Search results for: high frequency data

Authors: Khalida S. Rijab, Mohammed E. Safi, Ayad A. Ibrahim

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When electrical electrodes are mounted on the skin surface of the muscle, a signal is detected when a skeletal muscle undergoes contraction; the signal is known as surface electromyographic signal (EMG). This signal has a noise-like interference pattern resulting from the temporal and spatial summation of action potentials (AP) of all active motor units (MU) near electrode detection. By appropriate processing (Decomposition), the surface EMG signal may be used to give an estimate of motor unit action potential. In this work, a denoising technique is applied to the MUAP signals extracted from the spatial filter (IB2). A set of signals from a non-invasive two-dimensional grid of 16 electrodes from different types of subjects, muscles, and sex are recorded. These signals will acquire noise during recording and detection. A digital fourth order band- pass Butterworth filter is used for denoising, with a tuned band-pass frequency of suitable choice of cutoff frequencies is investigated, with the aim of obtaining a suitable band pass frequency. Results show an improvement of (1-3 dB) in the signal to noise ratio (SNR) have been achieved, relative to the raw spatial filter output signals for all cases that were under investigation. Furthermore, the research’s goal included also estimation and reconstruction of the mean shape of the MUAP.

Keywords: EMG, Motor Unit, Digital Filter, Denoising

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Authors: Abdul Soofi, Katherine Wolf, Egon Ranghini, Gregory Dressler

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Obesity and its associated complications, such as insulin resistance and non-alcoholic fatty liver disease, are reaching epidemic proportions. In mice, the TGF-β superfamily is implicated in the regulation of white and brown adipose tissues differentiation. The Kielin/Chordin-like Protein (KCP) is a secreted regulator of the TGF-β superfamily pathways that can inhibit both TGF-β and Activin signals while enhancing the Bone Morphogenetic protein (BMP) signaling. However, the effects of KCP on metabolism and obesity have not been studied in animal models. Thus, we examined the effects of KCP loss or gain of function in mice that were maintained on either a regular or a high fat diet. Loss of KCP sensitized mice to obesity and associated complications such as hepatic steatosis and glucose intolerance. In contrast, transgenic mice that expressed KCP in the kidney, liver and adipose tissues were resistant to developing high fat diet induced obesity and had significantly reduced white adipose tissue. KCP over-expression was able to shift the pattern of Smad signaling in vivo, to increase the levels of P-Smad1 and decrease P-Smad3, resulting in resistance to high fat diet induced hepatic steatosis and glucose intolerance. In aging mice, loss of KCP promoted liver pathology even when mice were fed a normal diet. The data demonstrate that shifting the TGF-β superfamily signaling with a secreted inhibitor or enhancer can alter the physiology of adipose tissue to reduce obesity and can inhibit the initiation and progression of hepatic steatosis to significantly reduce the effects of high fat diet induced metabolic disease.

Keywords: adipose tissue, KCP, obesity, TGF-β, BMP, hepatic steatosis, metabolic syndrome

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Authors: Valery A. Aurov, Maria D. Bausheva, Elena V. Uliyanova

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The problems of sustainability of contemporary high-rise buildings now demand an altogether new approach, which corresponds with the laws of dialectics. We should imply the principle “going from mega-object to the so called mezzo-object.” So the scientists have arrived at the conclusion that a contemporary “skyscraper” must not increase in height but develop horizontal space axes which unite a complex of high-rise buildings into a single composition. This is necessary both for safety issues and increasing skyscrapers’ functioning qualities. As a result, architects single out a quality unit in a dominating group of high-rise constructions and make a conclusion about the influence of visual fields on the designing parameters of this group.

Keywords: design, high-rise buildings, skyscrapers, sustainability, visual fields, dominating group, regulations, design recommendations

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Authors: Richard Okyere Boadu, Judith Obiri-Yeboah, Kwame Adu Okyere Boadu, Nathan Kumasenu Mensah, Grace Amoh-Agyei

