust vectoring analyses, at this point in time, are lacking variety. Additionally, the freely available test data is constrained to limited pitch angles and geometries. In this study, based on a test case provided by NASA, both steady and unsteady 3D CFD simulations are conducted to examine the aerodynamic performance of a mechanical thrust vectoring nozzle model and to validate the utilized numerical model. Steady analyses are performed to verify the flow characteristics of the nozzle at pitch angles of 0, 10 and 20 degrees, and the results are compared with experimental data. It is observed that the pressure data obtained on the inner surface of the nozzle at each specified pitch angle and under different flow conditions with pressure ratios of 1.5, 2 and 4, as well as at azimuthal angle of 0, 45, 90, 135, and 180 degrees exhibited a high level of agreement with the corresponding experimental results. To validate the CFD model, the insights from the steady analyses are utilized, followed by unsteady analyses covering a wide range of pitch angles from 0 to 20 degrees. Throughout the simulations, a mesh morphing method using a carefully calculated mathematical shape deformation model that simulates the vectored nozzle shape exactly at each point of its travel is employed to dynamically alter the divergent part of the nozzle over time within this pitch angle range. The mesh morphing based vectored nozzle shapes were compared with the drawings provided by NASA, ensuring a complete match was achieved. This computational approach allowed for the creation of a comprehensive database of results without the need to generate separate solution domains. The database contains results at every 0.01° increment of nozzle pitch angle. The unsteady analyses, generated using the morphing method, are found to be in excellent agreement with experimental data, further confirming the accuracy of the CFD model.

Keywords: thrust vectoring, computational fluid dynamics, 3d mesh morphing, mathematical shape deformation model

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19325 Productive Engagements and Psychological Wellbeing of Older Adults; An Analysis of HRS Dataset

Authors: Mohammad Didar Hossain

Abstract:

Background/Purpose: The purpose of this study was to examine the associations between productive engagements and the psychological well-being of older adults in the U.S by analyzing cross-sectional data from a secondary dataset. Specifically, this paper analyzed the associations of 4 different types of productive engagements, including current work status, caregiving to the family members, volunteering and religious strengths with the psychological well-being as an outcome variable. Methods: Data and sample: The study used the data from the Health and Retirement Study (HRS). The HRS is a nationally representative prospective longitudinal cohort study that has been conducting biennial surveys since 1992 to community-dwelling individuals 50 years of age or older on diverse issues. This analysis was based on the 2016 wave (cross-sectional) of the HRS dataset and the data collection period was April 2016 through August 2017. The samples were recruited from a multistage, national area-clustered probability sampling frame. Measures: Four different variables were considered as the predicting variables in this analysis. Firstly, current working status was a binary variable that measured by 0=Yes and 1= No. The second and third variables were respectively caregiving and volunteering, and both of them were measured by; 0=Regularly, 1= Irregularly. Finally, find in strength was measured by 0= Agree and 1= Disagree. Outcome (Wellbeing) variable was measured by 0= High level of well-being, 1= Low level of well-being. Control variables including age were measured in years, education in the categories of 0=Low level of education, 1= Higher level of education and sex r in the categories 0=male, 1= female. Analysis and Results: Besides the descriptive statistics, binary logistic regression analyses were applied to examine the association between independent and dependent variables. The results showed that among the four independent variables, three of them including working status (OR: .392, p<.001), volunteering (OR: .471, p<.003) and strengths in religion (OR .588, p<.003), were significantly associated with psychological well-being while controlling for age, gender and education factors. Also, no significant association was found between the caregiving engagement of older adults and their psychological well-being outcome. Conclusions and Implications: The findings of this study are mostly consistent with the previous studies except for the caregiving engagements and their impact on older adults’ well-being outcomes. Therefore, the findings support the proactive initiatives from different micro to macro levels to facilitate opportunities for productive engagements for the older adults, and all of these may ultimately benefit their psychological well-being and life satisfaction in later life.

