Search results for: random factor
5730 A Research Study of the Inclusiveness of VR Headsets for Higher Education
Authors: Fredrick Forster, Gareth Ward, Matthew Tubby, Pamela Lithgow, Anne Nortcliffe
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This paper presents the results from a research study of random adult participants accessing one of four different commercially available Virtual Reality (VR) Head Mounted Displays (HMDs) and completing a post user experience reflection questionnaire. The research sort to understand how inclusive commercially available VR HMDs are and identify any associated barriers that could impact the widespread adoption of the devices, specifically in Higher Education (HE). In the UK, education providers are legally required under the Equality Act 2010 to ensure all education facilities are inclusive and reasonable adjustments can be applied appropriately. The research specifically aimed to identify the considerations that academics and learning technologists need to make when adopting the use of commercial VR HMDs in HE classrooms, namely cybersickness, user comfort, Interpupillary Distance, inclusiveness, and user perceptions of VR. The research approach was designed to build upon previously published research on user reflections on presence, usability, and overall HMD comfort, using quantitative and qualitative research methods by way of a questionnaire. The quantitative data included the recording of physical characteristics such as the distance between eye pupils, known as Interpupillary Distance (IPD). VR HMDs require each user’s IPD measurement to enable the focusing of the VR HMDs virtual camera output to the right position in front of the eyes of the user. In addition, the questionnaire captured users’ qualitative reflections and evaluations of the broader accessibility characteristics of the VR HMDs. The initial research activity was accomplished by enabling a random sample of visitors, staff, and students at Canterbury Christ Church University, Kent to use a VR HMD for a set period of time and asking them to complete the post user experience questionnaire. The study identified that there is little correlation between users who experience cyber sickness and car sickness. Also, users with a smaller IPD than average (typically associated with females) were able to use the VR HMDs successfully; however, users with a larger than average IPD reported an impeded experience. This indicates that there is reduced inclusiveness for the tested VR HMDs for users with a higher-than-average IPD which is typically associated with males of certain ethnicities. As action education research, these initial findings will be used to refine the research method and conduct further investigations with the aim to provide verification and validation of the accessibility of current commercial VR HMDs. The conference presentation will report on the research results of the initial study and subsequent follow up studies with a larger variety of adult volunteers.Keywords: virtual reality, education technology, inclusive technology, higher education
Procedia PDF Downloads 685729 Development of Enhanced Data Encryption Standard
Authors: Benjamin Okike
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There is a need to hide information along the superhighway. Today, information relating to the survival of individuals, organizations, or government agencies is transmitted from one point to another. Adversaries are always on the watch along the superhighway to intercept any information that would enable them to inflict psychological ‘injuries’ to their victims. But with information encryption, this can be prevented completely or at worst reduced to the barest minimum. There is no doubt that so many encryption techniques have been proposed, and some of them are already being implemented. However, adversaries always discover loopholes on them to perpetuate their evil plans. In this work, we propose the enhanced data encryption standard (EDES) that would deploy randomly generated numbers as an encryption method. Each time encryption is to be carried out, a new set of random numbers would be generated, thereby making it almost impossible for cryptanalysts to decrypt any information encrypted with this newly proposed method.Keywords: encryption, enhanced data encryption, encryption techniques, information security
Procedia PDF Downloads 1505728 A Development of a Simulation Tool for Production Planning with Capacity-Booking at Specialty Store Retailer of Private Label Apparel Firms
Authors: Erika Yamaguchi, Sirawadee Arunyanrt, Shunichi Ohmori, Kazuho Yoshimoto
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In this paper, we suggest a simulation tool to make a decision of monthly production planning for maximizing a profit of Specialty store retailer of Private label Apparel (SPA) firms. Most of SPA firms are fabless and make outsourcing deals for productions with factories of their subcontractors. Every month, SPA firms make a booking for production lines and manpower in the factories. The booking is conducted a few months in advance based on a demand prediction and a monthly production planning at that time. However, the demand prediction is updated month by month, and the monthly production planning would change to meet the latest demand prediction. Then, SPA firms have to change the capacities initially booked within a certain range to suit to the monthly production planning. The booking system is called “capacity-booking”. These days, though it is an issue for SPA firms to make precise monthly production planning, many firms are still conducting the production planning by empirical rules. In addition, it is also a challenge for SPA firms to match their products and factories with considering their demand predictabilities and regulation abilities. In this paper, we suggest a model for considering these two issues. An objective is to maximize a total profit of certain periods, which is sales minus costs of production, inventory, and capacity-booking penalty. To make a better monthly production planning at SPA firms, these points should be considered: demand predictabilities by random trends, previous and next month’s production planning of the target month, and regulation abilities of the capacity-booking. To decide matching products and factories for outsourcing, it is important to consider seasonality, volume, and predictability of each product, production possibility, size, and regulation ability of each factory. SPA firms have to consider these constructions and decide orders with several factories per one product. We modeled these issues as a linear programming. To validate the model, an example of several computational experiments with a SPA firm is presented. We suppose four typical product groups: basic, seasonal (Spring / Summer), seasonal (Fall / Winter), and spot product. As a result of the experiments, a monthly production planning was provided. In the planning, demand predictabilities from random trend are reduced by producing products which are different product types. Moreover, priorities to produce are given to high-margin products. In conclusion, we developed a simulation tool to make a decision of monthly production planning which is useful when the production planning is set every month. We considered the features of capacity-booking, and matching of products and factories which have different features and conditions.Keywords: capacity-booking, SPA, monthly production planning, linear programming
Procedia PDF Downloads 5195727 The Use of the TRIGRS Model and Geophysics Methodologies to Identify Landslides Susceptible Areas: Case Study of Campos do Jordao-SP, Brazil
Authors: Tehrrie Konig, Cassiano Bortolozo, Daniel Metodiev, Rodolfo Mendes, Marcio Andrade, Marcio Moraes
