Search results for: hardy cross networks accuracy

Authors: I. Turk Cakir, A. Senol, A. T. Tasci, O. Cakir

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We study the anomalous WWγ and WWZ couplings by calculating total cross sections of the ep→νqγX and ep→νqZX processes at the LHeC with electron beam energy Ee=140 GeV and the proton beam energy Ep=7 TeV, and at the FCC-ep collider with the polarized electron beam energy Ee=80 GeV and the proton beam energy Ep=50 TeV. At the LHeC with electron beam polarization, we obtain the results for the difference of upper and lower bounds as (0.975, 0.118) and (0.285, 0.009) for the anomalous (Δκγ,λγ) and (Δκz,λz) couplings, respectively. As for FCC-ep collider, these bounds are obtained as (1.101,0.065) and (0.320,0.002) at an integrated luminosity of Lint=100 fb-1.

Keywords: anomalous couplings, future circular collider, large hadron electron collider, W-boson and Z-boson

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Authors: Huda Al Shuaily, Karen Renaud

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Databases comprise the foundation of most software systems. System developers inevitably write code to query these databases. The de facto language for querying is SQL and this, consequently, is the default language taught by higher education institutions. There is evidence that learners find it hard to master SQL, harder than mastering other programming languages such as Java. Educators do not agree about explanations for this seeming anomaly. Further investigation may well reveal the reasons. In this paper, we report on our investigations into how novices learn SQL, the actual problems they experience when writing SQL, as well as the differences between expert and novice SQL query writers. We conclude by presenting a model of SQL learning that should inform the instructional material design process better to support the SQL learning process.

Keywords: pattern, SQL, learning, model

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Authors: Matthew J. Emes, Azadeh Jafari, Maziar Arjomandi

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Velocity fluctuations of shear-generated turbulence are largest in the atmospheric surface layer (ASL) of nominal 100 m depth, which can lead to dynamic effects such as galloping and flutter on small physical structures on the ground when the turbulence length scales and characteristic length of the physical structure are the same order of magnitude. Turbulence length scales are a measure of the average sizes of the energy-containing eddies that are widely estimated using two-point cross-correlation analysis to convert the temporal lag to a separation distance using Taylor’s hypothesis that the convection velocity is equal to the mean velocity at the corresponding height. Profiles of turbulence length scales in the neutrally-stratified ASL, as predicted by Monin-Obukhov similarity theory in Engineering Sciences Data Unit (ESDU) 85020 for single-point data and ESDU 86010 for two-point correlations, are largely dependent on the aerodynamic roughness length. Field measurements have shown that longitudinal turbulence length scales show significant regional variation, whereas length scales of the vertical component show consistent Obukhov scaling from site to site because of the absence of low-frequency components. Hence, the objective of this experimental study is to compare the similarity theory relationships between the turbulence length scales and aerodynamic roughness length with those calculated using the autocorrelations and cross-correlations of field measurement velocity data at two sites: the Surface Layer Turbulence and Environmental Science Test (SLTEST) facility in a desert ASL in Dugway, Utah, USA and the Commonwealth Scientific and Industrial Research Organisation (CSIRO) wind tower in a rural ASL in Jemalong, NSW, Australia. The results indicate that the longitudinal turbulence length scales increase with increasing aerodynamic roughness length, as opposed to the relationships derived by similarity theory correlations in ESDU models. However, the ratio of the turbulence length scales in the lateral and vertical directions to the longitudinal length scales is relatively independent of surface roughness, showing consistent inner-scaling between the two sites and the ESDU correlations. Further, the diurnal variation of wind velocity due to changes in atmospheric stability conditions has a significant effect on the turbulence structure of the energy-containing eddies in the lower ASL.

Keywords: aerodynamic roughness length, atmospheric surface layer, similarity theory, turbulence length scales

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Authors: Pan Hongxia, Wang Zhenhua

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In this paper, the EMD decomposition in the process of endpoint effect adopted data based on AR model to predict the continuation and window function method of combining the two effective inhibition. Proven by simulation of the simulation signal obtained the ideal effect, then, apply this method to the gearbox test data is also achieved good effect in the process, for the analysis of the subsequent data processing to improve the calculation accuracy. In the end, under various working conditions for the gearbox fault diagnosis laid a good foundation.

Keywords: gearbox, fault diagnosis, ar model, end effect

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Authors: Hassan M. Al-Ahmadi, Hamad Bader Almobayedh

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Planning for urban transportation is essential for developing effective and sustainable transportation networks that meet the needs of various communities. Advanced modeling software is required for effective transportation planning, management, and optimization. This paper compares PTV VISUM, Aimsun, TransCAD, and Emme, four industry-leading software tools for transportation planning and modeling. Each software has strengths and limitations, and the project's needs, financial constraints, and level of technical expertise influence the choice of software. Transportation experts can design and improve urban transportation systems that are effective, sustainable, and meet the changing needs of their communities by utilizing these software tools.