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Routine health information system (RHIS) quality assurance has become an important issue, not only because of its significance in promoting a high standard of patient care but also because of its impact on government budgets for the maintenance of health services. A routine health information system comprises healthcare data collection, compilation, storage, analysis, report generation, and dissemination on a routine basis in various healthcare settings. The data from RHIS give a representation of health status, health services, and health resources. The sources of RHIS data are normally individual health records, records of services delivered, and records of health resources. Using reliable information from routine health information systems is fundamental in the healthcare delivery system. Quality assurance practices are measures that are put in place to ensure the health data that are collected meet required quality standards. Routine health information system quality assurance practices ensure that data that are generated from the system are fit for use. This study considered quality assurance practices in the RHIS processes. Methods: A cross-sectional study was conducted in eight health facilities in Tarkwa Sub-Municipal Health Service in the western region of Ghana. The study involved routine quality assurance practices among the 90 health staff and management selected from facilities in Tarkwa Sub-Municipal who collected or used data routinely from 24th December 2019 to 20th January 2020. Results: Generally, Tarkwa Sub-Municipal health service appears to practice quality assurance during data collection, compilation, storage, analysis and dissemination. The results show some achievement in quality control performance in report dissemination (77.6%), data analysis (68.0%), data compilation (67.4%), report compilation (66.3%), data storage (66.3%) and collection (61.1%). Conclusions: Even though the Tarkwa Sub-Municipal Health Directorate engages in some control measures to ensure data quality, there is a need to strengthen the process to achieve the targeted percentage of performance (90.0%). There was a significant shortfall in quality assurance practices performance, especially during data collection, with respect to the expected performance.

Keywords: quality assurance practices, assessment of routine health information system quality, routine health information system, data quality

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Authors: P. M. Kundu, L. R. Singo, J. O. Odiyo

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Luvuvhu River catchment in South Africa experiences floods resulting from heavy rainfall of intensities exceeding 15 mm per hour associated with the Inter-tropical Convergence Zone (ITCZ). The generation of runoff is triggered by the rainfall intensity and soil moisture status. In this study, remote sensing and GIS techniques were used to analyze the hydrologic response to land cover changes. Runoff was calculated as a product of the net precipitation and a curve number coefficient. It was then routed using the Muskingum-Cunge method using a diffusive wave transfer model that enabled the calculation of response functions between start and end point. Flood frequency analysis was determined using theoretical probability distributions. Spatial data on land cover was obtained from multi-temporal Landsat images while data on rainfall, soil type, runoff and stream discharges was obtained by direct measurements in the field and from the Department of Water. A digital elevation model was generated from contour maps available at http://www.ngi.gov.za. The results showed that land cover changes had impacted negatively to the hydrology of the catchment. Peak discharges in the whole catchment were noted to have increased by at least 17% over the period while flood volumes were noted to have increased by at least 11% over the same period. The flood time to peak indicated a decreasing trend, in the range of 0.5 to 1 hour within the years. The synergism between remotely sensed digital data and GIS for land surface analysis and modeling was realized, and it was therefore concluded that hydrologic modeling has potential for determining the influence of changes in land cover on the hydrologic response of the catchment.

Keywords: catchment, digital elevation model, hydrological model, routing, runoff

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Authors: Andrés Calvillo Téllez, Marianne Martínez Zanzarric, José Cruz Núñez Pérez

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A modular system that performs basic monitoring of both water and air quality is presented. Monitoring is essential for environmental, aquaculture, and agricultural disciplines, where this type of instrumentation is necessary for data collection. The system uses low-cost components, which allows readings close to those with high-cost probes. The probe collects readings such as the coordinates of the geographical position, as well as the time it records the target parameters of the monitored. The modules or subsystems that make up the probe are the global positioning (GPS), which shows the altitude, latitude, and longitude data of the point where the reading will be recorded, a real-time clock stage, the date marking the time, the module SD memory continuously stores data, data acquisition system, central processing unit, and energy. The system acquires parameters to measure water quality, conductivity, pressure, and temperature, and for air, three types of ammonia, dioxide, and carbon monoxide gases were censored. The information obtained allowed us to identify the schedule of modification of the parameters and the identification of the ideal conditions for the growth of microorganisms in the water.

Keywords: calibration, conductivity, datalogger, monitoring, real time clock, water quality

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Authors: Evgeny V. Blagin, Aleksandr I. Dovgjallo, Dmitry A. Uglanov

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This article deals with research of the working process in the thermocompressor which operates on cryogenic working fluid. Thermocompressor is device suited for the conversation of heat energy directly to the potential energy of pressure. Suggested thermocompressor is suited for operation during liquid natural gas (LNG) re-gasification and is placed after evaporator. Such application of thermocompressor allows using of the LNG cold energy for rising of working fluid pressure, which then can be used for electricity generation or another purpose. Thermocompressor consists of two chambers divided by the regenerative heat exchanger. Calculation algorithm for unsteady calculation of thermocompressor working process was suggested. The results of this investigation are to change of thermocompressor’s chambers temperature and pressure during the working cycle. These distributions help to find out the parameters, which significantly influence thermocompressor efficiency. These parameters include regenerative heat exchanger coefficient of the performance (COP) dead volume of the chambers, working frequency of the thermocompressor etc. Exergy analysis was performed to estimate thermocompressor efficiency. Cryogenic thermocompressor operated on nitrogen working fluid was chosen as a prototype. Calculation of the temperature and pressure change was performed with taking into account heat fluxes through regenerator and thermocompressor walls. Temperature of the cold chamber significantly differs from the results of steady calculation, which is caused by friction of the working fluid in regenerator and heat fluxes from the hot chamber. The rise of the cold chamber temperature leads to decreasing of thermocompressor delivery volume. Temperature of hot chamber differs negligibly because losses due to heat fluxes to a cold chamber are compensated by the friction of the working fluid in the regenerator. Optimal working frequency was selected. Main results of the investigation: -theoretical confirmation of thermocompressor operation capability on the cryogenic working fluid; -optimal working frequency was found; -value of the cold chamber temperature differs from the starting value much more than the temperature of the hot chamber; -main parameters which influence thermocompressor performance are regenerative heat exchanger COP and heat fluxes through regenerator and thermocompressor walls.

