Search results for: meteorological prediction data

Authors: Dmitry V. Fomichev, Vladimir V. Solonin

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This paper presents the findings from a numerical simulation of the flow in 37-rod fuel assembly models spaced by a double-wire trapezoidal wrapping as applied to the BREST-OD-300 experimental nuclear reactor. Data on a high static pressure distribution within the models, and equations for determining the fuel bundle flow friction factors have been obtained. Recommendations are provided on using the closing turbulence models available in the ANSYS Fluent. A comparative analysis has been performed against the existing empirical equations for determining the flow friction factors. The calculated and experimental data fit has been shown. An analysis into the experimental data and results of the numerical simulation of the BREST-OD-300 fuel rod assembly hydrodynamic performance are presented.

Keywords: BREST-OD-300, ware-spaces, fuel assembly, computation fluid dynamics

Procedia PDF Downloads 370

Authors: Abdel-Aziz M. Mohamed, Nermeen Coutry

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Lead time is an important measure of supply chain performance. It impacts both customer satisfactions as well as the total cost of inventory. This paper presents the result of a study on the analysis of the customer order lead-time for a multinational company. In the study, the lead time was divided into three stages: order entry, order fulfillment, and order delivery. A sample of size 2,425 order lines from the company records were considered for this study. The sample data includes information regarding customer orders from the time of order entry until order delivery. Data regarding the lead time of each sage for different orders were also provided. Summary statistics on lead time data reveals that about 30% of the orders were delivered after the scheduled due date. The result of the multiple linear regression analysis technique revealed that component type, logistics parameter, order size and the customer type have significant impact on lead time. Data analysis on the stages of lead time indicates that stage 2 consumes over 50% of the lead time. Pareto analysis was made to study the reasons for the customer order delay in each of the 3 stages. Recommendation was given to resolve the problem.

Keywords: lead time reduction, customer satisfaction, service quality, statistical analysis

Procedia PDF Downloads 715

Authors: Ali Alshumrani, Nathan Clarke, Bogdan Ghite, Stavros Shiaeles

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Digital forensics has become an essential tool in the investigation of cyber and computer-assisted crime. Arguably, given the prevalence of technology and the subsequent digital footprints that exist, it could have a significant role across almost all crimes. However, the variety of technology platforms (such as computers, mobiles, Closed-Circuit Television (CCTV), Internet of Things (IoT), databases, drones, cloud computing services), heterogeneity and volume of data, forensic tool capability, and the investigative cost make investigations both technically challenging and prohibitively expensive. Forensic tools also tend to be siloed into specific technologies, e.g., File System Forensic Analysis Tools (FS-FAT) and Network Forensic Analysis Tools (N-FAT), and a good deal of data sources has little to no specialist forensic tools. Increasingly it also becomes essential to compare and correlate evidence across data sources and to do so in an efficient and effective manner enabling an investigator to answer high-level questions of the data in a timely manner without having to trawl through data and perform the correlation manually. This paper proposes a Unified Forensic Analysis Tool (U-FAT), which aims to establish a common language for electronic information and permit multi-source forensic analysis. Core to this approach is the identification and development of forensic analyses that automate complex data correlations, enabling investigators to investigate cases more efficiently. The paper presents a systematic analysis of major crime categories and identifies what forensic analyses could be used. For example, in a child abduction, an investigation team might have evidence from a range of sources including computing devices (mobile phone, PC), CCTV (potentially a large number), ISP records, and mobile network cell tower data, in addition to third party databases such as the National Sex Offender registry and tax records, with the desire to auto-correlate and across sources and visualize in a cognitively effective manner. U-FAT provides a holistic, flexible, and extensible approach to providing digital forensics in technology, application, and data-agnostic manner, providing powerful and automated forensic analysis.

Keywords: digital forensics, evidence correlation, heterogeneous data, forensics tool

Procedia PDF Downloads 180

Authors: F. L. Motta, M. H. A. Santana

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Humic Acids (HA) were produced by a Trichoderma viride strain under submerged fermentation in a medium based on the oil palm Empty Fruit Bunch (EFB) and the main variables of the process were optimized by using response surface methodology. A temperature of 40°C and concentrations of 50g/L EFB, 5.7g/L potato peptone and 0.11g/L (NH4)2SO4 were the optimum levels of the variables that maximize the HA production, within the physicochemical and biological limits of the process. The optimized conditions led to an experimental HA concentration of 428.4±17.5 mg/L, which validated the prediction from the statistical model of 412.0mg/L. This optimization increased about 7–fold the HA production previously reported in the literature. Additionally, the time profiles of HA production and fungal growth confirmed our previous findings that HA production preferably occurs during fungal sporulation. The present study demonstrated that T. viride successfully produced HA via the submerged fermentation of EFB and the process parameters were successfully optimized using a statistics-based response surface model. To the best of our knowledge, the present work is the first report on the optimization of HA production from EFB by a biotechnological process, whose feasibility was only pointed out in previous works.