Keywords: productive engagements, older adults, psychological wellbeing, productive aging

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19324 Influences of Market Orientation and Supply Chain Management on Competitive Capability in Case of Automotive Parts Industry

Authors: Nattapong Techarattanased

Abstract:

The objectives of this research were to study the influence of market orientation and supply chain management on competitive capability in case of the automotive parts industry in Thailand. This study employed by survey research and questionnaire was used to collect the data from 400 entrepreneurs in the automotive parts industry in Thailand. The descriptive statistics and multiple regression analysis were used to analyze data. The results revealed that the overall dimensions of marketing orientation, namely, responsiveness, intelligence generation, and intelligence dissemination were rated at the high level. As well, the overall dimensions of supply chain management, namely, collaboration, communication, trust, and commitment were also rated at the high level. Furthermore, the hypothesis testing results showed that supply chain management and market orientation affected competitive capability of the automotive parts industry in Thailand which these two variables could be combined to predict competitive capability of the automotive parts industry in Thailand by 31.5 percent.

Keywords: automotive parts industry, competitive capability, market orientation, supply chain management

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19323 Evaluation of the Construction of Terraces on a Family Farm in the Municipality of Jaboticabal (SP), Brazil

Authors: Anderson dos Santos Ananias, Matheus Yuji Shigueoka, Roberto Saverio Souza Costa

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Soil and water conservation can be conceptualized as a combination of management and use methods, which have the function of protecting them against deterioration induced by anthropogenic or natural factors. Thus, the objective of this research was to evaluate the rural extension work in soil conservation carried out at Sítio do Alto in Jaboticabal-SP, through the analysis of planimetric data (latitude and longitude coordinates) and altimetric differences of the empirically constructed terraces by the rural producer and with technical guidance from CATI (Coordination of Integral Technical Assistance). A data collection procedure was carried out in the field, with GPS L1/L2, before the construction of five (5) terraces technically level and after their construction. The results showed that the greatest differences were found on terrace one (1), with a maximum latitude difference of 57 meters, the longitude of 23 m, and altitude of 2 m. These results corroborate the observations in the field, in which the presence of a great erosion caused by the incorrect construction of terrace 1 was verified rainwater to the side of the rural property, where the largest erosion furrows with the beginning of gully formation were found.

Keywords: GPS, mechanical pratice, surface runoff, erosion

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19322 Early Indications of the Success of Rehabilitating Degraded Lands through the Green Legacy Project Implemented in Ethiopia

Authors: Tamirat Solomon, Aberash Yohannis, Efrem Gulfo

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The plantation of trees, which harmonizes the agroecology of the environment, has been implemented in Ethiopia with great concern for a noticeably degraded environment. This study was designed to evaluate the effectiveness of green legacy, species selection and, the rate of survival, and the management status in the study areas. A systematic sampling method was employed to collect the required data from 144 quadrants measuring a 15m radius with an interval of 40m apart. Additionally, 244 sample households were selected for the socioeconomic study in addition to secondary data collected from office recordings. The data collected was analyzed using multivariate analysis, considering exposure and outcome variables. The findings of this study indicated that four exotic tree species, namely; A. salgina, C. fistula, A. indica, and G. robusta, were commonly selected tree species for degraded land restoration in the study areas. Among the seedlings planted at the four study sites, a total of 79.9% survived, and A. salgina was the dominant and best performed species, A. indica was the least survived species in the entire study area. The age of the seedling before planting significantly (p = 0.05) affected the survival potential of most seedlings of species, and the majority (82%) of local communities expressed their positive attitudes and willingness to manage the restoration works in the study areas. It was recommended to consider the inclusion of native species in the restoration effort and evaluate the co-existence of native flora with exotic and its competition for nutrients, water, and light in addition to the invading potentials in the ecosystem. In general, before embarking on degraded land restoration, species selection, adequate preparation of seedlings, and species diversity composition that exactly fit the socioeconomic and ecological demands of the areas must get the attention for the success of the restoration.