Keywords: cold energy, liquid natural gas, thermocompressor, regenerative heat exchanger

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Authors: John M. Lyne, K. Andrea Scott

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In fluid dynamics, direct numerical simulations (DNS) of turbulent flows require large amounts of nodes to appropriately resolve all scales of energy transfer. Due to the size of these databases, sharing these datasets amongst the academic community is a challenge. Recent work has been done to investigate the use of super-resolution to enable database sharing, where a low-resolution flow field is super-resolved to high resolutions using a neural network. Recently, Generative Adversarial Networks (GAN) have grown in popularity with impressive results in the generation of faces, landscapes, and more. This work investigates the generation of unique high-resolution channel flow velocity fields from a low-dimensional latent space using a GAN. The training objective of the GAN is to generate samples in which the distribution of the generated samplesis ideally indistinguishable from the distribution of the training data. In this study, the network is trained using samples drawn from a statistically stationary channel flow at a Reynolds number of 560. Results show that the turbulent statistics and energy spectra of the generated flow fields are within reasonable agreement with those of the DNS data, demonstrating that GANscan produce the intricate multi-scale phenomena of turbulence.

Keywords: computational fluid dynamics, channel flow, turbulence, generative adversarial network

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Authors: Djamila Benhaddouche, Abdelkader Benyettou

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In this paper, we used data mining to extract biomedical knowledge. In general, complex biomedical data collected in studies of populations are treated by statistical methods, although they are robust, they are not sufficient in themselves to harness the potential wealth of data. For that you used in step two learning algorithms: the Decision Trees and Support Vector Machine (SVM). These supervised classification methods are used to make the diagnosis of thyroid disease. In this context, we propose to promote the study and use of symbolic data mining techniques.

Keywords: biomedical data, learning, classifier, algorithms decision tree, knowledge extraction

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Authors: Usama Ahmed

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Data mining is the process of analyze data which are used to predict helpful information. It is the field of research which solve various type of problem. In data mining, classification is an important technique to classify different kind of data. Diabetes is most common disease. This paper implements different classification technique using Waikato Environment for Knowledge Analysis (WEKA) on diabetes dataset and find which algorithm is suitable for working. The best classification algorithm based on diabetic data is Naïve Bayes. The accuracy of Naïve Bayes is 76.31% and take 0.06 seconds to build the model.

Keywords: data mining, classification, diabetes, WEKA

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Authors: Viacheslav Shkuratskyy, Aminu Bello Usman, Michael O’Dea, Saifur Rahman Sabuj

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This paper examines relationships between solar activity and earthquakes; it applied machine learning techniques: K-nearest neighbour, support vector regression, random forest regression, and long short-term memory network. Data from the SILSO World Data Center, the NOAA National Center, the GOES satellite, NASA OMNIWeb, and the United States Geological Survey were used for the experiment. The 23rd and 24th solar cycles, daily sunspot number, solar wind velocity, proton density, and proton temperature were all included in the dataset. The study also examined sunspots, solar wind, and solar flares, which all reflect solar activity and earthquake frequency distribution by magnitude and depth. The findings showed that the long short-term memory network model predicts earthquakes more correctly than the other models applied in the study, and solar activity is more likely to affect earthquakes of lower magnitude and shallow depth than earthquakes of magnitude 5.5 or larger with intermediate depth and deep depth.

Keywords: k-nearest neighbour, support vector regression, random forest regression, long short-term memory network, earthquakes, solar activity, sunspot number, solar wind, solar flares

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Authors: Sanghyeon Kim, Cheolung Cheong

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Savonius wind turbines are a drag-type of vertical-axis wind turbine that has been used most commonly as a small-scale wind generator. However, noise is a main hindrance to wide spreading of Savonius wind turbines, just like other wind turbines. Although noise levels radiating from Savonius wind turbines may be relatively low because of their small size, they induce relatively high annoyance due to their prolonged noise exposure to the near community. Therefore, aerodynamic noise of small vertical-axis wind turbines is one of most important design parameters. In this paper, aerodynamic noise characteristics of Savonius wind turbines are investigated using the hybrid CAA techniques, and their low noise designs are proposed based on understanding of noise generation mechanism. First, flow field around the turbine are analyzed by solving 3-D unsteady incompressible RANS equations. Then, noise radiation is predicted using the Ffowcs Williams and Hawkings equation. Two distinct harmonic noise components, the well-know BPF components and the harmonics whose fundamental frequency is much higher than the BPF are identified. On a basis of this finding, S-shaped blades are proposed as low noise designs and it can reduce the noise levels of Savonius wind turbines by up to 2.7 dB.