Keywords: PTV VISUM, Aimsun, TransCAD, transportation modeling software

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Authors: V. Keim, J. Spachtholz, J. Hammer

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The importance of fibre reinforced plastics continually increases due to the excellent mechanical properties, low material and manufacturing costs combined with significant weight reduction. Today, components are usually designed and calculated numerically by using finite element methods (FEM) to avoid expensive laboratory tests. These programs are based on material models including material specific deformation characteristics. In this research project, material models for short glass fibre reinforced plastics are presented to simulate the visco-elasto-plastic deformation behaviour. Prior to modelling specimens of the material EMS Grivory HTV-5H1, consisting of a Polyphthalamide matrix reinforced by 50wt.-% of short glass fibres, are characterized experimentally in terms of the highly time dependent deformation behaviour of the matrix material. To minimize the experimental effort, the cyclic deformation behaviour under tensile and compressive loading (R = −1) is characterized by isothermal complex low cycle fatigue (CLCF) tests. Combining cycles under two strain amplitudes and strain rates within three orders of magnitude and relaxation intervals into one experiment the visco-elastic deformation is characterized. To identify visco-plastic deformation monotonous tensile tests either displacement controlled or strain controlled (CERT) are compared. All relevant modelling parameters for this complex superposition of simultaneously varying mechanical loadings are quantified by these experiments. Subsequently, two different material models are compared with respect to their accuracy describing the visco-elasto-plastic deformation behaviour. First, based on Chaboche an extended 12 parameter model (EVP-KV2) is used to model cyclic visco-elasto-plasticity at two time scales. The parameters of the model including a total separation of elastic and plastic deformation are obtained by computational optimization using an evolutionary algorithm based on a fitness function called genetic algorithm. Second, the 12 parameter visco-elasto-plastic material model by Launay is used. In detail, the model contains a different type of a flow function based on the definition of the visco-plastic deformation as a part of the overall deformation. The accuracy of the models is verified by corresponding experimental LCF testing.

Keywords: complex low cycle fatigue, material modelling, short glass fibre reinforced polyphthalamides, visco-elasto-plastic deformation

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Authors: Sedat Bilgili, Alper K. Demir

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The current Internet has become the dominant use with continuing growth in the home, medical, health, smart cities and industrial automation applications. Internet of Things (IoT) is an emerging technology to enable such applications in our lives. Moreover, Named Data Networking (NDN) is also emerging as a Future Internet architecture where it fits the communication needs of IoT networks. The aim of this study is to provide an NDN protocol stack implementation running on the Contiki operating system (OS). Contiki OS is an OS that is developed for constrained IoT devices. In this study, an NDN protocol stack that can work on top of IEEE 802.15.4 link and physical layers have been developed and presented.

Keywords: internet of things (IoT), named-data, named data networking (NDN), operating system

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Authors: Samia Dardouri, Ridha Bouallegue

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Scheduling is the process of dynamically allocating physical resources to User Equipment (UE) based on scheduling algorithms implemented at the LTE base station. Various algorithms have been proposed by network researchers as the implementation of scheduling algorithm which represents an open issue in Long Term Evolution (LTE) standard. This paper makes an attempt to study and compare the performance of PF, MLWDF and EXP/PF scheduling algorithms. The evaluation is considered for a single cell with interference scenario for different flows such as Best effort, Video and VoIP in a pedestrian and vehicular environment using the LTE-Sim network simulator. The comparative study is conducted in terms of system throughput, fairness index, delay, packet loss ratio (PLR) and total cell spectral efficiency.

Keywords: LTE, multimedia flows, scheduling algorithms, mobile computing

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Authors: Q. Raza

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Getting old is inevitable, tasks which were once simple are now a daily struggle. This paper is a study of how older users interact with web application based upon a series of experiments. The experiments conducted involved 12 participants and the experiments were split into two parts. The first set gives the users a feel of current social networks and the second set take into considerations from the participants and the results of the two are compared. This paper goes in detail on the psychological aspects such as social exclusion, Metacognition memory and Therapeutic memories and how this relates to users becoming isolated from society, social networking can be the roof on a foundation of successful computer interaction. The purpose of this paper is to carry out a study and to propose new ideas to help users to be able to use social networking sites easily and efficiently.

Keywords: cognitive psychology, special memory, social networking and human computer interaction

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Authors: L. Belounar, K. Gerraiche, C. Rebiai, S. Benmebarek

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This paper presents the development of a new three dimensional brick finite element by the use of the strain based approach for the linear analysis of plate bending behavior. The developed element has the three essential external degrees of freedom (U, V and W) at each of the eight corner nodes. The displacements field of the developed element is based on assumed functions for the various strains satisfying the compatibility and the equilibrium equations. The performance of this element is evaluated on several problems related to thick and thin plate bending in linear analysis. The obtained results show the good performances and accuracy of the present element.