Keywords: empty fruit bunch, humic acids, submerged fermentation, Trichoderma viride

Procedia PDF Downloads 291

Authors: Mohit Kumar, Mayur Betharia

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Healthcare domain, with the emergence of Electronic Medical Record (EMR), collects a lot of data which have been attracting Data Mining expert’s interest. In the past, doctors have relied on their intuition while making critical clinical decisions. This paper presents the means to analyze the Medical workflows to get business insights out of huge dumped medical databases. Market Basket Analysis (MBA) which is a special data mining technique, has been widely used in marketing and e-commerce field to discover the association between products bought together by customers. It helps businesses in increasing their sales by analyzing the purchasing behavior of customers and pitching the right customer with the right product. This paper is an attempt to demonstrate Market Basket Analysis applications in healthcare. In particular, it discusses the Market Basket Analysis Algorithm ‘Apriori’ applications within healthcare in major areas such as analyzing the workflow of diagnostic procedures, Up-selling and Cross-selling of Healthcare Systems, designing healthcare systems more user-friendly. In the paper, we have demonstrated the MBA applications using Angiography Systems, but can be extrapolated to other modalities as well.

Keywords: data mining, market basket analysis, healthcare applications, knowledge discovery in healthcare databases, customer relationship management, healthcare systems

Procedia PDF Downloads 162

Authors: Mostafa Jafarian Abyaneh, Khashayar Jafari, Vahab Toufigh

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The cost of experiments on different types of concrete has raised the demand for prediction of their behavior with numerical analysis. In this research, an advanced numerical model has been presented to predict the complete elastic-plastic behavior of polymer concrete (PC), high-strength concrete (HSC), high performance concrete (HPC) along with different steel fiber contents under uniaxial compression. The accuracy of the numerical response was satisfactory as compared to other conventional simple models such as Mohr-Coulomb and Drucker-Prager. In order to predict the complete elastic-plastic behavior of specimens including softening behavior, disturbed state concept (DSC) was implemented by nonlinear finite element analysis (NFEA) and hierarchical single surface (HISS) failure criterion, which is a failure surface without any singularity.

Keywords: disturbed state concept (DSC), hierarchical single surface (HISS) failure criterion, high performance concrete (HPC), high-strength concrete (HSC), nonlinear finite element analysis (NFEA), polymer concrete (PC), steel fibers, uniaxial compression test

Procedia PDF Downloads 303

Authors: Abdelmenen Abobghala, Mahmud Ahmed, Mohamed Alwaheshi, Anwar Fanan, Meftah Mehdawi, Ahmed Abuhatira

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This research aims to predict academic performance and identify weak points in students to aid teachers in understanding their learning needs. Both quantitative and qualitative methods are used to identify difficult test items and the factors causing difficulties. The study uses interventions like focus group discussions, interviews, and action plans developed by the students themselves. The research questions explore the predictability of final grades based on mock exams and assignments, the student's response to action plans, and the impact on learning performance. Ethical considerations are followed, respecting student privacy and maintaining anonymity. The research aims to enhance student engagement, motivation, and responsibility for learning.

Keywords: prediction, academic performance, weak points, understanding, learning, quantitative methods, qualitative methods, formative assessments, feedback, emotional responses, intervention, focus group discussion, interview, action plan, student engagement, motivation, responsibility, ethical considerations

Procedia PDF Downloads 58

Authors: Jonardan Koner, Basabi Bhattacharya, Avinash Purandare

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The study is focused to find out the impact of infrastructural investment on economic development in Indian states. The study uses panel data analysis to measure the impact of infrastructural investment on Real Gross Domestic Product in Indian States. Panel data analysis incorporates Unit Root Test, Cointegration Teat, Pooled Ordinary Least Squares, Fixed Effect Approach, Random Effect Approach, Hausman Test. The study analyzes panel data (annual in frequency) ranging from 1991 to 2012 and concludes that infrastructural investment has a desirable impact on economic development in Indian. Finally, the study reveals that the infrastructural investment significantly explains the variation of economic indicator.