Keywords: aerodynamic noise, Savonius wind turbine, vertical-axis wind turbine

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Authors: Chen Jun-Hong, He Pu, Tao Wen-Quan

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Proton exchange membrane fuel cell (PEMFC) is the most promising future energy source owing to its low operating temperature, high energy efficiency, high power density, and environmental friendliness. In this paper, a comprehensive PEMFC system control-oriented model is developed in the Matlab/Simulink environment, which includes the hydrogen supply subsystem, air supply subsystem, and thermal management subsystem. Besides, Improved Artificial Bee Colony (IABC) is used in the parameter identification of PEMFC semi-empirical equations, making the maximum relative error between simulation data and the experimental data less than 0.4%. Operation temperature is essential for PEMFC, both high and low temperatures are disadvantageous. In the thermal management subsystem, water pump and fan are both controlled with the PID controller to maintain the appreciate operation temperature of PEMFC for the requirements of safe and efficient operation. To improve the control effect further, fuzzy control is introduced to optimize the PID controller of the pump, and the Radial Basis Function (RBF) neural network is introduced to optimize the PID controller of the fan. The results demonstrate that Fuzzy-PID and RBF-PID can achieve a better control effect with 22.66% decrease in Integral Absolute Error Criterion (IAE) of T_st (Temperature of PEMFC) and 77.56% decrease in IAE of T_in (Temperature of inlet cooling water) compared with traditional PID. In the end, a novel thermal management structure is proposed, which uses the cooling air passing through the main radiator to continue cooling the secondary radiator. In this thermal management structure, the parasitic power dissipation can be reduced by 69.94%, and the control effect can be improved with a 52.88% decrease in IAE of T_in under the same controller.

Keywords: PEMFC system, parameter identification, temperature control, Fuzzy-PID, RBF-PID, parasitic power

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Authors: Tasir Khan, Yejuan Wang

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The study of extreme rainfall events is very important for flood management in river basins and the design of water conservancy infrastructure. Evaluation of quantiles of annual maximum rainfall (AMRF) is required in different environmental fields, agriculture operations, renewable energy sources, climatology, and the design of different structures. Therefore, the annual maximum rainfall (AMRF) was performed at different stations in Pakistan. Multiple probability distributions, log normal (LN), generalized extreme value (GEV), Gumbel (max), and Pearson type3 (P3) were used to find out the most appropriate distributions in different stations. The L moments method was used to evaluate the distribution parameters. Anderson darling test, Kolmogorov- Smirnov test, and chi-square test showed that two distributions, namely GUM (max) and LN, were the best appropriate distributions. The quantile estimate of a multi-parameter PD offers extreme rainfall through a specific location and is therefore important for decision-makers and planners who design and construct different structures. This result provides an indication of these multi-parameter distribution consequences for the study of sites and peak flow prediction and the design of hydrological maps. Therefore, this discovery can support hydraulic structure and flood management.

Keywords: RAMSE, multiple frequency analysis, annual maximum rainfall, L-moments

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Authors: Abdalla Mohamed Eblabla

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Due to the high increase and demand for a wide assortment of applications that require low-cost, high-efficiency, and compact systems, RF power amplifiers are considered the most critical design blocks and power consuming components in wireless communication, TV transmission, radar, and RF heating. Therefore, much research has been carried out in order to improve the performance of power amplifiers. Classes-A, B, C, D, E, and F are the main techniques for realizing power amplifiers. An implementation of high efficiency class-F power amplifier with Gallium Nitride (GaN) High Electron Mobility Transistor (HEMT) was realized in this paper. The simulation and optimization of the class-F power amplifier circuit model was undertaken using Agilent’s Advanced Design system (ADS). The circuit was designed using lumped elements.