Keywords: brick element, strain approach, plate bending, civil engineering

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Authors: Ole-Christian Galbo Engstrøm, Erik Schou Dreier, Birthe Møller Jespersen, Kim Steenstrup Pedersen

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Grain quality analysis is a multi-parameterized problem that includes a variety of qualitative and quantitative parameters such as grain type classification, damage type classification, and nutrient regression. Currently, these parameters require human inspection, a multitude of instruments employing a variety of sensor technologies, and predictive model types or destructive and slow chemical analysis. This paper investigates the feasibility of applying near-infrared hyperspectral imaging (NIR-HSI) to grain quality analysis. For this study two datasets of NIR hyperspectral images in the wavelength range of 900 nm - 1700 nm have been used. Both datasets contain images of sparsely and densely packed grain kernels. The first dataset contains ~87,000 image crops of bulk wheat samples from 63 harvests where protein value has been determined by the FOSS Infratec NOVA which is the golden industry standard for protein content estimation in bulk samples of cereal grain. The second dataset consists of ~28,000 image crops of bulk grain kernels from seven different wheat varieties and a single rye variety. In the first dataset, protein regression analysis is the problem to solve while variety classification analysis is the problem to solve in the second dataset. Deep convolutional neural networks (CNNs) have the potential to utilize spatio-spectral correlations within a hyperspectral image to simultaneously estimate the qualitative and quantitative parameters. CNNs can autonomously derive meaningful representations of the input data reducing the need for advanced preprocessing techniques required for classical chemometric model types such as artificial neural networks (ANNs) and partial least-squares regression (PLS-R). A comparison between different CNN architectures utilizing 2D and 3D convolution is conducted. These results are compared to the performance of ANNs and PLS-R. Additionally, a variety of preprocessing techniques from image analysis and chemometrics are tested. These include centering, scaling, standard normal variate (SNV), Savitzky-Golay (SG) filtering, and detrending. The results indicate that the combination of NIR-HSI and CNNs has the potential to be the foundation for an automatic system unifying qualitative and quantitative grain quality analysis within a single sensor technology and predictive model type.

Keywords: deep learning, grain analysis, hyperspectral imaging, preprocessing techniques

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Authors: Xuan Li, Weian Huang, Jinsheng Sun, Fuhao Zhao, Zhiyuan Wang, Jintang Wang

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Natural gas hydrates (NGHs) as promising alternative energy sources have gained increasing attention. Hydrate-bearing formation in marine areas is highly unconsolidated formation and is fragile, which is composed of weakly cemented sand-clay and silty sediments. During the drilling process, the invasion of drilling fluid can easily lead to excessive water content in the formation. It will change the soil liquid plastic limit index, which significantly affects the formation quality, leading to wellbore instability due to the metastable character of hydrate-bearing sediments. Therefore, controlling the filtrate loss into the formation in the drilling process has to be highly regarded for protecting the stability of the wellbore. In this study, the temperature-sensitive nanogel of P(NIPAM-co-AMPS-co-tBA) was prepared by soap-free emulsion polymerization, and the temperature-sensitive behavior was employed to achieve self-adaptive plugging in hydrate sediments. First, the effects of additional amounts of AMPS, tBA, and cross-linker MBA on the microgel synthesis process and temperature-sensitive behaviors were investigated. Results showed that, as a reactive emulsifier, AMPS can not only participate in the polymerization reaction but also act as an emulsifier to stabilize micelles and enhance the stability of nanoparticles. The volume phase transition temperature (VPTT) of nanogels gradually decreased with the increase of the contents of hydrophobic monomer tBA. An increase in the content of the cross-linking agent MBA can lead to a rise in the coagulum content and instability of the emulsion. The plugging performance of nanogel was evaluated in a core sample with a pore size distribution range of 100-1000nm. The temperature-sensitive nanogel can effectively improve the microfiltration performance of drilling fluid. Since a combination of a series of nanogels could have a wide particle size distribution at any temperature, around 200nm to 800nm, the self-adaptive plugging capacity of nanogels for the hydrate sediments was revealed. Thermosensitive nanogel is a potential intelligent plugging material for drilling operations in natural gas hydrate-bearing sediments.

Keywords: temperature-sensitive nanogel, NIPAM, self-adaptive plugging performance, drilling operations, hydrate-bearing sediments

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Authors: Le Zhao, Alain Nogaret

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We have built universal Central Pattern Generator (CPG) hardware by interconnecting Hodgkin-Huxley neurons with reciprocally inhibitory synapses. We investigate the dynamics of neuron oscillations as a function of the time delay between current steps applied to individual neurons. We demonstrate stimulus dependent switching between spiking polyrhythms and map the phase portraits of the neuron oscillations to reveal the basins of attraction of the system. We experimentally study the dependence of the attraction basins on the network parameters: the neuron response time and the strength of inhibitory connections.

