Search results for: scientific data mining

Authors: Fadwa Alaskar, Fang-Chieh Chou, Carlos Flores, Xiao-Yun Lu, Alexandre M. Bayen

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This article proposes a perception model for enhancing the accuracy and stability of car-following control of a longitudinally automated truck. We applied a fusion-based tracking algorithm on measurements of a single preceding vehicle needed for car-following control. This algorithm fuses two types of data, radar and LiDAR data, to obtain more accurate and robust longitudinal perception of the subject vehicle in various weather conditions. The filter’s resulting signals are fed to the gap control algorithm at every tracking loop composed by a high-level gap control and lower acceleration tracking system. Several highway tests have been performed with two trucks. The tests show accurate and fast tracking of the target, which impacts on the gap control loop positively. The experiments also show the fulfilment of control design requirements, such as fast speed variations tracking and robust time gap following.

Keywords: object tracking, perception, sensor fusion, adaptive cruise control, cooperative adaptive cruise control

Procedia PDF Downloads 233

Authors: Trang Huyen Nguyen, Thien Tri Huynh

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The objectives of this paper were to determine demographics of readers at Hochiminh city (HCMC), study reading motivation which affected citizens to read sports newspapers and measure readers’ satisfaction on issues related sports newspapers. Subjects of this survey were HCMC’s citizens. After collecting data, there were 568 useful feedbacks (the rate of response was 94.7%). The data analysis in the study included descriptive statistics and inferred statistics by SPSS 16.0 program for the research questions. The majority of respondents were male, from 24 to 32 years old, got the first degree and earned monthly from $US 150 to 300. Moreover, they were government officials and read newspaper from 11 to 20 times per month, bought newspapers by themselves. Finding information to predict results of sports matches was the highest motive affected readers; and the diversity information was the most pleasure that readers felt about sports newspapers. According to research findings, the board of editors could use the worthy information to make a strategic plan for newspaper on contents as well as design to meet the increasing demands of readers.

Keywords: motivation, satisfaction, readers, sports newspapers

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Authors: Tali Capua, Karin Hermon, Miguel Glatstein, Oren Tavor, Ayelet Rimon

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Background: Electric bicycles (E-bikes) are one of a wide range of light electric vehicles that provide convenient local transportation and attractive recreational opportunities. Along with their growing use worldwide, the E-bike related injury rate increases. To the best of our knowledge, this study is the first to specifically compare E-bike with classic bicycle related injuries in children. Methods: Data of all pediatric ( < 16 years of age) bicycle related injuries presenting to an urban level I trauma center between 2014 and 2015 were collected and analyzed. The recorded data included age, gender, details of the accident, as well severity of injury, medical diagnosis, and the outcome. Abbreviated Injury Score (AIS) and Injury Severity Score (ISS) were calculated for each patient. Data of E-bike related injuries and classic bicycle were then compared. Results: A total of 124 bicycle related injuries and 97 E-bike related injuries presented to the emergency department. Once pedestrians and bicycle passengers were removed, the groups of riders consisted of 111 bikers and 85 E-bikers. The mean age of bikers was 9.9 years (range 3-16 years) and of E-bikers was 13.7 years (range 7.5-16 years). Injuries to the head and the extremities were common in both groups. Compared to bikers, E-bikers had significantly more injuries to intra-abdominal organs (p = 0.04). Twenty patients (16%) with bicycle related injuries were admitted, and 13 (15%) patients with E-bike related injuries, of the latter group four underwent surgical intervention. ISS scores were low overall, but the injuries of higher severity (ISS > 9) were among the E-bikers. Conclusions: This study provides unique information which suggests that injuries in E-bikers tend to be more severe than in classic bikers. There is a need for regulation regarding the use of E-bikes to enhance the safety of both bikers and other road and pavement users.

Keywords: bicycle, electric bicycle, injury, pediatric, trauma

Procedia PDF Downloads 193

Authors: Mario Sandro F. Rocha, Carlos S. Ande, Anderson A. Oliveira, Felipe M. Bersotti, Lucas O. Venzel