Keywords: Power Amplifier (PA), gallium nitride (GaN), Agilent’s Advanced Design System (ADS), lumped elements

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Authors: Azzeddine Atibi, Khadija El Kababi, Salim Ahmed, Mohamed Radid

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The primary aim of the present study is to undertake an extensive comparative examination of distance learning and blended learning modalities, with a particular focus on assessing their efficacy during the period of confinement imposed by the COVID-19 pandemic. This investigation is grounded in the firsthand experiences of educators at the high school and secondary levels across both private and public educational institutions. To gather the necessary data, we designed and distributed a meticulously crafted survey to these educators, soliciting detailed accounts of their professional experiences throughout this challenging period. The survey's objectives include elucidating the specific difficulties faced by teachers, as well as highlighting the innovative pedagogical strategies they developed in response to these challenges. By synthesizing the insights gained from this survey, we aim to foster an exchange of experiences among educators and to generate informed recommendations that will guide future educational reforms. Ultimately, this study aspires to contribute to the ongoing discourse on optimizing educational practices in the face of unprecedented disruptions.

Keywords: distance learning, blended learning, covid 19, secondary/ high school, teachingperformance, evaluation

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Authors: Rashi Jain

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The Wireless Body Area Networks (WBANs) is an emerging interdisciplinary area where small sensors are placed on/within the human body. These sensors monitor the physiological activities and vital statistics of the body. The data from these sensors is aggregated and communicated to a remote doctor for immediate attention or to a database for records. On 6 Feb 2012, the IEEE 802.15.6 task group approved the standard for Body Area Network (BAN) technologies. The standard proposes the physical and MAC layer for the WBANs. The work provides an introduction to WBANs and overview of the physical and MAC layers of the standard. The physical layer specifications have been covered. A comparison of different protocols used at MAC layer is drawn. An introduction to the network layer and security aspects of the WBANs is made. The WBANs suffer certain limitations such as regulation of frequency bands, minimizing the effect of transmission and reception of electromagnetic signals on the human body, maintaining the energy efficiency among others. This has slowed down their implementation.

Keywords: vehicular networks, sensors, MicroController 8085, LTE

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Authors: Ye. Shapovalov, V. Shapovalov, O. Stryzhak, A. Salyuk

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Over the past decades, amount of scientific information has been growing exponentially. It became more complicated to process and systemize this amount of data. The approach to systematization of scientific information on the production of biogas based on the ontological IT platform “T.O.D.O.S.” has been developed. It has been proposed to select semantic characteristics of each work for their further introduction into the IT platform “T.O.D.O.S.”. An ontological graph with a ranking function for previous scientific research and for a system of selection of microorganisms has been worked out. These systems provide high performance of information management of scientific information.

Keywords: ontology-based analysis, analysis of scientific data, methanogenesis, microorganism hierarchy, 'T.O.D.O.S.'

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Authors: Asifa Amara, Prachi Singh, Kanishka, Debargho Pathak, Akshat Kumar, Jayakumar Eravelly

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Today's generation is totally dependent on technology that uses data as its fuel. The present study is all about innovations and developments in data science and gives an idea about how efficiently to use the data provided. This study will help to understand the core concepts of data science. The concept of artificial intelligence was introduced by Alan Turing in which the main principle was to create an artificial system that can run independently of human-given programs and can function with the help of analyzing data to understand the requirements of the users. Data science comprises business understanding, analyzing data, ethical concerns, understanding programming languages, various fields and sources of data, skills, etc. The usage of data science has evolved over the years. In this review article, we have covered a part of data science, i.e., machine learning. Machine learning uses data science for its work. Machines learn through their experience, which helps them to do any work more efficiently. This article includes a comparative study image between human understanding and machine understanding, advantages, applications, and real-time examples of machine learning. Data science is an important game changer in the life of human beings. Since the advent of data science, we have found its benefits and how it leads to a better understanding of people, and how it cherishes individual needs. It has improved business strategies, services provided by them, forecasting, the ability to attend sustainable developments, etc. This study also focuses on a better understanding of data science which will help us to create a better world.

Keywords: data science, machine learning, data analytics, artificial intelligence

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Authors: Phatthanan Chaiyabut

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This research paper investigates whether the development of environmentally friendly practices by luxury hotel resorts can be used as a strategy for gaining competitive advantage through differentiation, and suggests ways to do it. The focus is on luxury hotel resorts in Samut Songkram Province, Thailand. A questionnaire was utilized as a tool to collect data. Statistics utilized in this research included frequency, percentage, mean, standard deviation, and multiple regression analysis. Findings indicate that environmentally friendly development of hotel resorts in Samut Songkram Province has a very limited use as a corporate strategy. Only two luxury hotel resorts had it incorporated in their strategy, it is not much used in marketing indicating environmental issues are not seen as important. This was confirmed through the interviews with the managers that it is not seen as important issue to promote.

