Search results for: bivariate statistical techniques

Authors: Selin Küçük

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Pre-industrial architecture is integration of natural and subsequent properties by intelligence and experience. Since various settlements relatively industrialized or non-industrialized at any time, ‘pre-industrial’ term does not refer to a definite time. Natural properties, which are existent conditions and materials in natural local environment, are climate, geomorphology and local materials. Subsequent properties, which are all anthropological comparatives, are culture of societies, requirements of people and construction techniques that people use. Yet, after industrialization, technology took technique’s place, cultural effects are manipulated, requirements are changed and local/natural properties are almost disappeared in architecture. Technology is universal, global and expands simply; conversely technique is time and experience dependent and should has a considerable cultural background. This research is about construction techniques according to natural properties of a region and classification of these techniques. Understanding local architecture is only possible by searching its background which is hard to reach. There are always changes in positive and negative in architectural techniques through the time. Archaeological layers of a region sometimes give more accurate information about transformation of architecture. However, natural properties of any region are the most helpful elements to perceive construction techniques. Many international sources from different cultures are interested in local architecture by mentioning natural properties separately. Unfortunately, there is no literature deals with this subject as far as systematically in the correct way. This research aims to improve a clear perspective of local architecture existence by categorizing archetypes according to natural properties. The ultimate goal of this research is generating a clear classification of local architecture independent from subsequent (anthropological) properties over the world such like a handbook. Since local architecture is the most sustainable architecture with refer to its economic, ecologic and sociological properties, there should be an excessive information about construction techniques to be learned from. Constructing the same buildings in all over the world is one of the main criticism of modern architectural system. While this critics going on, the same buildings without identity increase incrementally. In post-industrial term, technology widely took technique’s place, yet cultural effects are manipulated, requirements are changed and natural local properties are almost disappeared in architecture. These study does not offer architects to use local techniques, but it indicates the progress of pre-industrial architectural evolution which is healthier, cheaper and natural. Immigration from rural areas to developing/developed cities should be prohibited, thus culture and construction techniques can be preserved. Since big cities have psychological, sensational and sociological impact on people, rural settlers can be convinced to not to immigrate by providing new buildings designed according to natural properties and maintaining their settlements. Improving rural conditions would remove the economical and sociological gulf between cities and rural. What result desired to arrived in, is if there is no deformation (adaptation process of another traditional buildings because of immigration) or assimilation in a climatic region, there should be very similar solutions in the same climatic regions of the world even if there is no relationship (trade, communication etc.) among them.

Keywords: climate zones, geomorphology, local architecture, local materials

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Authors: H. Abas Nejad, A. R. Teymoori

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Facial expression recognition is one of the open problems in computer vision. Robust neutral face recognition in real time is a major challenge for various supervised learning based facial expression recognition methods. This is due to the fact that supervised methods cannot accommodate all appearance variability across the faces with respect to race, pose, lighting, facial biases, etc. in the limited amount of training data. Moreover, processing each and every frame to classify emotions is not required, as the user stays neutral for the majority of the time in usual applications like video chat or photo album/web browsing. Detecting neutral state at an early stage, thereby bypassing those frames from emotion classification would save the computational power. In this work, we propose a light-weight neutral vs. emotion classification engine, which acts as a preprocessor to the traditional supervised emotion classification approaches. It dynamically learns neutral appearance at Key Emotion (KE) points using a textural statistical model, constructed by a set of reference neutral frames for each user. The proposed method is made robust to various types of user head motions by accounting for affine distortions based on a textural statistical model. Robustness to dynamic shift of KE points is achieved by evaluating the similarities on a subset of neighborhood patches around each KE point using the prior information regarding the directionality of specific facial action units acting on the respective KE point. The proposed method, as a result, improves ER accuracy and simultaneously reduces the computational complexity of ER system, as validated on multiple databases.

Keywords: neutral vs. emotion classification, Constrained Local Model, procrustes analysis, Local Binary Pattern Histogram, statistical model

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Authors: Nuo Xu, Kok Hun Goh, Jeyatharan Kumarasamy

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Pile load testing is significant during foundation construction due to its traditional role of design validation and routine quality control of the piling works. In order to verify whether piles can take loadings at specified settlements, piles will have to undergo working load test where the test load should normally up to 150% of the working load of a pile. Selection or sampling of piles for the working load test is done subject to the number specified in Singapore National Annex to Eurocode 7 SS EN 1997-1:2010. This paper presents an innovative way to rationalize the number of pile load test by adopting statistical analysis approach and looking at the coefficient of variance of pile elastic modulus using a case study at Singapore Tuas depot. Results are very promising and have shown that it is possible to reduce the number of working load test without influencing the reliability and confidence on the pile quality. Moving forward, it is suggested that more load test data from other geological formations to be examined to compare with the findings from this paper.