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Gravitational mass movements are recurrent events in Brazil, usually triggered by intense rainfall. When these events occur in urban areas, they end up becoming disasters due to the economic damage, social impact, and loss of human life. To identify the landslide-susceptible areas, it is important to know the geotechnical parameters of the soil, such as cohesion, internal friction angle, unit weight, hydraulic conductivity, and hydraulic diffusivity. The measurement of these parameters is made by collecting soil samples to analyze in the laboratory and by using geophysical methodologies, such as Vertical Electrical Survey (VES). The geophysical surveys analyze the soil properties with minimal impact in its initial structure. Statistical analysis and mathematical models of physical basis are used to model and calculate the Factor of Safety for steep slope areas. In general, such mathematical models work from the combination of slope stability models and hydrological models. One example is the mathematical model TRIGRS (Transient Rainfall Infiltration and Grid-based Regional Slope- Stability Model) which calculates the variation of the Factor of Safety of a determined study area. The model relies on changes in pore-pressure and soil moisture during a rainfall event. TRIGRS was written in the Fortran programming language and associates the hydrological model, which is based on the Richards Equation, with the stability model based on the principle of equilibrium limit. Therefore, the aims of this work are modeling the slope stability of Campos do Jordão with TRIGRS, using geotechnical and geophysical methodologies to acquire the soil properties. The study area is located at southern-east of Sao Paulo State in the Mantiqueira Mountains and has a historic landslide register. During the fieldwork, soil samples were collected, and the VES method applied. These procedures provide the soil properties, which were used as input data in the TRIGRS model. The hydrological data (infiltration rate and initial water table height) and rainfall duration and intensity, were acquired from the eight rain gauges installed by Cemaden in the study area. A very high spatial resolution digital terrain model was used to identify the slopes declivity. The analyzed period is from March 6th to March 8th of 2017. As results, the TRIGRS model calculates the variation of the Factor of Safety within a 72-hour period in which two heavy rainfall events stroke the area and six landslides were registered. After each rainfall, the Factor of Safety declined, as expected. The landslides happened in areas identified by the model with low values of Factor of Safety, proving its efficiency on the identification of landslides susceptible areas. This study presents a critical threshold for landslides, in which an accumulated rainfall higher than 80mm/m² in 72 hours might trigger landslides in urban and natural slopes. The geotechnical and geophysics methods are shown to be very useful to identify the soil properties and provide the geological characteristics of the area. Therefore, the combine geotechnical and geophysical methods for soil characterization and the modeling of landslides susceptible areas with TRIGRS are useful for urban planning. Furthermore, early warning systems can be developed by combining the TRIGRS model and weather forecast, to prevent disasters in urban slopes.Keywords: landslides, susceptibility, TRIGRS, vertical electrical survey
Procedia PDF Downloads 1735726 Levy Model for Commodity Pricing
Authors: V. Benedico, C. Anacleto, A. Bearzi, L. Brice, V. Delahaye
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The aim in present paper is to construct an affordable and reliable commodity prices based on a recalculation of its cost through time which allows visualize the potential risks and thus, take more appropriate decisions regarding forecasts. Here attention has been focused on Levy model, more reliable and realistic than classical random Gaussian one as it takes into consideration observed abrupt jumps in case of sudden price variation. In application to Energy Trading sector where it has never been used before, equations corresponding to Levy model have been written for electricity pricing in European market. Parameters have been set in order to predict and simulate the price and its evolution through time to remarkable accuracy. As predicted by Levy model, the results show significant spikes which reach unconventional levels contrary to currently used Brownian model.Keywords: commodity pricing, Lévy Model, price spikes, electricity market
Procedia PDF Downloads 4295725 Relationship between Quality Education and Organizational Culture at College Level in Punjab
Authors: Anam Noshaba, Mahr Muhammad Saeed Akhtar
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The aim of this study was to find out the relationship between quality education and organizational culture. The population of this study was all the teachers of Public Degree Colleges located in Punjab. A sample of 400 teachers was selected by using a simple random sampling technique. Quality Education Assessment Questionnaire (QEAQ) and Organizational Culture Assessment Instrument (OCAI) were used for data collection. Out of all, 90% of teachers responded. Findings showed that quality education and organizational culture are positively correlated. Results indicated that there is no difference in quality education and organizational culture by demographic variables of teachers. Future research is needed to study the viewpoint of other stakeholders of education regarding quality education and organizational culture.Keywords: quality education, minimum quality standards, organizational culture, college level
Procedia PDF Downloads 1395724 Memory and Narratives Rereading before and after One Week
Authors: Abigail M. Csik, Gabriel A. Radvansky
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As people read through event-based narratives, they construct an event model that captures information about the characters, goals, location, time, and causality. For many reasons, memory for such narratives is represented at different levels, namely, the surface form, textbase, and event model levels. Rereading has been shown to decrease surface form memory, while, at the same time, increasing textbase and event model memories. More generally, distributed practice has consistently shown memory benefits over massed practice for different types of materials, including texts. However, little research has investigated distributed practice of narratives at different inter-study intervals and these effects on these three levels of memory. Recent work in our lab has indicated that there may be dramatic changes in patterns of forgetting around one week, which may affect the three levels of memory. The present experiment aimed to determine the effects of rereading on the three levels of memory as a factor of whether the texts were reread before versus after one week. Participants (N = 42) read a set of stories, re-read them either before or after one week (with an inter-study interval of three days, seven days, or fourteen days), and then took a recognition test, from which the three levels of representation were derived. Signal detection results from this study reveal that differential patterns at the three levels as a factor of whether the narratives were re-read prior to one week or after one week. In particular, an ANOVA revealed that surface form memory was lower (p = .08) while textbase (p = .02) and event model memory (p = .04) were greater if narratives were re-read 14 days later compared to memory when narratives were re-read 3 days later. These results have implications for what type of memory benefits from distributed practice at various inter-study intervals.Keywords: memory, event cognition, distributed practice, consolidation
Procedia PDF Downloads 2255723 Elements of Creativity and Innovation
Authors: Fadwa Al Bawardi