Keywords: infrastructural investment, real GDP, unit root test, cointegration teat, pooled ordinary least squares, fixed effect approach, random effect approach, Hausman test

Procedia PDF Downloads 394

Authors: Migael van Zyl, Stefanie Visser, Awelani Phaswana

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The electricity landscape in South Africa is characterized by frequent occurrences of loadshedding, a measure implemented by Eskom to manage electricity generation shortages by curtailing demand. Loadshedding, classified into stages ranging from 1 to 8 based on severity, involves the systematic rotation of power cuts across municipalities according to predefined schedules. However, this practice introduces distortions in recorded electricity demand, posing challenges to accurate forecasting essential for budgeting, network planning, and generation scheduling. Addressing this challenge requires the development of a methodology to quantify the impact of loadshedding and integrate it back into metered electricity demand data. Fortunately, comprehensive records of loadshedding impacts are maintained in a database, enabling the alignment of Loadshedding effects with hourly demand data. This adjustment ensures that forecasts accurately reflect true demand patterns, independent of loadshedding's influence, thereby enhancing the reliability of electricity supply management in South Africa. This paper presents a methodology for determining the hourly impact of load scheduling and subsequently adjusting historical demand data to account for it. Furthermore, two forecasting models are developed: one utilizing the original dataset and the other using the adjusted data. A comparative analysis is conducted to evaluate forecast accuracy improvements resulting from the adjustment process. By implementing this methodology, stakeholders can make more informed decisions regarding electricity infrastructure investments, resource allocation, and operational planning, contributing to the overall stability and efficiency of South Africa's electricity supply system.

Keywords: electricity demand forecasting, load shedding, demand side management, data science

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Authors: Raif Parlakkaya, Ahmet Diken, Erkan Kara

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This paper examines the relationship between corporate governance rating and stock prices of 26 Turkish firms listed in Turkish stock exchange (Borsa Istanbul) by using panel data analysis over five-year period. The paper also investigates the stock performance of firms with governance rating with regards to the market portfolio (i.e. BIST 100 Index) both prior and after governance scoring began. The empirical results show that there is no relation between corporate governance rating and stock prices when using panel data for annual variation in both rating score and stock prices. Further analysis indicates surprising results that while the selected firms outperform the market significantly prior to rating, the same performance does not continue afterwards.

Keywords: corporate governance, stock price, performance, panel data analysis

Procedia PDF Downloads 383

Authors: Marco Khalaf Ayad Milhaail

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In thinking about the role of legal rules and their impact on social ethics and social structures, scholars have explored many issues related to gender, power, and ideology. First, it provides a framework for defining feminist legal studies through an overview of the field's evolution in terms of equality, rights, and justice. Secondly, it encourages those interested in equality, rights, and justice regarding women's issues to participate in international comparative law research. Third, we must emphasize that those seeking solutions to disability and discrimination must be aware of the need to confront the so-called undermining of culture. Therefore, an effective way for women to solve this problem is to rely heavily on international law, which establishes basic legal principles such as gender equality, rights, and justice and can help create a domestic environment. Woman has gained many advantages by adopting the law of Divorce in the Islamic Sharea. Any Egyptian woman can get divorce by letting her rightful rights and wealth to her husband in return for her freedom.

Keywords: stability, harsh environments, techniques, thermal, properties, materials, applications, brittleness, fragility, disadvantages, bank, branches, profitability, setting prediction, effective target, measurement, evaluation, performance, commercial, business, profitability, sustainability, financial, system, banks

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Authors: Kenneth Kapalu Muzata, Dikeledi Mahlo, Pinkie Mabunda Mabunda

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This paper presents results of a study conducted to establish special education teachers’ knowledge and application of curriculum adaptation of the 2013 revised curriculum in Zambia. From a sample of 134 respondents (120 special education teachers, 12 education officers, and 2 curriculum specialists), the study collected both quantitative and qualitative data to establish whether teachers understood and applied the concept of curriculum adaptation in teaching learners with special education needs. To obtain data validity and reliability, the researchers collected data by use of mixed methods. Semi-structured questionnaires and interviews were administered. Lesson Observations and post-lesson discussions were conducted on 12 selected teachers from the 120 sample that answered the questionnaires. Frequencies, percentages, and significant differences were derived through the statistical package for social sciences. Qualitative data were analyzed with the help of NVIVO qualitative software to create themes and obtain coding density to help with conclusions. Both quantitative and qualitative data were concurrently compared and related. The results revealed that special education teachers lacked a thorough understanding of the concept of curriculum adaptation, thus denying learners with special education needs the opportunity to benefit from the revised curriculum. The teachers were not oriented on the revised curriculum and hence facing numerous challenges trying to adapt the curriculum. The study recommended training of special education teachers in curriculum adaptation.

