Search results for: functional linear regression

Authors: N. F. Jamaluddin, N. A. H. Aizam

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This paper explains the educational timetabling problem, a type of scheduling problem that is considered as one of the most challenging problem in optimization and operational research. The university examination timetabling problem (UETP), which involves assigning a set number of exams into a set number of timeslots whilst fulfilling all required conditions, has been widely investigated. The limitation of available timeslots and resources with the increasing number of examinations are the main reasons in the difficulty of solving this problem. Dynamical change in the examination scheduling system adds up the complication particularly in coping up with the demand and new requirements by the communities. Our objective is to investigate these demands and requirements with subjects taken from Universiti Malaysia Terengganu (UMT), through questionnaires. Integer linear programming model which reflects the preferences obtained to produce an effective examination timetabling was formed.

Keywords: demands, educational timetabling, integer linear programming, scheduling, university examination timetabling problem (UETP)

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Authors: Abdel-Razzaq Mugdadi, Ruqayyah Sani

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The Kernel Distribution Function Estimator (KDFE) method is the most popular method for nonparametric estimation of the cumulative distribution function. The kernel and the bandwidth are the most important components of this estimator. In this investigation, we replace the kernel in the KDFE with a linear combination of kernels to obtain a new estimator based on the linear combination of kernels, the mean integrated squared error (MISE), asymptotic mean integrated squared error (AMISE) and the asymptotically optimal bandwidth for the new estimator are derived. We propose a new data-based method to select the bandwidth for the new estimator. The new technique is based on the Plug-in technique in density estimation. We evaluate the new estimator and the new technique using simulations and real-life data.

Keywords: estimation, bandwidth, mean square error, cumulative distribution function

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Authors: Shivani Sharma, Prashant Saxena, Inamul Hasan Madar

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Since the time of Darwin, it has been considered that genetic change is the direct indicator of variation in phenotype. But a few studies in system biology in the past years have proposed that epigenetic developmental processes also affect the phenotype thus shifting the focus from a linear genotype-phenotype map to a non-linear G-P map. In this paper, we attempt at explaining the evolution of colour vision in mammals by taking LWS/ Long-wave sensitive gene under consideration.

Keywords: evolution, phenotypes, epigenetics, LWS gene, G-P map

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Authors: Ghada Soltane

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The objective of this study was to identify factors impacting supply chain collaboration. a quantitative study was carried out on a sample of 84 Tunisian industrial companies. To verify the research hypotheses and test the direct effect of these factors on supply chain collaboration a multiple regression method was used using SPSS 26 software. The results show that there are four factors direct effects that affect supply chain collaboration in a meaningful and positive way, including: trust, engagement, information sharing and information quality

Keywords: supply chain collaboration, factors of collaboration, principal component analysis, multiple regression

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Authors: Fatma Abidi, Taoufik Harizi, Slah Msahli, Faouzi Sakli

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Nine different Tunisian handmade carpets were used for the investigation. The raw material of the carpet pile yarns was wool. The influence of the different structure parameters (linear density and pile height) on the carpet compression was investigated. Carpets were tested under dynamic loading in order to evaluate and observe the thickness loss and carpet behavior under dynamic loads. To determine the loss of pile height under dynamic loading, the pile height carpets were measured. The test method was treated according to the Tunisian standard NT 12.165 (corresponds to the standard ISO 2094). The pile height measurements are taken and recorded at intervals up to 1000 impacts (measures of this study were made after 50, 100, 200, 500, and 1000 impacts). The loss of pile height is calculated using the variation between the initial height and those measured after the number of reported impacts. The experimental results were statistically evaluated using Design Expert Analysis of Variance (ANOVA) software. As regards the deformation, results showed that both of the structure parameters of the pile yarn and the pile height have an influence. The carpet with the higher pile and the less linear density of pile yarn showed the worst performance. Results of a polynomial regression analysis are highlighted. There is a good correlation between the loss of pile height and the impacts number of dynamic loads. These equations are in good agreement with measured data. Because the prediction is reasonably accurate for all samples, these equations can also be taken into account when calculating the theoretical loss of pile height for the considered carpet samples. Statistical evaluations of the experimen¬tal data showed that the pile material and number of impacts have a significant effect on mean thickness and thickness loss variations.