Keywords: elastic modulus of pile under soil interaction, jurong formation, kentledge test, pile load test

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Authors: Selvaprakash Ramalingam, Rabi N. Sahoo, Dharmendra Saraswat, A. Kumar, Rajeev Ranjan, Joydeep Mukerjee, Viswanathan Chinnasamy, K. K. Chaturvedi, Sanjeev Kumar

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Rice is one of the most important staple food crops in the world. Among the various diseases that affect rice crops, rice blast is particularly significant, causing crop yield and economic losses. While the plant has defense mechanisms in place, such as chemical indicators (proteins, salicylic acid, jasmonic acid, ethylene, and azelaic acid) and resistance genes in certain varieties that can protect against diseases, susceptible varieties remain vulnerable to these fungal diseases. Early prediction of rice blast (RB) disease is crucial, but conventional techniques for early prediction are time-consuming and labor-intensive. Hyperspectral remote sensing techniques hold the potential to predict RB disease at its asymptomatic stage. In this study, we aimed to demonstrate the prediction of RB disease at the asymptomatic stage using non-imaging hyperspectral ASD spectroradiometer under controlled laboratory conditions. We applied statistical spectral discrimination theory to identify unknown spectra of M. Oryzae, the fungus responsible for rice blast disease. The infrared (IR) region was found to be significantly affected by RB disease. These changes may result in alterations in the absorption, reflection, or emission of infrared radiation by the affected plant tissues. Our research revealed that the protein spectrum in the IR region is impacted by RB disease. In our study, we identified strong correlations in the region (Amide group - I) around X 1064 nm and Y 1300 nm with the Lambda / Lambda derived spectra methods for protein detection. During the stages when the disease is developing, typically from day 3 to day 5, the plant's defense mechanisms are not as effective. This is especially true for the PB-1 variety of rice, which is highly susceptible to rice blast disease. Consequently, the proteins in the plant are adversely affected during this critical time. The spectral contour plot reveals the highly correlated spectral regions 1064 nm and Y 1300 nm associated with RB disease infection. Based on these spectral sensitivities, we developed new spectral disease indices for predicting different stages of disease emergence. The goal of this research is to lay the foundation for future UAV and satellite-based studies aimed at long-term monitoring of RB disease.

Keywords: rice blast, asymptomatic stage, spectral sensitivity, IR

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Authors: Nevila Bardhi, Joanna Magda, Kolapo Alex-Oni, Slavenka Sedlar, Paromita Hore

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The New York City Department of Health and Mental Hygiene (NYC DOHMH) receives blood lead test results for NYC residents and conducts lead poisoning case investigations for individuals with elevated blood lead levels exposed to lead occupationally and non-occupationally. To (1) improve participant engagement, (2) aid the identification of potential lead sources, and (3) better tailor recommendations to reduce lead exposure, Motivational Interviewing (MI) techniques were incorporated during risk assessment interviews of non-pregnant adults by DOHMH’s Adult Lead Poisoning Prevention (ALP) Program. MI is an evidence-based counselling method used in clinical settings that have been effective in promoting behavior change by resolving ambivalence and enhancing motivation in treating both physiological and psychological health conditions. The incorporation of MI techniques in the ALP risk assessment interview was effective in improving the identification of lead sources for non-pregnant adult cases, thus, allowing for the opportunity to better tailor lead poisoning prevention recommendations. The embedding of MI cues in the ALP risk assessment interview also significantly increased engagement in the interview process, resulting in approximately 50 more interviews conducted per year and a decrease in interview refusals during case investigations. Additionally, the pre-MI interview completion rate was 57%, while the post-MI Interview completion rate was 68%. We recommend MI techniques to be used by other lead poisoning prevention programs during lead poisoning investigations in similar diverse populations.

Keywords: lead poisoning prevention, motivational interviewing, behavior change, lead poisoning risk factors, self-efficacy

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Authors: Divya Sisodiya, Deepika Sipal

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Optical wireless communication (OWC) is a relatively new technology in optical communication systems that allows for high-speed wireless optical communication. This research focuses on developing a cost-effective OWC system using a hybrid configuration of optical amplifiers. In addition to using EDFA amplifiers, a comparison study was conducted to determine which modulation technique is more effective for communication. This research examines the performance of an OWC system based on ASK and PSK modulation techniques by varying OWC parameters under various atmospheric conditions such as rain, mist, haze, and snow. Finally, the simulation results are discussed and analyzed.

Keywords: OWC, bit error rate, amplitude shift keying, phase shift keying, attenuation, amplifiers

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Authors: Adane Kassa Shikur

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Today’s supply chains (SC) have become vulnerable to unexpected and ever-intensifying disruptions from myriad sources. Consequently, the concept of supply chain resilience (SCRes) has become crucial to complement the conventional risk management paradigm, which has failed to cope with unexpected SC disruptions, resulting in severe consequences affecting SC performances and making business continuity questionable. Advancements in cutting-edge technologies like artificial intelligence (AI) and their potential to enhance SCRes by improving critical antecedents in the different phases have attracted the attention of scholars and practitioners. The research from academia and the practical interest of the industry have yielded significant publications at the nexus of AI and SCRes during the last two decades. However, the applications and examinations have been primarily conducted independently, and the extant literature is dispersed into research streams despite the complex nature of SCRes. To close this research gap, this study conducts a systematic literature review of 106 peer-reviewed articles by curating, synthesizing, and consolidating up-to-date literature and presents the state-of-the-art development from 2010 to 2022. Bayesian networks are the most topical ones among the 13 AI techniques evaluated. Concerning the critical antecedents, visibility is the first ranking to be realized by the techniques. The study revealed that AI techniques support only the first 3 phases of SCRes (readiness, response, and recovery), and readiness is the most popular one, while no evidence has been found for the growth phase. The study proposed an AI-SCRes framework to inform research and practice to approach SCRes holistically. It also provided implications for practice, policy, and theory as well as gaps for impactful future research.