Keywords: curriculum adaptation, special education, learners with special education needs, special education teachers

Procedia PDF Downloads 168

Authors: Sayed Abdallah Mohamed Dahy

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Aswan High Dam Reservoir extends for 500 km along the Nile River; it is a vast reservoir in southern Egypt and northern Sudan. It was created as a result of the construction of the Aswan High Dam between 1958 and 1970; about 95% of the main water resources for Egypt are from it. The purpose of this study is to discuss and understand the effect of the fluctuation of the water level in the reservoir on natural and human-induced environmental like earthquakes in the Aswan area, Egypt. In summary, the correlation between the temporal variations of earthquake activity and water level changes in the Aswan reservoir from 1982 to 2014 are investigated and analyzed. This analysis confirms a weak relation between the fluctuation of the water level and earthquake activity in the area around Aswan reservoir. The result suggests that the seismicity in the area becomes active during a period when the water level is decreasing from the maximum to the minimum. Behavior of the water level in this reservoir characterized by a special manner that is the unloading season extends to July or August, and the loading season starts to reach its maximum in October or November every year. Finally, daily rate of change in the water level did not show any direct relation with the size of the earthquakes, hence, it is not possible to be used as a single tool for prediction.

Keywords: Aswan high dam reservoir, earthquake activity, environmental, Egypt

Procedia PDF Downloads 366

Authors: Marwa A. A. Ragab, Hadir M. Maher, Eman I. El-Kimary

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Co-administration of methotrexate (MTX) and aspirin (ASP) can cause a pharmacokinetic interaction and a subsequent increase in blood MTX concentrations which may increase the risk of MTX toxicity. Therefore, it is important to develop a sensitive, selective, accurate and precise method for their simultaneous determination in urine. A new hybrid chemometric method has been applied to the emission response data of the two drugs. Spectrofluorimetric method for determination of MTX through measurement of its acid-degradation product, 4-amino-4-deoxy-10-methylpteroic acid (4-AMP), was developed. Moreover, the acid-catalyzed degradation reaction enables the spectrofluorimetric determination of ASP through the formation of its active metabolite salicylic acid (SA). The proposed chemometric method deals with convolution of emission data using 8-points sin xi polynomials (discrete Fourier functions) after the derivative treatment of these emission data. The first and second derivative curves (D1 & D2) were obtained first then convolution of these curves was done to obtain first and second derivative under Fourier functions curves (D1/FF) and (D2/FF). This new application was used for the resolution of the overlapped emission bands of the degradation products of both drugs to allow their simultaneous indirect determination in human urine. Not only this chemometric approach was applied to the emission data but also the obtained data were subjected to non-parametric linear regression analysis (Theil’s method). The proposed method was fully validated according to the ICH guidelines and it yielded linearity ranges as follows: 0.05-0.75 and 0.5-2.5 µg mL-1 for MTX and ASP respectively. It was found that the non-parametric method was superior over the parametric one in the simultaneous determination of MTX and ASP after the chemometric treatment of the emission spectra of their degradation products. The work combines the advantages of derivative and convolution using discrete Fourier function together with the reliability and efficacy of the non-parametric analysis of data. The achieved sensitivity along with the low values of LOD (0.01 and 0.06 µg mL-1) and LOQ (0.04 and 0.2 µg mL-1) for MTX and ASP respectively, by the second derivative under Fourier functions (D2/FF) were promising and guarantee its application for monitoring the two drugs in patients’ urine samples.

Keywords: chemometrics, emission curves, derivative, convolution, Fourier transform, human urine, non-parametric regression, Theil’s method

Procedia PDF Downloads 419

Authors: Clare Cunningham

Abstract:

Whilst there is a strong global research base on the benefits of structured writing retreats and similar provisions, such as Shut Up and Write events, for academic staff and postgraduate researchers, very little has been published about the worth of such events for undergraduate students. This is despite the fact that, internationally, undergraduate student researchers experience similar pressures, distractions and feelings towards writing as those who are at more senior levels within the academy. This paper reports on a mixed-methods study with cohorts of third-year undergraduate students over the course of four academic years. This involved a range of research instruments adopted over the four years of the study. They include the administration of four questionnaires across three academic years, a collection of ethnographic recordings in the second year, and the collation of reflective journal entries and evaluations from all four years. The final two years of data collection took place during the period of Covid-19 restrictions when writing retreats moved to the virtual space which adds an additional dimension of interest to the analysis. The analysis involved the collation of quantitative questionnaire data to observe patterns in expressions of attitudes towards writing. Qualitative data were analysed thematically and used to corroborate and support the quantitative data when appropriate. The resulting data confirmed that one of the biggest challenges for undergraduate students mirrors those reported in the findings of studies focused on more experienced researchers. This is not surprising, especially given the number of undergraduate students who now work alongside their studies, as well as the increasing number who have caring responsibilities, but it has, as yet, been under-reported. The data showed that the groups of writing retreat participants all had very positive experiences, with accountability, a sense of community and procrastination avoidance some of the key aspects. The analysis revealed the sometimes transformative power of these events for a number of these students in terms of changing the way they viewed writing and themselves as writers. The data presented in this talk will support the proposal that retreats should much more widely be offered to undergraduate students across the world.