Keywords: Tunisian handmade carpet, loss of pile height, dynamic loads, performance

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Authors: R. B. Knudsen, O. T. Rasmussen, R. A. Alphinas

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The reason for conducting this research is to develop an algorithm that is capable of classifying news articles from the automobile industry, according to the competitive actions that they entail, with the use of Text Mining (TM) methods. It is needed to test how to properly preprocess the data for this research by preparing pipelines which fits each algorithm the best. The pipelines are tested along with nine different classification algorithms in the realm of regression, support vector machines, and neural networks. Preliminary testing for identifying the optimal pipelines and algorithms resulted in the selection of two algorithms with two different pipelines. The two algorithms are Logistic Regression (LR) and Artificial Neural Network (ANN). These algorithms are optimized further, where several parameters of each algorithm are tested. The best result is achieved with the ANN. The final model yields an accuracy of 0.79, a precision of 0.80, a recall of 0.78, and an F1 score of 0.76. By removing three of the classes that created noise, the final algorithm is capable of reaching an accuracy of 94%.

Keywords: Artificial Neural network, Competitive dynamics, Logistic Regression, Text classification, Text mining

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Authors: Reji Thankachan, Varsha PS

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Both image capturing devices and human visual systems are nonlinear. Hence nonlinear filtering methods outperforms its linear counterpart in many applications. Linear methods are unable to remove impulsive noise in images by preserving its edges and fine details. In addition, linear algorithms are unable to remove signal dependent or multiplicative noise in images. This paper presents an approach to denoise and smoothen the Bipolar impulse noised images and videos using improved Kuwahara filter. It involves a 2 stage algorithm which includes a noise detection followed by filtering. Numerous simulation demonstrate that proposed method outperforms the existing method by eliminating the painting like flattening effect along the local feature direction while preserving edge with improvement in PSNR and MSE.

Keywords: bipolar impulse noise, Kuwahara, PSNR MSE, PDF

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Authors: Chung Hyun Goh, Armin Yazdanshenas, X. Neil Dong, Yong Tai Wang

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Physical rehabilitation is a necessary step in regaining lower body function after a partial paralysis caused by a spinal cord injury or a stroke. The purpose of this paper is to present the development and optimization of a training device that accurately recreates the motions in a gait cycle with the goal of rehabilitation for individuals with incomplete spinal cord injuries or who are victims of a stroke. A functional electrical stimulator was used in conjunction with the training device to stimulate muscle groups pertaining to rehabilitative walking. The feasibility and reliability of the design are presented. To validate the design functionality, motion analyses of the knee and ankle gait paths were made using motion capture systems. Key results indicate that the robotic walking training device provides a viable mode of physical rehabilitation.

Keywords: functional electrical stimulation, rehabilitative walking, robotic walking training device, spinal cord injuries

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Authors: Protus A. Lumiti, Susan O. Wekesa, Mary Omondi

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Performance is a key pillar to the accomplishment of the goals of all organizations, whether private, public or non- profit. Employees are the intellectual assets of the organization and they are an avenue to the achievement of competitive advantage. An employee welfare service in an organization is vital in fostering employee motivation and improving their productivity. In view of this, the main goal of this research was to determine the relationship between employee welfare practices and the performance of non-governmental organizations in Kenya. The study was guided by four objectives, namely: to establish, determine, evaluate and assess the relationship between employee welfare practices and the performance of non-governmental organizations in Kenya. The study utilized a survey design using both qualitative and quantitative approaches. In this study, a purposive, stratified and simple random sampling technique was used to arrive at a sample of 355 respondents who comprised senior managers, middle level managers and operational employees out of the targeted population of 14,283 employees of non-governmental organizations working in Nairobi County. The primary data collection tools were questionnaires supplemented by an interview schedule, while secondary data was obtained from reviewed journals, published books and articles. Data analysis was done using Statistical Packages for Social Sciences Software version 23. The study utilized multiple linear regression and a structural equation model. The findings of the study were that: employee welfare practices had a positive and significant relationship with the performance of Non-governmental organizations in Kenya. In addition, there was also a linear relationship between the independent variables and the dependent variable and the study concluded that there was a relationship between the predictor variable and the dependent variable of the study. The study recommended that management of No-governmental organization boards in Kenya should come up with a comprehensive policy document on employee welfare practices in order to enhance the performance of non-governmental organizations in Kenya.

