Search results for: multivariate time series data

Authors: Tiffany Hollis

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Childhood trauma is well documented in mental health research, yet has received little attention in urban schools. Child trauma affects brain development and impacts cognitive, emotional, and behavioral functioning. When educators understand that some of the behaviors that appear to be aggressive in nature might be the result of a hidden diagnosis of trauma, learning can take place, and the child can thrive in the classroom setting. Traumatized children, however, do not fit neatly into any single ‘box.’ Although many children enter school each day carrying with them the experience of exposure to violence in the home, the symptoms of their trauma can be multifaceted and complex, requiring individualized therapeutic attention. The purpose of this study was to examine how prepared educators are to address the unique challenges facing children who experience trauma. Given the vast number of traumatized children in our society, it is evident that our education system must investigate ways to create an optimal learning environment that accounts for trauma, addresses its impact on cognitive and behavioral development, and facilitates mental and emotional health and well-being. The researcher describes the knowledge, attitudes, dispositions, and skills relating to trauma-informed knowledge of induction level teachers in a diverse middle school. The data for this study were collected through interviews with teachers, who are in the induction phase (the first three years of their teaching career). The study findings paint a clear picture of how ill-prepared educators are to address the needs of students who have experienced trauma and the implications for the development of a professional development workshop or series of workshops that train teachers how to recognize and address and respond to the needs of students. The study shows how teachers often lack skills to meet the needs of students who have experienced trauma. Traumatized children regularly carry a heavy weight on their shoulders. Children who have experienced trauma may feel that the world is filled with unresponsive, threatening adults, and peers. Despite this, supportive interventions can provide traumatized children with places to go that are safe, stimulating, and even fun. Schools offer an environment that potentially meets these requirements by creating safe spaces where students can feel at ease and have fun while also learning via stimulating educational activities. This study highlights the lack of preparedness of educators to address the academic, behavioral, and cognitive needs of students who have experienced trauma. These findings provide implications for the creation of a professional development workshop that addresses how to recognize and address the needs of students who have experienced some type of trauma. They also provide implications for future research with a focus on specific interventions that enable the creation of optimal learning environments where students who have experienced trauma and all students can succeed, regardless of their life experiences.

Keywords: educator preparation, induction educators, professional development, trauma-informed

Procedia PDF Downloads 106

Authors: Atul Kumar, Veeranjaneyulu Gannedi, Qazi Naveed Ahmed

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Oligosaccharides, which are essential to all cellular organisms, play vital roles in cell recognition, signaling, and are involved in a broad range of biological processes. The chemical synthesis of carbohydrates represents a powerful tool to provide homogeneous glycans. In carbohydrate synthesis, the major concern is the orthogonal protection of hydroxyl groups that can be unmasked independently. Classical protecting groups include benzyl ethers (Bn), which are normally cleaved through hydrogenolysis or by means of metal reduction, and acetate (Ac), benzoate (Bz) or pivaloate esters, which are removed using base promoted hydrolysis. In present work a series of α-Oxoester (COBz) protected saccharides, with divergent base sensitivity profiles against benzoyl (Bz) and acetyl (Ac), were designed and KHSO₅/CH₃COCl in methanol was identified as an easy, mild, selective and efficient deprotecting reagent for their removal in the perspective of carbohydrate synthesis. Timely monitoring of later reagent was advantageous in establishing both sequential as well as simultaneous deprotecting of COBz, Bz, and Ac. The salient feature of our work is its ease to generate different acceptors using designed monosaccharides. In summary, we demonstrated α-Oxoester (COBz) as a new protecting group for carbohydrates and the application of this group for the synthesis of Glycosylphosphatidylinositol (GPI) anchor are in progress.

Keywords: α-Oxoester, oligosaccharides, new protecting group, acceptor synthesis, glycosylation

Procedia PDF Downloads 134

Authors: Zhou Luchen, Wu Yubing, Burra Venkata Durga Kumar

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As the scale of the network becomes larger and more complex than before, the density of user devices is also increasing. The development of Unmanned Aerial Vehicle (UAV) networks is able to collect and transform data in an efficient way by using software-defined networks (SDN) technology. This paper proposed a three-layer distributed and dynamic cluster architecture to manage UAVs by using an AI-based resource allocation calculation algorithm to address the overloading network problem. Through separating services of each UAV, the UAV hierarchical cluster system performs the main function of reducing the network load and transferring user requests, with three sub-tasks including data collection, communication channel organization, and data relaying. In this cluster, a head node and a vice head node UAV are selected considering the Central Processing Unit (CPU), operational (RAM), and permanent (ROM) memory of devices, battery charge, and capacity. The vice head node acts as a backup that stores all the data in the head node. The k-means clustering algorithm is used in order to detect high load regions and form the UAV layered clusters. The whole process of detecting high load areas, forming and selecting UAV clusters, and moving the selected UAV cluster to that area is proposed as offloading traffic algorithm.