Keywords: academic writing, students, undergraduates, writing retreat

Procedia PDF Downloads 188

Authors: Farzad Khajavi

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Recognition of the interaction between active pharmaceutical ingredients (API) and excipients is a pivotal factor in the development of all pharmaceutical dosage forms. By predicting the interaction between API and excipients, we will be able to prevent the advent of impurities or at least lessen their amount. In this study, we used principle component analysis (PCA) to predict the interaction between Gliclazide as a secondary amine with Lactose in pharmaceutical solid dosage forms. The infrared spectra of binary mixtures of Gliclazide with Lactose at different mole ratios were recorded, and the obtained matrix was analyzed with PCA. By plotting score columns of the analyzed matrix, the incompatibility between Gliclazide and Lactose was observed. This incompatibility was seen experimentally. We observed the appearance of the impurity originated from the Maillard reaction between Gliclazide and Lactose at the chromatogram of the manufactured tablets in room temperature and under accelerated stability conditions. This impurity increases at the stability months. By changing Lactose to Mannitol and using Calcium Dibasic Phosphate in the tablet formulation, the amount of the impurity decreased and was in the acceptance range defined by British pharmacopeia for Gliclazide Tablets. This method is a fast and simple way to predict the existence of incompatibility between excipients and active pharmaceutical ingredients.

Keywords: PCA, gliclazide, impurity, infrared spectroscopy, interaction

Procedia PDF Downloads 197

Authors: Mohd Asrul Affedi, Nyi Nyi Naing

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Overdispersion is present in count data, and basically when a phenomenon happened, a Negative Binomial (NB) is commonly used to replace a standard Poisson model. Analysis of count data event, such as mortality cases basically Poisson regression model is appropriate. Hence, the model is not appropriate when existing a zero values. The zero-inflated negative binomial model is appropriate. In this article, we modelled the mortality cases as a dependent variable by age categorical. The objective of this study to determine existing overdispersion in mortality data of AIDS co-infection patients in Kelantan.

Keywords: negative binomial death rate, overdispersion, zero-inflation negative binomial death rate, AIDS

Procedia PDF Downloads 454

Authors: Mace Bentley, Zhuojun Duan, Tobias Gerken, Dudley Bonsal, Henry Way, Endre Szakal, Mia Pham, Hunter Donaldson, Chelsea Lang, Hayden Abbott, Leah Wilcynzski

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Air pollution has the potential to modify the lifespan and intensity of thunderstorms and the properties of lightning. Using data mining and geovisualization, we investigate how background climate and weather conditions shape variability in urban air pollution and how this, in turn, shapes thunderstorms as measured by the intensity, distribution, and frequency of cloud-to-ground lightning. A spatiotemporal analysis was conducted in order to identify thunderstorms using high-resolution lightning detection network data. Over seven million lightning flashes were used to identify more than 196,000 thunderstorms that occurred between 2006 - 2020 in the Washington, DC Metropolitan Region. Each lightning flash in the dataset was grouped into thunderstorm events by means of a temporal and spatial clustering algorithm. Once the thunderstorm event database was constructed, hourly wind direction, wind speed, and atmospheric thermodynamic data were added to the initiation and dissipation times and locations for the 196,000 identified thunderstorms. Hourly aerosol and air quality data for the thunderstorm initiation times and locations were also incorporated into the dataset. Developing thunderstorm climatologies using a lightning tracking algorithm and lightning detection network data was found to be useful for visualizing the spatial and temporal distribution of urban augmented thunderstorms in the region.