Keywords: ANNs, risk, Bauesian networks, vulnerability, resilience

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Authors: Surya R. Niraula, Devendra B Chhetry, Girish K. Singh, S. Nagesh, Frederick A. Connell

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Background: Although random sampling is generally considered to be the gold standard for population-based research, the majority of drug abuse research is based on non-random sampling despite the well-known limitations of this kind of sampling. Method: We compared the statistical properties of two surveys of drug abuse in the same community: one using snowball sampling of drug users who then identified “friend controls” and the other using a random sample of non-drug users (controls) who then identified “friend cases.” Models to predict drug abuse based on risk factors were developed for each data set using conditional logistic regression. We compared the precision of each model using bootstrapping method and the predictive properties of each model using receiver operating characteristics (ROC) curves. Results: Analysis of 100 random bootstrap samples drawn from the snowball-sample data set showed a wide variation in the standard errors of the beta coefficients of the predictive model, none of which achieved statistical significance. One the other hand, bootstrap analysis of the random-sample data set showed less variation, and did not change the significance of the predictors at the 5% level when compared to the non-bootstrap analysis. Comparison of the area under the ROC curves using the model derived from the random-sample data set was similar when fitted to either data set (0.93, for random-sample data vs. 0.91 for snowball-sample data, p=0.35); however, when the model derived from the snowball-sample data set was fitted to each of the data sets, the areas under the curve were significantly different (0.98 vs. 0.83, p < .001). Conclusion: The proposed method of random sampling of controls appears to be superior from a statistical perspective to snowball sampling and may represent a viable alternative to snowball sampling.

Keywords: drug abuse, matched case-control study, non-probability sampling, probability sampling

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Authors: Tahir Mehmood, Mumtaz Akhter

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The global need for conflict management is greater now in the early 21st century than ever before. According to UNESCO, half of the world’s 195 countries will have to expand their stock of educationist significantly, some by tens of thousands, if the goal development targets are desired to achieve. Socioeconomic inequities, political instability, demographic changes and crises such as the HIV/AIDs epidemic have engendered huge shortfalls in teacher supply and low teacher quality in many developing countries. Education serves as back bone in development process. Open learning and distance education programs are serving as pivotal part of development process. It is now clear that ‘bricks and mortar’ approaches to expanding teacher education may not be adequate if the current and projected shortfalls in teacher supply and low teacher quality are to be properly addressed. The study is designed to measure the perceptions of teaching learning community about conflict management with special reference to open and distance learning. It was descriptive study which targeted teachers, students, community members and experts. Data analysis was carried out by using statistical techniques served by SPSS. Findings reflected that audience perceives open and distance learning as change agent and as development tool. It is noticed that target audience has driven prominent performance by using facility of open and distance learning.

Keywords: conflict management, open and distance learning, teachers, students

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Authors: Vidhu Mitha Goutham, Ruma Mukherjee

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The low availability of well-trained, unlimited, dynamic-access models for specific languages makes it hard for corporate users to adopt quick translation techniques and incorporate them into product solutions. As translation tasks increasingly require a dynamic sequence learning curve; stable, cost-free opensource models are scarce. We survey and compare current translation techniques and propose a modified sequence to sequence model repurposed with attention techniques. Sequence learning using an encoder-decoder model is now paving the path for higher precision levels in translation. Using a Convolutional Neural Network (CNN) encoder and a Recurrent Neural Network (RNN) decoder background, we use Fairseq tools to produce an end-to-end bilingually trained Spanish-English machine translation model including source language detection. We acquire competitive results using a duo-lingo-corpus trained model to provide for prospective, ready-made plug-in use for compound sentences and document translations. Our model serves a decent system for large, organizational data translation needs. While acknowledging its shortcomings and future scope, it also identifies itself as a well-optimized deep neural network model and solution.

Keywords: attention, encoder-decoder, Fairseq, Seq2Seq, Spanish, translation

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Authors: John M. Ikome, Martha E. Ikome, Therese Van Wyk

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Productivity optimization of a company can significantly increase the company’s output and productivity which can be in the form of corrective actions of ineffective activities, process simplification, and reduction of variations, responsiveness, and reduction of set-up-time which are all under the classification of waste within the manufacturing environment. Deriving a means to eliminate a number of these issues has a key importance for manufacturing organization. This paper focused on a number of industrial engineering techniques which include a cause and effect diagram, to identify and optimize the method or systems being used. Based on our results, it shows that there are a number of variations within the production processes that can significantly disrupt the expected output.