Keywords: k-means, resource allocation, SDN, UAV network, unmanned aerial vehicles

Procedia PDF Downloads 90

Authors: R. K. Apalowo, D. Chronopoulos

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A Finite Element (FE) based scheme is presented for quantifying guided wave interaction with Localised Nonlinear Structural Damage (LNSD) within structures of arbitrary layering and geometric complexity. The through-thickness mode-shape of the structure is obtained through a wave and finite element method. This is applied in a time domain FE simulation in order to generate time harmonic excitation for a specific wave mode. Interaction of the wave with LNSD within the system is computed through an element activation and deactivation iteration. The scheme is validated against experimental measurements and a WFE-FE methodology for calculating wave interaction with damage. Case studies for guided wave interaction with crack and delamination are presented to verify the robustness of the proposed method in classifying and identifying damage.

Keywords: layered structures, nonlinear ultrasound, wave interaction with nonlinear damage, wave finite element, finite element

Procedia PDF Downloads 139

Authors: Azeddine El-Hassouny, Chandrashekhar Meshram, Geraldin Nanfack

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In recent years, learning from data with noisy labels (Label Noise) has been a major concern in supervised learning. This problem has become even more worrying in Deep Learning, where the generalization capabilities have been questioned lately. Indeed, deep learning requires a large amount of data that is generally collected by search engines, which frequently return data with unreliable labels. In this paper, we investigate the Label Noise in Deep Learning using variational inference. Our contributions are : (1) exploiting Label Noise concept where the true labels are learnt using reparameterization variational inference, while observed labels are learnt discriminatively. (2) the noise transition matrix is learnt during the training without any particular process, neither heuristic nor preliminary phases. The theoretical results shows how true label distribution can be learned by variational inference in any discriminate neural network, and the effectiveness of our approach is proved in several target datasets, such as MNIST and CIFAR32.

Keywords: label noise, deep learning, discrete latent variable, variational inference, MNIST, CIFAR32

Procedia PDF Downloads 107

Authors: Simon Arunga, Teddy Kwaga, Rita Kageni, Michael Gichangi, Nyawira Mwangi, Fred Kagwa, Rogers Mwavu, Amos Baryashaba, Luis F. Nakayama, Katharine Morley, Michael Morley, Leo A. Celi, Jessica Haberer, Celestino Obua

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Purpose: The main aim for creating the Multimodal Database of Retinal Images for Africa (MoDRIA) was to provide a publicly available repository of retinal images for responsible researchers to conduct algorithm development in a bid to curb the challenges of ophthalmic artificial intelligence (AI) in Africa. Methods: Data and retina images were ethically sourced from sites in Uganda and Kenya. Data on medical history, visual acuity, ocular examination, blood pressure, and blood sugar were collected. Retina images were captured using fundus cameras (Foru3-nethra and Canon CR-Mark-1). Images were stored on a secure online database. Results: The database consists of 7,859 retinal images in portable network graphics format from 1,988 participants. Images from patients with human immunodeficiency virus were 18.9%, 18.2% of images were from hypertensive patients, 12.8% from diabetic patients, and the rest from normal’ participants. Conclusion: Publicly available data repositories are a valuable asset in the development of AI technology. Therefore, is a need for the expansion of MoDRIA so as to provide larger datasets that are more representative of Sub-Saharan data.

Keywords: retina images, MoDRIA, image repository, African database

Procedia PDF Downloads 98

Authors: Abderrahmane El Kachani, El Mahjoub Chakir, Anass Ait Laachir, Abdelhamid Niaaniaa, Jamal Zerouaoui, Tarik Jarou

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This paper presents a wind turbine based on the doubly fed induction generator (DFIG) connected to the utility grid through a shunt active power filter (SAPF). The whole system is controlled by a double nonlinear predictive controller (DNPC). A Taylor series expansion is used to predict the outputs of the system. The control law is calculated by optimization of the cost function. The first nonlinear predictive controller (NPC) is designed to ensure the high performance tracking of the rotor speed and regulate the rotor current of the DFIG, while the second one is designed to control the SAPF in order to compensate the harmonic produces by the three-phase diode bridge supplied by a passive circuit (rd, Ld). As a result, we obtain sinusoidal waveforms of the stator voltage and stator current. The proposed nonlinear predictive controllers (NPCs) are validated via simulation on a 1.5 MW DFIG-based wind turbine connected to an SAPF. The results obtained appear to be satisfactory and promising.