Keywords: lightning, urbanization, thunderstorms, climatology

Procedia PDF Downloads 62

Authors: Zahra Ramezanpanah, Joachim Carvallo, Aurelien Rodriguez

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This paper aims to detect anomalies in streaming data using machine learning algorithms. In this regard, we designed two separate pipelines and evaluated the effectiveness of each separately. The first pipeline, based on supervised machine learning methods, consists of two phases. In the first phase, we trained several supervised models using the UNSW-NB15 data-set. We measured the efficiency of each using different performance metrics and selected the best model for the second phase. At the beginning of the second phase, we first, using Argus Server, sniffed a local area network. Several types of attacks were simulated and then sent the sniffed data to a running algorithm at short intervals. This algorithm can display the results of each packet of received data in real-time using the trained model. The second pipeline presented in this paper is based on unsupervised algorithms, in which a Temporal Graph Network (TGN) is used to monitor a local network. The TGN is trained to predict the probability of future states of the network based on its past behavior. Our contribution in this section is introducing an indicator to identify anomalies from these predicted probabilities.

Keywords: temporal graph network, anomaly detection, cyber security, IDS

Procedia PDF Downloads 92

Authors: Usiobaifo Agharese Rosemary, Osaseri Roseline Oghogho

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Diabetes is a complex group of disease with a variety of causes; it is a disorder of the body metabolism in the digestion of carbohydrates food. The application of machine learning in the field of medical diagnosis has been the focus of many researchers and the use of recognition and classification model as a decision support tools has help the medical expert in diagnosis of diseases. Considering the large volume of medical data which require special techniques, experience, and high diagnostic skill in the diagnosis of diseases, the application of an artificial intelligent system to assist medical personnel in order to enhance their efficiency and accuracy in diagnosis will be an invaluable tool. In this study will propose a diabetes diagnosis model using rough set and K-nearest Neighbor classifier algorithm. The system consists of two modules: the feature extraction module and predictor module, rough data set is used to preprocess the attributes while K-nearest neighbor classifier is used to classify the given data. The dataset used for this model was taken for University of Benin Teaching Hospital (UBTH) database. Half of the data was used in the training while the other half was used in testing the system. The proposed model was able to achieve over 80% accuracy.

Keywords: classifier algorithm, diabetes, diagnostic model, machine learning

Procedia PDF Downloads 325

Authors: Budhvin T. Withana, Sulochana Rupasinghe

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The problem of Dyslexia and Dysgraphia, two learning disabilities that affect reading and writing abilities, respectively, is a major concern for the educational system. Due to the complexity and uniqueness of the Sinhala language, these conditions are especially difficult for children who speak it. The traditional risk detection methods for Dyslexia and Dysgraphia frequently rely on subjective assessments, making it difficult to cover a wide range of risk detection and time-consuming. As a result, diagnoses may be delayed and opportunities for early intervention may be lost. The project was approached by developing a hybrid model that utilized various deep learning techniques for detecting risk of Dyslexia and Dysgraphia. Specifically, Resnet50, VGG16 and YOLOv8 were integrated to detect the handwriting issues, and their outputs were fed into an MLP model along with several other input data. The hyperparameters of the MLP model were fine-tuned using Grid Search CV, which allowed for the optimal values to be identified for the model. This approach proved to be effective in accurately predicting the risk of Dyslexia and Dysgraphia, providing a valuable tool for early detection and intervention of these conditions. The Resnet50 model achieved an accuracy of 0.9804 on the training data and 0.9653 on the validation data. The VGG16 model achieved an accuracy of 0.9991 on the training data and 0.9891 on the validation data. The MLP model achieved an impressive training accuracy of 0.99918 and a testing accuracy of 0.99223, with a loss of 0.01371. These results demonstrate that the proposed hybrid model achieved a high level of accuracy in predicting the risk of Dyslexia and Dysgraphia.

Keywords: neural networks, risk detection system, Dyslexia, Dysgraphia, deep learning, learning disabilities, data science

Procedia PDF Downloads 86

Authors: Wei Yongxiang, Zhu Haoyue, Tang Heng, Yuan Qunwei

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In order to study the preparation method of gear fatigue load spectrum for loaders, the load signal of four typical working conditions of loader is collected. The signal that reflects the law of load change is obtained by preprocessing the original signal. The torque of the drive axle is calculated by using the rain flow counting method. According to the operating time ratio of each working condition, the two-dimensional load spectrum based on the real working conditions of the drive axle of loader is established by the cycle extrapolation and synthesis method. The two-dimensional load spectrum is converted into one-dimensional load spectrum by means of the mean of torque equal damage method. Torque amplification includes the maximum load torque of the main reduction gear. Based on the theory of equal damage, the accelerated cycles are calculated. In this way, the load spectrum of the loading condition of the drive axle is prepared to reflect loading condition of the loader. The load spectrum can provide reference for fatigue life test and life prediction of loader drive axle.