Keywords: plantation forest, degraded land, forest restoration, plantation survival, species selection

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19321 Deep Learning based Image Classifiers for Detection of CSSVD in Cacao Plants

Authors: Atuhurra Jesse, N'guessan Yves-Roland Douha, Pabitra Lenka

Abstract:

The detection of diseases within plants has attracted a lot of attention from computer vision enthusiasts. Despite the progress made to detect diseases in many plants, there remains a research gap to train image classifiers to detect the cacao swollen shoot virus disease or CSSVD for short, pertinent to cacao plants. This gap has mainly been due to the unavailability of high quality labeled training data. Moreover, institutions have been hesitant to share their data related to CSSVD. To fill these gaps, image classifiers to detect CSSVD-infected cacao plants are presented in this study. The classifiers are based on VGG16, ResNet50 and Vision Transformer (ViT). The image classifiers are evaluated on a recently released and publicly accessible KaraAgroAI Cocoa dataset. The best performing image classifier, based on ResNet50, achieves 95.39\% precision, 93.75\% recall, 94.34\% F1-score and 94\% accuracy on only 20 epochs. There is a +9.75\% improvement in recall when compared to previous works. These results indicate that the image classifiers learn to identify cacao plants infected with CSSVD.

Keywords: CSSVD, image classification, ResNet50, vision transformer, KaraAgroAI cocoa dataset

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19320 Classification of Factors Influencing Buyer-Supplier Relationship: A Case Study from the Cement Industry

Authors: Alberto Piatto, Zaza Nadja Lee Hansen, Peter Jacobsen

Abstract:

This paper examines the quantitative and qualitative factors influencing the buyer-supplier relationship. Understanding and acting on the right factors influencing supplier relationship management is crucial when a company outsource an important part of its business as it can be for engineering to order (ETO) company executing only the designing part in-house. Acting on these factors increase the quality of the relationship obtaining for both parties what they want and expect from an improved relationship. Best practices in supplier relationship management are considered and a case study of a large global company, called Cement A/S, operating in the cement business is carried out. One study is conducted including a large international company and hundreds of its suppliers. Data from the company is collected using semi-structured interviews and data from the suppliers is collected using a survey. Based on these inputs and an extensive literature review a classification of factors influencing the relationship buyer-supplier is presented and discussed. The results show that different managers among the company are assessing supplier from various perspectives, a standard approach to measure the performance of suppliers does not exist. The factors used nowadays in the company to measure performances of the suppliers are mostly related to time and cost. Quality is a key factor, but it has not been addressed properly since no data are available in the system. From a practical perspective, managers can learn from this paper which factors to consider when applying best practices of Supplier Relationship Management. Furthermore, from a theoretical perspective, this paper contributes with new knowledge in the area as limited research in collaboration with the company has been conducted. For this reason, a company, its suppliers and few studies for this type of industry have been conducted. For further research, it is suggested to define the correlation of factors to the profitability of the company and calculate its impact. When conducting this analysis it is important to focus on the efficient and effective use of factors that can be measurable and accepted from the supplier.

Keywords: buyer-supplier relationship, cement industry, classification of factors, ETO

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19319 Hormone Replacement Therapy (HRT) and Its Impact on the All-Cause Mortality of UK Women: A Matched Cohort Study 1984-2017

Authors: Nurunnahar Akter, Elena Kulinskaya, Nicholas Steel, Ilyas Bakbergenuly

Abstract:

Although Hormone Replacement Therapy (HRT) is an effective treatment in ameliorating menopausal symptoms, it has mixed effects on different health outcomes, increasing, for instance, the risk of breast cancer. Because of this, many symptomatic women are left untreated. Untreated menopausal symptoms may result in other health issues, which eventually put an extra burden and costs to the health care system. All-cause mortality analysis may explain the net benefits and risks of the HRT therapy. However, it received far less attention in HRT studies. This study investigated the impact of HRT on all-cause mortality using electronically recorded primary care data from The Health Improvement Network (THIN) that broadly represents the female population in the United Kingdom (UK). The study entry date for this study was the record of the first HRT prescription from 1984, and patients were followed up until death or transfer to another GP practice or study end date, which was January 2017. 112,354 HRT users (cases) were matched with 245,320 non-users by age at HRT initiation and general practice (GP). The hazards of all-cause mortality associated with HRT were estimated by a parametric Weibull-Cox model adjusting for a wide range of important medical, lifestyle, and socio-demographic factors. The multilevel multiple imputation techniques were used to deal with missing data. This study found that during 32 years of follow-up, combined HRT reduced the hazard ratio (HR) of all-cause mortality by 9% (HR: 0.91; 95% Confidence Interval, 0.88-0.94) in women of age between 46 to 65 at first treatment compared to the non-users of the same age. Age-specific mortality analyses found that combined HRT decreased mortality by 13% (HR: 0.87; 95% CI, 0.82-0.92), 12% (HR: 0.88; 95% CI, 0.82-0.93), and 8% (HR: 0.92; 95% CI, 0.85-0.98), in 51 to 55, 56 to 60, and 61 to 65 age group at first treatment, respectively. There was no association between estrogen-only HRT and women’s all-cause mortality. The findings from this study may help to inform the choices of women at menopause and to further educate the clinicians and resource planners.