Keywords: employee, economic, performance, welfare

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Authors: B. S Kaith, K. Sharma, V. Kumar, S. Kalia

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Superabsorbent are three-dimensional networks of linear or branched polymeric chains which can uptake large volume of biological fluids. The ability is due to the presence of functional groups like –NH2, -COOH and –OH. Such cross-linked products based on natural materials, such as cellulose, starch, dextran, gum and chitosan, because of their easy availability, low production cost, non-toxicity and biodegradability have attracted the attention of Scientists and Technologists all over the world. Since natural polymers have better biocompatibility and are non-toxic than most synthetic one, therefore, such materials can be applied in the preparation of controlled drug delivery devices, biosensors, tissue engineering, contact lenses, soil conditioning, removal of heavy metal ions and dyes. Gums are natural potential antioxidants and are used as food additives. They have excellent properties like high solubility, pH stability, non-toxicity and gelling characteristics. Till date lot of methods have been applied for the synthesis and modifications of cross-linked materials with improved properties suitable for different applications. It is well known that ion beam irradiation can play a crucial role to synthesize, modify, crosslink or degrade polymeric materials. High energetic heavy ions irradiation on polymer film induces significant changes like chain scission, cross-linking, structural changes, amorphization and degradation in bulk. Various researchers reported the effects of low and heavy ion irradiation on the properties of polymeric materials and observed significant improvement in optical, electrical, chemical, thermal and dielectric properties. Moreover, modifications induced in the materials mainly depend on the structure, the ion beam parameters like energy, linear energy transfer, fluence, mass, charge and the nature of the target material. Ion-beam irradiation is a useful technique for improving the surface properties of biodegradable polymers without missing the bulk properties. Therefore, a considerable interest has been grown to study the effects of SHIs irradiation on the properties of synthesized semi-IPNs and IPNs. The present work deals with the preparation of semi-IPNs and IPNs and impact of SHI like O7+ and Ni9+ irradiation on optical, chemical, structural, morphological and thermal properties along with impact on different applications. The results have been discussed on the basis of Linear Energy Transfer (LET) of the ions.

Keywords: adsorbent, gel, IPNs, semi-IPNs

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Authors: Jason Sheng-Hong Tsai, Faezeh Ebrahimzadeh, Min-Ching Chung, Shu-Mei Guo, Leang-San Shieh, Tzong-Jiy Tsai, Li Wang

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In this paper, we first construct a new state and disturbance estimator using discrete-time proportional plus integral observer to estimate the system state and the unknown external disturbance for the discrete-time system with an input-to-output direct-feedthrough term. Then, the generalized optimal linear quadratic digital tracker design is applied to construct a proportional plus integral observer-based tracker for the system with an unknown external disturbance to have a desired tracking performance. Finally, a numerical simulation is given to demonstrate the effectiveness of the new application of our proposed approach.

Keywords: non-minimum phase system, optimal linear quadratic tracker, proportional plus integral observer, state and disturbance estimator

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Authors: G. Espriú-Pérez, F. A. Vargas-Oviedo, I. Zenteno-Aguirrezábal, M. D. Moya-Bencomo

