Search results for: multi linear regression

Authors: Abdul Rauf, Xiaoxing Liu, Rizwan Qaisar Danish, Waqas Amin

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The core intention of this study is to analyze the linkage of training, job attitudes and motivation through a mediation model in the banking sector of Pakistan. Moreover, this study is executed to answer a range of queries regarding the consideration of employees about training, job satisfaction, motivation and organizational commitment. Hence, the association of training with job satisfaction, job satisfaction with motivation, organizational commitment with job satisfaction, organization commitment as independently with motivation and training directly related to motivation is determined in this course of study. A questionnaire crafted for comprehending the purpose of this study by including four variables such as training, job satisfaction, motivation and organizational commitment which have to measure. A sample of 450 employees from seventeen private (17) banks and two (2) public banks was taken on the basis of convenience sampling from Pakistan. However, 357 questionnaires, completely filled were received back. AMOS used for assessing the conformity factor analysis (CFA) model and statistical techniques practiced to scan the collected data (i.e.) descriptive statistics, regression analysis and correlation analysis. The empirical findings revealed that training and organizational commitment has a significant and positive impact directly on job satisfaction and motivation as well as through the mediator (job satisfaction) also the impact sensing in the same way on the motivation of employees in the financial Banks of Pakistan. In this research study, the banking sector is under discussion, so the findings could not generalize on other sectors such as manufacturing, textiles, telecom, and medicine, etc. The low sample size is also the limitation of this study. On the foundation of these results the management fascinates to make the revised strategies regarding training program for the employees as it enhances their motivation level, and job satisfaction on a regular basis.

Keywords: job satisfaction, motivation, organizational commitment, Pakistan, training

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Authors: Essa Njie

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One of the challenges that Africa needs to overcome for the sustenance of its democratic gains is to separate the state from the ruling party to avoid the latter’s attempt in monopolizing the former’s resources and institutions for political supremacy. But this separation must go along with the process of depoliticizing the civil services (separation from partisan politics) which have been politicized by incumbents to register electoral successes. While researches conducted on the Gambia’s democratic reality tend to have looked at a wide range of challenges confronting the country’s democratic progress, this paper focuses on state power monopolization and its impediment to democratic governance in the country. The paper explores the involvement of civil/public servants in partisan politics in the Gambia. It looks at the intertwined nature of the state and the ruling party as state resources could not be separated from that of the ruling party (lack of separation between political and non-political resources) in both Dawda Jawara and Yahya Jammeh eras, and how such affected the country’s democratic credential. The paper in particular addresses the need for the current government to depoliticize the country’s civil service and concomitantly separate the state from the ruling party by not monopolizing the former’s resources and institutions to galvanize political support.

Keywords: civil service, democratic consolidation, monopolisation, multi-party elections, public institutions, ruling party, state resources

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Authors: C. J. Coetzee, E. Horn

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One of the main challenges in using the Discrete Element Method (DEM) is to specify the correct input parameter values. In general, the models are sensitive to the input parameter values and accurate results can only be achieved if the correct values are specified. For the linear contact model, micro-parameters such as the particle density, stiffness, coefficient of friction, as well as the particle size and shape distributions are required. There is a need for a procedure to accurately calibrate these parameters before any attempt can be made to accurately model a complete bulk materials handling system. Since DEM is often used to model applications in the mining and quarrying industries, a calibration procedure was developed for materials that consist of relatively large (up to 40 mm in size) particles. A coarse crushed aggregate was used as the test material. Using a specially designed large shear box with a diameter of 590 mm, the confined Young’s modulus (bulk stiffness) and internal friction angle of the material were measured by means of the confined compression test and the direct shear test respectively. DEM models of the experimental setup were developed and the input parameter values were varied iteratively until a close correlation between the experimental and numerical results was achieved. The calibration process was validated by modelling the pull-out of an anchor from a bed of material. The model results compared well with experimental measurement.

Keywords: Discrete Element Method (DEM), calibration, shear box, anchor pull-out

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Authors: Marina Kartseva, Polina Kuznetsova

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In our work, we estimate the contribution of inequality of opportunity to inequality in the health of the Russian population aged 25 to 74 years. The empirical basis of the study is the nationally representative data of the RLMS for 2018. Individual health is measured using a self-reported status on five-point scale. The startconditions are characterized by parental education and place of birth (country, type of settlement). Personal efforts to maintain health include the level of education, smoking status, and physical activity. To understand how start opportunities affect an individual's health, we use the methodology proposed in (Trannoy et al., 2010), which takes into account both direct and indirect (through the influence on efforts) effects. Regression analysis shows that all other things being equal, the starting capabilities of individuals have a significant impact on their health. In particular, parental education has a positive effect on self-reported health. Birth in another country, in another settlement, and in an urban area, on the contrary, reduceself-reported health. This allows to conclude that there exists an unfair inequality in health, namely inequality caused by factors that are independent of a person's own efforts. We estimate the contribution of inequality of opportunity to inequality in health using a nonparametric approach (Checchi, Peragine, 2010; Lazar, 2013). According to the obtained results, the contribution of unfair inequality as 72-74% for the population as a whole, being slightly higher for women (62-74% and 60-69% for men and women, respectively) and for older age (59- 62% and 67-75% for groups 25-44 years old and 45-74 years old, respectively). The obtained estimates are comparable with the results for other countries and indicate the importance of the problem of inequality of opportunities in health in Russia.