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The inertial motion capture systems (mocap) are among the most suitable tools for quantitative clinical analysis in rehabilitation and sports medicine. The inertial measuring units (IMUs), composed by accelerometers, gyroscopes, and magnetometers, are able to measure spatial orientations and calculate displacements with sufficient precision for applications in biomechanical analysis of movement. Furthermore, this type of system is relatively affordable and has the advantages of portability and independence from external references. In this work, we present the last version of our inertial motion capture system, based on the foregoing technology, with a unity interface designed for rehabilitation and sports. In our hardware architecture, only one serial port is required. First, the board client must be connected to the computer by a USB cable. Next, an available serial port is configured and opened to establish the communication between the client and the application, and then the client starts scanning for the active MOCAP_S servers around. The servers play the role of the inertial measuring units that capture the movements of the body and send the data to the client, which in turn create a package composed by the ID of the server, the current timestamp, and the motion capture data defined in the client pre-configuration of the capture session. In the current version, we can measure the game rotation vector (grv) and linear acceleration (lacc), and we also have a step detector that can be abled or disabled. The grv data are processed and directly linked to the bones of the 3D model, and, along with the data of lacc and step detector, they are also used to perform the calculations of displacements and other variables shown on the graphical user interface. Our user interface was designed to calculate and present variables that are important for rehabilitation and sports, such as cadence, speed, total gait cycle, gait cycle length, obliquity and rotation, and center of gravity displacement. Our goal is to present a low-cost portable and wearable system with a friendly interface for application in biomechanics and sports, which also performs as a product of high precision and low consumption of energy.

Keywords: biomechanics, inertial sensors, motion capture, rehabilitation

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Authors: Nkereke Essien

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The study seeks to analyze tone in the Educated Nigerian accent of English (ENAE) using the three tones: Low (L), High (H) and Low-High (LH). The aim is to find out whether there are any differences or similarities in the performance of the experimental group and the control. To achieve this, twenty educated Nigerian speakers of English who are educated in the language were selected by a Stratified Random Sampling (SRS) technique from two federal universities in Nigeria. They were given a passage to read and their intonation patterns were compared with that of a native speaker (control). The data were analyzed using Pierrehumbert’s (1980) intonation system of analysis. Three different approaches were employed in the analysis of the intonation Phrase (IP) as used by Pierrehumbert: perceptual, statistical and acoustic. We first analyzed our data from the passage and utterances using Willcoxon Matched Pairs Signs Ranks Test to establish the differences between the performance of the experimental group and the control. Then, the one-way Analysis of variance (ANOVA) statistical and Tukey-Krammar Post Hoc Tests were used to test for any significant difference in the performances of the twenty subjects. The acoustic data were presented to corroborate both the perceptual and statistical findings. Finally, the tonal patterns of the selected subjects in the three categories - A, B, C, were compared with those of the control. Our findings revealed that the tonal pattern of the Educated Nigerian Accent of English (ENAE) is significantly different from the tonal pattern of the Standard British Accent of English (SBAE) as represented by the control. A high preference for unidirectional tones, especially, the high tones was observed in the performance of the experimental group. Also, high tones do not necessarily correspond to stressed syllables and low tones to unstressed syllables.

Keywords: accent, intonation phrase (IP), tonal patterns, tone

Procedia PDF Downloads 237

Authors: Amirhossein Safi

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Internet of things (IOT) is a kind of advanced information technology which has drawn societies’ attention. Sensors and stimulators are usually recognized as smart devices of our environment. Simultaneously, IOT security brings up new issues. Internet connection and possibility of interaction with smart devices cause those devices to involve more in human life. Therefore, safety is a fundamental requirement in designing IOT. IOT has three remarkable features: overall perception, reliable transmission, and intelligent processing. Because of IOT span, security of conveying data is an essential factor for system security. Hybrid encryption technique is a new model that can be used in IOT. This type of encryption generates strong security and low computation. In this paper, we have proposed a hybrid encryption algorithm which has been conducted in order to reduce safety risks and enhancing encryption's speed and less computational complexity. The purpose of this hybrid algorithm is information integrity, confidentiality, non-repudiation in data exchange for IOT. Eventually, the suggested encryption algorithm has been simulated by MATLAB software, and its speed and safety efficiency were evaluated in comparison with conventional encryption algorithm.

Keywords: internet of things, security, hybrid algorithm, privacy

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Authors: J. M. de Luis Ruiz, P. M. Sierra García, R. P. García, R. P. Álvarez, F. P. García, E. C. López

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Given the evolution of viaducts, structural health monitoring requires more complex techniques to define their state. two alternatives can be distinguished: experimental and operational modal analysis. Although accelerometers or Global Positioning System (GPS) have been applied for the monitoring of structures under exploitation, the dynamic monitoring during the stage of construction is not common. This research analyzes whether GPS data can be applied to certain dynamic geometric controls of evolving structures. The fundamentals of this work were applied to the New Bridge of Cádiz (Spain), a worldwide milestone in bridge building. GPS data were recorded with an interval of 1 second during the erection of segments and turned to the frequency domain with Fourier transform. The vibration period and amplitude were contrasted with those provided by the finite element model, with differences of less than 10%, which is admissible. This process provides a vibration record of the structure with GPS, avoiding specific equipment.