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One of the injuries with a higher incidence among university-level athletes in the North of Mexico is presented in the knee. This injury generates absenteeism in training and competitions for at least 8 weeks. There is no active quantitative methodology, or protocol, that directly contributes to the clinical evaluation performed by the medical personnel at the prevalence of knee injuries. The main objective is to contribute with a quantitative tool that allows further development of preventive and corrective measures to these injuries. The study analyzed 55 athletes for 6 weeks, belonging to the disciplines of basketball, volleyball, soccer and swimming. Using a motion capture system (Nexus®, Vicon®), a three-dimensional analysis was developed that allows the measurement of the range of movement of the joint. To focus on the performance of the lower limb, eleven different movements were chosen from the Functional Performance Test, Functional Movement Screen, and the Cincinnati Jump Test. The research identifies the profile of the natural movement of a healthy knee, with the use of medical guidance, and its differences between each sport. The data recovered by the single-leg crossover hop managed to differentiate the type of knee movement among athletes. A maximum difference of 60° of offset was found in the adduction movement between male and female athletes of the same discipline. The research also seeks to serve as a guideline for the implementation of protocols that help identify the recovery level of such injuries.

Keywords: Cincinnati jump test, functional movement screen, functional performance test, knee, motion capture system

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Authors: Surinder Deswal, Mahesh Pal

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The paper investigates the potential of support vector machines based regression approach to model the mass transfer capacity of multiple plunging jets, both vertical (θ = 90°) and inclined (θ = 60°). The data set used in this study consists of four input parameters with a total of eighty eight cases. For testing, tenfold cross validation was used. Correlation coefficient values of 0.971 and 0.981 (root mean square error values of 0.0025 and 0.0020) were achieved by using polynomial and radial basis kernel functions based support vector regression respectively. Results suggest an improved performance by radial basis function in comparison to polynomial kernel based support vector machines. The estimated overall mass transfer coefficient, by both the kernel functions, is in good agreement with actual experimental values (within a scatter of ±15 %); thereby suggesting the utility of support vector machines based regression approach.

Keywords: mass transfer, multiple plunging jets, support vector machines, ecological sciences

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Authors: Davood Rajabi, Mojgan Yazdani

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Non-linear Muskingum model is an efficient method for flood routing, however, the efficiency of this method is influenced by three applied parameters. Therefore, efficiency assessment of Imperialist Competition Algorithm (ICA) to evaluate optimum parameters of non-linear Muskingum model was addressed through this study. In addition to ICA, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) were also used aiming at an available criterion to verdict ICA. In this regard, ICA was applied for Wilson flood routing; then, routing of two flood events of DoAab Samsami River was investigated. In case of Wilson flood that the target function was considered as the sum of squared deviation (SSQ) of observed and calculated discharges. Routing two other floods, in addition to SSQ, another target function was also considered as the sum of absolute deviations of observed and calculated discharge. For the first floodwater based on SSQ, GA indicated the best performance, however, ICA was on first place, based on SAD. For the second floodwater, based on both target functions, ICA indicated a better operation. According to the obtained results, it can be said that ICA could be used as an appropriate method to evaluate the parameters of Muskingum non-linear model.

Keywords: Doab Samsami river, genetic algorithm, imperialist competition algorithm, meta-exploratory algorithms, particle swarm optimization, Wilson flood

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Authors: Quan Gu, Daniel Dimitrov

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BingleSeq was developed as a shiny-based, intuitive, and comprehensive application that enables the analysis of single-Cell RNA-Sequencing count data. This was achieved via incorporating three state-of-the-art software packages for each type of RNA sequencing analysis, alongside functional annotation analysis and a way to assess the overlap of differential expression method results. At its current state, the functionality implemented within BingleSeq is comparable to that of other applications, also developed with the purpose of lowering the entry requirements to RNA Sequencing analyses. BingleSeq is available on GitHub and will be submitted to R/Bioconductor.

Keywords: bioinformatics, functional annotation analysis, single-cell RNA-sequencing, transcriptomics

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Authors: Kristina Colovic, Mari Janikian, Nikolaos Takis, Fotini-Sonia Apergi