Keywords: central pattern generator, winnerless competition principle, artificial neural networks, synapses

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Authors: Rohit Vashistha, Amit Kumar Gupta, G. P. Ravishankar, Mahesh P. Padwale

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Accurate thrust measurement is required for aircraft during takeoff and after ski-jump. In a developmental aircraft, takeoff from ship is extremely critical and thrust produced by the engine should be known to the pilot before takeoff so that if thrust produced is not sufficient then take-off can be aborted and accident can be avoided. After ski-jump, thrust produced by engine is required because the horizontal speed of aircraft is less than the normal takeoff speed. Engine should be able to produce enough thrust to provide nominal horizontal takeoff speed to the airframe within prescribed time limit. The contemporary low bypass gas turbine engines generally have three mounts where the two side mounts transfer the engine thrust to the airframe. The third mount only takes the weight component. It does not take any thrust component. In the present method of thrust estimation, the strain gauging of the two side mounts is carried out. The strain produced at various power settings is used to estimate the thrust produced by the engine. The quarter Wheatstone bridge is used to acquire the strain data. The engine mount assembly is subjected to Universal Test Machine for determination of equivalent elasticity of assembly. This elasticity value is used in the analytical approach for estimation of engine thrust. The estimated thrust is compared with the test bed load cell thrust data. The experimental strain data is also compared with strain data obtained from FEM analysis. Experimental setup: The strain gauge is mounted on the tapered portion of the engine mount sleeve. Two strain gauges are mounted on diametrically opposite locations. Both of the strain gauges on the sleeve were in the horizontal plane. In this way, these strain gauges were not taking any strain due to the weight of the engine (except negligible strain due to material's poison's ratio) or the hoop's stress. Only the third mount strain gauge will show strain when engine is not running i.e. strain due to weight of engine. When engine starts running, all the load will be taken by the side mounts. The strain gauge on the forward side of the sleeve was showing a compressive strain and the strain gauge on the rear side of the sleeve shows a tensile strain. Results and conclusion: the analytical calculation shows that the hoop stresses dominate the bending stress. The estimated thrust by strain gauge shows good accuracy at higher power setting as compared to lower power setting. The accuracy of estimated thrust at max power setting is 99.7% whereas at lower power setting is 78%.

Keywords: engine mounts, finite elements analysis, strain gauge, stress

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Authors: Graziele Zwielewski, Suzana R. Tolfo

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The globalization of markets, the need to develop competitive advantages and core competencies, among other things, lead organizations to increasingly cross borders to operate in other countries. The expatriation of professionals who go to work in another country besides their own becomes increasingly common. In order to generate data about this issue, research was conducted concerning the perception of expatriate employees concerning expatriation success. The research method used was case study through a qualitative approach. This research was done through interviews with five India expatriates and five China expatriates, interview with expatriate department heads and analysis of company documents. It was found that there are differences between the organizational perception and perception of expatriates of what constitutes mission success. The paper also provides suggestions for further research and suggestions for future expatriates.

Keywords: expatriation success, international assignments, success factors, success for expatriates

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Authors: Jaroslav Masek, Juraj Camaj, Eva Nedeliakova

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The paper is focused on the operational model for transport the single wagon consignments on railway network by using two different models of train formation. The paper gives an overview of possibilities of improving the quality of transport services. Paper deals with two models used in problematic of train formatting - time continuously and time discrete. By applying these models in practice, the transport company can guarantee a higher quality of service and expect increasing of transport performance. The models are also applicable into others transport networks. The models supplement a theoretical problem of train formation by new ways of looking to affecting the organization of wagon flows.

Keywords: train formation, wagon flows, marshalling yard, railway technology

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Authors: Kais Manai

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The main part of this work focuses on the study of pion/muon separation at low energy using a nuclear Emulsion Cloud Chamber (ECC) made of lead and nuclear emulsion films. The work consists of two parts: particle reconstruction algorithm and a Neural Network that assigns to each reconstructed particle the probability to be a muon or a pion. The pion/muon separation algorithm has been optimized by using a detailed Monte Carlo simulation of the ECC and tested on real data. The algorithm allows to achieve a 60% muon identification efficiency with a pion misidentification smaller than 3%.

Keywords: nuclear emulsion, particle identification, tracking, neural network

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Authors: C. Fernandez-Plaza, I. Abad, E. Diaz, I. Diaz

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Births occurring before the 37th week of gestation are considered preterm births. A threat of preterm is defined as the beginning of regular uterine contractions, dilation and cervical effacement between 23 and 36 gestation weeks. To author's best knowledge, the factors that determine the beginning of the birth are not completely defined yet. In particular, the incidence of sleep habits on preterm births is weekly studied. The aim of this study is to develop a model to predict the factors affecting premature delivery on pregnancy, based on the above potential risk factors, including those derived from sleep habits and light exposure at night (introduced as 12 variables obtained by a telephone survey using two questionnaires previously used by other authors). Thus, three groups of variables were included in the study (maternal, fetal and sleep habits). The study was approved by Research Ethics Committee of the Principado of Asturias (Spain). An observational, retrospective and descriptive study was performed with 481 births between January 1, 2015 and May 10, 2016 in the University Central Hospital of Asturias (Spain). A statistical analysis using SPSS was carried out to compare qualitative and quantitative variables between preterm and term delivery. Chi-square test qualitative variable and t-test for quantitative variables were applied. Statistically significant differences (p < 0.05) between preterm vs. term births were found for primiparity, multi-parity, kind of conception, place of residence or premature rupture of membranes and interruption during nights. In addition to the statistical analysis, machine learning methods to look for a prediction model were tested. In particular, tree based models were applied as the trade-off between performance and interpretability is especially suitable for this study. C5.0, recursive partitioning, random forest and tree bag models were analysed using caret R-package. Cross validation with 10-folds and parameter tuning to optimize the methods were applied. In addition, different noise reduction methods were applied to the initial data using NoiseFiltersR package. The best performance was obtained by C5.0 method with Accuracy 0.91, Sensitivity 0.93, Specificity 0.89 and Precision 0.91. Some well known preterm birth factors were identified: Cervix Dilation, maternal BMI, Premature rupture of membranes or nuchal translucency analysis in the first trimester. The model also identifies other new factors related to sleep habits such as light through window, bedtime on working days, usage of electronic devices before sleeping from Mondays to Fridays or change of sleeping habits reflected in the number of hours, in the depth of sleep or in the lighting of the room. IF dilation < = 2.95 AND usage of electronic devices before sleeping from Mondays to Friday = YES and change of sleeping habits = YES, then preterm is one of the predicting rules obtained by C5.0. In this work a model for predicting preterm births is developed. It is based on machine learning together with noise reduction techniques. The method maximizing the performance is the one selected. This model shows the influence of variables related to sleep habits in preterm prediction.