Keywords: Fourier transform, global position system, operational modal analysis, structural health monitoring

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Authors: K. Volkonitskaya, S. Lyapina

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According to the National Monitoring Centre of innovation infrastructure, scientific and technical activities and regional innovation systems by December 2014. 166 technology parks were established in Russia. Comparative analysis of technological parks performance in Russia, the USA, Israel and the European Union countries revealed significant reduction of key performance indicators in Russian innovation infrastructure institutes. The largest deviations were determined in the following indicators: new products and services launched, number of companies and jobs, amount of venture capital invested. Lower performance indicators of Russian technology parks can be partly explained by slack demand for national high-tech products and services, lack of qualified specialists in the sphere of innovation management and insufficient cooperation between different innovation infrastructure institutes. In spite of all constraints in innovation segment of Russian economy in 2010-2012 private investors for the first time proceeded to finance building of technological parks. The general purpose of the research is to answer two questions: why despite the significant investment risks private investors continue to implement such comprehensive infrastructure projects in Russia and is business model of private technological park more efficient than strategies of state innovation infrastructure institutes? The goal of the research was achieved by analyzing business models of private technological parks in Moscow, Kaliningrad, Astrakhan and Kazan. The research was conducted in two stages: the on-line survey of key performance indicators of private and state Russian technological parks and in-depth interviews with top managers and investors, who have already build private technological parks in by 2014 or are going to complete investment stage in 2014-2016. The results anticipated are intended to identify the reasons of efficient and inefficient technological parks performance. Furthermore, recommendations for improving the efficiency of state technological and industrial parks were formulated. Particularly, the recommendations affect the following issues: networking with other infrastructural institutes, services and infrastructure provided, mechanisms of public-private partnership and investment attraction. In general intensive study of private technological parks performance and development of effective mechanisms of state support can have a positive impact on the growth rates of the number of Russian technological, industrial and science parks.

Keywords: innovation development, innovation infrastructure, private technology park, public-private partnership

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Authors: Mihriban Hacisalihoğlu Karadeniz, Figen Bozkuş, Tuğba Baran, Ümit Akar

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Creating the correct symmetry of conceptual knowledge about students, conceptual information about the symmetry of the instructors is important. However, teachers’, the students should be aware of the existing misconceptions and be able to develop strategies to correct these misconceptions. In this study, the purpose, the prospective teachers’, the students’ explanations for corrections of misconceptions and misconceptions were asked to be introduced. The working group during the 2012-2013 academic year, Kocaeli University Faculty of Education Mathematics Education consists of studying at the twenty-six prospective teachers. The study adopted a qualitative approach. The data prepared by the researchers were obtained with an open-ended test. As a result of analysis of the data, prospective with teaching the concept of symmetry observed in more developed practical solutions. These solutions are focused on the method, students utilization mirrors, paper folding, such as using a square piece of registration of events. Prospective teachers’ who think this way, students observed that overlooked the creation of conceptual knowledge.

Keywords: symmetry concepts, misconceptions, elementary mathematics, prospective teachers-students

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Authors: K. M. Yoo, M. H. Kang

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Conventional commercial wind turbine design software is limited to large wind turbines due to not incorporating with low Reynold’s Number aerodynamic characteristics typically for small wind turbines. To extract maximum annual energy product from an intermediately designed small wind turbine associated with measured wind data, numerous simulation is highly recommended to have a best fitting planform design with proper airfoil configuration. Since depending upon wind distribution with average wind speed, an optimal wind turbine planform design changes accordingly. It is theoretically not difficult, though, it is very inconveniently time-consuming design procedure to finalize conceptual layout of a desired small wind turbine. Thus, to help simulations easier and faster, a GUI software is developed to conveniently iterate and change airfoil types, wind data, and geometric blade data as well. With magnetic generator torque curve, peak power tracking simulation is also available to better match with the magnetic generator. Small wind turbine often lacks starting torque due to blade optimization. Thus this simulation is also embedded along with yaw design. This software provides various blade cross section details at user’s design convenience such as skin thickness control with fiber direction option, spar shape, and their material properties. Since small wind turbine is under international safety regulations with fatigue damage during normal operations and safety load analyses with ultimate excessive loads, load analyses are provided with each category mandated in the safety regulations.

Keywords: GUI software, Low Reynold’s number aerodynamics, peak power tracking, safety regulations, wind turbine performance optimization

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Authors: Nicholas S. Norbert Jr., John E. Bischoff, Christopher J. Willy