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In March 2021, the Saudi Arabian Council of Ministers issued a decision to form a committee called the "Higher Committee for Research, Development and Innovation," a committee linked to the Council of Economic and Development Affairs, chaired by the Chairman of the Council of Economic and Development Affairs, and concerned with the development of the research, development and innovation sector in the Kingdom. In order to talk about the dimensions of this wonderful step, let us first try to answer the following questions. Is there a difference between creativity and innovation..? What are the factors of creativity in the individual. Are they mental genetic factors or are they factors that an individual acquires through learning..? The methodology included surveys that have been conducted on more than 500 individuals, males and females, between the ages of 18 till 60. And the answer is. "Creativity" is the creation of a new idea, while "Innovation" is the development of an already existing idea in a new, successful way. They are two sides of the same coin, as the "creative idea" needs to be developed and transformed into an "innovation" in order to achieve either strategic achievements at the level of countries and institutions to enhance organizational intelligence, or achievements at the level of individuals. For example, the beginning of smart phones was just a creative idea from IBM in 1994, but the actual successful innovation for the manufacture, development and marketing of these phones was through Apple later. Nor does creativity have to be hereditary. There are three basic factors for creativity: The first factor is "the presence of a challenge or an obstacle" that the individual faces and seeks thinking to find solutions to overcome, even if thinking requires a long time. The second factor is the "environment surrounding" of the individual, which includes science, training, experience gained, the ability to use techniques, as well as the ability to assess whether the idea is feasible or otherwise. To achieve this factor, the individual must be aware of own skills, strengths, hobbies, and aspects in which one can be creative, and the individual must also be self-confident and courageous enough to suggest those new ideas. The third factor is "Experience and the Ability to Accept Risk and Lack of Initial Success," and then learn from mistakes and try again tirelessly. There are some tools and techniques that help the individual to reach creative and innovative ideas, such as: Mind Maps tool, through which the available information is drawn by writing a short word for each piece of information and arranging all other relevant information through clear lines, which helps in logical thinking and correct vision. There is also a tool called "Flow Charts", which are graphics that show the sequence of data and expected results according to an ordered scenario of events and workflow steps, giving clarity to the ideas, their sequence, and what is expected of them. There are also other great tools such as the Six Hats tool, a useful tool to be applied by a group of people for effective planning and detailed logical thinking, and the Snowball tool. And all of them are tools that greatly help in organizing and arranging mental thoughts, and making the right decisions. It is also easy to learn, apply and use all those tools and techniques to reach creative and innovative solutions. The detailed figures and results of the conducted surveys are available upon request, with charts showing the %s based on gender, age groups, and job categories.Keywords: innovation, creativity, factors, tools
Procedia PDF Downloads 555722 Newspaper Framing of President Buhari’s Handling of Insecurity in Nigeria, January 2016 - December 2017
Authors: Onyekwere Okpara, Kingsley C. Izuogu
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This paper examined newspaper framing of President Buhari's handling of insecurity in Nigeria between January 2016-December 2017. The objectives were to examine the tone and sources of news frames used in reporting President Buhari's handling of insecurity in Nigeria. This paper did a content analysis of three newspapers-Daily Sun, The Nation, and the Leadership. Using a systematic random sampling, the study sampled a total of 732 editions of the selected newspapers and found out that the newspapers used neutral tone and government frame. The study, therefore, recommended that newspapers should improve their investigative reporting efforts.Keywords: insecurity, newspapers, framing, media
Procedia PDF Downloads 945721 Tumor Detection Using Convolutional Neural Networks (CNN) Based Neural Network
Authors: Vinai K. Singh
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In Neural Network-based Learning techniques, there are several models of Convolutional Networks. Whenever the methods are deployed with large datasets, only then can their applicability and appropriateness be determined. Clinical and pathological pictures of lobular carcinoma are thought to exhibit a large number of random formations and textures. Working with such pictures is a difficult problem in machine learning. Focusing on wet laboratories and following the outcomes, numerous studies have been published with fresh commentaries in the investigation. In this research, we provide a framework that can operate effectively on raw photos of various resolutions while easing the issues caused by the existence of patterns and texturing. The suggested approach produces very good findings that may be used to make decisions in the diagnosis of cancer.Keywords: lobular carcinoma, convolutional neural networks (CNN), deep learning, histopathological imagery scans
Procedia PDF Downloads 1365720 Influence of Specimen Geometry (10*10*40), (12*12*60) and (5*20*120), on Determination of Toughness of Concrete Measurement of Critical Stress Intensity Factor: A Comparative Study
Authors: M. Benzerara, B. Redjel, B. Kebaili
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The cracking of the concrete is a more crucial problem with the development of the complex structures related to technological progress. The projections in the knowledge of the breaking process make it possible today for better prevention of the risk of the fracture. The breaking strength brutal of a quasi-fragile material like the concrete called Toughness is measured by a breaking value of the factor of the intensity of the constraints K1C for which the crack is propagated, it is an intrinsic property of the material. Many studies reported in the literature treating of the concrete were carried out on specimens which are in fact inadequate compared to the intrinsic characteristic to identify. We started from this established fact, in order to compare the evolution of the parameter of toughness K1C measured by calling upon ordinary concrete specimens of three prismatic geometries different (10*10*40) Cm3, (12*12*60) Cm3 & (5*20*120) Cm3 containing from the side notches various depths simulating of the cracks was set up.The notches are carried out using triangular pyramidal plates into manufactured out of sheet coated placed at the center of the specimens at the time of the casting, then withdrawn to leave the trace of a crack. The tests are carried out in 3 points bending test in mode 1 of fracture, by using the techniques of mechanical fracture. The evolution of the parameter of toughness K1C measured with the three geometries specimens gives almost the same results. They are acceptable and return in the beach of the results determined by various researchers (toughness of the ordinary concrete turns to the turn of the 1 MPa √m). These results inform us about the presence of an economy on the level of the geometry specimen (5*20*120) Cm3, therefore, to use plates specimens later if one wants to master the toughness of this material complexes, astonishing but always essential that is the concrete.Keywords: concrete, fissure, specimen, toughness
Procedia PDF Downloads 2985719 Machine Learning Prediction of Diabetes Prevalence in the U.S. Using Demographic, Physical, and Lifestyle Indicators: A Study Based on NHANES 2009-2018
Authors: Oluwafunmibi Omotayo Fasanya, Augustine Kena Adjei