Keywords: inequality of opportunity, inequality in health, self-reported health, efforts, health-related lifestyle, Russia, RLMS

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Authors: WonHo Lee, Hyo-Gyoung Kwak

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A numerical model considering slip behavior of steel-concrete composite structure is introduced. This model is based on a linear bond stress-slip relation along the interface. Single node was considered at the interface of steel and concrete member in finite element analysis, and it improves analytical problems of model that takes double nodes at the interface by adopting spring elements to simulate the partial interaction. The slip behavior is simulated by modifying material properties of steel element contacting concrete according to the derived formulation. Decreased elastic modulus simulates the slip occurrence at the interface and decreased yield strength simulates drop in load capacity of the structure. The model is verified by comparing numerical analysis applying this model with experimental studies. Acknowledgment—This research was supported by a grant(13SCIPA01) from Smart Civil Infrastructure Research Program funded by Ministry of Land, Infrastructure and Transport(MOLIT) of Korea government and Korea Agency for Infrastructure Technology Advancement(KAIA) and financially supported by Korea Ministry of Land, Infrastructure and Transport(MOLIT) as U-City Master and Doctor Course Grant Program.

Keywords: bond-slip, composite structure, partial interaction, steel-concrete structure

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Authors: Jane Mullen, Ann Rheaume, Kevin Kelloway

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Research on the effects of inconsistent safety leadership is limited, particularly regarding employee safety behavior in organizations. Inconsistent safety leadership occurs when organizational leaders display both effective and ineffective styles of safety leadership (i.e., transformational vs laissez-faire). In this study, we examine the effect of inconsistent safety leadership style on employee safety participation. Defined as the interaction of S.A.F.E.R (Speak, Act, Focus, Engage and Recognize) leadership style and passive leadership style, inconsistent safety leadership was found to be a significant predictor of safety participation in a sample of 307 nurses in Eastern Canada. Results of the moderated regression analysis also showed a significant main effect for S.A.F.E.R leadership, but not for passive leadership. To further explore the significant interaction, the simple slopes for S.A.F.E.R leadership at high and low levels (1 SD above and below the mean) of passive leadership were plotted. As predicted, the positive effects of S.A.F.E.R leadership behavior were attenuated when leaders were perceived by employees as also displaying high levels of passive leadership (i.e., inconsistent leadership styles). The research makes important theoretical and practical contributions to the occupational health and safety literature. The results demonstrate that leadership behavior, which is characteristic of the S.A.F.E.R model, is positively associated with employee safety participation. This finding is particularly important as researchers continue to explore what leaders can do to engage employees in work-related safety activities. The results also demonstrate how passive leadership may undermine the positive outcomes associated with safety leadership behavior in organizations. The data suggest that employee safety behavior is highest when leaders engage in safety effective leadership behavior on a consistent basis, rather than periodically.

Keywords: employee safety behavior, leadership, participation, safety training

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Authors: Korban Oosthuizen, Robert C. Luckay

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Due to the growing popularity of electric vehicles and the importance of cobalt as part of the cathode material for lithium-ion batteries, demand for this metal is on the rise. Recycling of the cathode materials by means of solvent extraction is an attractive means of recovering cobalt and easing the pressure on limited natural resources. In this study, a series of straight chain and macrocyclic diamine ligands were developed for the selective recovery of cobalt from the solution containing nickel and manganese by means of solvent extraction. This combination of metals is the major cathode material used in electric vehicle batteries. The ligands can be protonated and function as ion-pairing ligands targeting the anionic [CoCl₄]²⁻, a species which is not observed for Ni or Mn. Selectivity for Co was found to be good at very high chloride concentrations and low pH. Longer chains or larger macrocycles were found to enhance selectivity, and linear chains on the amide side groups also resulted in greater selectivity over the branched groups. The cation of the chloride salt used for adjusting chloride concentrations seems to play a major role in extraction through salting-out effects. The ligands developed in this study show good selectivity for Co over Ni and Mn but require very high chloride concentrations to function. This research does, however, open the door for further investigations into using diamines as solvent extraction ligands for the recovery of cobalt from spent lithium-ion batteries.