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Knowledge Management (KM) is globally recognized as a crucial element in securing competitive advantage through building and maintaining organizational memory, codifying and protecting intellectual capital and business intelligence, and providing mechanisms for collaboration and innovation. KM frameworks and approaches have been developed and defined identifying critical success factors for conducting KM within numerous industries ranging from scientific to business, and for ranges of organization scales from small groups to large enterprises. However, engineering and technical teams operating within restricted environments are subject to unique barriers and KM challenges which cannot be directly treated using the approaches and tools prescribed for other industries. This research identifies barriers in conducting KM within Hardware Development Engineering (HDE) teams and statistically compares significance to barriers upholding the four KM pillars of organization, technology, leadership, and learning for HDE teams. HDE teams suffer from restrictions in knowledge sharing (KS) due to classification of information (national security risks), customer proprietary restrictions (non-disclosure agreement execution for designs), types of knowledge, complexity of knowledge to be shared, and knowledge seeker expertise. As KM evolved leveraging information technology (IT) and web-based tools and approaches from Web 1.0 to Enterprise 2.0, KM may also seek to leverage emergent tools and analytics including expert locators and hybrid recommender systems to enable KS across barriers of the technical teams. The research will test hypothesis statistically evaluating if KM barriers for HDE teams affect the general set of expected benefits of a KM System identified through previous research. If correlations may be identified, then generalizations of success factors and approaches may also be garnered for HDE teams. Expert elicitation will be conducted using a questionnaire hosted on the internet and delivered to a panel of experts including engineering managers, principal and lead engineers, senior systems engineers, and knowledge management experts. The feedback to the questionnaire will be processed using analysis of variance (ANOVA) to identify and rank statistically significant barriers of HDE teams within the four KM pillars. Subsequently, KM approaches will be recommended for upholding the KM pillars within restricted environments of HDE teams.

Keywords: engineering management, knowledge barriers, knowledge management, knowledge sharing

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Authors: Sawsan Eissa, Omnia Kabbany

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The coastline of Togo has been historically suffering from erosion for decades, which requires a solution to help control and reduce the erosion to allow for the development of the coastal area. A morpho-dynamic model using X-beach software was developed for the Western 14 Km of the Togolese coast. The model was coupled with the hydrodynamic module of DELFT 3D, flow, and the Wave module, SWAN. The data used as input included a recent bathymetric survey, a recent shoreline topographic survey, aerial photographs, ERA 5 water level and wave data, and recent test results of seabed samples. A number of scenarios were modeled: do nothing scenario, groynes, detached breakwaters system with different crest levels and alignments. The findings showed that groynes is not expected to be effective for protection against erosion, and that the best option is a system of detached breakwater, partially emerged-partially submerged couples with periodical maintenance.

Keywords: hydrodynamics, morphology, Togo, Delft3D, SWAN, XBeach, coastal erosion, detached breakwaters

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Authors: Khin Fai Chen, Jee-Hou Ho, Eng Hwa Yap

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An acoustic micro-energy harvester (AMEH) is developed to convert wasted acoustical energy into useful electrical energy. AMEH is mathematically modeled using lumped element modelling (LEM) and Euler-Bernoulli beam (EBB) modelling. An experiment is designed to validate the mathematical model and assess the feasibility of AMEH. Comparison of theoretical and experimental data on critical parameter value such as Mm, Cms, dm and Ceb showed the variances are within 1% to 6%, which is reasonably acceptable. Hence, AMEH mathematical model is validated. Then, AMEH undergoes bandwidth tuning for performance optimization for further experimental work. The AMEH successfully produces 0.9 V⁄(m⁄s^2) and 1.79 μW⁄(m^2⁄s^4) at 60Hz and 400kΩ resistive load which only show variances about 7% compared to theoretical data. By integrating a capacitive load of 200µF, the discharge cycle time of AMEH is 1.8s and the usable energy bandwidth is available as low as 0.25g. At 1g and 60Hz resonance frequency, the averaged power output is about 2.2mW which fulfilled a range of wireless sensors and communication peripherals power requirements. Finally, the design for AMEH is assessed, validated and deemed as a feasible design.

Keywords: piezoelectric, acoustic, energy harvester

Procedia PDF Downloads 283

Authors: Collins Ekpiwre Augustine

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Taking into account the impact of teacher training on primary and secondary teachers’ classroom competencies and practices, as revealed by many empirical studies, this study investigated the impact of teacher qualifications on the pedagogical competencies of university teachers in Northwest Nigeria.Four research questions were answered while four hypotheses were tested. Both descriptive statistic of frequencies/arithmetic mean and inferential statistic oft-test were used to analyze the data collected. In order to provide a focus to the study,an observational rating scale titled “University Teachers’ Pedagogical Competency Observation Rating Scale” (UTPCORS) was used to collect data for the study. The population for the study comprised all the university teachers in the three Federal Universities in Northwest Nigeria totaling about 3,401. However, this pilot study was administered on 8 teachers - with 4 participants in each comparison group in Bayero University, Kano.The findings of the study revealed that there was no significant difference in the four hypotheses postulated for the study.