Keywords: load spectrum, axle, torque, rain-flow counting method, extrapolation

Procedia PDF Downloads 353

Authors: Thanduxolo Nomngcoyiya, Simon M. Kang’ethe

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The paper aimed to critically analyse gaps pertaining to the cultural policy environments governing traditional male circumcision in the Eastern Cape as exemplified by an empirical case study. The original study which this paper is derived from utilized qualitative paradigm; and encompassed 28 participants. It used in-depth one-on-one interviews complemented by focus group discussions and key informants as a method of data collection. It also adopted interview guide as a data collection instrument. The original study was cross-sectional in nature, and the data was audio recorded and transcribed later during the data analysis and coding process. The study data analysis was content thematic analysis and identified the following key major findings on the culture of male circumcision policy: Lack of clarity on culture of male circumcision policy operations; Myths surrounding procedures on culture of male circumcision; Divergent views on cultural policies between government and male circumcision custodians; Unclear cultural policies on selection criteria of practitioners; and Lack of policy enforcement and implementation on transgressors of culture of male circumcision. It recommended: a stringent selection criteria of practitioners; a need to carry out death-free male circumcision; a need for male circumcision stakeholders to work with other culture and tradition-friendly stakeholders.

Keywords: human rights, policy enforcement, traditional male circumcision, traditional surgeons and nurses

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Authors: Christopher B. Obida, George A. Blackburn, James D. Whyatt, Kirk T. Semple

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In many regions of the world, especially in developing countries, river network data are outdated or completely absent, yet such information is critical for supporting important functions such as flood mitigation efforts, land use and transportation planning, and the management of water resources. In this study, a method was developed for delineating river networks using Sentinel 1 imagery. Unsupervised classification was applied to multi-temporal Sentinel 1 data to discriminate water bodies from other land covers then the outputs were combined to generate a single persistent water bodies product. A thinning algorithm was then used to delineate river centre lines, which were converted into vector features and built into a topologically structured geometric network. The complex river system of the Niger Delta was used to compare the performance of the Sentinel-based method against alternative freely available water body products from United States Geological Survey, European Space Agency and OpenStreetMap and a river network derived from a Shuttle Rader Topography Mission Digital Elevation Model. From both raster-based and vector-based accuracy assessments, it was found that the Sentinel-based river network products were superior to the comparator data sets by a substantial margin. The geometric river network that was constructed permitted a flow routing analysis which is important for a variety of environmental management and planning applications. The extracted network will potentially be applied for modelling dispersion of hydrocarbon pollutants in Ogoniland, a part of the Niger Delta. The approach developed in this study holds considerable potential for generating up to date, detailed river network data for the many countries where such data are deficient.

Keywords: Sentinel 1, image processing, river delineation, large scale mapping, data comparison, geometric network

Procedia PDF Downloads 131

Authors: Katsuyuki Umezawa, Makoto Nakazawa, Manabu Kobayashi, Yutaka Ishii, Michiko Nakano, Shigeichi Hirasawa

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This research aims to develop a self-study system equipped with an artificial teacher who gives advice to students by detecting the learners and to evaluate language learning in a unified framework. 'Detecting the learners' means that the system understands the learners' learning conditions, such as each learner’s degree of understanding, the difference in each learner’s thinking process, the degree of concentration or boredom in learning, and problem solving for each learner, which can be interpreted from learning behavior. In this paper, we propose a system to efficiently collect brain waves from learners by focusing on only the brain waves among the biological information for 'detecting the learners'. The conventional Electroencephalograph (EEG) measurement method during learning using a simple EEG has the following disadvantages. (1) The start and end of EEG measurement must be done manually by the experiment participant or staff. (2) Even when the EEG signal is weak, it may not be noticed, and the data may not be obtained. (3) Since the acquired EEG data is stored in each PC, there is a possibility that the time of data acquisition will be different in each PC. This time, we developed a system to collect brain wave data on the server side. This system overcame the above disadvantages.

Keywords: artificial teacher, e-learning, self-study system, simple EEG

Procedia PDF Downloads 134

Authors: Valentina Alessandra Carvalho do Vale, Elmo Thiago Lins Cöuras Ford

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Increasingly telecommunications sectors are adopting optical technologies, due to its ability to transmit large amounts of data over long distances. However, as in all systems of data transmission, optical communication channels suffer from undesirable and non-deterministic effects, being essential to know the same. Thus, this research allows the assessment of these effects, as well as their characterization and beneficial uses of these effects.