Keywords: hormone replacement therapy, multiple imputations, primary care data, the health improvement network (THIN)

Procedia PDF Downloads 153
19318 Assessment of Air Pollution Impacts On Population Health in Béjaia City

Authors: Benaissa Fatima, Alkama Rezak, Annesi-Maesano Isabella

Abstract:

To assess the health impact of the air pollution on the population of Béjaia, we carried out a descriptive epidemiologic inquiry near the medical establishments of three areas. From the registers of hospital admissions, we collected data on the hospital mortality and admissions relating to the various cardiorespiratory pathologies generated by this type of pollution. In parallel, data on the automobile fleet of Bejaia and other measurements were exploited to show that the concentrations of the pollutants are strongly correlated with the concentration the urban traffic. This study revealed that the whole of the population is touched, but the sensitivity to pollution can show variations according to the age, the sex and the place of residence. So the under population of the town of Bejaia marked the most raised death and morbidity rates, followed that of Kherrata. Weak rates are recorded for under rural population of Feraoun. This approach enables us to conclude that the population of Béjaia could not escape the urban pollution generated by her old automobile fleet. To install a monitoring and measuring site of the air pollution in this city could provide a beneficial tool to protect its inhabitants by them informing on quality from the air that they breathe and measurements to follow to minimize the impacts on their health and by alerting the authorities during the critical situations.

Keywords: air, urban pollution, health, impacts

Procedia PDF Downloads 343
19317 Intelligent Crop Circle: A Blockchain-Driven, IoT-Based, AI-Powered Sustainable Agriculture System

Authors: Mishak Rahul, Naveen Kumar, Bharath Kumar

Abstract:

Conceived as a high-end engine to revolutionise sustainable agri-food production, the intelligent crop circle (ICC) aims to incorporate the Internet of Things (IoT), blockchain technology and artificial intelligence (AI) to bolster resource efficiency and prevent waste, increase the volume of production and bring about sustainable solutions with long-term ecosystem conservation as the guiding principle. The operating principle of the ICC relies on bringing together multidisciplinary bottom-up collaborations between producers, researchers and consumers. Key elements of the framework include IoT-based smart sensors for sensing soil moisture, temperature, humidity, nutrient and air quality, which provide short-interval and timely data; blockchain technology for data storage on a private chain, which maintains data integrity, traceability and transparency; and AI-based predictive analysis, which actively predicts resource utilisation, plant growth and environment. This data and AI insights are built into the ICC platform, which uses the resulting DSS (Decision Support System) outlined as help in decision making, delivered through an easy-touse mobile app or web-based interface. Farmers are assumed to use such a decision-making aid behind the power of the logic informed by the data pool. Building on existing data available in the farm management systems, the ICC platform is easily interoperable with other IoT devices. ICC facilitates connections and information sharing in real-time between users, including farmers, researchers and industrial partners, enabling them to cooperate in farming innovation and knowledge exchange. Moreover, ICC supports sustainable practice in agriculture by integrating gamification techniques to stimulate farm adopters, deploying VR technologies to model and visualise 3D farm environments and farm conditions, framing the field scenarios using VR headsets and Real-Time 3D engines, and leveraging edge technologies to facilitate secure and fast communication and collaboration between users involved. And through allowing blockchain-based marketplaces, ICC offers traceability from farm to fork – that is: from producer to consumer. It empowers informed decision-making through tailor-made recommendations generated by means of AI-driven analysis and technology democratisation, enabling small-scale and resource-limited farmers to get their voice heard. It connects with traditional knowledge, brings together multi-stakeholder interactions as well as establishes a participatory ecosystem to incentivise continuous growth and development towards more sustainable agro-ecological food systems. This integrated approach leverages the power of emerging technologies to provide sustainable solutions for a resilient food system, ensuring sustainable agriculture worldwide.