Keywords: impact, university teachers, teachers' qualifications, competencies

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Authors: Louis Okon Akpan

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National Open University of Nigeria (NOUN) is an open and distance learning institution whose aim is to provide education for all and also promote lifelong learning in Nigeria. Before now, student-centred learning was adopted. In recent times, online facilitation has been introduced. Therefore, the study explores ways in which students are satisfied with online facilitation provided by NOUN lecturers. A qualitative approach was adopted. The interpretive paradigm was employed as a lens to interpret narratives from the participants. In order to gather information for the study, a semi-structured interview was developed for sixteen participants who were purposively selected from eight facilities of the university. After data gathering from the field, it was subjected to transcription and coding. The emergence of themes from the coded data was analysed using thematic analysis. Findings indicated that students found online learning, recently introduced by the university management, extremely fulfilling and rewarding.

Keywords: online facilitation, lecturer, students’ satisfaction, National Open University of Nigeria

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Authors: Thawtar Htun, Kim N. Irvine, Ranjna Jindal

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This study aimed at modelling the wastewater collection system in Cha-Am Municipality using PCSWMM to investigate the quantity of combined sewage delivered to the aeration lagoon treatment system (ALTS). Cha-Am is a small sea resort town in Petchaburi Province located about 175 km southwest of Bangkok and is facing increasing development so it is important to understand current system performance and plan for future build out. PCSWMM was calibrated using observed ALTS inflow data for the period 15 June to 20 July 2015. The model was validated using observed ALTS inflow data for the periods 19 July to 20 October 2015 and 1 October to 31 December 2015, respectively. The 1:1 lines between modeled and observed peak flow and event volume for the calibration events qualitatively showed good correspondence. The r2 values between modeled and observed peak flow (99%) and event volume (89%) also were strong.

Keywords: combined sewer system, mathematical modelling, PCSWMM, wastewater collection system

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Authors: Kasirga Yildirak, Ismail Gur

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We propose a model to measure hail risk of an Agricultural Insurance portfolio. Hail is one of the major catastrophic event that causes big amount of loss to an insurer. Moreover, it is very hard to predict due to its strange atmospheric characteristics. We make use of parcel based claims data on apricot damage collected by the Turkish Agricultural Insurance Pool (TARSIM). As our ultimate aim is to compute the loadings assigned to specific parcels, we build a portfolio risk model that makes use of PD and the severity of the exposures. PD is computed by Spherical-Linear and Circular –Linear regression models as the data carries coordinate information and seasonality. Severity is mapped into integer brackets so that Probability Generation Function could be employed. Individual regressions are run on each clusters estimated on different criteria. Loss distribution is constructed by Panjer Recursion technique. We also show that one risk-one crop model can easily be extended to the multi risk–multi crop model by assuming conditional independency.

Keywords: hail insurance, spherical regression, circular regression, spherical clustering

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Authors: Nattida Wannaruk, Wasawat Nakkiew

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This research aims to study the factors that affect the performance of green supply chain management in the Lampang ceramics industry. The data investigation of this research was questionnaires which were gathered from 20 factories in the Lampang ceramics industry. The research factors are divided into five major groups which are green design, green purchasing, green manufacturing, green logistics and reverse logistics. The questionnaire has consisted of four parts that related to factors green supply chain management and general information of the Lampang ceramics industry. Then, the data were analyzed using descriptive statistic and priority of each factor by using the analytic hierarchy process (AHP). The understanding of factors affecting the green supply chain management of Lampang ceramics industry was indicated in the summary result along with each factor weight. The result of this research could be contributed to the development of indicators or performance evaluation in the future.

Keywords: Lampang ceramics industry, green supply chain management, analysis hierarchy process (AHP), factors affecting

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Authors: Suparman

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Piecewise polynomial regression model is very flexible model for modeling the data. If the piecewise polynomial regression model is matched against the data, its parameters are not generally known. This paper studies the parameter estimation problem of piecewise polynomial regression model. The method which is used to estimate the parameters of the piecewise polynomial regression model is Bayesian method. Unfortunately, the Bayes estimator cannot be found analytically. Reversible jump MCMC algorithm is proposed to solve this problem. Reversible jump MCMC algorithm generates the Markov chain that converges to the limit distribution of the posterior distribution of piecewise polynomial regression model parameter. The resulting Markov chain is used to calculate the Bayes estimator for the parameters of piecewise polynomial regression model.

Keywords: piecewise regression, bayesian, reversible jump MCMC, segmentation

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Authors: Mohammad Yahaghifar

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Nowadays Wireless system designers have been facing the continuously increasing demand for high data rates and mobility required by new wireless applications. Evolving future communication network generation cellular wireless networks are envisioned to overcome the fundamental challenges of existing cellular networks, for example, higher data rates, excellent end-to-end performance, and user coverage in hot-spots and crowded areas with lower latency,energy consumption and cost per information transfer. In this paper we propose a potential cellular architecture that separates indoor and outdoor scenarios and discuss various promising technologies for future wireless communication systemssystems, such as massive MIMO, energy-efficient communications,cognitive radio networks, and visible light communications and we disscuse about 5G that is next generation of wireless networks.