Keywords: hydrometallurgy, solvent extraction, cobalt, lithium-ion batteries

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Authors: A. Alhusban, M. Alqawasmeh, F. Alfawares

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Introduction: Despite improvements in stroke management, it remains the leading cause of disability worldwide. It has been suggested that enhancing brain angiogenesis after stroke will improve stroke outcome. Promoting post stroke angiogenesis requires the upregulation of angiogenic factors with a simultaneous reduction of anti-angiogenic factors. Thrombospondin-1 is the main anti-angiogenic protein in the living cells. Counterintuitively, it has been shown that animals with Thrombospondin-1 knockdown will have better stroke outcome. Data about the clinical significance of Thrombspondin-1 levels at the time of admission is still lacking. The objective of this work is to assess the association between serum Thrombospondin-1 levels measured at the time of admission and baseline neurologic severity after stroke. Patients and Methods: Blood samples were collected from patients admitted to the King Abdullah University Hospital (KAUH) with ischemic stroke at the time of admission and serum Thrombopsondin-1 levels were measured using ELISA. Patients neurologic severity was evaluated using the National Institute of Health Stroke Scale (NIHSS). Results: Samples from 50 patients admitted between January 2016 and December 2016 were collected. The median age of participants was 68 years and the median NIHSS was 3. Multinomial regression identified serum Thrombospondin-1 as an independent predictor of stroke outcome (p=0.003). Baseline serum Thrombsopondin-1 was negatively associated with NIHSS at the time of admission (spearman rho correlation coefficient=0.272, p=0.032). Conclusion: Serum Thrombospondin-1 at the time of admission may be a useful marker of stroke severity that predicts more severe neurologic severity.

Keywords: thrombospondin, stroke, neuroprotection, biomarkers

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Authors: Soha A. Bahanshal, Vaibhav Verdhan, Bayong Kim

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Graduation rates at six-year colleges are becoming a more essential indicator for incoming fresh students and for university rankings. Predicting student graduation is extremely beneficial to schools and has a huge potential for targeted intervention. It is important for educational institutions since it enables the development of strategic plans that will assist or improve students' performance in achieving their degrees on time (GOT). A first step and a helping hand in extracting useful information from these data and gaining insights into the prediction of students' progress and performance is offered by machine learning techniques. Data analysis and visualization techniques are applied to understand and interpret the data. The data used for the analysis contains students who have graduated in 6 years in the academic year 2017-2018 for science majors. This analysis can be used to predict the graduation of students in the next academic year. Different Predictive modelings such as logistic regression, decision trees, support vector machines, Random Forest, Naïve Bayes, and KNeighborsClassifier are applied to predict whether a student will graduate. These classifiers were evaluated with k folds of 5. The performance of these classifiers was compared based on accuracy measurement. The results indicated that Ensemble Classifier achieves better accuracy, about 91.12%. This GOT prediction model would hopefully be useful to university administration and academics in developing measures for assisting and boosting students' academic performance and ensuring they graduate on time.

Keywords: prediction, decision trees, machine learning, support vector machine, ensemble model, student graduation, GOT graduate on time

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Authors: Yiwei Li, Boyu Tian, Mingyu Gao

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Hybrid main memory systems combine both performance and capacity advantages from heterogeneous memory technologies. With larger capacities, higher associativities, and finer granularities, hybrid memory systems currently exhibit significant metadata storage and lookup overheads for flexibly remapping data blocks between the two memory tiers. To alleviate the inefficiencies of existing designs, we propose Trimma, the combination of a multi-level metadata structure and an efficient metadata cache design. Trimma uses a multilevel metadata table to only track truly necessary address remap entries. The saved memory space is effectively utilized as extra DRAM cache capacity to improve performance. Trimma also uses separate formats to store the entries with non-identity and identity mappings. This improves the overall remap cache hit rate, further boosting the performance. Trimma is transparent to software and compatible with various types of hybrid memory systems. When evaluated on a representative DDR4 + NVM hybrid memory system, Trimma achieves up to 2.4× and on average 58.1% speedup benefits, compared with a state-of-the-art design that only leverages the unallocated fast memory space for caching. Trimma addresses metadata management overheads and targets future scalable large-scale hybrid memory architectures.

Keywords: memory system, data cache, hybrid memory, non-volatile memory

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Authors: Omar A. Abuobidalla, Mingyuan Chen, Satyaveer S. Chauhan

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Railroad transportation of hazardous materials freights is important to the North America economics that supports the national’s supply chain. This paper introduces various extensions of the dynamic hazardous materials trip plan problems. The problem captures most of the operational features of a real-world railroad transportations systems that dynamically initiates a set of blocks and assigns each shipment to a single block path or multiple block paths. The dynamic hazardous materials trip plan policies have distinguishing features that are integrating the blocking plan, and the block activation decisions. We also present a non-linear mixed integer programming formulation for each variant and present managerial insights based on a hypothetical railroad network. The computation results reveal that the dynamic car scheduling policies are not only able to take advantage of the capacity of the network but also capable of diminishing the population, and environment risks by rerouting the active blocks along the least risky train services without sacrificing the cost advantage of the railroad. The empirical results of this research illustrate that the issue of integrating the blocking plan, and the train makeup of the hazardous materials freights must receive closer attentions.