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To develop a machine learning model to predict diabetes (DM) prevalence in the U.S. population using demographic characteristics, physical indicators, and lifestyle habits, and to analyze how these factors contribute to the likelihood of diabetes. We analyzed data from 23,546 participants aged 20 and older, who were non-pregnant, from the 2009-2018 National Health and Nutrition Examination Survey (NHANES). The dataset included key demographic (age, sex, ethnicity), physical (BMI, leg length, total cholesterol [TCHOL], fasting plasma glucose), and lifestyle indicators (smoking habits). A weighted sample was used to account for NHANES survey design features such as stratification and clustering. A classification machine learning model was trained to predict diabetes status. The target variable was binary (diabetes or non-diabetes) based on fasting plasma glucose measurements. The following models were evaluated: Logistic Regression (baseline), Random Forest Classifier, Gradient Boosting Machine (GBM), Support Vector Machine (SVM). Model performance was assessed using accuracy, F1-score, AUC-ROC, and precision-recall metrics. Feature importance was analyzed using SHAP values to interpret the contributions of variables such as age, BMI, ethnicity, and smoking status. The Gradient Boosting Machine (GBM) model outperformed other classifiers with an AUC-ROC score of 0.85. Feature importance analysis revealed the following key predictors: Age: The most significant predictor, with diabetes prevalence increasing with age, peaking around the 60s for males and 70s for females. BMI: Higher BMI was strongly associated with a higher risk of diabetes. Ethnicity: Black participants had the highest predicted prevalence of diabetes (14.6%), followed by Mexican-Americans (13.5%) and Whites (10.6%). TCHOL: Diabetics had lower total cholesterol levels, particularly among White participants (mean decline of 23.6 mg/dL). Smoking: Smoking showed a slight increase in diabetes risk among Whites (0.2%) but had a limited effect in other ethnic groups. Using machine learning models, we identified key demographic, physical, and lifestyle predictors of diabetes in the U.S. population. The results confirm that diabetes prevalence varies significantly across age, BMI, and ethnic groups, with lifestyle factors such as smoking contributing differently by ethnicity. These findings provide a basis for more targeted public health interventions and resource allocation for diabetes management.Keywords: diabetes, NHANES, random forest, gradient boosting machine, support vector machine
Procedia PDF Downloads 85718 Prevalence of Breast Cancer Molecular Subtypes at a Tertiary Cancer Institute
Authors: Nahush Modak, Meena Pangarkar, Anand Pathak, Ankita Tamhane
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Background: Breast cancer is the prominent cause of cancer and mortality among women. This study was done to show the statistical analysis of a cohort of over 250 patients detected with breast cancer diagnosed by oncologists using Immunohistochemistry (IHC). IHC was performed by using ER; PR; HER2; Ki-67 antibodies. Materials and methods: Formalin fixed Paraffin embedded tissue samples were obtained by surgical manner and standard protocol was followed for fixation, grossing, tissue processing, embedding, cutting and IHC. The Ventana Benchmark XT machine was used for automated IHC of the samples. Antibodies used were supplied by F. Hoffmann-La Roche Ltd. Statistical analysis was performed by using SPSS for windows. Statistical tests performed were chi-squared test and Correlation tests with p<.01. The raw data was collected and provided by National Cancer Insitute, Jamtha, India. Result: Luminal B was the most prevailing molecular subtype of Breast cancer at our institute. Chi squared test of homogeneity was performed to find equality in distribution and Luminal B was the most prevalent molecular subtype. The worse prognostic indicator for breast cancer depends upon expression of Ki-67 and her2 protein in cancerous cells. Our study was done at p <.01 and significant dependence was observed. There exists no dependence of age on molecular subtype of breast cancer. Similarly, age is an independent variable while considering Ki-67 expression. Chi square test performed on Human epidermal growth factor receptor 2 (HER2) statuses of patients and strong dependence was observed in percentage of Ki-67 expression and Her2 (+/-) character which shows that, value of Ki depends upon Her2 expression in cancerous cells (p<.01). Surprisingly, dependence was observed in case of Ki-67 and Pr, at p <.01. This shows that Progesterone receptor proteins (PR) are over-expressed when there is an elevation in expression of Ki-67 protein. Conclusion: We conclude from that Luminal B is the most prevalent molecular subtype at National Cancer Institute, Jamtha, India. There was found no significant correlation between age and Ki-67 expression in any molecular subtype. And no dependence or correlation exists between patients’ age and molecular subtype. We also found that, when the diagnosis is Luminal A, out of the cohort of 257 patients, no patient shows >14% Ki-67 value. Statistically, extremely significant values were observed for dependence of PR+Her2- and PR-Her2+ scores on Ki-67 expression. (p<.01). Her2 is an important prognostic factor in breast cancer. Chi squared test for Her2 and Ki-67 shows that the expression of Ki depends upon Her2 statuses. Moreover, Ki-67 cannot be used as a standalone prognostic factor for determining breast cancer.Keywords: breast cancer molecular subtypes , correlation, immunohistochemistry, Ki-67 and HR, statistical analysis
Procedia PDF Downloads 1235717 Detection of Muscle Swelling Using the Cnts-Based Poc Wearable Strain Sensor
Authors: Nadeem Qaiser, Sherjeel Munsif Khan, Muhammad Mustafa Hussian, Vincent Tung
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One of the emerging fields in the detection of chronic diseases is based on the point-of-care (POC) early monitoring of the symptoms and thus provides a state-of-the-art personalized healthcare system. Nowadays, wearable and flexible sensors are being used for analyzing sweat, glucose, blood pressure, and other skin conditions. However, localized jaw-bone swelling called parotid-swelling caused by some viruses has never been tracked before. To track physical motion or deformations, strain sensors, especially piezoresistive ones, are widely used. This work, for the first time, reports carbon nanotubes (CNTs)-based piezoresistive sensing patch that is highly flexible and stretchable and can record muscle deformations in real-time. The developed patch offers an excellent gauge factor for in-plane stretching and spatial expansion with low hysteresis. To calibrate the volumetric muscle expansion, we fabricated the pneumatic actuator that experienced volumetric expansion and thus redefined the gauge factor. Moreover, we employ a Bluetooth-low-energy system that can send information about muscle activity in real-time to a smartphone app. We utilized COMSOL calculations to reveal the mechanical robustness of the patch. The experiments showed the sensing patch's greater cyclability, making it a patch for personal healthcare and an excellent choice for monitoring the real-time POC monitoring of the human muscle swelling.Keywords: piezoresistive strain sensor, FEM simulations, CNTs sensor, flexible
Procedia PDF Downloads 885716 Study of Aging Behavior of Parallel-Series Connection Batteries
Authors: David Chao, John Lai, Alvin Wu, Carl Wang