Keywords: future challenges in networks, cellur architecture, visible light communication, 5G wireless technologies, spatial modulation, massiva mimo, cognitive radio network, green communications

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Authors: Mombaur Busisiwe, Lesosky Maia, Liebenberg Lisa, Heckmann Jeannine

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Introduction: To assess age- and gender-specific incidence rates (IR) of acetylcholine receptor (AChR)-antibody positive myasthenia gravis (MG) in South Africa, and geographical variation in incidence. Methods: IRs were calculated from positive AChR antibody laboratory data between 2011 and 2012, using 2011 population census data. Results:890 individuals were seropositive, for an annual IR of 8.5 per million. Age-standardized IR for early- (< 50) and late-onset (≥ 50) MG were 4.1 and 24 per million, respectively, and for juveniles, 4.3 per million. The IR between provinces ranged from 1 to 19 per million. Conclusions: In this Southern hemisphere African population, the overall IR and peak IR (in older men) for seropositive MG is comparable to that in Europe and North America, arguing against environmental factors. However, IRs may be higher among children with African genetic ancestry. Geographical variation in incidence underscores the importance of outreach programs for regions with limited resources.

Keywords: incidence rates (IR), acetylcholine receptor (AChR), myasthenia gravis (MG), South Africa

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Authors: Farid Habibi Tanha, Mojtaba Jahanbazi, Morteza Foroutan, Rasidah Mohd Rashid

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This paper depicts the effects of asymmetric information in determining capital inflows to be captured through stock market microstructure. The model can explain several stylized facts regarding the capital immobility. The first phase of the research involves in collecting and refining 150,000,000 daily data of 11 stock markets over a period of one decade in an effort to minimize the impact of survivorship bias. Three micro techniques were used to measure information asymmetries. The final phase analyzes the model through panel data approach. As a unique contribution, this research will provide valuable information regarding negative effects of information asymmetries in stock markets on attracting foreign investments. The results of this study can be directly considered by policy makers to monitor and control changes of capital flow in order to keep market conditions in a healthy manner, by preventing and managing possible shocks to avoid sudden reversals and market failures.

Keywords: asymmetric information, capital inflow, market microstructure, investment

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Authors: Ashi Gautam, Isha Shukla, Akhil Seghal

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Biosensors are analytical devices that use a biological sensing element to detect and measure a specific chemical substance or biomolecule in a sample. These devices are widely used in various fields, including medical diagnostics, environmental monitoring, and food analysis, due to their high specificity, sensitivity, and selectivity. In this research paper, a machine learning model is proposed for predicting the suitability of skin care products based on biosensor readings. The proposed model takes in features extracted from biosensor readings, such as biomarker concentration, skin hydration level, inflammation presence, sensitivity, and free radicals, and outputs the most appropriate skin care product for an individual. This model is trained on a dataset of biosensor readings and corresponding skin care product information. The model's performance is evaluated using several metrics, including accuracy, precision, recall, and F1 score. The aim of this research is to develop a personalised skin care product recommendation system using biosensor data. By leveraging the power of machine learning, the proposed model can accurately predict the most suitable skin care product for an individual based on their biosensor readings. This is particularly useful in the skin care industry, where personalised recommendations can lead to better outcomes for consumers. The developed model is based on supervised learning, which means that it is trained on a labeled dataset of biosensor readings and corresponding skin care product information. The model uses these labeled data to learn patterns and relationships between the biosensor readings and skin care products. Once trained, the model can predict the most suitable skin care product for an individual based on their biosensor readings. The results of this study show that the proposed machine learning model can accurately predict the most appropriate skin care product for an individual based on their biosensor readings. The evaluation metrics used in this study demonstrate the effectiveness of the model in predicting skin care products. This model has significant potential for practical use in the skin care industry for personalised skin care product recommendations. The proposed machine learning model for predicting the suitability of skin care products based on biosensor readings is a promising development in the skin care industry. The model's ability to accurately predict the most appropriate skin care product for an individual based on their biosensor readings can lead to better outcomes for consumers. Further research can be done to improve the model's accuracy and effectiveness.

Keywords: biosensors, data model, machine learning, skin care

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Authors: Chi-Yueh Hsu, Hsuan-Liang Hsu, Hsiu-Hui Chiang

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This study is to explore the relationship between the conspicuous consumption, leisure involvement and physical and mental health, and to understand the prediction of conspicuous consumption and leisure involvement to physical and mental health. The data was collected and analysed by purposive sampling, and the research objects were the dog walkers in Taiwan area. A total of 300 questionnaires were issued and after shaving the invalid questionnaire, a total of 246 valid samples were collected, and the effective rate was 82%.. The data were analyzed by correlation analysis and multiple stepwise regression analysis. The results showed that there was a significant correlation between conspicuous consumption and leisure involvement, and the conspicuous consumption and leisure involvement of dog walkers have a significant impact on physical and mental health, especially in self-expression, attractiveness and centrality of leisure involvement have a significant impact on physical and mental health.