Keywords: dynamic car scheduling, planning and scheduling hazardous materials freights, airborne hazardous materials, gaussian plume model, integrated blocking and routing plans, box model

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Authors: Lindiwe Ngcobo

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The aim of the study is to describe and understand the benefits and costs of having biogas digesters at both household and society level. On a household level, the purpose is to understand how rural households benefit from the biogas digesters, for example, by converting animal and human waste through biogas digesters, and at what costs the benefits are realized. At a societal level, the purpose is to understand the costs and benefits of biogas digesters relative to the situation of rural communities who do not have flush toilets and have no appropriate waste disposal services while they incur electricity costs. Multiple regression analysis was used to determine the effect of biogas digesters on electricity availability and waste management. The results showed that beneficiaries spent less on electricity using household waste, and also waste disposal costs were eliminated from household expenses. A move to biogas energy production can be beneficial to rural households. It is economically and environmentally friendly. Small-scale farmers need to be introduced to agricultural innovations that can assist them in producing nutritious crops at a low cost. This can be a good opportunity to start an agribusiness that focuses on organic crops. Extensions and training institutions have to play a part in supporting households to develop entrepreneurial skills. Cost-benefit analysis showed that the benefits of biogas exceed the costs of the biogas projects. This implies that this technology should be promoted in rural households. Government financial incentives must be put in place to motivate a generation of organic Agri-prenuers.

Keywords: Agri-prenuers, biogas digester, biogas energy, disposal costs

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Authors: Murast Dicleli, Ali SalemMilani

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In this paper, a summary of analytical and experimental studies into the behavior of a new hysteretic damper, designed for seismic protection of structures is presented. The Multi-directional Torsional Hysteretic Damper (MRSD) is a patented invention in which a symmetrical arrangement of identical cylindrical steel cores is so configured as to yield in torsion while the structure experiences planar movements due to earthquake shakings. The new device has certain desirable properties. Notably, it is characterized by a variable and controllable-via-design post-elastic stiffness. The mentioned property is a result of MRSD’s kinematic configuration which produces this geometric hardening, rather than being a secondary large-displacement effect. Additionally, the new system is capable of reaching high force and displacement capacities, shows high levels of damping, and very stable cyclic response. The device has gone through many stages of design refinement, multiple prototype verification tests and development of design guide-lines and computer codes to facilitate its implementation in practice. Practicality of the new device, as offspring of an academic sphere, is assured through extensive collaboration with industry in its final design stages, prototyping and verification test programs.

Keywords: seismic, isolation, damper, adaptive stiffness

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Authors: Ivanova B. Natalia, Djambova Т. Svetlana, Hristev S. Ivailo

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The acoustic properties of recycled felt panels have been investigated using various methods. Experimentally, the sound insulation of the panels has been evaluated for frequencies in the range of 600 Hz to 4000 Hz, utilizing a small-sized acoustic chamber. Additionally, the sound absorption coefficient for the frequency range of 63 Hz to 4000 Hz was measured according to the EN ISO 354 standard in a laboratory reverberation room. This research was deemed necessary after conducting reverberation time measurements of a university classroom following the EN ISO 3382-2 standard. The measurements indicated values of 2.86 s at 500 Hz, 3.23 s at 1000 Hz, and 2.53 s at 2000 Hz, which significantly exceeded the requirements set by the national regulatory framework (0.6s) for such premises. For this reason, recycled felt panels have been investigated in the laboratory, showing very good acoustic properties at high frequencies. To enhance performance in the low frequencies, the influence of the distance of the panel spacing was examined. Furthermore, the sound insulation of the panels was studied to expand the possibilities of their application, both for the acoustic treatment of educational and multifunctional halls and for sound insulation purposes (e.g., a suspended ceiling with an air gap passing from room to room). As a conclusion, a theoretical acoustic design of the classroom has been carried out with suggestions for improvements to achieve the necessary acoustic and aesthetic parameters for such rooms.

Keywords: acoustic panels, recycled felt, sound absorption, sound insulation, classroom acoustics

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Authors: Chao Sima, Shanaz Ghandhi, Sally A. Amundson, Michael L. Bittner, David J. Brenner

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In a large-scale radiologic emergency, potentially affected population need to be triaged efficiently using various biomarkers where personal dosimeters are not likely worn by the individuals. It has long been established that radiation injury can be estimated effectively using panels of genetic biomarkers. Furthermore, the rate of radiation, in addition to dose of radiation, plays a major role in determining biological responses. Therefore, a better and more accurate triage involves estimating both the dose level of the exposure and the length of time of that exposure. To that end, a large in vivo study was carried out on mice with internal emitter caesium-137 (¹³⁷Cs). Four different injection doses of ¹³⁷Cs were used: 157.5 μCi, 191 μCi, 214.5μCi, and 259 μCi. Cohorts of 6~7 mice from the control arm and each of the dose levels were sacrificed, and blood was collected 2, 3, 5, 7 and 14 days after injection for microarray RNA gene expression analysis. Using a generalized linear model with penalized maximum likelihood, a panel of 244 genes was established and both the doses of injection and the number of days after injection were accurately predicted for all 155 subjects using this panel. This has proven that microarray gene expression can be used effectively in radiation biodosimetry in predicting both the dose levels and the length of exposure time, which provides a more holistic view on radiation exposure and helps improving radiation damage assessment and treatment.