Keywords: competitive advantage, competitive strategy, Samut Songkram Province, hotel and resort

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Authors: Jihad S. Daba, Jean-Pierre Dubois, Georges El Soury

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Fifth generation wireless networks guarantee significant capacity enhancement to suit more clients and services at higher information rates with better reliability while consuming less power. The deployment of massive multiple-input-multiple-output technology guarantees broadband wireless networks with the use of base station antenna arrays to serve a large number of users on the same frequency and time-slot channels. In this work, we evaluate the performance of massive multiple-input-multiple-output systems (MIMO) systems in 5^th generation cellular networks in terms of capacity and bit error rate. Several cases were considered and analyzed to compare the performance of massive MIMO systems while varying the number of antennas at both transmitting and receiving ends. We found that, unlike classical MIMO systems, reducing the number of transmit antennas while increasing the number of antennas at the receiver end provides a better solution to performance enhancement. In addition, enhanced orthogonal frequency division multiplexing and beam division multiple access schemes further improve the performance of massive MIMO systems and make them more reliable.

Keywords: beam division multiple access, D2D communication, enhanced OFDM, fifth generation broadband, massive MIMO

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Authors: Yeonjeong Lee, Kyoung-jae Kim, Youngtae Kim

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This study proposes a novel recommender system that uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user’s preference. The proposed model consists of two steps. In the first step, this study uses logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. Then, this study combines the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. In the second step, this study uses the market basket analysis to extract association rules for co-purchased products. Finally, the system selects customers who have high likelihood to purchase products in each product group and recommends proper products from same or different product groups to them through above two steps. We test the usability of the proposed system by using prototype and real-world transaction and profile data. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The results also show that the proposed system may be useful in real-world online shopping store.

Keywords: product recommender system, ensemble technique, association rules, decision tree, artificial neural networks

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Authors: Adel A. Ghobbar, Ahmad Bakkar

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Although special care is given to maintenance, aircraft systems fail, and these failures cause delays and cancellations. The occurrence of Delays and Cancellations affects operators and manufacturers negatively. To reduce technical delays and cancellations, one should be able to determine the important systems causing them. The goal of this research is to find a method to define the most expensive delays and cancellations systems for Airline operators. A predictive model was introduced to forecast the failure and their impact after carrying out research that identifies relevant information to tackle the problems faced while answering the questions of this paper. Data were obtained from the manufacturers’ services reliability team database. Subsequently, delays and cancellations evaluation methods were identified. No cost estimation methods were used due to their complexity. The model was developed, and it takes into account the frequency of delays and cancellations and uses weighting factors to give an indication of the severity of their duration. The weighting factors are based on customer experience. The data Analysis approach has shown that delays and cancellations events are not seasonal and do not follow any specific trends. The use of weighting factor does have an influence on the shortlist over short periods (Monthly) but not the analyzed period of three years. Landing gear and the navigation system are among the top 3 factors causing delays and cancellations for all three aircraft types. The results did confirm that the cooperation between certain operators and manufacture reduce the impact of delays and cancellations.

Keywords: reliability, availability, delays & cancellations, aircraft maintenance

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Authors: Sittampalam Manoharan, Gary Chai, Sanaul Chowdhury, Andrew Golding

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The primary objective of this paper is to present a simplified approach to develop the structural deterioration model using traffic speed deflectometer data for flexible pavements. Maintaining assets to meet functional performance is not economical or sustainable in the long terms, and it would end up needing much more investments for road agencies and extra costs for road users. Performance models have to be included for structural and functional predicting capabilities, in order to assess the needs, and the time frame of those needs. As such structural modelling plays a vital role in the prediction of pavement performance. A structural condition is important for the prediction of remaining life and overall health of a road network and also major influence on the valuation of road pavement. Therefore, the structural deterioration model is a critical input into pavement management system for predicting pavement rehabilitation needs accurately. The Traffic Speed Deflectometer (TSD) is a vehicle-mounted Doppler laser system that is capable of continuously measuring the structural bearing capacity of a pavement whilst moving at traffic speeds. The device’s high accuracy, high speed, and continuous deflection profiles are useful for network-level applications such as predicting road rehabilitations needs and remaining structural service life. The methodology adopted in this model by utilizing time series TSD maximum deflection (D0) data in conjunction with rutting, rutting progression, pavement age, subgrade strength and equivalent standard axle (ESA) data. Then, regression analyses were undertaken to establish a correlation equation of structural deterioration as a function of rutting, pavement age, seal age and equivalent standard axle (ESA). This study developed a simple structural deterioration model which will enable to incorporate available TSD structural data in pavement management system for developing network-level pavement investment strategies. Therefore, the available funding can be used effectively to minimize the whole –of- life cost of the road asset and also improve pavement performance. This study will contribute to narrowing the knowledge gap in structural data usage in network level investment analysis and provide a simple methodology to use structural data effectively in investment decision-making process for road agencies to manage aging road assets.