Keywords: walking dog, attractiveness, self-expression, multiple stepwise regression analysis

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Authors: Gabrielle Peck, Ryan Hayes

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This research presents the design and creation of a drone gas analyser, aimed at addressing the need for independent data collection and analysis of gas emissions during large-scale fires, particularly wasteland fires. The analyser drone, comprising a lightweight gas analysis system attached to a remote-controlled drone, enables the real-time assessment of smoke toxicity and the monitoring of gases released into the atmosphere during such incidents. The key components of the analyser unit included two gas line inlets connected to glass wool filters, a pump with regulated flow controlled by a mass flow controller, and electrochemical cells for detecting nitrogen oxides, hydrogen cyanide, and oxygen levels. Additionally, a non-dispersive infrared (NDIR) analyser is employed to monitor carbon monoxide (CO), carbon dioxide (CO₂), and hydrocarbon concentrations. Thermocouples can be attached to the analyser to monitor temperature, as well as McCaffrey probes combined with pressure transducers to monitor air velocity and wind direction. These additions allow for monitoring of the large fire and can be used for predictions of fire spread. The innovative system not only provides crucial data for assessing smoke toxicity but also contributes to fire prediction and management. The remote-controlled drone's mobility allows for safe and efficient data collection in proximity to the fire source, reducing the need for human exposure to hazardous conditions. The data obtained from the gas analyser unit facilitates informed decision-making by emergency responders, aiding in the protection of both human health and the environment. This abstract highlights the successful development of a drone gas analyser, illustrating its potential for enhancing smoke toxicity analysis and fire prediction capabilities. The integration of this technology into fire management strategies offers a promising solution for addressing the challenges associated with wildfires and other large-scale fire incidents. The project's methodology and results contribute to the growing body of knowledge in the field of environmental monitoring and safety, emphasizing the practical utility of drones for critical applications.

Keywords: fire prediction, drone, smoke toxicity, analyser, fire management

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Authors: Samarpreet Singh, Gerald Giesbrecht

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Both c-section and antibiotic exposure are linked to gut microbiota imbalance in infants. Such disturbance is associated with the Hypothalamic-Pituitary-Adrenal (HPA) axis function. However, the literature only has contradicting evidence for the association between c-sections and the HPA axis. Therefore, this study aims to test if the mode of delivery and antibiotics exposure is associated with the HPA axis. Also, whether exposure to both interacts with the HPA-axis. It was hypothesized that associations and interactions would be observed. Secondary data analysis was used for this co-relational study. Data for the mode of delivery and antibiotics exposure variables were documented from hospital records or self-questionnaires. In addition, cortisol levels (Area under the curve with respect to increasing (AUCi) and Area under the curve with respect to ground (AUCg)) were based on saliva collected from three months old during the infant’s visit to the lab and after drawing blood. One-way and between-subject ANOVA analyses were run on data. No significant association between delivery mode and infant cortisol level was found, AUCi and AUCg, p > .05. Only the infant’s AUCg was found to be significantly higher if there were antibiotics exposure at delivery (p = .001) or their mothers were exposed during pregnancy (p < .05). Infants born by c-section and exposed to antibiotics at three months had higher AUCi than those born vaginally, p < .02. These results imply that antibiotic exposure before three months is associated with an infant’s stress response. The association might increase if antibiotic exposure occurs three months after a c-section birth. However, more robust and causal evidence in future studies is needed, given a variable group’s statistically weak sample size. Nevertheless, the results of this study still highlight the unintended consequences of antibiotic exposure during delivery and pregnancy.

Keywords: HPA-axis, antibiotics, c-section, gut-microbiota, development, stress

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Authors: Nabin Prasad Joshi

Abstract:

A new variant of the coronavirus family found in the Wuhan city market of China is causing serious harm to human beings. After the WHO decided COVID-19 was a pandemic situation, everyone started to measure the prevention of infectious diseases according to WHO guidelines. It includes social distancing, isolation, quarantine, lockdown, sanitation, and masking, respectively. During this time, the researcher has observed the difficulties of cultivating the new normal in people in Nepal. People have perceived the single coronavirus differently; common populations and frontline workers have different perceptions of coronavirus. The researcher started to measure the psychosocial impact of the COVID-19 pandemic on frontline workers and general populations in Kathmandu valley. The total number of sample units for this research is 82; it includes 52 general populations and 30 frontline workers. These sample units are selected through convenient sampling and purposive sampling, respectively. This research is based on descriptive and exploratory design. DASS-21 of the Nepali version is a comprehensive data collection tool for depression, anxiety, and stress measurement in this research, and simultaneously the psychosocial checklist, key-informant interview, and case study have been done. Quantitative data are analyzed with the help of excel, and qualitative data are through thematic analysis. The study has shown that the occurrence of psychosocial issues among frontline workers is greater than in general populations. It is found that the informants with higher education status have greater psychosocial issues in comparison to low education status. In the context of a pandemic, family/friends’ support can function as a protective factor when at adequate levels.