Keywords: machine learning, noise reduction, preterm birth, sleep habit

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Authors: Nur Hidayah Iwani Mohd Kamal

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The higher education institutions in Malaysia is challenged with a more socially and culturally diverse student population than ever before, especially with the increasing number of international students studying in Malaysia in the recent years. First year university is a critical time in students’ lives. Students are not only developing intelectually, they are also establishing and maintaining personal relationships, developing an identity, deciding about career and lifestyle, maintaining personal health and wellness, and developing an integrated philosohy of life. The higher education institutions work as a diverse community of learners to provide a supportive environment for these first year students in assisting them in their transition from high school to university. Although many universities are taking steps to improve the first year experience for their new local and international students, efforts must be taken to ensure organized and coordinated manner in order for the initiatives to be successful. The objectives of the study are to examine the international students’ perceptions and interpretation of their first year experiences in shaping and determining their attitudes toward study and the quality of their entire undergraduate academic career; and identify an appropriate mechanism to encounter the international students’ adjustment in the new environment in order to facilitate cross-functional communication and create a coherent and meaningful first year experience. A key construct in this study is that if universities wish to recruiting and retaining international students, it is their ethical responsibility to determine how they can best meet their needs at the academic and social level, create a supportive ‘learning community’ as a foundation of their educational experience, hence facilitate cross-cultural communication and create a coherent and meaningful first year experience. This study is simultaneously frames in relation to focus on the factors that influence a successful and satisfying transition to university life by the first year international students. The study employs a mixed-method data collection involving semi-structured interviews, questionnaire, classroom observation and document analysis. This study provides valuable insight into the struggles that many international students face as they attempt to make the adjustment not only to a new educational system but factors such as psychosocial and cultural problems. It would discuss some of the factors that impact the international students during their first year in university in their quest to be academically successful. It concludes with some recommendations on how Malaysian universities provide these students with a good first year experience based on some the best practices of universities around the world.

Keywords: first year experience, Malaysian universities, international students, education

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Authors: Mohammad Ghahramani, Fahimeh Saei Manesh

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Winning a soccer game is based on thorough and deep analysis of the ongoing match. On the other hand, giant gambling companies are in vital need of such analysis to reduce their loss against their customers. In this research work, we perform deep, real-time analysis on every soccer match around the world that distinguishes our work from others by focusing on particular seasons, teams and partial analytics. Our contributions are presented in the platform called “Analyst Masters.” First, we introduce various sources of information available for soccer analysis for teams around the world that helped us record live statistical data and information from more than 50,000 soccer matches a year. Our second and main contribution is to introduce our proposed in-play performance evaluation. The third contribution is developing new features from stable soccer matches. The statistics of soccer matches and their odds before and in-play are considered in the image format versus time including the halftime. Local Binary patterns, (LBP) is then employed to extract features from the image. Our analyses reveal incredibly interesting features and rules if a soccer match has reached enough stability. For example, our “8-minute rule” implies if 'Team A' scores a goal and can maintain the result for at least 8 minutes then the match would end in their favor in a stable match. We could also make accurate predictions before the match of scoring less/more than 2.5 goals. We benefit from the Gradient Boosting Trees, GBT, to extract highly related features. Once the features are selected from this pool of data, the Decision trees decide if the match is stable. A stable match is then passed to a post-processing stage to check its properties such as betters’ and punters’ behavior and its statistical data to issue the prediction. The proposed method was trained using 140,000 soccer matches and tested on more than 100,000 samples achieving 98% accuracy to select stable matches. Our database from 240,000 matches shows that one can get over 20% betting profit per month using Analyst Masters. Such consistent profit outperforms human experts and shows the inefficiency of the betting market. Top soccer tipsters achieve 50% accuracy and 8% monthly profit in average only on regional matches. Both our collected database of more than 240,000 soccer matches from 2012 and our algorithm would greatly benefit coaches and punters to get accurate analysis.