Keywords: wind power, doubly fed induction generator, shunt active power filter, double nonlinear predictive controller

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Authors: Madhawa Basnayaka, Jouni Paltakari

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Fully passive backscattering chipless RFID tags are an emerging wireless technology with low cost, higher reading distance, and fast automatic identification without human interference, unlike already available technologies like optical barcodes. The design optimization of chipless RFID tags is crucial as it requires replacing integrated chips found in conventional RFID tags with printed geometric designs. These designs enable data encoding and decoding through backscattered electromagnetic (EM) signatures. The applications of chipless RFID tags have been limited due to the constraints of data encoding capacity and the ability to design accurate yet efficient configurations. The traditional approach to accomplishing design parameters for a desired EM response involves iterative adjustment of design parameters and simulating until the desired EM spectrum is achieved. However, traditional numerical simulation methods encounter limitations in optimizing design parameters efficiently due to the speed and resource consumption. In this work, a deep learning neural network (DNN) is utilized to establish a correlation between the EM spectrum and the dimensional parameters of nested centric rings, specifically square and octagonal. The proposed bi-directional DNN has two simultaneously running neural networks, namely spectrum prediction and design parameters prediction. First, spectrum prediction DNN was trained to minimize mean square error (MSE). After the training process was completed, the spectrum prediction DNN was able to accurately predict the EM spectrum according to the input design parameters within a few seconds. Then, the trained spectrum prediction DNN was connected to the design parameters prediction DNN and trained two networks simultaneously. For the first time in chipless tag design, design parameters were predicted accurately after training bi-directional DNN for a desired EM spectrum. The model was evaluated using a randomly generated spectrum and the tag was manufactured using the predicted geometrical parameters. The manufactured tags were successfully tested in the laboratory. The amount of iterative computer simulations has been significantly decreased by this approach. Therefore, highly efficient but ultrafast bi-directional DNN models allow rapid and complicated chipless RFID tag designs.

Keywords: artificial intelligence, chipless RFID, deep learning, machine learning

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Authors: Anuradha Banerjee

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Energy aware operation is one of the visionary goals in the area of robotics because operability of robots is greatly dependent upon their residual energy. Practically, the tasks allocated to robots carry different priority and often an upper limit of time stamp is imposed within which the task needs to be completed. If a robot is unable to complete one particular task given to it the task is reallocated to some other robot. The collection of robots is controlled by a Central Monitoring Unit (CMU). Selection of the new robot is performed by a fuzzy controller called Task Reallocator (TRAC). It accepts the parameters like residual energy of robots, possibility that the task will be successfully completed by the new robot within stipulated time, distance of the new robot (where the task is reallocated) from distance of the old one (where the task was going on) etc. The proposed methodology increases the probability of completing globally assigned tasks and saves huge amount of energy as far as the collection of robots is concerned.

Keywords: energy-efficiency, fuzzy-controller, priority, reallocation, task

Procedia PDF Downloads 295

Authors: Dewi Retno Sari Saputro, Purnami Widyaningsih, Hendrika Handayani

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Extreme data on an observation can occur due to unusual circumstances in the observation. The data can provide important information that can’t be provided by other data so that its existence needs to be further investigated. The method for obtaining extreme data is one of them using maxima block method. The distribution of extreme data sets taken with the maxima block method is called the distribution of extreme values. Distribution of extreme values is Gumbel distribution with two parameters. The parameter estimation of Gumbel distribution with maximum likelihood method (ML) is difficult to determine its exact value so that it is necessary to solve the approach. The purpose of this study was to determine the parameter estimation of Gumbel distribution with quasi-Newton BFGS method. The quasi-Newton BFGS method is a numerical method used for nonlinear function optimization without constraint so that the method can be used for parameter estimation from Gumbel distribution whose distribution function is in the form of exponential doubel function. The quasi-New BFGS method is a development of the Newton method. The Newton method uses the second derivative to calculate the parameter value changes on each iteration. Newton's method is then modified with the addition of a step length to provide a guarantee of convergence when the second derivative requires complex calculations. In the quasi-Newton BFGS method, Newton's method is modified by updating both derivatives on each iteration. The parameter estimation of the Gumbel distribution by a numerical approach using the quasi-Newton BFGS method is done by calculating the parameter values that make the distribution function maximum. In this method, we need gradient vector and hessian matrix. This research is a theory research and application by studying several journals and textbooks. The results of this study obtained the quasi-Newton BFGS algorithm and estimation of Gumbel distribution parameters. The estimation method is then applied to daily rainfall data in Purworejo District to estimate the distribution parameters. This indicates that the high rainfall that occurred in Purworejo District decreased its intensity and the range of rainfall that occurred decreased.

Keywords: parameter estimation, Gumbel distribution, maximum likelihood, broyden fletcher goldfarb shanno (BFGS)quasi newton

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Authors: Feng Yang

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Machine learning (ML), especially deep learning (DL), has been extensively applied to many applications in recently years and gained great success in solving different problems, including scientific problems. However, conventional ML/DL methodologies are purely data-driven which have the limitations, such as need of ample amount of labelled training data, lack of consistency to physical principles, and lack of generalizability to new problems/domains. Recently, there is a growing consensus that ML models need to further take advantage of prior knowledge to deal with these limitations. Physics-informed machine learning, aiming at integration of physics/domain knowledge into ML, has been recognized as an emerging area of research, especially in the recent 2 to 3 years. In this work, physics-informed ML, specifically physics-informed neural network (NN), is employed and implemented to estimate the displacements at x, y, z directions in a solid mechanics problem that is controlled by equilibrium equations with boundary conditions. By incorporating the physics (i.e. the equilibrium equations) into the learning process of NN, it is showed that the NN can be trained very efficiently with a small set of labelled training data. Experiments with different settings of the NN model and the amount of labelled training data were conducted, and the results show that very high accuracy can be achieved in fulfilling the equilibrium equations as well as in predicting the displacements, e.g. in setting the overall displacement of 0.1, a root mean square error (RMSE) of 2.09 × 10−4 was achieved.