Keywords: caesium-137, gene expression microarray, multivariate responses prediction, radiation biodosimetry

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Authors: Carolyne Ndungu, Wesley Too, Diana Kassaman

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Diabetes is a global public health problem with an increasing morbidity and mortality rate across the globe. It is reported that 422 million people worldwide have diabetes with type 2 diabetes more common in people of African descent. Whilst prevalence of diabetes is four times more than it was in the last three decades, making it the world's ninth greatest cause of mortality, treatment of complications resulting from poor glycemic control is still high, contributing to poverty level in sub-Saharan. Poor treatment adherence has also been identified as a major contributing factor poor glycemic control among diabetic patients and still remains a significant challenge especially among patients living in rural Kenya. This study therefore seeks to identify gaps, barriers and challenges towards medication non-adherence among diabetic patients on follow-up at Kiambu County Referral Hospital, Kenya. Methods: A cross- sectional descriptive study was carried out at Gatundu Level five Hospital in Kiambu County. The study population consisted of adult patients with type two diabetes mellitus (T2DM) on follow up, at the Diabetes clinic between the month of June to July 2022. Systematic sampling of 200 participants was carried out. Ethical approvals from relevant authorities were done and ethical aspects of the study were also observed. Data analysis is ongoing using logistic regression analysis. Results, recommendations -contribution of this study will be highlighted within the next one month.

Keywords: adherence, diabetes, medication, Kenya

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Authors: Kamil Dydek, Szymon Demski, Kamil Majchrowicz, Paulina Kozera, Bogna Sztorch, Dariusz Brząkalski, Zuzanna Krawczyk, Robert Przekop, Anna Boczkowska

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Carbon fibre reinforced polymers (CFRPs) are characterized by very high strength and stiffness in relation to their weight. In addition, properties such as corrosion resistance and low thermal expansion allow them to replace traditional materials, i.e., wood or metals, in many industries such as aerospace, automotive, marine, and sports goods. However, CFRPs, have some disadvantages -they have relatively low electrical conductivity and break brittle, which significantly limits their application possibilities. Moreover, conventional CFRPs are usually manufactured based on thermosets, which makes them difficult to recycle. The solution to these drawbacks is the use of the innovative thermoplastic resin (ELIUM from ARKEMA) as a matrix of composites and the modification by introducing into their structure thermoplastic nonwovens based on PET-G with the addition of multi-wall carbon nanotubes (MWCNTs). The acrylic-carbon composites, which were produced by the infusion technique, were tested for mechanical, thermo-mechanical, and electrical properties, and the effect of modifications on their microstructure was studied. Acknowledgment: This study was carried out with funding from grant no. LIDER/46/0185/L-11/19/NCBR/2020, financed by The National Centre for Research and Development.

Keywords: CFRP, MWCNT, ELIUM, electrical properties, infusion

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Authors: Ruangdech Sirikit

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The purposes of this research were to study the variables affecting the quality assessment of mathematics subject in Thailand by using value-added analysis on TIMSS 2011. The data used in this research is the secondary data from the 2011 Trends in International Mathematics and Science Study (TIMSS), collected from 6,124 students in 172 schools from Thailand, studying only mathematics subjects. The data were based on 14 assessment tests of knowledge in mathematics. There were 3 steps of data analysis: 1) To analyze descriptive statistics 2) To estimate competency of students from the assessment of their mathematics proficiency by using MULTILOG program; 3) analyze value added in the model of quality assessment using Value-Added Model with Hierarchical Linear Modeling (HLM) and 2 levels of analysis. The research results were as follows: 1. Student level variables that had significant effects on the competency of students at .01 levels were Parental care, Resources at home, Enjoyment of learning mathematics and Extrinsic motivation in learning mathematics. Variable that had significant effects on the competency of students at .05 levels were Education of parents and self-confident in learning mathematics. 2. School level variable that had significant effects on competency of students at .01 levels was Extra large school. Variable that had significant effects on competency of students at .05 levels was medium school.

Keywords: quality assessment, value-added model, TIMSS, mathematics, Thailand

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Authors: Sandra Mitrovic, Gaurav Singh

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In many industries, including telecommunications, churn prediction has been a topic of active research. A lot of attention has been drawn on devising the most informative features, and this area of research has gained even more focus with spread of (social) network analytics. The call detail records (CDRs) have been used to construct customer networks and extract potentially useful features. However, to the best of our knowledge, no studies including network features have yet proposed a generic way of representing network information. Instead, ad-hoc and dataset dependent solutions have been suggested. In this work, we build upon a recently presented method (node2vec) to obtain representations for nodes in observed network. The proposed approach is generic and applicable to any network and domain. Unlike node2vec, which assumes a static network, we consider a dynamic and time-evolving network. To account for this, we propose an approach that constructs the feature representation of each node by generating its node2vec representations at different timestamps, concatenating them and finally compressing using an auto-encoder-like method in order to retain reasonably long and informative feature vectors. We test the proposed method on churn prediction task in telco domain. To predict churners at timestamp ts+1, we construct training and testing datasets consisting of feature vectors from time intervals [t1, ts-1] and [t2, ts] respectively, and use traditional supervised classification models like SVM and Logistic Regression. Observed results show the effectiveness of proposed approach as compared to ad-hoc feature selection based approaches and static node2vec.