Keywords: blockchain, internet of things, artificial intelligence, decision support system, virtual reality, gamification, traceability, sustainable agriculture

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19316 The Effect of Nanoscience and Nanotechnology Education on Preservice Science Teachers' Awareness of Nanoscience and Nanotechnology

Authors: Tuba Senel Zor, Oktay Aslan

Abstract:

With current trends in nanoscience and nanotechnology (NST), scientists have paid much attention to education and nanoliteracy in parallel with the developments on these fields. To understand the advances in NST research requires a population with a high degree of science literacy. All citizens should soon need nanoliteracy in order to navigate some of the important science-based issues faced to their everyday lives. While the fields of NST are advancing rapidly and raising their societal significance, general public’s awareness of these fields has remained at a low level. Moreover, students enrolled different education levels and teachers don’t have awareness at expected level. This problem may be stemmed from inadequate education and training. To remove the inadequacy, teachers have greatest duties and responsibilities. Especially science teachers at all levels need to be made aware of these developments and adequately prepared so that they are able to teach about these advances in a developmentally appropriate manner. If the teachers develop understanding and awareness of NST, they can also discuss the topic with their students. Therefore, the awareness and conceptual understandings of both the teachers who will teach science to students and the students who will be introduced about NST should be increased, and the necessary training should be provided. The aim of this study was to examine the effect of NST education on preservice science teachers’ awareness of NST. The study was designed in one group pre-test post-test quasi-experimental pattern. The study was conducted with 32 preservice science teachers attending the Elementary Science Education Program at a large Turkish university in central Anatolia. NST education was given during five weeks as two hours per week. Nanoscience and Nanotechnology Awareness Questionnaire was used as data collected tool and was implemented for pre-test and post-test. The collected data were analyzed using Statistical package for the Social Science (SPSS). The results of data analysis showed that there was a significant difference (z=6.25, p< .05) on NST awareness of preservice science teachers after implemented NST education. The results of the study indicate that NST education has an important effect for improving awareness of preservice science teachers on NST.

Keywords: awareness level, nanoliteracy, nanoscience and nanotechnology education, preservice science teachers

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19315 Harnessing Entrepreneurial Opportunities for National Security

Authors: Itiola Kehinde Adeniran

Abstract:

This paper investigated the influence of harnessing entrepreneurial opportunities on the national security in Nigeria with a specific focus on the security situation of the post-amnesty programmes of the Federal Government in Ondo State. The self-administered structured questionnaire was employed to collect data from one hundred and twenty participants through purposive sampling method. Inferential statistics was used to analyze the data, specifically; ordinary least squares linear regression method was employed with the aid of statistical package for social science (SPSS) version 20 in order to determine the influence of independent variable (entrepreneurial opportunities) on dependent variable (national security). The result showed that business opportunities have a significant influence on the rate of criminal activities. The study also revealed that entrepreneurial opportunity creation and discovery as well as providing a model on how these entrepreneurial opportunities could be effectively and efficiently utilized jointly predict better national security, which counted for 69% variance of crime rate reduction. The paper, therefore, recommended that citizens should be encouraged to develop an interest in the skill-based activities in order to change their mindset towards self-employment which can motivate them in identify entrepreneurial opportunities.

Keywords: entrepreneurship, entrepreneurial opportunities, national security, unemployment

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19314 Quantifying User-Related, System-Related, and Context-Related Patterns of Smartphone Use

Authors: Andrew T. Hendrickson, Liven De Marez, Marijn Martens, Gytha Muller, Tudor Paisa, Koen Ponnet, Catherine Schweizer, Megan Van Meer, Mariek Vanden Abeele

Abstract:

Quantifying and understanding the myriad ways people use their phones and how that impacts their relationships, cognitive abilities, mental health, and well-being is increasingly important in our phone-centric society. However, most studies on the patterns of phone use have focused on theory-driven tests of specific usage hypotheses using self-report questionnaires or analyses of smaller datasets. In this work we present a series of analyses from a large corpus of over 3000 users that combine data-driven and theory-driven analyses to identify reliable smartphone usage patterns and clusters of similar users. Furthermore, we compare the stability of user clusters across user- and system-initiated sessions, as well as during the hypothesized ritualized behavior times directly before and after sleeping. Our results indicate support for some hypothesized usage patterns but present a more complete and nuanced view of how people use smartphones.