Keywords: soccer, analytics, machine learning, database

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Authors: H. Arzani, Z. Arzani

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Every piece of rangeland has a different set of physical and biological characteristics. This requires the manager to synthesis various information for regular monitoring to define changes trend to get wright decision for sustainable management. So range managers need to use computerized technologies to monitor rangeland, and select. The best management practices. There are four examples of computerized technologies that can benefit sustainable management: (1) Photographic method for cover measurement: The method was tested in different vegetation communities in semi humid and arid regions. Interpretation of pictures of quadrats was done using Arc View software. Data analysis was done by SPSS software using paired t test. Based on the results, generally, photographic method can be used to measure ground cover in most vegetation communities. (2) GPS application for corresponding ground samples and satellite pixels: In two provinces of Tehran and Markazi, six reference points were selected and in each point, eight GPS models were tested. Significant relation among GPS model, time and location with accuracy of estimated coordinates was found. After selection of suitable method, in Markazi province coordinates of plots along four transects in each 6 sites of rangelands was recorded. The best time of GPS application was in the morning hours, Etrex Vista had less error than other models, and a significant relation among GPS model, time and location with accuracy of estimated coordinates was found. (3) Application of satellite data for rangeland monitoring: Focusing on the long term variation of vegetation parameters such as vegetation cover and production is essential. Our study in grass and shrub lands showed that there were significant correlations between quantitative vegetation characteristics and satellite data. So it is possible to monitor rangeland vegetation using digital data for sustainable utilization. (4) Rangeland suitability classification with GIS: Range suitability assessment can facilitate sustainable management planning. Three sub-models of sensitivity to erosion, water suitability and forage production out puts were entered to final range suitability classification model. GIS was facilitate classification of range suitability and produced suitability maps for sheep grazing. Generally digital computers assist range managers to interpret, modify, calibrate or integrating information for correct management.

Keywords: computer, GPS, GIS, remote sensing, photographic method, monitoring, rangeland ecosystem, management, suitability, sheep grazing

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Authors: Somveer Singh, Vineet Kumar Singh

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We present a new model based on viscoelasticity for the Non-Newtonian fluids.We use a matrix formulated algorithm to approximate solutions of a class of partial integro-differential equations with the given initial and boundary conditions. Some numerical results are presented to simplify application of operational matrix formulation and reduce the computational cost. Convergence analysis, error estimation and numerical stability of the method are also investigated. Finally, some test examples are given to demonstrate accuracy and efficiency of the proposed method.

Keywords: Legendre Wavelets, operational matrices, partial integro-differential equation, viscoelasticity

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Authors: N. P. D. Tran, H. Q. D. Nguyen, M. C. Yang

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In this study, contact lenses were prepared through the polymerization of tris-(trimethyl-silyl-propyl-methacrylate) (TRIS), N,N-dimethylacrylamide (DMA), N-vinylpyrrolidone (NVP), and cross-linked with ethylene glycol dimethylacrylate (EGDMA). The equilibrium water content (EWC), oxygen permeability (Dk), light transmittance, and in vitro cytotoxicity of TRIS-DMA-NVP with various ratios were measured. The results showed that the EWC increased while the Dk decreased with the increase of NVP content. For the sample with 25 wt% NVP, the EWC attained 53% whereas the Dk decreased to 46 barrers. All these lenses exhibited light transmittance over than 95%. In addition, all these lenses exhibited no inhibition to the growth of L292 fibroblasts. Thus, this study showed that TRIS-DMA-NVP can be applicable for making contact lens.

Keywords: DMA, TRIS, NVP, silicone hydrogel, contact lens

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Authors: Adaku Thelma Olatise

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Mental health disparities among women from diverse ethnic, cultural, and religious backgrounds remain a pressing concern, particularly as current psychotherapeutic models often fail to address the unique challenges these groups face. This is of particular concern since epidemiological studies across various countries and cultures consistently demonstrate higher prevalence rates of common mental disorders amongst these groups of women because of a lack of access to culturally oriented psychotherapeutic services. This literature review aims to examine how CCAs in psychotherapy can address the specific ethnic, cultural, and religious challenges women encounter in accessing mental health care. A search of relevant articles was conducted through PsycARTICLES and PubMed databases, using terms such as ‘mental health’, ‘women’, ‘culture’, and ‘ethnic minorities’. Supplementary searches on Google Scholar were also performed to capture literature not covered by traditional databases. While the importance of cross-cultural approaches in psychotherapy has become more apparent because people from diverse ethnic backgrounds inevitably perceive the world through different lenses, influencing their interpretations of human behavior and norms, there is a notable gap in the literature in understanding the influences of using of CCAs in psychotherapy amongst women of an ethnic minority. This gap not only reflects a poor understanding of the complex stressors faced by these women—such as familial, communal, and societal expectations—but also highlights the lack of support and culturally adapted interventions available to them. Even though scholars have posited that aligning treatment approaches with patients' cultural backgrounds is important to enhance therapeutic effectiveness, and the acknowledgment of culture is crucial in psychotherapy theory and practice. As well as the increasing global focus on psychotherapy applications that integrate non-Western practices, such as spiritual healing and community-based interventions, the adaptation of these approaches in mainstream mental health care has remained limited. This review found that the expectations and experiences of ethnic minority women were heavily influenced by family and community pressures. However, there were limited evidence-based, culturally oriented psychotherapeutic interventions tailored to ethnic minority women. This gap extends to inadequate representation of minority groups in clinical research, as well as a lack of culturally validated mental health outcome measures. Furthermore, studies have shown that psychotherapeutic models have largely been Western-oriented and Euro-centric because of socially constructed hierarchies. The origin of psychology from the Western world has predominantly reflected Western cultural traditions, shaped by historical, linguistic, and sociopolitical influences. These factors have led to a lack of recognition of therapeutic approaches from minority ethnic groups and the biases that emanate from hegemonic cultural beliefs and power dynamics influence the decisions about which psychotherapeutic modalities to integrate and practice. Therefore, this plethora of factors adds to the challenges women from ethnically and culturally diverse backgrounds face in accessing mental health services at the individual, familial, community, and societal levels. In conclusion, a cross-cultural approach is urgently needed within psychotherapy to address these challenges, ensuring that treatment frameworks are both culturally sensitive and gender responsive. Only by considering the lived experiences of minority women, particularly in relation to their cultural and religious contexts, can mental health services provide the appropriate care necessary to support their well-being.