Keywords: churn prediction, dynamic networks, node2vec, auto-encoders

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Authors: Frankie Burgos, Emely Munar, Conrado Basa

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This paper aimed at developing an artificial neural network (ANN) model specifically for the Philippine Stock Exchange index closing value. The inputs to the ANN are US Dollar and Philippine Peso(USD-PHP) exchange rate, GDP growth of the country, quarterly inflation rate, 10-year bond yield, credit rating of the country, previous open, high, low, close values and volume of trade of the Philippine Stock Exchange Index (PSEi), gold price of the previous day, National Association of Securities Dealers Automated Quotations (NASDAQ), Standard and Poor’s 500 (S & P 500) and the iShares MSCI Philippines ETF (EPHE) previous closing value. The target is composed of the closing value of the PSEi during the 627 trading days from November 3, 2011, to May 30, 2014. MATLAB’s Neural Network toolbox was employed to create, train and simulate the network using multi-layer feed forward neural network with back-propagation algorithm. The results satisfactorily show that the neural network developed has the ability to model the PSEi, which is affected by both internal and external economic factors. It was found out that the inputs used are the main factors that influence the movement of the PSEi closing value.

Keywords: artificial neural networks, artificial intelligence, philippine stocks exchange index, stocks trading

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Authors: Saw Thiha, Jay Rajasekera

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A boom in video conferencing generated millions of hours of video data daily to be analyzed. However, such enormous data pose certain scalability issues to be analyzed efficiently, let alone do it in real-time, as online conferences can involve hundreds of people and can last for hours. This paper proposes an efficient online proctoring solution that can analyze the online conferences real-time on edge devices such as Android, iOS, and desktops. Since the computation can be done upfront on the devices where online conferences take place, it can scale well without requiring intensive resources such as GPU servers and complex cloud infrastructure. According to the linear models, face orientation does indeed impact the perceived eye openness. Also, the proposed z score facial landmark standardization was proven to be functional in detecting face orientation and contributed to classifying eye blinks with single eyelid distance computation while achieving a better f1 score and accuracy than the Eye Aspect Ratio (EAR) threshold method. Last but not least, the authors implemented the solution natively in the MediaPipe framework and open-sourced it along with the reproducible experimental results on GitHub. The solution provides face orientation, eye blink, facial activity, and translation detections out of the box and is highly customizable and extensible.

Keywords: android, desktop, edge computing, blink, face orientation, facial activity and translation, MediaPipe, open source, real-time, video conference, web, iOS, Z score facial landmark standardization

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Authors: Christian Angerer, Markus Lienkamp

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Electric vehicles offer a high variety of possible drivetrain topologies with up to 4 motors. Multi-motor-designs can have several advantages regarding traction, vehicle dynamics, safety and even efficiency. With a rising number of motors, the whole drivetrain becomes more complex. All permutations of gearings, drivetrain-layouts, motor-types and –sizes lead up in a very large solution space. Single elements of this solution space can be analyzed by simulation methods. In addition to longitudinal vehicle behavior, which most optimization-approaches are restricted to, also lateral dynamics are important for vehicle dynamics, stability and efficiency. In order to compete large solution spaces and to find an optimal result, genetic algorithm based optimization is state-of-the-art. As lateral dynamics simulation is way more CPU-intensive, optimization takes much more time than in case of longitudinal-only simulation. Therefore, this paper shows an approach how to create meta-models from a 14-degree of freedom vehicle model in order to enable a numerically efficient drivetrain-layout optimization process under consideration of lateral dynamics. Different meta-modelling approaches such as neural networks or DoE are implemented and comparatively discussed.

Keywords: driving dynamics, drivetrain layout, genetic optimization, meta-modeling, lateral dynamicx

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Authors: Kalu Samuel Ukanwa, Kumar Patchigolla, Ruben Sakrabani

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The use of biosolids from thermal conversion of palm waste for soil fertility enhancement was tested in acidic soil of Southern Nigeria for the growing of Habanero chili pepper (Capsicum chinense jacq.). Soil samples from the two sites, showed pH 4.8 and 4.8 for site A and B respectively, below 5.6-6.8 optimum range and other fertility parameters indicating a low threshold for pepper growth. Nursery planting was done at different weeks to determine the optimum planting period. Ash analysis showed that it contains 26% of total K, 20% of total Ca, 0.27% of total P, and pH 11. The two sites were laid for an experiment in randomized complete block design and setup with three replications side by side. Each plot measured 3 x 2 m and a total of 15 plots for each site, four treatments, and one control. Outlined as control, 2, 4, 6 and 8 tonnes/hectare of palm waste ash, the combined average for both sites with correspondent yield after six harvests in one season are; 0, 5.8, 6, 6, 14.5 tonnes/hectare respectively to treatments. Optimum nursery survival rate was high in July; the crop yield was linear to the ash application. Site A had 6% yield higher than site B. Fruit development, weight, and total yield in relation to the control plot showed that palm waste ash is effective for soil amendment, nutrient delivery, and exchange.