Keywords: deep learning, neural network, physics-informed machine learning, solid mechanics

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Authors: Lev Chernyshev, Ekaterina Lieshout, Natalia Kabaliuk

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Sit-skis enable individuals with limited lower limb or core movement to ski unassisted confidently. The rise in popularity of the Winter Paralympics has seen an influx of engineering innovation, especially for the Downhill and Super-Giant Slalom events, where the athletes achieve speeds as high as 160km/h. The growth in the sport has inspired recent research into sit-ski aerodynamics. Crosswinds are expected in mountain climates and, therefore, can greatly impact a skier's maneuverability and aerodynamics. This research investigates the impact of crosswinds on the drag force of a Paralympic sit-ski using Computational Fluid Dynamics (CFD). A Paralympic sit-ski with a model of a skier, a leg cover, a bucket seat, and a simplified suspension system was used for CFD analysis in ANSYS Fluent. The hybrid initialisation tool and the SST k–ω turbulence model were used with two tetrahedral mesh bodies of influence. The crosswinds (10, 30, and 50 km/h) acting perpendicular to the sit-ski's direction of travel were simulated, corresponding to the straight-line skiing speeds of 60, 80, and 100km/h. Following the initialisation, 150 iterations for both first and second order steady-state solvers were used, before switching to a transient solver with a computational time of 1.5s and a time step of 0.02s, to allow the solution to converge. CFD results were validated against wind tunnel data. The results suggested that for all crosswind and sit-ski speeds, on average, 64% of the total drag on the ski was due to the athlete's torso. The suspension was associated with the second largest overall sit-ski drag force contribution, averaging at 27%, followed by the leg cover at 10%. While the seat contributed a negligible 0.5% of the total drag force, averaging at 1.2N across the conditions studied. The effect of the crosswind increased the total drag force across all skiing speed studies, with the drag on the athlete's torso and suspension being the most sensitive to the changes in the crosswind magnitude. The effect of the crosswind on the ski drag reduced as the simulated skiing speed increased: for skiing at 60km/h, the drag force on the torso increased by 154% with the increase of the crosswind from 10km/h to 50km/h; whereas, at 100km/h the corresponding drag force increase was halved (75%). The analysis of the flow and pressure field characteristics for a sit-ski in crosswind conditions indicated the flow separation localisation and wake size correlated with the magnitude and directionality of the crosswind relative to straight-line skiing. The findings can inform aerodynamic improvements in sit-ski design and increase skiers' medalling chances.

Keywords: sit-ski, aerodynamics, CFD, crosswind effects

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Authors: Bonaventure Naab Dery, Abdul Muntaka Samad

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During the past two decades, huge population growth has been recorded in developing countries. Thisled to an increase in the demand for transport services for human and merchandises. The study sought to examine the effect of freight transport intensity on firm performance. Among others, this study sought to examine the link between freight transport intensity and firm performance; the link between operational capability and firm performance, and the mediating role of operational capability on the relationship between freight transport intensity and firm performance. The study used a descriptive research design and a quantitative research approach. Questionnaireswereusedfor the data collection through snowball sampling and purposive sampling. SPSS and Mplus are being used to analyze the data. It is anticipated that, when the data is analyzed, it would validate the hypotheses that have been proposed by the researchers. Base on the findings, relevant recommendations would be made for managerial implications and future studies.

Keywords: freight transport intensity, freight economy transport intensity, freight efficiency transport intensity, operational capability, firm performance

Procedia PDF Downloads 129

Authors: Jonathan Nash, Allen Hartt, Catherine Plante

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In many nations, community colleges, or similar institutions, play a crucial role in higher education. For example, in the United States more than half of all undergraduate students enroll in a community college at some point during their academic career. Similar statistics have been reported for Australia and Canada. Recognizing the important role these institutions play in educating future accountants, the American Accounting Association has called for research that contributes to a better understanding of these members of the academic community. Although previous literature has shown that community colleges and 4-year institutions differ on many levels, the extant literature has provided data on the characteristics of introductory accounting courses for four-year institutions but not for community colleges. We fill a void in the literature by providing data on the characteristics of introductory accounting courses offered by community colleges in the United States. Data are collected on several dimensions including: course size and staffing, pedagogical orientation, standardization of course elements, textbook selection, and use of technology-based course management tools. Many of these dimensions have been used in previous research examining four-year institutions thereby facilitating comparisons. The resulting data should be of interest to instructors, regulators and administrators, researchers, and the accounting profession. The data provide information on the introductory accounting courses completed by the average community college student which can help instructors identify areas where transfer students’ experiences might differ from their contemporaries at four-year colleges. Regulators and administrators may be interested in the differences between accounting courses offered by two- and four-year institutions when implementing standardized transfer programs. Researchers might use the data to motivate future research into whether differences between two- and four-year institutions affect outcomes like the probability of students choosing to major in accounting and their performance within the major. Accounting professionals may use our findings as a springboard for facilitating discussions related to the accounting labor supply.