Keywords: mental health, women, culture, ethnicity

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Authors: H. A. Alzomor, B. K. Ouda, A. M. Eldeib

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Successful regional anesthesia depends upon precise location of the peripheral nerve or nerve plexus. Locating peripheral nerves is preferred to be done using nerve stimulation. In order to generate a nerve impulse by electrical means, a minimum threshold stimulus of current “rheobase” must be applied to the nerve. The technique depends on stimulating muscular twitching at a close distance to the nerve without actually touching it. Success rate of this operation depends on the accuracy of current intensity pulses used for stimulation. In this paper, we will discuss a circuit and algorithm for closed loop control for the current, theoretical analysis and test results and compare them with previous techniques.

Keywords: Close Loop Control (CLC), constant current, nerve locator, rheobase

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Authors: C. Jameke

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During the cognitivist era in cognitive psychology, a theory of internal rules and symbolic representations was posited as an account of human cognition. This type of cognitive architecture had its heyday during the 1970s and 80s, but it has now been largely abandoned in favour of subsymbolic architectures (e.g. connectionism), non-representational frameworks (e.g. dynamical systems theory), and statistical approaches such as Bayesian theory. In this presentation I describe this changing landscape of research, and comment on the increasing influence of neuroscience on cognitive psychology. I then briefly review a few recent developments in connectionism, and neurocomputation relevant to cognitive psychology, and critically discuss the assumption made by some researchers in these frameworks that higher-level aspects of human cognition are simply emergent properties of massively large distributed neural networks

Keywords: connectionism, emergentism, postocgnitivist, representations, subsymbolic archiitecture

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Authors: Hamed Ahari, Behrouz Akbari Adreghani, Vadood Razavilar, Amirali Anvar, Sima Moradi, Hourieh Shalchi

Abstract:

Considering the ever increasing population and industrialization of the developmental trend of humankind's life, we are no longer able to detect the toxins produced in food products using the traditional techniques. This is due to the fact that the isolation time for food products is not cost-effective and even in most of the cases, the precision in the practical techniques like the bacterial cultivation and other techniques suffer from operator errors or the errors of the mixtures used. Hence with the advent of nanotechnology, the design of selective and smart sensors is one of the greatest industrial revelations of the quality control of food products that in few minutes time, and with a very high precision can identify the volume and toxicity of the bacteria. Methods and Materials: In this technique, based on the bacterial antibody connection to nanoparticle, a sensor was used. In this part of the research, as the basis for absorption for the recognition of bacterial toxin, medium sized silica nanoparticles of 10 nanometer in form of solid powder were utilized with Notrino brand. Then the suspension produced from agent-linked nanosilica which was connected to bacterial antibody was positioned near the samples of distilled water, which were contaminated with Staphylococcus aureus bacterial toxin with the density of 10-3, so that in case any toxin exists in the sample, a connection between toxin antigen and antibody would be formed. Finally, the light absorption related to the connection of antigen to the particle attached antibody was measured using spectrophotometry. The gene of 23S rRNA that is conserved in all Staphylococcus spp., also used as control. The accuracy of the test was monitored by using serial dilution (l0-6) of overnight cell culture of Staphylococcus spp., bacteria (OD600: 0.02 = 107 cell). It showed that the sensitivity of PCR is 10 bacteria per ml of cells within few hours. Result: The results indicate that the sensor detects up to 10-4 density. Additionally, the sensitivity of the sensors was examined after 60 days, the sensor by the 56 days had confirmatory results and started to decrease after those time periods. Conclusions: Comparing practical nano biosensory to conventional methods like that culture and biotechnology methods(such as polymerase chain reaction) is accuracy, sensitiveness and being unique. In the other way, they reduce the time from the hours to the 30 minutes.