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For lithium-ion batteries with multiple cell configurations, some use scenarios can cause uneven aging effects to each cell within the battery because of uneven current distribution. Hence the focus of the study is to explore the aging effect(s) on batteries with different construction designs. In order to systematically study the influence of various factors in some key battery configurations, a detailed analysis of three key battery construction factors is conducted. And those key factors are (1) terminal position; (2) cell alignment matrix; and (3) interconnect resistance between cells. In this study, the 2S2P circuitry has been set as a model multi-cell battery to set up different battery samples, and the aging behavior is studied by a cycling test to analyze the current distribution and recoverable capacity. According to the outcome of aging tests, some key findings are: (I) different cells alignment matrices can have an impact on the cycle life of the battery; (II) symmetrical structure has been identified as a critical factor that can influence the battery cycle life, and unbalanced resistance can lead to inconsistent cell aging status; (III) the terminal position has been found to contribute to the uneven current distribution, that can cause an accelerated battery aging effect; and (IV) the internal connection resistance increase can actually result in cycle life increase; however, it is noteworthy that such increase in cycle life is accompanied by a decline in battery performance. In summary, the key findings from the study can help to identify the key aging factor of multi-cell batteries, and it can be useful to effectively improve the accuracy of battery capacity predictions.Keywords: multiple cells battery, current distribution, battery aging, cell connection
Procedia PDF Downloads 805715 Measurements of Radial Velocity in Fixed Fluidized Bed for Fischer-Tropsch Synthesis Using LDV
Authors: Xiaolai Zhang, Haitao Zhang, Qiwen Sun, Weixin Qian, Weiyong Ying
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High temperature Fischer-Tropsch synthesis process use fixed fluidized bed as a reactor. In order to understand the flow behavior in the fluidized bed better, the research of how the radial velocity affect the entire flow field is necessary. Laser Doppler Velocimetry (LDV) was used to study the radial velocity distribution along the diameter direction of the cross-section of the particle in a fixed fluidized bed. The velocity in the cross-section is fluctuating within a small range. The direction of the speed is a random phenomenon. In addition to r/R is 1, the axial velocity are more than 6 times of the radial velocity, the radial velocity has little impact on the axial velocity in a fixed fluidized bed.Keywords: Fischer-Tropsch synthesis, Fixed fluidized bed, LDV, Velocity
Procedia PDF Downloads 4045714 Strain Based Failure Criterion for Composite Notched Laminates
Authors: Ibrahim A. Elsayed, Mohamed H. Elalfy, Mostafa M. Abdalla
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A strain-based failure criterion for composite notched laminates is introduced where the most critical stress concentration factor for the anisotropic notched laminates could be related to the failure of the corresponding quasi-isotropic laminate and the anisotropy ratio of the laminate. The proposed criterion will simplify the design of composites to meet notched failure requirements by eliminating the need for the detailed specifications of the stacking sequence at the preliminary design stage. The designer will be able to design based on the stiffness of the laminate, then at a later stage, select an appropriate stacking sequence to meet the stiffness requirements. The failure strains for the notched laminates are computed using the material’s Omni-strain envelope. The concept of Omni-strain envelope concerns the region of average strain where the laminate is safe regardless of ply orientation. In this work, we use Hashin’s failure criteria and the strains around the hole are computed using Savin’s analytic solution. A progressive damage analysis study has been conducted where the failure loads for the notched laminates are computed using finite element analysis. The failure strains are computed and used to estimate the concentration factor. It is found that the correlation found using Savin’s analytic solution predicts the same ratio of concentration factors between anisotropic and quasi-isotropic laminates as the more expensive progressive failure analysis.Keywords: anisotropy ratio, failure criteria, notched laminates, Omni-strain envelope, savin’s solution
Procedia PDF Downloads 1165713 Association of Human Immunodeficiency Virus with Incident Autoimmune Hemolytic Anemia: A Population-Based Cohort Study in Taiwan
Authors: Yung-Feng Yen, I-an Jen, Yi-Ming Arthur Chen
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The molecular mimicry between human immunodeficiency virus (HIV) protein and red blood cell (RBC) antigens could induce the production of anti-RBC autoantibodies. However, the association between HIV infection and subsequent development of autoimmune hemolytic anemia (AIHA) remains unclear. This nationwide population-based cohort study aimed to determine the association between incident AIHA and HIV in Taiwan. From 2000–2012, we identified adult people living with HIV/AIDS (PLWHA) from the Taiwan centers for disease control HIV Surveillance System. HIV-infected individuals were defined by positive HIV-1 western blot. Age- and sex-matched controls without HIV infection were selected from the Taiwan National Health Insurance Research Database for comparison. All patients were followed until Dec. 31, 2012, and observed for occurrence of AIHA. Of 171,468 subjects (19,052 PLWHA, 152,416 controls), 30 (0.02%) had incident AIHA during a mean follow-up of 5.45 years, including 23 (0.12%) PLWHA and 7 (0.01%) controls. After adjusting for potential confounders, HIV infection was found to be an independent risk factor of incident AIHA (adjusted hazard ratio [AHR], 20.9; 95% confidence interval [CI], 8.34-52.3). Moreover, PLWHA receiving HAART were more likely to develop AIHA than those not receiving HAART (AHR, 10.8; 95% CI, 2.90-40.1). Additionally, the risk of AIHA was significantly increased in those taking efavirenz (AHR, 3.15; 95% CI, 1.18-8.43) or atazanavir (AHR, 6.58; 95% CI, 1.88-22.9) component of the HAART. In conclusion, HIV infection is an independent risk factor for incident AIHA. Clinicians need to be aware of the higher risk of AIHA in PLWHA.Keywords: autoimmune disease , hemolytic anemia, HIV, highly active antiretroviral treatment
Procedia PDF Downloads 2355712 On Disaggregation and Consolidation of Imperfect Quality Shipments in an Extended EPQ Model
Authors: Hung-Chi Chang
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For an extended EPQ model with random yield, the existent study revealed that both the disaggregating and consolidating shipment policies for the imperfect quality items are independent of holding cost, and recommended a model with economic benefit by comparing the least total cost for each of the three models investigated. To better capture the real situation, we generalize the existent study to include different holding costs for perfect and imperfect quality items. Through analysis, we show that the above shipment policies are dependent on holding costs. Furthermore, we derive a simple decision rule solely based on the thresholds of problem parameters to select a superior model. The results are illustrated analytically and numerically.Keywords: consolidating shipments, disaggregating shipments, EPQ, imperfect quality, inventory
Procedia PDF Downloads 3765711 Reading Behavior of Undergraduate Students at Suan Sunandha Rajabhat University
Authors: Ratanavadee Takerngsukvatana
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The purposes of this research were to study reading behavior of undergraduate students at Suan Sunandha Rajabhat University. A stratified random sample of 380 participants was collected. A Likert five-scale questionnaire was developed to collect data and to obtain students’ opinions regarding their reading behavior. The findings revealed that the majority of respondents read mainly for academic purpose. They preferred to read magazines. The majority of respondents read an average of 3-7 pages a day. The places to read were home and library. Buying with their own money and borrowing from the library were two main sources of books. The suggested activity to promote is planning the curriculum to suit students’ reading behavior.Keywords: reading, reading behavior, undergraduate students, Suan Sunandha Rajabhat University