Keywords: optimization, fishbone, diagram, productivity

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Authors: Abdullah Alsaeed

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Virtualized computing and cloud computing infrastructures are no longer fuzz or marketing term. They are a core reality in today’s corporate Information Technology (IT) organizations. Hence, developing an effective and efficient methodologies for data backup and data recovery is required more than any time. The purpose of data backup and recovery techniques are to assist the organizations to strategize the business continuity and disaster recovery approaches. In order to accomplish this strategic objective, a variety of mechanism were proposed in the recent years. This research paper will explore and examine the latest techniques and solutions to provide data backup and restoration for the cloud computing platforms.

Keywords: data backup, data recovery, cloud computing, business continuity, disaster recovery, cost-effective, data encryption.

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Authors: Aparna Gulhane

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Biometrics is the science and technology of measuring and analyzing biological data form the basis of research in biological measuring techniques for the purpose of people identification and recognition. In information technology, biometrics refers to technologies that measure and analyze human body characteristics, such as DNA, fingerprints, eye retinas and irises, voice patterns, facial patterns and hand measurements. Biometric systems are used to authenticate the person's identity. The idea is to use the special characteristics of a person to identify him. These papers present a biometric authentication techniques and actual deployment of potential by overall invocation of biometrics recognition, with an independent testing of various biometric authentication products and technology.

Keywords: types of biometrics, importance of biometric, review for biometrics and getting a new implementation, biometric authentication technique

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Authors: M. E. Khiav, D. J. Borah, H. T. S. Santos, V. T. Faria

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For automobile companies, it has become very important to ensure sound quality in manufacturing and assembling in order to prevent occurrence of defects and to reduce the amount of parts replacements to be done in the service centers during the warranty period. Statistical Process Control (SPC) is widely used as the tool to analyze the quality of such processes and plays a significant role in the improvement of the processes by identifying the patterns and the location of the defects. In this paper, a case study has been conducted on an Iranian automobile company. This paper performs a quality analysis of a particular component called “Internal Bearing for the Back Wheel” of a particular car model, manufactured by the company, based on the 10 million data received from its service centers located all over the country. By creating control charts including X bar–S charts and EWMA charts, it has been observed after the year 2009, the specific component underwent frequent failures and there has been a sharp dip in the average distance covered by the cars till the specific component requires replacement/maintenance. Correlation analysis was performed to find out the reasons that might have affected the quality of the specific component in all the cars produced by the company after the year 2009. Apart from manufacturing issues, some political and environmental factors have been identified to have a potential impact on the quality of the component. A maiden attempt has been made to analyze the quality issues within an Iranian automobile manufacturer; such issues often get neglected in developing countries. The paper also discusses the possibility of political scenario of Iran and the country’s environmental conditions affecting the quality of the end products, which not only strengthens the extant literature but also provides a new direction for future research.

Keywords: capability analysis, car manufacturing, statistical process control, quality control, quality tools

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Authors: Tshaiya Devi Thandauthapani, Adam J. Reeve, Adam S. Long, Ian J. Turner, James S. Sharp

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Fingermarks are a crucial form of evidence for identifying a person at a crime scene. However, visualising latent (hidden) fingermarks can be difficult, and the correct choice of techniques is essential to develop and preserve any fingermarks that might be present. Knives, firearms and other metal weapons have proven to be challenging substrates (stainless steel in particular) from which to reliably obtain fingermarks. In this study, time of flight secondary ion mass spectroscopy (ToF-SIMS) was used to image fingermarks on metal surfaces. This technique was compared to a conventional superglue based fuming technique that was accompanied by a series of contrast enhancing dyes (basic yellow 40 (BY40), crystal violet (CV) and Sudan black (SB)) on three different metal surfaces. The conventional techniques showed little to no evidence of fingermarks being present on the metal surfaces after a few days. However, ToF-SIMS images revealed fingermarks on the same and similar substrates with an exceptional level of detail demonstrating clear ridge definition as well as detail about sweat pore position and shape, that persist for over 26 days after deposition when the samples were stored under ambient conditions.

Keywords: conventional techniques, latent fingermarks, metal substrates, time of flight secondary ion mass spectroscopy

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Authors: Mustafa Ekici

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Natural convection is a basic process which is important in a wide variety of practical applications. In essence, a heated fluid expands and rises from buoyancy due to decreased density. Numerous papers have been written on natural or mixed convection in vertical ducts heated on the side. These equations have been proved to be valuable tools for the modelling of many phenomena such as fluid dynamics. Finding solutions to such equations or system of equations are in general not an easy task. We propose a method, which is called differential transform method, of solving a non-linear equations and compare the results with some of the other techniques. Illustrative examples shows that the results are in good agreement.