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A considerable number of Afghan asylum seekers in Greece are still waiting for answers about their future and status for personal, social and societal advancement. Most have been trapped in a stalemate of continuously postponed or temporarily progressed levels of integration into the EU/Greek process of asylum. Limited quantitative research exists investigating the psychological effects of long-term displacement among Afghans refugees in Greece. The purpose of this study is to investigate factors that are associated with and predict psychological distress symptoms among this population. Data from a sample of native Afghan nationals (N > 70) living in Greece for approximately the last ten years will be collected from May to July 2016. Criteria for participation include the following: being 18 years of age or older, and emigration from Afghanistan to Greece from 2003 onwards (i.e., long-term refugees or part of the 'old system of asylum'). Snowball sampling will be used to recruit participants, as this is considered the most effective option when attempting to study refugee populations. Participants will complete self-report questionnaires, consisting of the Afghan Symptom Checklist (ASCL), a culturally validated measure of psychological distress, the World Health Organization Quality of Life scale (WHOQOL-BREF), an adapted version of the Comprehensive Trauma Inventory-104 (CTI-104), and a modified Psychological Acculturation Scale. All instruments will be translated in Greek, through the use of forward- and back-translations by bilingual speakers of English and Greek, following WHO guidelines. A pilot study with 5 Afghan participants will take place to check for discrepancies in understanding and for further adapting the instruments as needed. Demographic data, including age, gender, year of arrival to Greece and current asylum status will be explored. Three different types of analyses (descriptive statistics, bivariate correlations, and multivariate linear regression) will be used in this study. Descriptive findings for respondent demographics, psychological distress symptoms, traumatic life events and quality of life will be reported. Zero-order correlations will assess the interrelationships among demographic, traumatic life events, psychological distress, and quality of life variables. Lastly, a multivariate linear regression model will be estimated. The findings from the study will contribute to understanding the determinants of acculturation, distress and trauma on daily functioning for Afghans in Greece. The main implications of the current study will be to advocate for capacity building and empower communities through effective program evaluation and design for mental health services for all refugee populations in Greece.

Keywords: Afghan refugees, evaluation, Greece, mental health, quality of life

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Authors: Ahmed Torad

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Background: Knee osteoarthritis (OA) is a prevalent musculoskeletal condition characterized by pain and functional impairment. While various rehabilitation approaches have been employed, the effectiveness of high-intensity interval training (HIIT) compared to traditional rehabilitation exercises remains unclear. Objective: This randomized controlled trial aimed to compare the effects of HIIT and traditional rehabilitation exercises on pain reduction, functional improvement, and quality of life in individuals with knee OA. Methods: A total of 120 participants diagnosed with knee OA were randomly allocated into two groups: the HIIT group (n=60) and the traditional rehabilitation group (n=60). The HIIT group participated in a 12-week supervised program consisting of high-intensity interval exercises, while the traditional rehabilitation group followed a conventional physiotherapy regimen. Outcome measures included visual analog scale (VAS) pain scores, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), and the Short Form-36 Health Survey (SF-36) at baseline and after the intervention period. Results: Both groups showed significant improvements in pain scores, functional outcomes (WOMAC), and quality of life (SF-36) after 12 weeks of intervention. However, the HIIT group demonstrated superior pain reduction (p<0.001), functional improvement (p<0.001), and physical health-related quality of life (p=0.002) compared to the traditional rehabilitation group. No significant differences were observed in mental health-related quality of life between the two groups. Conclusion: High-intensity interval training appears to be a more effective rehabilitation approach than traditional exercises for individuals with knee osteoarthritis, resulting in greater pain reduction, improved function, and enhanced physical health-related quality of life. These findings suggest that HIIT may represent a promising intervention strategy for managing knee OA and enhancing the overall well-being of affected individuals.

Keywords: knee osteoarthritis, high-intensity interval training, traditional rehabilitation exercises, randomized controlled trial, pain reduction, functional improvement, quality of life

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Authors: Aslı Taş, Şebnem Ertaş

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Culture consists of material and spiritual values adopted by the emerging societies during the historical and social processes and continues to exist from past to present by being transferred through generations. Culture and cultural sustainability are interdependent concepts. Cultural sustainability exists when the requirements established cultural expression are added to the social life as lifestyle and habits. However, sustainability renders change inevitable. Changes that take place in the culture of a society also shows the impact in the daily life places. Functional changes occur in the spaces in order to adapt particularly to cultural change that appear in the aftermath of the user change, to modern technology and living standards. In this context, in this study, it was aimed to investigate the effect of the time-dependent functional changes that took place in the housing where non-Muslim population who was subject to population exchange and Muslim population lived after the population exchange in the vacated housing in Sille. Therefore, the changed and newly added venues in the house belonging to Ali Oğuz in Hacı Ali Ağa Street were investigated over the generated graphic in order to clearly perceive the cultural exchange on the housing and settlement and the functional changes were demonstrated.