Keywords: data mining, experience sampling, smartphone usage, health and well being

Procedia PDF Downloads 147
19313 Forecast Based on an Empirical Probability Function with an Adjusted Error Using Propagation of Error

Authors: Oscar Javier Herrera, Manuel Angel Camacho

Abstract:

This paper addresses a cutting edge method of business demand forecasting, based on an empirical probability function when the historical behavior of the data is random. Additionally, it presents error determination based on the numerical method technique ‘propagation of errors’. The methodology was conducted characterization and process diagnostics demand planning as part of the production management, then new ways to predict its value through techniques of probability and to calculate their mistake investigated, it was tools used numerical methods. All this based on the behavior of the data. This analysis was determined considering the specific business circumstances of a company in the sector of communications, located in the city of Bogota, Colombia. In conclusion, using this application it was possible to obtain the adequate stock of the products required by the company to provide its services, helping the company reduce its service time, increase the client satisfaction rate, reduce stock which has not been in rotation for a long time, code its inventory, and plan reorder points for the replenishment of stock.

Keywords: demand forecasting, empirical distribution, propagation of error, Bogota

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19312 Nine Year Trend Analysis of Malaria in Kahsay Abera General Hospital Humera Town: Western Tigrai, Northern Ethiopia: A Retrospective Study

Authors: Getachew Belay, Getachew Kahsu, Brhane Berhe, Kebede Tesfay, Fitsum Mardu, Nigus Shishay, Hadush Negash, Aster Tsegaye

Abstract:

Background: Malaria kills million people around the world, and it is still a serious public health problem in Ethiopia. Over the past years, the disease has been consistently reported as leading cause of outpatient visits, hospitalization and death in health facilities across the country. This study assessed malaria trend in Humera Town Kahsay Abera Hospital Tigrai region, Northern Ethiopia. Method: A Health facility retrospective cross sectional study was conducted in Kahsay Abera General Hospital from January 2011 to December 2019. Data of Malaria cases were reviewed from Health Management Information System with the help of experts in the office. The nine year data were extracted and analyzed using Excel by excluding those which lack demographic data. Result: A total of 36,604 smear positive malaria cases were confirmed in last nine years in the study area. Plasmodim falcifarum was the most prevalent reported species. Higher number of malaria cases were reported during October season.Males were more infected by the disese (63.1%) than females and males aged 15 years and above were the most iffected ones. The percentage proportion of P.falcifarum and P.vivax were 61.6% to 38.4%, respectively. There was a decreasing trend over the nine years following the peak in 2013. Conclusion: Malaria smear positivity, with highest cases being recorded in October, was declined over the nine years after peaking in 2013. Males aged 15 years and above were more affected, and P falciparum was the predominat species. Strengtheing the prevention and control activities is warranted in the study area.

Keywords: trend, malaria, kahsay abera general hospital, tigray, ethiopia

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19311 Feasibility of Deployable Encasing for a CVDR (Cockpit Voice and Data Recorder) in Commercial Aircraft

Authors: Vishnu Nair, Rohan Kapoor

Abstract:

Recent commercial aircraft crashes demand a paradigm shift in how the CVDRs are located and recovered, particularly if the aircraft crashes in the sea. CVDR (Cockpit Voice and Data Recorder) is most vital component out of the entire wreckage that can be obtained in order to investigate the sequence of events leading to the crash. It has been a taxing and exorbitantly expensive process locating and retrieving the same in the massive water bodies as it was seen in the air crashes in the recent past, taking the unfortunate Malaysia airlines MH-370 crash into account. The study aims to provide an aid to the persisting problem by improving the buoyant as-well-as the aerodynamic properties of the proposed CVDR encasing. Alongside this the placement of the deployable CVDR on the surface of the aircraft and floatability in case of water submersion are key factors which are taken into consideration for a better resolution to the problem. All of which results into the Deployable-CVDR emerging to the surface of the water-body. Also the whole system is designed such that it can be seamlessly integrated with the current crop of commercial aircraft. The work is supported by carrying out a computational study with the help Ansys-Fluent combination.