Keywords: differential transform method, momentum, energy equation, boundry value problem

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Authors: Y. Sunecher, N. Mamode Khan, V. Jowaheer

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This paper considers the modelling of a non-stationary bivariate integer-valued autoregressive moving average of order one (BINARMA(1,1)) with correlated Poisson innovations. The BINARMA(1,1) model is specified using the binomial thinning operator and by assuming that the cross-correlation between the two series is induced by the innovation terms only. Based on these assumptions, the non-stationary marginal and joint moments of the BINARMA(1,1) are derived iteratively by using some initial stationary moments. As regards to the estimation of parameters of the proposed model, the conditional maximum likelihood (CML) estimation method is derived based on thinning and convolution properties. The forecasting equations of the BINARMA(1,1) model are also derived. A simulation study is also proposed where BINARMA(1,1) count data are generated using a multivariate Poisson R code for the innovation terms. The performance of the BINARMA(1,1) model is then assessed through a simulation experiment and the mean estimates of the model parameters obtained are all efficient, based on their standard errors. The proposed model is then used to analyse a real-life accident data on the motorway in Mauritius, based on some covariates: policemen, daily patrol, speed cameras, traffic lights and roundabouts. The BINARMA(1,1) model is applied on the accident data and the CML estimates clearly indicate a significant impact of the covariates on the number of accidents on the motorway in Mauritius. The forecasting equations also provide reliable one-step ahead forecasts.

Keywords: non-stationary, BINARMA(1, 1) model, Poisson innovations, conditional maximum likelihood, CML

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Authors: M. Budakoglu, M. Karaman, A. Abdelnasser, M. Kumral

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The spatial interpolation and spatial correlation of the rare earth elements (REE) of lake surface sediments of Lake Acıgöl and its surrounding lithological units is carried out by using GIS techniques like Inverse Distance Weighted (IDW) and Geographically Weighted Regression (GWR) techniques. IDW technique which makes the spatial interpolation shows that the lithological units like Hayrettin Formation at north of Lake Acigol have high REE contents than lake sediments as well as ∑LREE and ∑HREE contents. However, Eu/Eu* values (based on chondrite-normalized REE pattern) show high value in some lake surface sediments than in lithological units and that refers to negative Eu-anomaly. Also, the spatial interpolation of the V/Cr ratio indicated that Acıgöl lithological units and lake sediments deposited in in oxic and dysoxic conditions. But, the spatial correlation is carried out by GWR technique. This technique shows high spatial correlation coefficient between ∑LREE and ∑HREE which is higher in the lithological units (Hayrettin Formation and Cameli Formation) than in the other lithological units and lake surface sediments. Also, the matching between REEs and Sc and Al refers to REE abundances of Lake Acıgöl sediments weathered from local bedrock around the lake.

Keywords: spatial geochemical modeling, IDW, GWR techniques, REE, lake sediments, Lake Acıgöl, Turkey

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Authors: Suangsuda Subjaroen, Chutikarn Sriviboon, Rosjana Chandhasa

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This research aims to examine the graduates' overall satisfaction and influential factors that affect the image of Suan Sunandha Rajabhat University, according to the graduates' viewpoints on the graduation rehearsal day. In accordance with the graduates' perceptions, the study is related to the levels of graduates' satisfaction, their perceived quality, perceived value, and the image of Suan Sunandha Rajabhat University. The sample group in this study involved 1,129 graduates of Suan Sunandha Rajabhat University who attended on 2019 graduation rehearsal day. A questionnaire was used as an instrument in order to collect data. By the use of computing software, the statistics used for data analysis were various, ranging from frequencies, percentage, mean, and standard deviation, One-Way ANOVA, and Multiple Regression Analysis. The majority of participants were graduates with a bachelor's degree, followed by masters graduates and PhD graduates, respectively. Among the participants, most of them graduated from the Faculty of Management Sciences, followed by the Faculty of Humanities and Social Sciences and Faculty of Education, respectively. Overall, the graduates were satisfied with the graduation rehearsal day, and each aspect was rated at a satisfactory level. Formality, steps, and procedures were the aspects that graduates were most satisfied with, followed by graduation rehearsal personnel and staff, venue, and facilities. Referring to graduates' perceptions, the perceived quality was rated at a very good level, the perceived value was at a good level, whereas the image of Suan Sunandha Rajabhat University was perceived at a good level, respectively. There were differences in satisfaction levels among graduates with a bachelor's degree, graduates with a master's degree and a doctoral degree with statistical significance at the level of 0.05. There was a statistical significance at the level of 0.05 in perceived quality and perceived value affecting the image of Suan Sunandha Rajabhat University. The image of Suan Sunandha Rajabhat University influenced graduates' satisfaction level with statistical significance at the level of 0.01.