Keywords: Accounting curricula, Community college, Descriptive study, Introductory accounting

Procedia PDF Downloads 89

Authors: Yuanxiaoyue Yang

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Emissions trading, or ‘cap-and-trade', has been long promoted by economists as a more cost-effective pollution control approach than traditional performance standard approaches. While there is a large body of empirical evidence for the overall effectiveness of emissions trading, relatively little attention has been paid to other unintended consequences brought by emissions trading. One important consequence is that cap-and-trade could introduce the risk of creating high-level emission concentrations in areas where emitting facilities purchase a large number of emission allowances, which may cause an unequal distribution of environmental benefits. This study will contribute to the current environmental policy literature by linking trading activity with environmental injustice concerns and empirically analyzing the causal relationship between trading activity and emissions reduction under a cap-and-trade program for the first time. To investigate the potential environmental injustice concern in cap-and-trade, this paper uses a differences-in-differences (DID) with instrumental variable method to identify the causal effect of allowance trading behaviors on emission reduction levels under the clean air interstate rule (CAIR), a cap-and-trade program targeting on the power sector in the eastern US. The major data source is the facility-year level emissions and allowance transaction data collected from US EPA air market databases. While polluting facilities from CAIR are the treatment group under our DID identification, we use non-CAIR facilities from the Acid Rain Program - another NOx control program without a trading scheme – as the control group. To isolate the causal effects of trading behaviors on emissions reduction, we also use eligibility for CAIR participation as the instrumental variable. The DID results indicate that the CAIR program was able to reduce NOx emissions from affected facilities by about 10% more than facilities who did not participate in the CAIR program. Therefore, CAIR achieves excellent overall performance in emissions reduction. The IV regression results also indicate that compared with non-CAIR facilities, purchasing emission permits still decreases a CAIR participating facility’s emissions level significantly. This result implies that even buyers under the cap-and-trade program have achieved a great amount of emissions reduction. Therefore, we conclude little evidence of environmental injustice from the CAIR program.

Keywords: air pollution, cap-and-trade, emissions trading, environmental justice

Procedia PDF Downloads 127

Authors: Ladaporn Pithuk

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This study aims to investigate the marketing mixed factors that affecting on expectations about commercial transactions through social networks. The research method will using quantitative research, data was collected by questionnaires to person have experience access to trading over the internet for 400 sample by purposive sampling method. Data was analyzed by descriptive statistic including percentage, mean, standard deviation and using quality function deployment for hypothesis testing. Finding the most significant interrelationship between marketing mixed factors and commercial transactions expectations through social networks are product and place the relationship of five ties product and place (location) is involved in almost all will make the site a model that meets the needs of the user visit. In terms of price, the promotion, privacy, personalization and providing a process technical. This will make operations more efficient, reduce confusion, duplication, delays in data transmission, including the creation of different elements in products and services.

Keywords: commercial transactions expectations, marketing mixed factors, social networks, consumer behavior

Procedia PDF Downloads 218

Authors: Bin Su

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The draft Auckland Unitary Plan outlines the future land used for new housing and businesses with Auckland population growth over the next thirty years. According to Auckland Unitary Plan, over the next 30 years, the population of Auckland is projected to increase by one million, and up to 70% of total new dwellings occur within the existing urban area. Intensification will not only increase the number of median or higher density houses such as terrace house, apartment building, etc. within the existing urban area but also change mean housing design data that can impact building thermal performance under the local climate. Based on mean energy consumption and building design data, and their relationships of a number of Auckland sample houses, this study is to estimate the future mean housing energy consumption associated with the change of mean housing design data and evaluate housing energy efficiency with the Auckland Unitary Plan.

Keywords: Auckland Unitary Plan, building thermal design, housing design, housing energy efficiency

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Authors: Elvira Wahyuni

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This study is a classroom action research. The general objective of this study was to find out students’ speaking ability through teaching English by using video and to find out the effectiveness of using video in teaching English to improve students’ speaking ability. The subjects of this study were 34 of the first-year students of SMAN 12 Pekanbaru who were learning English as a foreign language (EFL). Students were given pre-test before the treatment and post-test after the treatment. Quantitative data was collected by using speaking test requiring the students to respond to the recorded questions. Qualitative data was collected through observation sheets and field notes. The research finding reveals that there is a significant improvement of the students’ speaking ability through the use of video in speaking class. The qualitative data gave a description and additional information about the learning process done by the students. The research findings indicate that the use of video in teaching and learning is good in increasing learning outcome.