Keywords: adjusted structural number (SNP), maximum deflection (D0), equant standard axle (ESA), traffic speed deflectometer (TSD)

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Authors: M. J. Reis Lima, J. Oliveira, M. Brito, C. Lemos, A. Mascarenhas, E. Teixeira Lemos

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Hypertension is a common condition causing cardio and cerebrovascular complications. Portugal has one of the highest mortality rates from stroke and a high prevalence of hypertension. Systolic blood pressure (SBP) is an important risk factor for cardiovascular events (myocardial infarction and stroke) and premature mortality, particularly in the elderly population. The present study aims to estimate the prevalence of hypertension in a Portuguese population living in a coastal city and to identify some of its determinants (namely gender, age, the body mass index and physical activity frequency). A total of 91 adults who attended three pharmacies of a coastal city in the center of Portugal, between May and August of 2013 were evaluated. Attendants who reported to have diabetes or taking antihypertensive drugs in the 2 previous weeks were excluded from the study. Sociodemographic factors, BMI, habits of exercise and BP were assessed. Hypertension was defined as blood pressure ≥140/90 mmHg. The majority of the studied population was constituted by women (75.8%), with a mean age of 54.2±1.6 years old, married or living in civil union and that had completed secondary school or had higher education (40%). They presented a mean BMI of 26.2±4.76 Kg/m2. and were sedentary. The mean BP was 127.0±17.77mmHg- 74.69 ± 9.53. In this population, we found 4.3% of people with hypertension and 16.1% with normal high blood pressure. Men exhibit a tendency to present higher systolic blood pressure values than women. Of all the factors considered, SBP values also tended to be higher with age and higher BMI values. Despite the fact that the mean values of SBP did not present values higher than 140 mmHg we must be concerned because the studied population is undiagnosed for hypertension. Our study even with some limitations might be a prelude to the upcoming research about the underlying factors responsible for the occurrence of SBP.

Keywords: hypertension, age, exercise, obesity and gender

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Authors: Yingisani Chabalala, Elhadi Adam, Khalid Adem Ali

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Mapping smallholder fruit plantations using optical data is challenging due to morphological landscape heterogeneity and crop types having overlapped spectral signatures. Furthermore, cloud covers limit the use of optical sensing, especially in subtropical climates where they are persistent. This research assessed the effectiveness of Sentinel-1 (S1) and Sentinel-2 (S2) data for mapping fruit trees and co-existing land-use types by using support vector machine (SVM) and random forest (RF) classifiers independently. These classifiers were also applied to fused data from the two sensors. Feature ranks were extracted using the RF mean decrease accuracy (MDA) and forward variable selection (FVS) to identify optimal spectral windows to classify fruit trees. Based on RF MDA and FVS, the SVM classifier resulted in relatively high classification accuracy with overall accuracy (OA) = 0.91.6% and kappa coefficient = 0.91% when applied to the fused satellite data. Application of SVM to S1, S2, S2 selected variables and S1S2 fusion independently produced OA = 27.64, Kappa coefficient = 0.13%; OA= 87%, Kappa coefficient = 86.89%; OA = 69.33, Kappa coefficient = 69. %; OA = 87.01%, Kappa coefficient = 87%, respectively. Results also indicated that the optimal spectral bands for fruit tree mapping are green (B3) and SWIR_2 (B10) for S2, whereas for S1, the vertical-horizontal (VH) polarization band. Including the textural metrics from the VV channel improved crop discrimination and co-existing land use cover types. The fusion approach proved robust and well-suited for accurate smallholder fruit plantation mapping.

Keywords: smallholder agriculture, fruit trees, data fusion, precision agriculture

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Authors: Sridhar Rapuru, D. Mallikarjunreddy, Rajanarendra Sai

Abstract:

In this reign of the internet, the access of any multimedia file to the users at any time with a superior quality is needed. To achieve this goal, it is very important to have a good network without any interruptions between the satellites along with various earth stations. For that purpose, a high speed inter-satellite optical wireless communication system (IsOWC) is designed with space and polarization diversity techniques. IsOWC offers a high bandwidth, small size, less power requirement and affordable when compared with the present microwave satellite systems. To improve the efficiency and to reduce the propagation delay, inter-satellite link is established between the satellites. High accurate tracking systems are required to establish the reliable connection between the satellites as they have their own orbits. The only disadvantage of this IsOWC system is laser beam width is narrower than the RF because of this highly accurate tracking system to meet this requirement. The satellite uses the 'ephemerides data' for rough pointing and tracking system for fine pointing to the other satellite. In this proposed IsOWC system, laser light is used as a wireless connectedness between the source and destination and free space acts as the channel to carry the message. The proposed system will be designed, simulated and analyzed for 6000km with an improvement of data rate over previously existing systems. The performance parameters of the system are Q-factor, eye opening, bit error rate, etc., The proposed system for Inter-satellite Optical Wireless Communication System Design Using Diversity Techniques finds huge scope of applications in future generation communication purposes.