Keywords: encasing, buoyancy, deployable CVDR, floatability, water submersion

Procedia PDF Downloads 285
19310 A Neural Network Approach to Evaluate Supplier Efficiency in a Supply Chain

Authors: Kishore K. Pochampally

Abstract:

The success of a supply chain heavily relies on the efficiency of the suppliers involved. In this paper, we propose a neural network approach to evaluate the efficiency of a supplier, which is being considered for inclusion in a supply chain, using the available linguistic (fuzzy) data of suppliers that already exist in the supply chain. The approach is carried out in three phases, as follows: In phase one, we identify criteria for evaluation of the supplier of interest. Then, in phase two, we use performance measures of already existing suppliers to construct a neural network that gives weights (importance values) of criteria identified in phase one. Finally, in phase three, we calculate the overall rating of the supplier of interest. The following are the major findings of the research conducted for this paper: (i) linguistic (fuzzy) ratings of suppliers such as 'good', 'bad', etc., can be converted (defuzzified) to numerical ratings (1 – 10 scale) using fuzzy logic so that those ratings can be used for further quantitative analysis; (ii) it is possible to construct and train a multi-level neural network in order to determine the weights of the criteria that are used to evaluate a supplier; and (iii) Borda’s rule can be used to group the weighted ratings and calculate the overall efficiency of the supplier.

Keywords: fuzzy data, neural network, supplier, supply chain

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19309 Contractual Complexity and Contract Parties' Opportunistic Behavior in Construction Projects: In a Contractual Function View

Authors: Mengxia Jin, Yongqiang Chen, Wenqian Wang, Yu Wang

Abstract:

The complexity and specificity of construction projects have made common opportunism phenomenon, and contractual governance for opportunism has been a topic of considerable ongoing research. Based on TCE, the research distinguishes control and coordination as different functions of the contract to investigate their complexity separately. And in a nuanced way, the dimensionality of contractual control is examined. Through the analysis of motivation and capability of strong or weak form opportunism, the framework focuses on the relationship between the complexity of above contractual dimensions and different types of opportunistic behavior and attempts to verify the possible explanatory mechanism. The explanatory power of the research model is evaluated in the light of empirical evidence from questionnaires. We collect data from Chinese companies in the construction industry, and the data collection is still in progress. The findings will speak to the debate surrounding the effects of contract complexity on opportunistic behavior. This nuanced research will derive implications for research on the role of contractual mechanisms in dealing with inter-organizational opportunism and offer suggestions for curbing contract parties’ opportunistic behavior in construction projects.

Keywords: contractual complexity, contractual control, contractual coordinatio, opportunistic behavior

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19308 Indoor Visible Light Communication Channel Characterization for User Mobility: A Use-Case Study

Authors: Pooja Sanathkumar, Srinidhi Murali, Sethuraman TV, Saravanan M, Paventhan Arumugam, Ashwin Ashok

Abstract:

The last decade has witnessed a significant interest in visible light communication (VLC) technology, as VLC can potentially achieve high data rate links and secure communication channels. However, the use of VLC under mobile settings is fundamentally limited as its a line-of-sight (LOS) technology and there has been limited breakthroughs in realizing VLC for mobile settings. In this regard, this work targets to study the VLC channel under mobility. Through a use-case study analysis with experiment data traces this paper presents an empirical VLC channel study considering the application of VLC for smart lighting in an indoor room environment. This paper contributes a calibration study of a prototype VLC smart lighting system in an indoor environment and through the inferences gained from the calibration, and considering a user is carrying a mobile device fit with a VLC receiver, this work presents recommendations for user's position adjustments, with the goal to ensure maximum connectivity across the room.

Keywords: visible light communication, mobility, empirical study, channel characterization

Procedia PDF Downloads 117