Keywords: English teaching, fun learning, speaking ability, video

Procedia PDF Downloads 238

Authors: E. Izsó, M. Bartalné-Berceli, Sz. Gergely, A. Salgó

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The aims of this investigation is to elaborate near-infrared methods for testing and recognition of chemical components and quality in “Pannon wheat” allied (i.e. true to variety or variety identified) milling fractions as well as to develop spectroscopic methods following the milling processes and evaluate the stability of the milling technology by different types of milling products and according to sampling times, respectively. This wheat categories produced under industrial conditions where samples were collected versus sampling time and maximum or minimum yields. The changes of the main chemical components (such as starch, protein, lipid) and physical properties of fractions (particle size) were analysed by dispersive spectrophotometers using visible (VIS) and near-infrared (NIR) regions of the electromagnetic radiation. Close correlation were obtained between the data of spectroscopic measurement techniques processed by various chemometric methods (e.g. principal component analysis (PCA), cluster analysis (CA) and operation condition of milling technology. Its obvious that NIR methods are able to detect the deviation of the yield parameters and differences of the sampling times by a wide variety of fractions, respectively. NIR technology can be used in the sensitive monitoring of milling technology.

Keywords: near infrared spectroscopy, wheat categories, milling process, monitoring

Procedia PDF Downloads 391

Authors: Gao ya

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This present study aims to find the relationship between self-efficacy and life satisfaction and the effects of self-efficacy on life satisfaction among Chinese people whose age is from 27-32, born between 1990 and 1995. People who were born between 1990 and 1995 are worthy to receive more attention now because the 90s was always received a lot of focus and labeled negatively as soon as they were born. And a large number of researches study people in individualism society more. So we chose the specific population whose age is from 27 to 32 live in a collectivist society. Demographic information was collected, including age, gender, education level, marital status, income level, number of children. We used the general self-efficacy scale(GSC) and the satisfaction with Life Scale(SLS) to collect data. A total of 350 questionnaires were distributed in and collected from mainland China, then 261 valid questionnaires were returned in the end, making a response rate of 74.57 percent. Some statistics techniques were used, like regression, correlation, ANOVA, T-test and general linear model, to measure variables. The findings were that self-efficacy positively related to life satisfaction. And self-efficacy influences life satisfaction significantly. At the same time, the relationship between demographic information and life satisfaction was analyzed.

Keywords: marital status, life satisfaction, number of children, self-efficacy, income level

Procedia PDF Downloads 108

Authors: Brittany Richardson, Ying Wang

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For physical therapy, exercise prescription, athlete training, and regular fitness training, it is crucial to perform health assessments or fitness assessments periodically. An accurate assessment is propitious for tracking recovery progress, preventing potential injury and making long-range training plans. Assessments include necessary measurements, height, weight, blood pressure, heart rate, body fat, etc. and advanced evaluation, muscle group strength, stability-mobility, and movement evaluation, etc. In the current standard assessment procedures, the accuracy of assessments, especially advanced evaluations, largely depends on the experience of physicians, coaches, and personal trainers. And it is challenging to track clients’ progress in the current assessment. Unlike the tradition assessment, in this paper, we present a deep learning based face recognition algorithm for accurate, comprehensive and trackable assessment. Based on the result from our assessment, physicians, coaches, and personal trainers are able to adjust the training targets and methods. The system categorizes the difficulty levels of the current activity for the client or user, furthermore make more comprehensive assessments based on tracking muscle group over time using a designed landmark detection method. The system also includes the function of grading and correcting the form of the clients during exercise. Experienced coaches and personal trainer can tell the clients' limit based on their facial expression and muscle group movements, even during the first several sessions. Similar to this, using a convolution neural network, the system is trained with people’s facial expression to differentiate challenge levels for clients. It uses landmark detection for subtle changes in muscle groups movements. It measures the proximal mobility of the hips and thoracic spine, the proximal stability of the scapulothoracic region and distal mobility of the glenohumeral joint, as well as distal mobility, and its effect on the kinetic chain. This system integrates data from other fitness assistant devices, including but not limited to Apple Watch, Fitbit, etc. for a improved training and testing performance. The system itself doesn’t require history data for an individual client, but the history data of a client can be used to create a more effective exercise plan. In order to validate the performance of the proposed work, an experimental design is presented. The results show that the proposed work contributes towards improving the quality of exercise plan, execution, progress tracking, and performance.

Keywords: exercise prescription, facial recognition, landmark detection, fitness assessments

Procedia PDF Downloads 116

Authors: Yumi Okano

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The low level of English proficiency among Japanese people has been a problem for a long time. Japanese non-native English language teachers, under social or ideological constraints, feel a gap between government policy and their language proficiency and cannot maintain high self-esteem. This paper focuses on current Japanese policies and the social context in which teachers are placed and examines the measures necessary for their positive identity formation from a macro-meso-micro perspective. Some suggestions for achieving this are: 1) Teachers should free themselves from the idea of native speakers and embrace local needs and accents, 2) Teachers should be involved in student discussions as facilitators and individuals so that they can be good role models for their students, and 3) Teachers should invest in their classrooms. 4) Guidelines and training should be provided to help teachers gain confidence. In addition to reducing the workload to make more time available, 5) expanding opportunities for investment outside the classroom into the real world is necessary.