Keywords: ash, palm waste, pepper, soil amendment

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Authors: Nihat Dipova, Bulent Cangir

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This article presents the results of probabilistic seismic hazard analysis (PSHA) for Antalya (SW Turkey). South west of Turkey is characterized by large earthquakes resulting from the continental collision between the African, Arabian and Eurasian plates and crustal faults. Earthquakes around the study area are grouped into two; crustal earthquakes (D=0-50 km) and subduction zone earthquakes (50-140 km). Maximum observed magnitude of subduction earthquakes is Mw=6.0. Maximum magnitude of crustal earthquakes is Mw=6.6. Sources for crustal earthquakes are faults which are related with Isparta Angle and Cyprus Arc tectonic structures. A new earthquake catalogue for Antalya, with unified moment magnitude scale has been prepared and seismicity of the area around Antalya city has been evaluated by defining ‘a’ and ‘b’ parameters of the Gutenberg-Richter recurrence relationship. The Standard Cornell-McGuire method has been used for hazard computation utilizing CRISIS2007 software. Attenuation relationships proposed by Chiou and Youngs (2008) has been used for 0-50 km earthquakes and Youngs et. al (1997) for deep subduction earthquakes. Finally, Seismic hazard map for peak horizontal acceleration on a uniform site condition of firm rock (average shear wave velocity of about 1130 m/s) at a hazard level of 10% probability of exceedance in 50 years has been prepared.

Keywords: Antalya, peak ground acceleration, seismic hazard assessment, subduction

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Authors: Manpreet Kaur, Amita Rani, Sanjay Kumar

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The Internet of Things (IoT), a cyber-physical paradigm, allows a large number of devices to connect and send the sensory data in the network simultaneously. This tremendous amount of data generated leads to very high network load consequently resulting in network congestion. It further amounts to frequent loss of useful information and depletion of significant amount of nodes’ energy. Therefore, there is a need to control congestion in IoT so as to prolong network lifetime and improve the quality of service (QoS). Hence, we propose a two-level clustering based routing algorithm considering congestion score and packet priority metrics that focus on minimizing the network congestion. In the proposed Priority based Congestion Control (PBCC) protocol the sensor nodes in IoT network form clusters that reduces the amount of traffic and the nodes are prioritized to emphasize important data. Simultaneously, a congestion score determines the occurrence of congestion at a particular node. The proposed protocol outperforms the existing Packet Discard Network Clustering (PDNC) protocol in terms of buffer size, packet transmission range, network region and number of nodes, under various simulation scenarios.

Keywords: internet of things, cyber-physical systems, congestion control, priority, transmission rate

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Authors: Yulmaida Amir, Fahrul Rozi, Insany C. Kamil, Fanny Aryani

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ODAPUS (Orang dengan Lupus) is an Indonesian term for people with Lupus, a chronic autoimmune disease in which immune system of the body becomes hyperactive and attacks normal tissue. The number of ODAPUS indicate an increase in Indonesia, thereby helping to improve their quality of life to be important to help their recovery. This study aims to examine the effect of resilience, self-esteem, and social support on the quality of life of women who had been diagnosed as having Lupus. Data were collected from 64 ODAPUS in Indonesia, using the World Health Organization Quality of Life (WHOQOL), Resilience Scale from Wagnil and Young (1993), self-esteem scale (developed from Coopersmith’s theory), and Social Support Questioner from Northouse (1988). Regression data analysis showed that resilience, social support, and self-esteem predict the quality of life of the ODAPUS simultaneously. If the variable was analysed individually, self-esteem did not significantly contribute to the quality of life. Resilience contributed most significantly to the quality of life, followed by social support. Of five sources of social supports included in the research, support from family members (parents and brother/sisters) has the most significant contribution to the quality of life, followed by support from spouse, and from friends. Interestingly, social support from medical personnel (medical doctors and nurses) had not a significant contribution to the quality of life of ODAPUS. As a conclusion, this research showed that the ability of ODAPUS to cope with difficulty in life, and support from family members, spouse, and friends were the significant predictors for their quality of life.