Procedia PDF Downloads 3035710 Enhancing Cybersecurity Protective Behaviour: Role of Information Security Competencies and Procedural Information Security Countermeasure Awareness
Authors: Norshima Humaidi, Saif Hussein Abdallah Alghazo
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Cybersecurity threat have become a serious issue recently, and one of the cause is because human error, which is usually constituted by carelessness, ignorance, and failure to practice cybersecurity behaviour adequately. Using a data from a quantitative survey, Partial Least Squares-Structural Equation Modelling (PLS-SEM) analysis was used to determine the factors that affect cybersecurity protective behaviour (CPB). This study adapts cybersecurity protective behaviour model by focusing on two constructs that can enhance CPB: manager’s information security competencies (MISI) and procedural information security countermeasure (PCM) awareness. Theory of leadership competencies were adapted to measure user’s perception towards competencies among security managers/leader in the organization. Confirmatory factor analysis (CFA) testing shows that all the measurement items of each constructs were adequate in their validity individually based on their factor loading value. Moreover, each constructs are valid based on their parameter estimates and statistical significance. The quantitative research findings show that PCM awareness strongly influences CPB compared to MISI. Meanwhile, MISI was significantlyPCM awarenss. This study believes that the research findings can contribute to human behaviour in IS studies and are particularly beneficial to policy makers in improving organizations’ strategic plans in information security, especially in this new era. Most organizations spend time and resources to provide and establish strategic plans of information security; however, if employees are not willing to comply and practice information security behaviour appropriately, then these efforts are in vain.Keywords: cybersecurity, protection behaviour, information security, information security competencies, countermeasure awareness
Procedia PDF Downloads 955709 Joint Path and Push Planning among Moveable Obstacles
Authors: Victor Emeli, Akansel Cosgun
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This paper explores the navigation among movable obstacles (NAMO) problem and proposes joint path and push planning: which path to take and in what direction the obstacles should be pushed at, given a start and goal position. We present a planning algorithm for selecting a path and the obstacles to be pushed, where a rapidly-exploring random tree (RRT)-based heuristic is employed to calculate a minimal collision path. When it is necessary to apply a pushing force to slide an obstacle out of the way, the planners leverage means-end analysis through a dynamic physics simulation to determine the sequence of linear pushes to clear the necessary space. Simulation experiments show that our approach finds solutions in higher clutter percentages (up to 49%) compared to the straight-line push planner (37%) and RRT without pushing (18%).Keywords: motion planning, path planning, push planning, robot navigation
Procedia PDF Downloads 1645708 Effects of Egg Yolk Peptide on the Retardation of Bone Growth Induced by Low-Calcium Diets
Authors: Kang-Hyun Leem, Myung-Gyou Kim, Hye Kyung Kim
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Eggs have long been an important contributor to the nutritional quality of the human, and recognized as a very valuable source of proteins for human nutrition. Egg yolk is composed of various important chemical substances for human health. Growth means not only the increase of body weight but also the elongation of height and the enlargement of each organ's anatomical and morphological size. A calcium shortage causes the growth retardation on the body growth. In this study, we examined the therapeutic effects of egg yolk peptide (EYP) on the retardation of the longitudinal bone growth induced by low-calcium diet (0.05%) in adolescent rats. Low calcium diets were administrated for 15 days. During the last five days, calcium and/or vitamin D and/or EYP were administrated. The body weights, longitudinal bone growth rates, the heights of growth plates, and bone morphogenetic protein (BMP)-2 and insulin-like growth factor (IGF)-1 expressions were measured using histochemical analysis. Low calcium diets caused the significant reduction in body weight gains and the longitudinal bone growth. The heights of growth plates and the expressions of BMP-2 and IGF-1 showed the impairment of body growth as well. Calcium and/or vitamin D administration could not significantly increase the longitudinal bone growth. However, calcium, vitamin D, and EYP administration significantly increased the bone growth, the growth plate height, and BMP-2 and IGF-1 expressions. These results suggest that EYP enhances the longitudinal bone growth in the calcium and/or vitamin D deficiency and it could be a promising agent for the treatment of children suffering from malnutrition.Keywords: egg yolk peptide, low-calcium diet, longitudinal bone growth, morphogenetic protein-2, insulin-like growth factor-1, vitamin D
Procedia PDF Downloads 4495707 A Comparative Study on South-East Asian Leading Container Ports: Jawaharlal Nehru Port Trust, Chennai, Singapore, Dubai, and Colombo Ports
Authors: Jonardan Koner, Avinash Purandare
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In today’s globalized world international business is a very key area for the country's growth. Some of the strategic areas for holding up a country’s international business to grow are in the areas of connecting Ports, Road Network, and Rail Network. India’s International Business is booming both in Exports as well as Imports. Ports play a very central part in the growth of international trade and ensuring competitive ports is of critical importance. India has a long coastline which is a big asset for the country as it has given the opportunity for development of a large number of major and minor ports which will contribute to the maritime trades’ development. The National Economic Development of India requires a well-functioning seaport system. To know the comparative strength of Indian ports over South-east Asian similar ports, the study is considering the objectives of (I) to identify the key parameters of an international mega container port, (II) to compare the five selected container ports (JNPT, Chennai, Singapore, Dubai, and Colombo Ports) according to user of the ports and iii) to measure the growth of selected five container ports’ throughput over time and their comparison. The study is based on both primary and secondary databases. The linear time trend analysis is done to show the trend in quantum of exports, imports and total goods/services handled by individual ports over the years. The comparative trend analysis is done for the selected five ports of cargo traffic handled in terms of Tonnage (weight) and number of containers (TEU’s). The comparative trend analysis is done between containerized and non-containerized cargo traffic in the five selected five ports. The primary data analysis is done comprising of comparative analysis of factor ratings through bar diagrams, statistical inference of factor ratings for the selected five ports, consolidated comparative line charts of factor rating for the selected five ports, consolidated comparative bar charts of factor ratings of the selected five ports and the distribution of ratings (frequency terms). The linear regression model is used to forecast the container capacities required for JNPT Port and Chennai Port by the year 2030. Multiple regression analysis is carried out to measure the impact of selected 34 explanatory variables on the ‘Overall Performance of the Port’ for each of the selected five ports. The research outcome is of high significance to the stakeholders of Indian container handling ports. Indian container port of JNPT and Chennai are benchmarked against international ports such as Singapore, Dubai, and Colombo Ports which are the competing ports in the neighbouring region. The study has analysed the feedback ratings for the selected 35 factors regarding physical infrastructure and services rendered to the port users. This feedback would provide valuable data for carrying out improvements in the facilities provided to the port users. These installations would help the ports’ users to carry out their work in more efficient manner.Keywords: throughput, twenty equivalent units, TEUs, cargo traffic, shipping lines, freight forwarders