Keywords: university image, perceived quality, perceived value, intention to study higher education, intention to recommend the university to others

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Authors: Waraphorn Sribuakaew, Chutikarn Sriviboon, Rosjana Chandhasa

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The purpose of this research is to study the satisfaction level of graduates and factors that affect the image of Suan Sunandha Rajabhat University based on the perceptions of graduates on the graduation ceremony day. By studying the satisfaction of graduates, the image of Suan Sunandha Rajabhat University according to the graduates' perceptions and the loyalty to the university (in the aspects of intention to continue studying at a higher level, intention to recommend the university to a friend), the sample group used in this study was 1,000 graduates of Suan Sunandha Rajabhat University who participated on the 2019 graduation ceremony day. A questionnaire was utilized as a tool for data collection. By the use of computing software, the statistics used for data analysis were frequencies, percentage, mean, and standard deviation, One-Way ANOVA, and multiple regression analysis. Most of the respondents were graduates with a bachelor's degree, followed by graduates with a master's degree and PhD graduates, respectively. Major participants graduated from the Faculty of Management Sciences, followed by the Faculty of Humanities and Social Sciences and Faculty of Education, respectively. The graduates were satisfied on the ceremony day as a whole and rated each aspect at a satisfactory level. Formality, steps, and procedures were the aspects that graduates were most satisfied with, followed by graduation ceremony personnel and staff, venue, and facilities. On the perception of the graduates, the image of Suan Sunandha Rajabhat University was at a good level, while loyalty to the university was at a very high level. The intention of recommendation to others was at the highest level, followed by the intention to pursue further education at a very high level. The graduates graduating from different faculties have different levels of satisfaction on the graduation day with statistical significance at the level of 0.05. The image of Suan Sunandha Rajabhat University affected the satisfaction of graduates with statistical significance at the level of 0.01. The satisfactory level of graduates on the graduation ceremony day influenced the level of loyalty to the university with statistical significance at the level of 0.05.

Keywords: university image, loyalty to the university, intention to study higher education, intention to recommend the university to others, graduates' satisfaction

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Authors: Laid Fekih

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Background: It is difficult to detect lying, deception, and misrepresentation just by looking at verbal or non-verbal expression during the criminal investigation process, as there is a common belief that it is possible to tell whether a person is lying or telling the truth just by looking at the way they act or behave. The process of detecting lies and deception during the criminal investigation process needs more studies and research to overcome the difficulties facing the investigators. Method: The present study aimed to identify the effectiveness of cognitive methods and techniques in detecting deception during the criminal investigation. It adopted the quasi-experimental method and covered a sample of (20) defendants distributed randomly into two homogeneous groups, an experimental group of (10) defendants be subject to criminal investigation by applying cognitive techniques to detect deception and a second experimental group of (10) defendants be subject to the direct investigation method. The tool that used is a guided interview based on models of investigative questions according to the cognitive deception detection approach, which consists of three techniques of Vrij: imposing the cognitive burden, encouragement to provide more information, and ask unexpected questions, and the Direct Investigation Method. Results: Results revealed a significant difference between the two groups in term of lie detection accuracy in favour of defendants be subject to criminal investigation by applying cognitive techniques, the cognitive deception detection approach produced superior total accuracy rates both with human observers and through an analysis of objective criteria. The cognitive deception detection approach produced superior accuracy results in truth detection: 71%, deception detection: 70% compared to a direct investigation method truth detection: 52%; deception detection: 49%. Conclusion: The study recommended if practitioners use a cognitive deception detection technique, they will correctly classify more individuals than when they use a direct investigation method.

Keywords: the cognitive lie detection approach, deception, criminal investigation, mental health

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Authors: Sungwon Jung

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The percentage of 20 years or older apartment houses in South Korea is approximately 20% (1.55 million houses), and the explosive increase of aged houses is expected around the first planned new towns. Accordingly, we should prepare for social issues such as difficulty of housing lease and degradation of housing performance. The improvement of performance of aged houses is essential for achieving the national energy and carbon reduction goals, and we should develop techniques to respond to the changing construction environment. Furthermore, we should develop a performance evaluation system that is appropriate for the demands of residents such as the improvement of remodeling floor plan by performance improvement in line with the residence type of the housing vulnerable groups such as low-income group and elderly people living alone. For this purpose, remodeling techniques and business models optimized for the target complexes must be spread through the development of various business models. In addition, it is necessary to improve the remodeling business by improving the laws and systems related to the improvement of the residential performance and to prepare techniques to respond to the increasing business demands. In other words, performance improvement and evaluation and knowledge systems need to be researched as new issues related to remodeling that has not been addressed in the existing research.

Keywords: remodelling, performance evaluation, web-based system, big data

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Authors: Tshegofatso Rambau, Tonderai Muchenje

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Zero-day attacks (ZDA) are increasing day by day; there are many vulnerabilities in systems and software that date back decades. Companies keep discovering vulnerabilities in their systems and software and work to release patches and updates. A zero-day vulnerability is a software fault that is not widely known and is unknown to the vendor; attackers work very quickly to exploit these vulnerabilities. These are major security threats with a high success rate because businesses lack the essential safeguards to detect and prevent them. This study focuses on the factors and techniques that can help us detect zero-day attacks. There are various methods and techniques for detecting vulnerabilities. Various companies like edges can offer penetration testing and smart vulnerability management solutions. We will undertake literature studies on zero-day attacks and detection methods, as well as modeling approaches and simulations, as part of the study process.