Keywords: inter-satellite optical wireless system, space and polarization diversity techniques, line of sight, bit error rate, Q-factor

Procedia PDF Downloads 269

Authors: Tracie Catlett

Abstract:

Students enrolled in high-achieving schools are under tremendous pressure to perform at high levels inside and outside the classroom. Achievement pressure is a prevalent source of stress for students enrolled in high-achieving schools, and female students in particular experience a higher frequency and higher levels of stress compared to their male peers. The practice of mindfulness in a school setting is one tool that has been linked to improved self-regulation of emotions, increased positive emotions, and stress reduction. A mixed methods randomized pretest-posttest no-treatment control trial, evaluated the effects of a six-session mindfulness intervention taught during a regularly scheduled life skills period in an independent day school, one type of high-achieving school. Twenty-nine students in Grades 10 and 11 were randomized by class where Grade 11 students were in the intervention group (n = 14) and Grade 10 students were in the control group (n = 15). Findings from the study produced mixed results. There was no evidence that the mindfulness program reduced participants’ stress levels and negative emotions. In fact, contrary to what was expected, students enrolled in the intervention group experienced higher levels of stress and increased negative emotions at posttreatment when compared to pretreatment. Neither the within-group nor the between-groups changes in stress level were statistically significant, p > .05, and the between-groups effect size was small, d = .2. The study found evidence that the mindfulness program may have had a positive impact on students’ ability to regulate their emotions. The within-group comparison and the between-groups comparison at posttreatment found that students in the mindfulness course experienced statistically significant improvement in the in their ability to regulate their emotions at posttreatment, p = .009 < .05 and p =. 034 < .05, respectively. The between-groups effect size was medium, d =.7, suggesting that the positive differences in emotion regulation difficulties were substantial and have practical implications. The analysis of gender differences as they relate to stress and emotions revealed that female students perceive higher levels of stress and report experiencing stress more often than males. There were no gender differences when analyzing sources of stress experienced by the student participants. Both females and males experience regular achievement pressures related to their school performance and worry about their future, college acceptance, grades, and parental expectations. Females reported an increased awareness of their stress and actively engaged in practicing mindfulness to manage their stress. Students in the treatment group expressed that the practice of mindfulness resulted in feelings of relaxation and calmness.

Keywords: achievement pressure, adolescents, emotion regulation, emotions, high-achieving schools, independent schools, mindfulness, negative affect, positive affect, stress

Procedia PDF Downloads 71

Authors: El Korchi Ayoub, Cherif Raef

Abstract:

Interior noise in vehicles is an essential factor affecting occupant comfort. Over recent decades, much work has been done to develop simulation tools for vehicle NVH. At the medium high-frequency range, the statistical energy analysis method (SEA) shows significant effectiveness in predicting noise and vibration responses of mechanical systems. In this paper, the evaluation of the sound pressure level (SPL) inside an automobile cabin has been performed numerically using the statistical energy analysis (SEA) method. A test car cabin was performed using a monopole source as a sound source. The decay rate method was employed to obtain the damping loss factor (DLF) of each subsystem of the developed SEA model. These parameters were then used to predict the sound pressure level in the interior cabin. The results show satisfactory agreement with the directly measured SPL. The developed SEA vehicle model can be used in early design phases and allows the engineer to identify sources contributing to the total noise and transmission paths.

Keywords: SEA, SPL, DLF, NVH

Procedia PDF Downloads 91

Authors: Kamel Taıbı, Abdelmadjid Rais

Abstract:

Nickel–Aluminium ferrites with the general formula Ni Alx Fe2-x O4 (0 ≤ x ≤ 1) were studied using X-ray diffraction, Infra Red and Raman spectroscopy. XRD diffraction patterns and their Reitveld refinements show that all samples have a pure single-phase cubic spinel structure. From these patterns, the lattice parameters of these samples have been calculated and compared with those predicted theoretically. Most of the values were found to decrease with increasing Al content. Infra Red spectra showed two significant absorption bands. The high band corresponds to tetrahedral (A) sites and the lower band to octahedral [B] sites, thus confirming the single phase spinel structure. For all compositions, Raman spectra show the five active modes A1g + E1g + 3 T2g of the motion of O2- ions and both the A-site and B-site ions. The Raman frequencies trend with aluminium concentration show a blue shift for all modes consistent with the replacement of Fe3+ by lower mass Al3+. Composition dependence of the Raman frequency modes is discussed in relationship with the cations distribution among the A-sites and B-sites.

Keywords: Ni-Al ferrites, spinel structure, XRD, Raman spectroscopy

Procedia PDF Downloads 374