Procedia PDF Downloads 1315706 The Effect of Aerobic Training and Consumption of Apple Vinegar on Cardiovascular Risk Factor in Older Women
Authors: S. Fazelifar, M. Ghasemi
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Aim: Recent studies on cardiovascular risk factors have been focused on the new markers of inflammatory diseases such as C-reactive protein (CRP). Research evidence shows that physical activity along with other factors such as reduced smoking, controlling blood pressure, control blood lipids TC, LDL-c, HDL-c and having a healthy weight can reduce the risk of chronic heart disease (CHD) .Therefore, the aim of this study was to determine the effect of twelve weeks aerobic exercise and consumption of apple vinegar on cardiovascular risk factor in older women. Methodology: 28 inactive women (mean body weight 72.13 ± 8.6 kg, height 157 ± 7.4cm, age 48.06 ± 5.18 years and BMI 28.2 ± 3.2 kg/m2) by recall and notice of investigation, among of the eligible voters recruited and randomly divided in 4 groups: control, apple vinegar, exercise, exercise + apple vinegar. The training program includes a 20-minute warm-up and stretching, running for 15 minutes in the first session with an intensity of 80% of maximum heart rate and an increase in one-minute run time in next training session. Also, subjects in experimental groups received daily specified amount of 50 ml apple vinegar. Blood samples were collected from the brachial vein in before and after training to measure CRP and blood lipids (cholesterol, HDL, VLDL, LDL). The levels of CRP were measured by ELISA way. K-S test to determine the normality of the data and analysis of variance for repeated measures was used to analyze the data. A significant difference in the p < 0/05 accepted. Results: The results indicated that individual characteristics including height, weight, age, and body mass index were not significantly different among the four groups. The results showed that levels of CRP and LDL cholesterol were significantly reduced in all groups at post-test compared to the pre-test. The HDL levels increased significantly in all groups in post-test compared to the pre-test. Analysis of the data indicates that levels of CRP, TC, and LDL were significantly reduced in all groups compared to the control group, while the changes in the other groups were not significant relative to each other. Conclusion: Results of this study showed that twelve weeks of aerobic exercise with apple vinegar cause a significant decrease in CRP, cholesterol, LDL, and significantly increased HDL levels. According to the results of this study, it is possible that aerobic exercise with apple vinegar can inhibit CRP and undesirable fats. Considering the strong association between the inflammatory indices and the prevalence of cardiovascular diseases, every factor that decreases these indices can reduce the cardiovascular complications.Keywords: aerobic exercise, apple vinegar, CRP, older women
Procedia PDF Downloads 4725705 Fractal Behaviour of Earthquake Sequences in Himalaya
Authors: Kamal, Adil Ahmad
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Earthquakes are among the most versatile natural and dynamic processes, and hence a fractal model is considered to be the best representative of the same. We present a novel method to process and analyse information hidden in earthquake sequences using Fractal Dimensions and Iterative Function Systems (IFS). Spatial and temporal variations in the fractal dimensions of seismicity observed around the Indian peninsula in last 30 years are studied. This was used as a possible precursor before large earthquakes in the region. IFS images for observed seismicity in the Himalayan belt were also obtained. We scan the whole data set and coarse grain of a selected window to reduce it to four bins. A critical analysis of four-cornered chaos-game clearly shows that the spatial variation in earthquake occurrences in Himalayan range is not random. Two subzones of Himalaya have a tendency to follow each other in time.Keywords: earthquakes, fractals, Himalaya, iterated function systems
Procedia PDF Downloads 3005704 Development and Validation of a Quantitative Measure of Engagement in the Analysing Aspect of Dialogical Inquiry
Authors: Marcus Goh Tian Xi, Alicia Chua Si Wen, Eunice Gan Ghee Wu, Helen Bound, Lee Liang Ying, Albert Lee
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The Map of Dialogical Inquiry provides a conceptual look at the underlying nature of future-oriented skills. According to the Map, learning is learner-oriented, with conversational time shifted from teachers to learners, who play a strong role in deciding what and how they learn. For example, in courses operating on the principles of Dialogical Inquiry, learners were able to leave the classroom with a deeper understanding of the topic, broader exposure to differing perspectives, and stronger critical thinking capabilities, compared to traditional approaches to teaching. Despite its contributions to learning, the Map is grounded in a qualitative approach both in its development and its application for providing feedback to learners and educators. Studies hinge on openended responses by Map users, which can be time consuming and resource intensive. The present research is motivated by this gap in practicality by aiming to develop and validate a quantitative measure of the Map. In addition, a quantifiable measure may also strengthen applicability by making learning experiences trackable and comparable. The Map outlines eight learning aspects that learners should holistically engage. This research focuses on the Analysing aspect of learning. According to the Map, Analysing has four key components: liking or engaging in logic, using interpretative lenses, seeking patterns, and critiquing and deconstructing. Existing scales of constructs (e.g., critical thinking, rationality) related to these components were identified so that the current scale could adapt items from. Specifically, items were phrased beginning with an “I”, followed by an action phrase, to fulfil the purpose of assessing learners' engagement with Analysing either in general or in classroom contexts. Paralleling standard scale development procedure, the 26-item Analysing scale was administered to 330 participants alongside existing scales with varying levels of association to Analysing, to establish construct validity. Subsequently, the scale was refined and its dimensionality, reliability, and validity were determined. Confirmatory factor analysis (CFA) revealed if scale items loaded onto the four factors corresponding to the components of Analysing. To refine the scale, items were systematically removed via an iterative procedure, according to their factor loadings and results of likelihood ratio tests at each step. Eight items were removed this way. The Analysing scale is better conceptualised as unidimensional, rather than comprising the four components identified by the Map, for three reasons: 1) the covariance matrix of the model specified for the CFA was not positive definite, 2) correlations among the four factors were high, and 3) exploratory factor analyses did not yield an easily interpretable factor structure of Analysing. Regarding validity, since the Analysing scale had higher correlations with conceptually similar scales than conceptually distinct scales, with minor exceptions, construct validity was largely established. Overall, satisfactory reliability and validity of the scale suggest that the current procedure can result in a valid and easy-touse measure for each aspect of the Map.Keywords: analytical thinking, dialogical inquiry, education, lifelong learning, pedagogy, scale development