Keywords: culture, house, spatial changes, sustainability

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Authors: Cherifi Mehdi, Lahdir Mourad, Ameur Soltane

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Image compression is used to reduce the number of bits required to represent an image. The Meteosat Second Generation satellite (MSG) allows the acquisition of 12 image files every 15 minutes. Which results a large databases sizes. The transform selected in the images compression should contribute to reduce the data representing the images. The Radon transform retrieves the Radon points that represent the sum of the pixels in a given angle for each direction. Linear predictive coding (LPC) with filtering provides a good decorrelation of Radon points using a Predictor constitute by the Symmetric Nearest Neighbor filter (SNN) coefficients, which result losses during decompression. Finally, Run Length Coding (RLC) gives us a high and fixed compression ratio regardless of the input image. In this paper, a novel image compression method based on the Radon transform and linear predictive coding (LPC) for MSG images is proposed. MSG image compression based on the Radon transform and the LPC provides a good compromise between compression and quality of reconstruction. A comparison of our method with other whose two based on DCT and one on DWT bi-orthogonal filtering is evaluated to show the power of the Radon transform in its resistibility against the quantization noise and to evaluate the performance of our method. Evaluation criteria like PSNR and the compression ratio allows showing the efficiency of our method of compression.

Keywords: image compression, radon transform, linear predictive coding (LPC), run lengthcoding (RLC), meteosat second generation (MSG)

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Authors: Abdulrahman Sumayli, Saad M. AlShahrani

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For the hydrogenation process, knowing the solubility of hydrogen (H2) in hydrocarbons is critical to improve the efficiency of the process. We investigated the H2 solubility computation in four heavy crude oil feedstocks using machine learning techniques. Temperature, pressure, and feedstock type were considered as the inputs to the models, while the hydrogen solubility was the sole response. Specifically, we employed three different models: Support Vector Regression (SVR), Gaussian process regression (GPR), and Bayesian ridge regression (BRR). To achieve the best performance, the hyper-parameters of these models are optimized using the whale optimization algorithm (WOA). We evaluated the models using a dataset of solubility measurements in various feedstocks, and we compared their performance based on several metrics. Our results show that the WOA-SVR model tuned with WOA achieves the best performance overall, with an RMSE of 1.38 × 10− 2 and an R-squared of 0.991. These findings suggest that machine learning techniques can provide accurate predictions of hydrogen solubility in different feedstocks, which could be useful in the development of hydrogen-related technologies. Besides, the solubility of hydrogen in the four heavy oil fractions is estimated in different ranges of temperatures and pressures of 150 ◦C–350 ◦C and 1.2 MPa–10.8 MPa, respectively

Keywords: temperature, pressure variations, machine learning, oil treatment

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Authors: Ozden Saygili, Eser Cakti

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The masonry building stock in Istanbul and in other cities of Turkey are exposed to significant earthquake hazard. Determination of the safety of masonry structures against earthquakes is a complex challenge. This study deals with experimental tests and non-linear dynamic analysis of masonry structures modeled through discrete element method. The 1:10 scale model of Mustafa Paşa Mosque was constructed and the data were obtained from the sensors on it during its testing on the shake table. The results were used in the calibration/validation of the numerical model created on the basis of the 1:10 scale model built for shake table testing. 3D distinct element model was developed that represents the linear and nonlinear behavior of the shake table model as closely as possible during experimental tests. Results of numerical analyses with those from the experimental program were compared and discussed.