Keywords: zero-day attacks, exploitation, vulnerabilities

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Authors: Mahdiar Hosseinghadiry, Razali Ismail, F. Fotovati

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One of the most important and challenging tasks in testing network-on-chip based system-on-chips (NoC based SoCs) is to verify the communication entity. It is important because of its usage for transferring both data packets and test patterns for intellectual properties (IPs) during normal and test mode. Hence, ensuring of NoC reliability is required for reliable IPs functionality and testing. On the other hand, it is challenging due to the required time to test it and the way of transferring test patterns from the tester to the NoC components. In this paper, two testing techniques for mesh-based NoC interconnections are proposed. The first one is based on one-by-one testing and the second one divides NoC interconnects into three parts, horizontal links of switches in even columns, horizontal links of switches in odd columns and all vertical. A design for testability (DFT) architecture is represented to send test patterns directly to each switch under test and also support the proposed testing techniques by providing a loopback path in each switch. The simulation results shows the second proposed testing mechanism outperforms in terms of test time because this method test all the interconnects in only three phases, independent to the number of existed interconnects in the network, while test time of other methods are highly dependent to the number of switches and interconnects in the NoC.

Keywords: on chip, interconnection testing, horizontal-vertical testing, enhanced unicast

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Authors: William Mahony, L. Jacqueline Hirth, Richard Rupp, Sandra Gonzalez, Roger Zoorob

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Background: The impact of the COVID-19 pandemic on physicians has been considered by many researchers, but less is known about non-physician healthcare workers. The aim of this study is to examine the association of COVID-19 safety training and communication with stress. Methods: A 91-item online survey was distributed, starting January 2, 2021, to non-physician healthcare workers, including physician assistants, nurse practitioners, and medical assistants (MAs) in the United States through email and social media. A $1 donation was made to the Red Cross for each completed survey. The survey consisted of demographics, occupational questions, and perceived stress (perceived stress scale, PSS). Items on the PSS were combined for an overall score and categorized according to the severity of perceived stress. Chi-square tests were performed for bivariate analyses of categorical variables. Results: Of the 284 participants consenting to complete the survey, 197 participants completed the full survey. MAs made up most of the sample at 79%. Among all respondents, 47% had moderate PSS scores (scored between 14 and 26), and 51% had severe PSS scores (scored between 27 and 40). Unvaccinated participants reported statistically significantly lower levels of perceived stress (p = 0.002). Performing tasks outside of typical job responsibilities was not associated with PSS scores (p = .667). Discussion: Non-physician healthcare workers demonstrated a high level of perceived stress overall. The association between vaccination status and perceived stress should be examined in order to evaluate whether vaccination levels could be improved with further education about the virus and associated risks.

Keywords: COVID-19, SARS-Cov-2, nursing, public health

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Authors: Kanu Priya Mohan

Abstract:

Innovation in education is one of the essential pathways to achieve both educational, and development goals in today’s dynamically changing world. Over the last decade, coaching and mentoring have been applied in the field of education as positive intervention techniques for fostering teaching and learning reforms in the developed countries. The context of this research was Thailand’s educational reform process, wherein a project on coaching and mentoring (C&M) was launched in 2014. The C&M project endeavored to support the professional development of the school teachers in the various provinces of Thailand, and to also enable them to apply C&M for teaching innovative instructional techniques. This research aimed to empirically investigate the learning outcomes for the master trainers, who trained for coaching and mentoring as the first step in the process to train the school teachers. A mixed method study was used for evaluating the learning outcomes of training in terms of cognitive- behavioral-affective dimensions. In the first part of the research a quantitative research design was incorporated to evaluate the effects of learner characteristics and instructional techniques, on the learning outcomes. In the second phase, a qualitative method of in-depth interviews was used to find details about the training outcomes, as well as the perceived barriers and enablers of the training process. Sample size constraints were there, yet these exploratory results, integrated from both methods indicated the significance of evaluating training outcomes from the three dimensions, and the perceived role of other factors in the training. Findings are discussed in terms of their implications for the training of C&M, and also their impact in fostering positive education through innovative educational techniques in the developing countries.

Keywords: cognitive-behavioral-affective learning outcomes, mixed method research, teachers in Thailand, training evaluation

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Authors: Allahyar Arabmomeni, Hojjatollah Alaei

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Background: The objectives of this study was to investigate effect of anthropometric variables and body composition on physical capabilities among male and female students. Materials and Methods: The study had a descriptive correlation method. The statistical population consisted of all students of Islamic Azad University, Khomeinishahr Branch, from 2011 to 2013, which was about 7000 students. The statistical sample included 300 male and 300 female students who were randomly selected from among university students in proportion to frequency of students in each faculty. Descriptive statistical methods, t-test and Pearson correlation coefficient were used for data analysis. Results: Results of this research showed that body size of male students in the studied variables was more than that of female students (p<0.05). Moreover, there was significant difference between all the variables based on significance level of the table. Also, the results taken from the Pearson correlation of this study's variables showed a positive relationship between height and leg and hand length and sit-up, full-ups bar and vertical jump tests (p<0/01). Besides, there was a positive correlation between hand length, sit-up, full-ups bar and vertical jump tests. As far as tests of length of legs and vertical jump were concerned, a highly positive correlation was observed between them. Additionally, results of this study indicated a significant correlation at alpha level of 0.05 between age and height of the students; but, there was a negative correlation between age, sit-up and 1600-m tests (p<0.05). Conclusion: The results of this study indicated a relationship between size of weight, height, length of hands and legs and some physical fitness tests. Therefore, it is required to consider anthropometric factors in addition to gender and age while preparing norms of physical fitness since variables of height and length of hands also affect physical fitness evaluation.