Procedia PDF Downloads 915703 Identification and Characterization of Novel Genes Involved in Quinone Synthesis in the Odoriferous Defensive Stink Glands of the Red Flour Beetle, Tribolium castaneum
Authors: B. Atika, S. Lehmann, E. Wimmer
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The defense strategy is very common in the insect world. Defensive substances play a wide variety of functions for beetles, such as repellents, toxicants, insecticides, and antimicrobics. Beetles react to predators, invaders, and parasitic microbes with the release of toxic and repellent substances. Defensive substances are directed against a large array of potential target organisms or may function for boiling bombardment or as surfactants. Usually, Coleoptera biosynthesize and store their defensive compounds in a complex secretory organ, known as odoriferous defensive stink glands. The red flour beetle, Tribolium castaneum (Coleoptera: Tenebrionidae), uses these glands to produce antimicrobial p-benzoquinones and 1-alkenes. In the past, the morphology of stink gland has been studied in detail in tenebrionid beetles; however, very little is known about the genes that are involved in the production of gland secretion. In this study, we studied a subset of genes that are essential for the benzoquinone production in red flour beetle. In the first phase, we selected 74 potential candidate genes from a genome-wide RNA interference (RNAi) knockdown screen named 'iBeetle.' All these 74 candidate genes were functionally characterized by RNAi-mediated gene knockdown. Therefore, they were selected for a subsequent gas chromatography-mass spectrometry (GC-MS) analysis of secretion volatiles in respective RNAi knockdown glands. 33 of them were observed to alter the phenotype of stink gland. In the GC-MS analysis, 7 candidate genes were noted to display a strongly altered gland, in terms of secretion color and chemical composition, upon knockdown, showing their key role in the biosynthesis of gland secretion. Morphologically altered stink glands were found for odorant receptor and protein kinase superfamily. Subsequent GC-MS analysis of secretion volatiles revealed reduced benzoquinone levels in LIM domain, PDZ domain, PBP/GOBP family knockdowns and a complete lack of benzoquinones in the knockdown of sulfatase-modifying factor enzyme 1, sulfate transporter family. Based on stink gland transcriptome data, we analyzed the function of sulfatase-modifying factor enzyme 1 and sulfate transporter family via RNAi-mediated gene knockdowns, GC-MS, in situ hybridization, and enzymatic activity assays. Morphologically altered stink glands were noted in knockdown of both these genes. Furthermore, GC-MS analysis of secretion volatiles showed a complete lack of benzoquinones in the knockdown of these two genes. In situ hybridization showed that these two genes are expressed around the vesicle of certain subgroup of secretory stink gland cells. Enzymatic activity assays on stink gland tissue showed that these genes are involved in p-benzoquinone biosynthesis. These results suggest that sulfatase-modifying factor enzyme 1 and sulfate transporter family play a role specifically in benzoquinone biosynthesis in red flour beetles.Keywords: Red Flour Beetle, defensive stink gland, benzoquinones, sulfate transporter, sulfatase-modifying factor enzyme 1
Procedia PDF Downloads 1545702 Predicting Football Player Performance: Integrating Data Visualization and Machine Learning
Authors: Saahith M. S., Sivakami R.
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In the realm of football analytics, particularly focusing on predicting football player performance, the ability to forecast player success accurately is of paramount importance for teams, managers, and fans. This study introduces an elaborate examination of predicting football player performance through the integration of data visualization methods and machine learning algorithms. The research entails the compilation of an extensive dataset comprising player attributes, conducting data preprocessing, feature selection, model selection, and model training to construct predictive models. The analysis within this study will involve delving into feature significance using methodologies like Select Best and Recursive Feature Elimination (RFE) to pinpoint pertinent attributes for predicting player performance. Various machine learning algorithms, including Random Forest, Decision Tree, Linear Regression, Support Vector Regression (SVR), and Artificial Neural Networks (ANN), will be explored to develop predictive models. The evaluation of each model's performance utilizing metrics such as Mean Squared Error (MSE) and R-squared will be executed to gauge their efficacy in predicting player performance. Furthermore, this investigation will encompass a top player analysis to recognize the top-performing players based on the anticipated overall performance scores. Nationality analysis will entail scrutinizing the player distribution based on nationality and investigating potential correlations between nationality and player performance. Positional analysis will concentrate on examining the player distribution across various positions and assessing the average performance of players in each position. Age analysis will evaluate the influence of age on player performance and identify any discernible trends or patterns associated with player age groups. The primary objective is to predict a football player's overall performance accurately based on their individual attributes, leveraging data-driven insights to enrich the comprehension of player success on the field. By amalgamating data visualization and machine learning methodologies, the aim is to furnish valuable tools for teams, managers, and fans to effectively analyze and forecast player performance. This research contributes to the progression of sports analytics by showcasing the potential of machine learning in predicting football player performance and offering actionable insights for diverse stakeholders in the football industry.Keywords: football analytics, player performance prediction, data visualization, machine learning algorithms, random forest, decision tree, linear regression, support vector regression, artificial neural networks, model evaluation, top player analysis, nationality analysis, positional analysis
Procedia PDF Downloads 385701 Analytic Hierarchy Process and Multi-Criteria Decision-Making Approach for Selecting the Most Effective Soil Erosion Zone in Gomati River Basin
Authors: Rajesh Chakraborty, Dibyendu Das, Rabindra Nath Barman, Uttam Kumar Mandal
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In the present study, the objective is to find out the most effective zone causing soil erosion in the Gumati river basin located in the state of Tripura, a north eastern state of India using analytical hierarchy process (AHP) and multi-objective optimization on the basis of ratio analysis (MOORA).The watershed is segmented into 20 zones based on Area. The watershed is considered by pointing the maximum elevation from sea lever from Google earth. The soil erosion is determined using the universal soil loss equation. The different independent variables of soil loss equation bear different weightage for different soil zones. And therefore, to find the weightage factor for all the variables of soil loss equation like rainfall runoff erosivity index, soil erodibility factor etc, analytical hierarchy process (AHP) is used. And thereafter, multi-objective optimization on the basis of ratio analysis (MOORA) approach is used to select the most effective zone causing soil erosion. The MCDM technique concludes that the maximum soil erosion is occurring in the zone 14.Keywords: soil erosion, analytic hierarchy process (AHP), multi criteria decision making (MCDM), universal soil loss equation (USLE), multi-objective optimization on the basis of ratio analysis (MOORA)
Procedia PDF Downloads 538