Keywords: quality of life, resilience, self-esteem, social supports

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Authors: Davit Shahnazaryan, Diogo Gomes, Mher Safaryan

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Many symbolic computations and manipulations required in the analysis of partial differential equations (PDE) or systems of PDEs are tedious and error-prone. These computations arise when determining conservation laws, entropies or integral identities, which are essential tools for the study of PDEs. Here, we discuss a new Mathematica package for the symbolic analysis of PDEs that automate multiple tasks, saving time and effort. Methodologies: During the research, we have used concepts of linear algebra and partial differential equations. We have been working on creating algorithms based on theoretical mathematics to find results mentioned below. Major Findings: Our package provides the following functionalities; finding symmetry group of different PDE systems, generation of polynomials invariant with respect to different symmetry groups; simplification of integral quantities by integration by parts and null Lagrangian cleaning, computing general forms of expressions by integration by parts; finding equivalent forms of an integral expression that are simpler or more symmetric form; determining necessary and sufficient conditions on the coefficients for the positivity of a given symbolic expression. Conclusion: Using this package, we can simplify integral identities, find conserved and dissipated quantities of time-dependent PDE or system of PDEs. Some examples in the theory of mean-field games and semiconductor equations are discussed.

Keywords: partial differential equations, symbolic computation, conserved and dissipated quantities, mathematica

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Authors: Bin Liu, Weijie Liu, Bin Sun, Yihui Luo

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In order to solve the problem of lower spatial resolution and block effect in the fusion method based on separable wavelet transform in the resulting fusion image, a new sampling mode based on multi-resolution analysis of two-channel non separable wavelet transform, whose dilation matrix is [1,1;1,-1], is presented and a multispectral image fusion method based on this kind of sampling mode is proposed. Filter banks related to this kind of wavelet are constructed, and multiresolution decomposition of the intensity of the MS and panchromatic image are performed in the sampled mode using the constructed filter bank. The low- and high-frequency coefficients are fused by different fusion rules. The experiment results show that this method has good visual effect. The fusion performance has been noted to outperform the IHS fusion method, as well as, the fusion methods based on DWT, IHS-DWT, IHS-Contourlet transform, and IHS-Curvelet transform in preserving both spectral quality and high spatial resolution information. Furthermore, when compared with the fusion method based on nonsubsampled two-channel non separable wavelet, the proposed method has been observed to have higher spatial resolution and good global spectral information.

Keywords: image fusion, two-channel sampled nonseparable wavelets, multispectral image, panchromatic image

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Authors: Nurul Aini Abdul Wahab, Nor Syamim Halidin, Sayidatina Aisah Masnan, Nur Izzati Romli

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There are many applications of principle component method for reducing the large set of variables in various fields. Fisher’s Discriminant function is also a popular tool for classification. In this research, the researcher focuses on studying the performance of Principle Component-Fisher’s Discriminant function in helping to classify rice kernels to their defined classes. The data were collected on the smells or odour of the rice kernel using odour-detection sensor, Cyranose. 32 variables were captured by this electronic nose (e-nose). The objective of this research is to measure how well a combination model, between principle component and linear discriminant, to be as a classification model. Principle component method was used to reduce all 32 variables to a smaller and manageable set of components. Then, the reduced components were used to develop the Fisher’s Discriminant function. In this research, there are 4 defined classes of rice kernel which are Aromatic, Brown, Ordinary and Others. Based on the output from principle component method, the 32 variables were reduced to only 2 components. Based on the output of classification table from the discriminant analysis, 40.76% from the total observations were correctly classified into their classes by the PC-Discriminant function. Indirectly, it gives an idea that the classification model developed has committed to more than 50% of misclassifying the observations. As a conclusion, the Fisher’s Discriminant function that was built on a 2-component from PCA (2-PC-D) is not satisfying to classify the rice kernels into its defined classes.

Keywords: classification model, discriminant function, principle component analysis, variable reduction

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Authors: Yan Liu

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The Gini coefficient indicates that the inequality of income distribution is rising in China. How individuals viewing the equality of current society is an important predicator of social turbulence. Perceptions of social justice may vary according to the social stratification. People usually use socioeconomic status to identify divisions between social stratifications. The objective of this study is to explore the potential influence of socioeconomic status on citizens’ perceptions of social justice in China. Socioeconomic status (SES) is usually reflected by either an SES indicator or a composite of three core dimensions: education, income and occupation. With data collected in the 2010 Chinese General Social Survey (CGSS), this study uses OLS regression analyses to examine the relationship between socioeconomic status (SES) and citizens’ perceptions of social justice. This study finds that most Chinese citizens believe that the current society is fair or more than fair. Socioeconomic status (SES) has a positive impact on citizens’ perceptions of social justice, which means individuals with higher indicator of socioeconomic status prefer to believe current society is fair. However, the three core dimensions which are used to measure socioeconomic status (SES) have different influences on perceptions of social justice: First, income helps enhance citizens’ sense of social justice. Second, education weakens citizens’ sense of social justice. Third, compared to the middle occupational status, people of both higher occupational status and lower occupational status have higher levels of perceptions of social justice. Though education creates a negative influence on perceptions of social justice, its effect is much weaker than that of income, which indicates income is a determining factor for enhancing people’s perceptions of social justice in China’s market society. Policy implications are discussed.

Keywords: education, income, occupation, perceptions of social justice, social stratification, socioeconomic status

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