Keywords: optical communication, optical fiber, non-deterministic effects, telecommunication

Procedia PDF Downloads 782

Authors: Arturo Daag

Abstract:

The Philippine Institute of Volcanology and Seismology (PHIVOLCS) is enhancing its liquefaction hazard map towards a detailed probabilistic approach using SDS and geophysical data. Target sites for liquefaction assessment are public schools in Metro Manila. Since target sites are in highly urbanized-setting, the objective of the project is to conduct both non-destructive geotechnical studies using Screw Driving Testing (SDFS) combined with geophysical data such as refraction microtremor array (ReMi), 3 component microtremor Horizontal to Vertical Spectral Ratio (HVSR), and ground penetrating RADAR (GPR). Initial test data was conducted in liquefaction impacted areas from the Mw 6.1 earthquake in Central Luzon last April 22, 2019 Province of Pampanga. Numerous accounts of liquefaction events were documented areas underlain by quaternary alluvium and mostly covered by recent lahar deposits. SDS estimated values showed a good correlation to actual SPT values obtained from available borehole data. Thus, confirming that SDS can be an alternative tool for liquefaction assessment and more efficient in terms of cost and time compared to SPT and CPT. Conducting borehole may limit its access in highly urbanized areas. In order to extend or extrapolate the SPT borehole data, non-destructive geophysical equipment was used. A 3-component microtremor obtains a subsurface velocity model in 1-D seismic shear wave velocity of the upper 30 meters of the profile (Vs30). For the ReMi, 12 geophone array with 6 to 8-meter spacing surveys were conducted. Microtremor data were computed through the Factor of Safety, which is the quotient of Cyclic Resistance Ratio (CRR) and Cyclic Stress Ratio (CSR). Complementary GPR was used to study the subsurface structure and used to inferred subsurface structures and groundwater conditions.

Keywords: screw drive testing, microtremor, ground penetrating RADAR, liquefaction

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Authors: Abir Derouiche, Abdesslem Layeb

Abstract:

Association Rule Mining (ARM) is one of the most popular data mining tasks and it is widely used in various areas. The search for association rules is an NP-complete problem that is why metaheuristics have been widely used to solve it. The present paper presents the ARM as an optimization problem and surveys the proposed approaches in the literature based on metaheuristics.

Keywords: Optimization, Metaheuristics, Data Mining, Association rules Mining

Procedia PDF Downloads 151

Authors: Mehrnaz Alibeikloo, Hadi Khabbaz, Behzad Fatahi

Abstract:

The spectral random field method is one of the widely used methods to obtain more reliable and accurate results in geotechnical problems involving material variability. Karhunen-Loeve (K-L) expansion method was applied to perform random field discretization of cross-correlated creep parameters. Karhunen-Loeve expansion method is based on eigenfunctions and eigenvalues of covariance function adopting Kernel integral solution. In this paper, the accuracy of Karhunen-Loeve expansion was investigated to predict long-term settlement of soft soils adopting elastic visco-plastic creep model. For this purpose, a parametric study was carried to evaluate the effect of K-L expansion terms and spatial correlation length on the reliability of results. The results indicate that small values of spatial correlation length require more K-L expansion terms. Moreover, by increasing spatial correlation length, the coefficient of variation (COV) of creep settlement increases, confirming more conservative and safer prediction.

Keywords: Karhunen-Loeve expansion, long-term settlement, reliability analysis, spatial correlation length

Procedia PDF Downloads 149

Authors: Yi-Ping Lo, Shi-Yao Wei, Chih-Chun Ma

Abstract:

Since Google launched Google Glass in 2012, numbers of commercial wearable devices were released, such as smart belt, smart band, smart shoes, smart clothes ... etc. However, most of these devices perform as sensors to show the readings of measurements and few of them provide the interactive feedback to the user. Furthermore, these devices are single task devices which are not able to communicate with each other. In this paper a new health promotion system, Ubiquitous Life People Informatics Engine (U-Life PIE), will be presented. This engine consists of People Informatics Engine (PIE) and the interactive user interface. PIE collects all the data from the compatible devices, analyzes this data comprehensively and communicates between devices via various application programming interfaces. All the data and informations are stored on the PIE unit, therefore, the user is able to view the instant and historical data on their mobile devices any time. It also provides the real-time hands-free feedback and instructions through the user interface visually, acoustically and tactilely. These feedback and instructions suggest the user to adjust their posture or habits in order to avoid the physical injuries and prevent illness.

Keywords: machine learning, wearable devices, user interface, user experience, internet of things

Procedia PDF Downloads 276