Keywords: language teacher identity, native speakers, government policy, critical pedagogy, investment

Procedia PDF Downloads 86

Authors: Mohammed Auwal Ibrahim, Isa Yunusa, Nafisa Kabir, Shazali Ali Baba, Amina Muhammad Yushau, Suraj Suraj Ibrahim, Zaharaddeen Idris Bello, Suleiman Haruna Suleiman, Murtala Bindawa Isah

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Background: Inhibition of intestinal maltase and sucrase prevents postprandial blood glucose excursions which are beneficial in ameliorating diabetes-associated complications. Objective: In this study, the inhibitory effects of fruit extracts of Parinari macrophylla, Detarium microcarpum, Ziziphus spina-christi, Z. mairei and Parkia biglobosa were investigated against intestinal maltase and sucrase. Methods: Rats were given co-administration of the fruit extracts with maltose or sucrose and blood glucose levels were measured at 0, 30, 90 and 120 min. Results: The glucose-time curves indicated that all the fruits had the most potent inhibitory effects on both maltase and sucrase within the first 30 min. The computed Area Under the Curves (AUC0-120)for all the fruits indicated more potent inhibitory effects against intestinal maltase than sucrase.The ED50 range for the fruits extract against maltase and sucrase were 647.15-1118.35 and 942.44-1851.94 mg/kg bw respectively. Conclusion: The data suggests that the fruits could prevent postprandial hyperglycemia via inhibition of intestinal maltase and sucrase.

Keywords: diabetes mellitus, fruits, α-glucosidases, maltase, sucrase

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Authors: Asma Rebaya, Imen Amari, Kaouther Gasmi, Salem Hasnaoui

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Over these last years, the number of cores witnessed a spectacular increase in digital signal and general use processors. Concurrently, significant researches are done to get benefit from the high degree of parallelism. Indeed, these researches are focused to provide an efficient scheduling from hardware/software systems to multicores architecture. The scheduling process consists on statically choose one core to execute one task and to specify an execution order for the application tasks. In this paper, we describe an efficient scheduler that calculates the optimal number of cores required to schedule an application, gives a heuristic scheduling solution and evaluates its cost. Our proposal results are evaluated and compared with Preesm scheduler results and we prove that ours allows better scheduling in terms of latency, computation time and number of cores.

Keywords: computation time, hardware/software system, latency, optimization, multi-cores platform, scheduling

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Authors: Manasi Roy, Raju Mondal

Abstract:

During last two decades the synthesis and design of MOFs or novel coordination polymers (CPs) has flourished as an emerging area of research due to their role as functional materials. Accordingly, ten new cobalt-based MOFs have been synthesized using a simple bispyrazole ligand, 4,4′-methylene-bispyrazole (H2MBP), and isophthalic acid (H2IPA) and its four 5-substituted derivatives R-H2IPA (R = COOH, OH, tBu, NH2). The major aim of this study was to validate the mutual influence of temperature and substitutions on the final structural self-assembly. Five different isophthalic acid derivatives were used to study the influence of substituents while each reaction was carried out at two different temperatures to assess the temperature effect. A clear correlation was observed between the reaction temperature and the coordination number of the cobalt atoms which consequently changes the self assembly pattern. Another fact that the periodical change in coordination number did bring about some systematic changes in the structural network via secondary building unit selectivity. With the presence of a tunable cavity inside the network, and unsaturated metal centers, MOFs show highly encouraging photocatalytic degradation of toxic dye with a potential application in waste water purification. Another fascinating aspect of this work is the construction of magnetic coordination polymers with the occurrence of a not-so-common MCE behavior of cobalt-based MOF.

Keywords: MOFs, temperature effect, MCE, dye degradation

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Authors: Sloka Bhushan

Abstract:

Dark matter constitutes a majority of matter in the universe, yet very little is known about it due to its extreme lack of interaction with regular matter and the fundamental forces. Weakly Interacting Massive Particles, or WIMPs, have been contested to be one of the strongest candidates for dark matter due to their promising theoretical properties. However, various endeavors to detect these elusive particles have failed. This paper explores the various particles which may be WIMPs and the detection techniques being employed to detect WIMPs (such as underground detectors, LHC experiments, and so on). There is a special focus on the reasons for the lack of detection of WIMPs so far, and the possibility of limits in detection being a reason for the lack of physical evidence of the existence of WIMPs. This paper also explores possible inconsistencies within the WIMP particle theory as a reason for the lack of physical detection. There is a brief review on the possible solutions and alternatives to these inconsistencies. Additionally, this paper also reviews the supersymmetry theory and the possibility of the supersymmetric neutralino (A possible WIMP particle) being detectable. Lastly, a review on alternate candidates for dark matter such as axions and MACHOs has been conducted. The explorative study in this paper is conducted through a series of literature reviews.