Keywords: anthropometric variables, physical fitness factors, students, body composition

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Authors: Ruchika Malhotra, Megha Khanna

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The development of change prediction models can help the software practitioners in planning testing and inspection resources at early phases of software development. However, a major challenge faced during the training process of any classification model is the imbalanced nature of the software quality data. A data with very few minority outcome categories leads to inefficient learning process and a classification model developed from the imbalanced data generally does not predict these minority categories correctly. Thus, for a given dataset, a minority of classes may be change prone whereas a majority of classes may be non-change prone. This study explores various alternatives for adeptly handling the imbalanced software quality data using different sampling methods and effective MetaCost learners. The study also analyzes and justifies the use of different performance metrics while dealing with the imbalanced data. In order to empirically validate different alternatives, the study uses change data from three application packages of open-source Android data set and evaluates the performance of six different machine learning techniques. The results of the study indicate extensive improvement in the performance of the classification models when using resampling method and robust performance measures.

Keywords: change proneness, empirical validation, imbalanced learning, machine learning techniques, object-oriented metrics

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Authors: Nadia Sghaier

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In this paper, we examine the influence of the COVID-19 pandemic on the performance of the Tunisian stock market and 12 sectors over a recent period from 23 March 2020 to 18 August 2021, including several waves and the introduction of vaccination. The empirical study is conducted using cointegration techniques which allows for long and short-run relationships. The obtained results indicate that both daily growth in confirmed cases and deaths have a negative and significant effect on the stock market returns. In particular, this effect differs across sectors. It seems more pronounced in financial, consumer goods and industrials sectors. These findings have important implications for investors to predict the behavior of the stock market or sectors returns and to implement hedging strategies during the COVID-19 pandemic.

Keywords: Tunisian stock market, sectors, COVID-19 pandemic, cointegration techniques

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Authors: Victoria Eugenia Garnacho-Garnacho, Elena Sonsoles Rodriguez-Lopez, Raquel Delgado-Delgado, Alvaro Otero-Campos, Jesus Guodemar-Perez, Angelo Michelle Vagali, Juan Pablo Hervas-Perez

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Asthma is a heterogeneous disease which has always had a drug treatment. Osteopathic treatment that we propose is aimed, seen through a dorsal manipulation (Dog Technic D1-D4) and a technique for diaphragm (Longitudinal Stroke) forced expiratory flow in spirometry changes there are in particular that there is an increase in the volumes of the Peak Flow and Post intervention and effort and that the application of these two techniques together is more powerful if we applied only a Longitudinal (Stroke). Also rating if this type of treatment will have repercussions on breathlessness, a very common symptom in asthma. And finally to investigate if provided vertebra pain decreased after a manipulation. Methods—Participants were recruited between students and professors of the University, aged 18-65, patients (n = 18) were assigned randomly to one of the two groups, group 1 (longitudinal Stroke and manipulation dorsal Dog Technic) and group 2 (diaphragmatic technique, Longitudinal Stroke). The statistical analysis is characterized by the comparison of the main indicator of obstruction of via area PEF (peak expiratory flow) in various situations through the peak flow meter Datospir Peak-10. The measurements were carried out in four phases: at rest, after the stress test, after the treatment, after treatment and the stress test. After each stress test was evaluated, through the Borg scale, the level of Dyspnea on each patient, regardless of the group. In Group 1 in addition to these parameters was calculated using an algometer spinous pain before and after the manipulation. All data were taken at the minute. Results—12 Group 1 (Dog Technic and Longitudinal Stroke) patients responded positively to treatment, there was an increase of 5.1% and 6.1% of the post-treatment PEF and post-treatment, and effort. The results of the scale of Borg by which we measure the level of Dyspnea were positive, a 54.95%, patients noted an improvement in breathing. In addition was confirmed through the means of both groups group 1 in which two techniques were applied was 34.05% more effective than group 2 in which applied only a. After handling pain fell by 38% of the cases. Conclusions—The impact of the technique of Dog-Technic for D1-D4 and the Longitudinal Stroke technique for diaphragm in the volumes of peak expiratory flow (PEF) in asthmatic patients were positive, there was a change of the PEF Post intervention and post-treatment, and effort and showed the most effective group in which only a technique was applied. Furthermore this type of treatment decreased facilitated vertebrae pain and was efficient in the improvement of Dyspnea and the general well-being of the patient.

Keywords: ANS, asthma, manipulation, manual therapy, osteopathic

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