Keywords: anxiety, depression, isolation, lockdown

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Authors: Mahdi Aghaei, Saeid Jamshidi, Mastaneh Hajipour

Abstract:

Effective factors on the mechanical wellbore stability are divided in to two categories: 1) Controllable factors, 2) Uncontrollable factors. The purpose of geo-mechanical modeling of wells is to determine the limit of controlled parameters change based on the stress regime at each point and by solving the governing equations the pore-elastic environment around the well. In this research, the mechanical analysis of wellbore stability was carried out for Soroush oilfield. For this purpose, the geo-mechanical model of the field is made using available data. This model provides the necessary parameters for obtaining the distribution of stress around the wellbore. Initially, a basic model was designed to perform various analysis, based on obtained data, using Abaqus software. All of the subsequent sensitivity analysis such as sensitivity analysis on porosity, permeability, etc. was done on the same basic model. The results obtained from these analysis gives various result such as: with the constant geomechanical parameters, and sensitivity analysis on porosity permeability is ineffective. After the most important parameters affecting the wellbore stability and instability are geo-mechanical parameters.

Keywords: wellbore stability, movement, stress, instability

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Authors: Arunai Nambi Raj N., Kaviarasu Karunakaran, Krishnamurthy K.

Abstract:

The purpose of this study was to create American Association of Physicist in Medicine (AAPM) Task Group 119 (TG 119) benchmark plans for flattening filter free beam (FFF) deliveries of intensity modulated radiation therapy (IMRT) and volumetric arc therapy (VMAT) in the Eclipse treatment planning system. The planning data were compared with the flattening filter (FF) IMRT & VMAT plan data to verify the dosimetric commissioning accuracy of FFF deliveries. AAPM TG 119 proposed a set of test cases called multi-target, mock prostate, mock head and neck, and C-shape to ascertain the overall accuracy of IMRT planning, measurement, and analysis. We used these test cases to investigate the performance of the Eclipse Treatment planning system for the flattening filter free beam deliveries. For these test cases, we generated two sets of treatment plans, the first plan using 7–9 IMRT fields and a second plan utilizing two arc VMAT technique for both the beam deliveries (6 MV FF, 6MV FFF, 10 MV FF and 10 MV FFF). The planning objectives and dose were set as described in TG 119. The dose prescriptions for multi-target, mock prostate, mock head and neck, and C-shape were taken as 50, 75.6, 50 and 50 Gy, respectively. The point dose (mean dose to the contoured chamber volume) at the specified positions/locations was measured using compact (CC‑13) ion chamber. The composite planar dose and per-field gamma analysis were measured with IMatriXX Evaluation 2D array with OmniPro IMRT Software (version 1.7b). FFF beam deliveries of IMRT and VMAT plans were comparable to flattening filter beam deliveries. Our planning and quality assurance results matched with TG 119 data. AAPM TG 119 test cases are useful to generate FFF benchmark plans. From the obtained data in this study, we conclude that the commissioning of FFF IMRT and FFF VMAT delivery were found within the limits of TG-119 and the performance of the Eclipse treatment planning system for FFF plans were found satisfactorily.

Keywords: flattening filter free beams, intensity modulated radiation therapy, task group 119, volumetric modulated arc therapy

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Authors: Rania Jradi, Christophe Marvillet, Mohamed Razak Jeday

Abstract:

One of the most frequently encountered problems in industrial heat exchangers is fouling, which degrades the thermal and hydraulic performances of these types of equipment, leading thus to failure if undetected. And it occurs due to the accumulation of undesired material on the heat transfer surface. So, it is necessary to know about the heat exchanger fouling dynamics to plan mitigation strategies, ensuring a sustainable and safe operation. This paper proposes an Artificial Neural Network (ANN) approach to estimate the fouling resistance in a cross-flow heat exchanger by the collection of the operating data of the phosphoric acid concentration loop. The operating data of 361 was used to validate the proposed model. The ANN attains AARD= 0.048%, MSE= 1.811x10⁻¹¹, RMSE= 4.256x 10⁻⁶ and r²=99.5 % of accuracy which confirms that it is a credible and valuable approach for industrialists and technologists who are faced with the drawbacks of fouling in heat exchangers.

Keywords: cross-flow heat exchanger, fouling, estimation, phosphoric acid concentration loop, artificial neural network approach

Procedia PDF Downloads 202