Keywords: dark matter, particle detection, supersymmetry, weakly interacting massive particles

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Authors: Niyi Adegoke, Saanumi Jimmy Omolou

Abstract:

The prevalence rate of youth involving in cybercrime is alarming, which calls for concern among the government, parents, NGO and religious bodies, hence this paper aims at examining youth involvement in cybercrime in Nigeria. Achievement motivation theory was used to explain the activities of cyber-criminals in Nigerian society. A descriptive survey method was adopted for the study. The sample for the study was one hundred and fifty (150) respondents randomly selected from the population of the study. A questionnaire was used to gather information and data from the respondents. Data collected through the questionnaire were analyzed using percentage tool for the respondents’ bio-data while chi-square was employed to test the hypotheses. Findings from the study have revealed that parental negligence, unemployment, peer influence, and quest for materialism were responsible for cyber-crimes in Nigeria. The study concludes with the following recommendations among which are: creating employment opportunities for the youths and ensure good governance and accountability among other things will go a long way to solve the problem of cybercrime in our society.

Keywords: cybercrime, youth, Nigeria, unemployment, information communication technology

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Authors: Muge Unal, Cengiz Uslu, Mehmet Faruk Altunkasa

Abstract:

Walkability relates to the ability of the places to connect people with varied destinations within a reasonable amount of time and effort, and to offer visual interest in journeys throughout the network. So, the good quality of the physical environment and arrangement of walkway and sidewalk appear to be more crucial in influencing the pedestrian route choice. Also, proximity, connectivity, and accessibility are significant factor for walkability in terms of an equal opportunity for using public spaces. As a result, there are two important points for walkability. Firstly, the place should have a well-planned street network for accessible and secondly facilitate the pedestrian need for comfort. In this respect, this study aims to examine the both physical and bioclimatic comfort levels of the current condition of pedestrian route with reference to design criteria of a street to access the urban green spaces. These aspects have been identified as the main indicators for walkable streets such as continuity, materials, slope, bioclimatic condition, walkway width, greenery, and surface. Additionally, the aim was to identify the factors that need to be considered in future guidelines and policies for planning and design in urban spaces especially streets. Adana city was chosen as a study area. Adana is a province of Turkey located in south-central Anatolia. This study workflow can be summarized in four stages: (1) environmental and physical data were collected by referred to literature and used in a weighted criteria method to determine the importance level of these data , (2) environmental characteristics of pedestrian routes gained from survey studies are evaluated to hierarchies these criteria of the collected information, (3) and then each pedestrian routes will have a score that provides comfortable access to the park, (4) finally, the comfortable routes to park will be mapped using GIS. It is hoped that this study will provide an insight into future development planning and design to create a friendly and more comfort street environment for the users.

Keywords: comfort level, geographical information system (GIS), walkability, weighted criteria method

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Authors: Takashi Nakamura

Abstract:

In the Tokyo metropolitan area, traffic congestion and long commute times are caused by overconcentration in the central area. To resolve these problems, a core business city development policy was adopted in 1988. The core business cities, which include Yokohama, Chiba, Saitama, Tachikawa, and others, have designated business facilities accumulation districts where assistance measures are applied. Focusing on Yokohama city, this study investigates the trends in the number of offices, employees, and commuters at 2001 and 2012 Economic Census, as well as the average commute time in the Tokyo metropolitan area from 2005 to 2015 Metropolitan Transportation Census. Surveys were administered in 2001 and 2012 Economic Census to participants who worked in Yokohama, according to their distribution in the city's 1,757 subregions. Four main findings emerged: (1) The number of offices increased in Yokohama when the number of offices decreased in the Tokyo metropolitan area overall. Additionally, the number of employees at Yokohama increased. (2) The number of commuters to Tokyo's central area increased from Saitama prefecture, Tokyo Tama area, and Tokyo central area. However, it decreased from other areas. (3) The average commute time in the Tokyo metropolitan area was 67.7 minutes in 2015, a slight decrease from 2005 and 2010. (4) The number of employees at business facilities accumulation districts in Yokohama city increased greatly.

Keywords: core business city development policy, commute time, number of employees, Yokohama city, distribution of employees

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Authors: Wang Yanping Karen, Mohd Rafeah Siti, Park MI Kyoung

Abstract:

Formalin-fixed paraffin embedded (FFPE) tissue is important in the area of oncological diagnostics. This method of preserving tissues enabling them to be stored easily at ambient temperature for a long time. This decreases the risk of losing the DNA quantity and quality after extraction, reducing sample wastage, and making FFPE more cost effective. However, extracting DNA from FFPE tissue is a challenge as DNA purified is often highly cross-linked, fragmented, and degraded. In addition, this causes problems for many downstream processes. In this study, there will be a comparison of DNA extraction efficiency between One BioMed’s Xceler8 automated platform with commercial available extraction kits (Qiagen and Roche). The FFPE tissue slices were subjected to deparaffinization process, pretreatment and then DNA extraction using the three mentioned platforms. The DNA quantity were determined with real-time PCR (BioRad CFX ) and gel electrophoresis. The amount of DNA extracted with the One BioMed’s X8 platform was found to be comparable with the other two manual extraction kits.

Keywords: DNA extraction, FFPE tissue, qiagen, roche, one biomed X8

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