Keywords: exotoxin, nanobiosensor, recognition, Staphylococcus aureus

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Authors: Mohammad Didar Hossain

Abstract:

Background/Purpose: The purpose of this study was to examine the associations between productive engagements and the psychological well-being of older adults in the U.S by analyzing cross-sectional data from a secondary dataset. Specifically, this paper analyzed the associations of 4 different types of productive engagements, including current work status, caregiving to the family members, volunteering and religious strengths with the psychological well-being as an outcome variable. Methods: Data and sample: The study used the data from the Health and Retirement Study (HRS). The HRS is a nationally representative prospective longitudinal cohort study that has been conducting biennial surveys since 1992 to community-dwelling individuals 50 years of age or older on diverse issues. This analysis was based on the 2016 wave (cross-sectional) of the HRS dataset and the data collection period was April 2016 through August 2017. The samples were recruited from a multistage, national area-clustered probability sampling frame. Measures: Four different variables were considered as the predicting variables in this analysis. Firstly, current working status was a binary variable that measured by 0=Yes and 1= No. The second and third variables were respectively caregiving and volunteering, and both of them were measured by; 0=Regularly, 1= Irregularly. Finally, find in strength was measured by 0= Agree and 1= Disagree. Outcome (Wellbeing) variable was measured by 0= High level of well-being, 1= Low level of well-being. Control variables including age were measured in years, education in the categories of 0=Low level of education, 1= Higher level of education and sex r in the categories 0=male, 1= female. Analysis and Results: Besides the descriptive statistics, binary logistic regression analyses were applied to examine the association between independent and dependent variables. The results showed that among the four independent variables, three of them including working status (OR: .392, p<.001), volunteering (OR: .471, p<.003) and strengths in religion (OR .588, p<.003), were significantly associated with psychological well-being while controlling for age, gender and education factors. Also, no significant association was found between the caregiving engagement of older adults and their psychological well-being outcome. Conclusions and Implications: The findings of this study are mostly consistent with the previous studies except for the caregiving engagements and their impact on older adults’ well-being outcomes. Therefore, the findings support the proactive initiatives from different micro to macro levels to facilitate opportunities for productive engagements for the older adults, and all of these may ultimately benefit their psychological well-being and life satisfaction in later life.

Keywords: productive engagements, older adults, psychological wellbeing, productive aging

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Authors: Bilel Chalghaf, Mathieu Varin

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Forest characterization in Quebec, Canada, is usually assessed based on photo-interpretation at the stand level. For species identification, this often results in a lack of precision. Very high spatial resolution imagery, such as DigitalGlobe, and Light Detection and Ranging (LiDAR), have the potential to overcome the limitations of aerial imagery. To date, few studies have used that data to map a large number of species at the tree level using machine learning techniques. The main objective of this study is to map 11 individual high tree species ( > 17m) at the tree level using an object-based approach in the broadleaf forest of Kenauk Nature, Quebec. For the individual tree crown segmentation, three canopy-height models (CHMs) from LiDAR data were assessed: 1) the original, 2) a filtered, and 3) a corrected model. The corrected CHM gave the best accuracy and was then coupled with imagery to refine tree species crown identification. When compared with photo-interpretation, 90% of the objects represented a single species. For modeling, 313 variables were derived from 16-band WorldView-3 imagery and LiDAR data, using radiance, reflectance, pixel, and object-based calculation techniques. Variable selection procedures were employed to reduce their number from 313 to 16, using only 11 bands to aid reproducibility. For classification, a global approach using all 11 species was compared to a semi-hierarchical hybrid classification approach at two levels: (1) tree type (broadleaf/conifer) and (2) individual broadleaf (five) and conifer (six) species. Five different model techniques were used: (1) support vector machine (SVM), (2) classification and regression tree (CART), (3) random forest (RF), (4) k-nearest neighbors (k-NN), and (5) linear discriminant analysis (LDA). Each model was tuned separately for all approaches and levels. For the global approach, the best model was the SVM using eight variables (overall accuracy (OA): 80%, Kappa: 0.77). With the semi-hierarchical hybrid approach, at the tree type level, the best model was the k-NN using six variables (OA: 100% and Kappa: 1.00). At the level of identifying broadleaf and conifer species, the best model was the SVM, with OA of 80% and 97% and Kappa values of 0.74 and 0.97, respectively, using seven variables for both models. This paper demonstrates that a hybrid classification approach gives better results and that using 16-band WorldView-3 with LiDAR data leads to more precise predictions for tree segmentation and classification, especially when the number of tree species is large.

Keywords: tree species, object-based, classification, multispectral, machine learning, WorldView-3, LiDAR

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Authors: Hongmin Deng, Qionghua Wang

Abstract:

A modified two dimensional (2D) logistic map based on cross feedback control is proposed. This 2D map exhibits more random chaotic dynamical properties than the classic one dimensional (1D) logistic map in the statistical characteristics analysis. So it is utilized as the pseudo-random (PN) sequence generator, where the obtained real-valued PN sequence is quantized at first, then applied to radio frequency identification (RFID) communication system in this paper. This system is experimentally validated on a cortex-M₀ development board, which shows the effectiveness in key generation, the size of key space and security. At last, further cryptanalysis is studied through the test suite in the National Institute of Standards and Technology (NIST).

Keywords: chaos encryption, logistic map, pseudo-random sequence, RFID

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