Keywords: dynamic analysis, non-linear modeling, shake table tests, masonry

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Authors: Klary Geisler, Dalit Lev-Arey, Yael Hacohen

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It is a well-known fact that exercise has favorable effects on people's physical health, as well as mental well-being. However, as for as excessive exercise, it may likely elevate negative consequences (e.g., physical injuries, negligence of everyday responsibilities such as work, family life). Lately, there is a growing interest in exercise addiction, sometimes referred to as exercise dependence, which is defined as a craving for physical activity that results in extreme work-out sessions and generates negative physiological and psychological symptoms (e.g., withdrawal symptoms, tolerance, social conflict). Exercise addiction is considered a behavioral addiction, yet it was not included in the latest editions of the diagnostic and statistical manual of mental disorders (DSM-IV), due to lack of significant research. Specifically, there is scarce research on the relationship between exercise addiction and personality dimensions. The purpose of the current research was to examine the relationship between primary exercise addiction symptoms and the big five dimensions, perfectionism (high performance expectations and self-critical performance evaluations) and subjective affect. participants were 152 trainees on a variety of aerobic sports activities (running, cycling, swimming) that were recruited through sports groups and trainers. 88% of participants trained for at least 5 hours per week, 24% of the participants trained above 10 hours per week. To test the predictive ability of the IVs a hierarchical linear regression with forced block entry was performed. It was found that Neuroticism significantly predicted exercise addiction symptoms (20% of the variance, p<0.001), while consciousness was negatively correlated with exercise addiction symptoms (14% of variance p<0.05); both had a unique contribution. Other dimensions of the big five (agreeableness, openness and extraversion) did not have any contribution to the dependent. Moreover, maladaptive perfectionism (self-critical performance evaluations) significantly predicted exercise addiction symptoms as well (10% of the variance P < 0.05). The overall regression model explained 54% of variance.

Keywords: big five, consciousness, excessive exercise, exercise addiction, neuroticism, perfectionism, personality

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Authors: Ridha Fethi Mechlouch, Ahlem Ayadi, Ammar Ben Brahim

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Given the importance of the preservation of polyphenols and carotenoids during thermal processing, we attempted in this study to investigate the variation of these two parameters in faba beans during microwave treatment using different power densities (1; 2; and 3W/g), then to perform a mathematical modeling by using non-linear regression analysis to evaluate the models constants. The variation of the carotenoids and polyphenols ratio of faba beans and the models are tested to validate the experimental results. Exponential models were found to be suitable to describe the variation of caratenoid ratio (R²= 0.945, 0.927 and 0.946) for power densities (1; 2; and 3W/g) respectively, and polyphenol ratio (R²= 0.931, 0.989 and 0.982) for power densities (1; 2; and 3W/g) respectively. The effect of microwave power density Pd(W/g) on the coefficient k of models were also investigated. The coefficient is highly correlated (R² = 1) and can be expressed as a polynomial function.

Keywords: microwave treatment, power density, carotenoid, polyphenol, modeling

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Authors: Itiola Kehinde Adeniran

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The study examined the effect of employees’ training on the performance of small scale enterprises in Oyo State. A structured questionnaire was used to collect data from 150 respondents through purposive sampling method. Linear regression was used with the aid of statistical package for social science (SPSS) version 20 to analyze the data collected in order to examine the effect of independent variable, employees’ training on dependent variable, performance (profit) of small scale enterprises. The result revealed that employees’ training has a significant effect on the performance of small scale enterprises. It was concluded that predictor variable namely (training) is 55.5% variance of enterprises performance (profitability). Therefore, the paper recommended that all small scale enterprises in Nigeria should embrace manpower training and development in order to improve employees’ performance leading to organizational profitability.

Keywords: training, employee performance, small scale enterprise, organizational profitability

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Authors: Hellal Abdelkader, Chafaa Salah, Boudjemaa Fouzia

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A new, convenient, and high yielding procedure for the preparation of diethyl α-aminophosphonates in water via Kabachnik-Fields reaction by one-pot reaction of aromatic aldehydes, ortho-aminophenols, and dialkylphosphites in the presence of a low catalytic amount of citric, malic, tartaric, and oxalic acids as a natural, bi-functional, and highly stable catalyst is described, the obtained products were characterized by elemental analyses, molar conductance, magnetic susceptibility, FTIR, Uv-Vis spectral data, NMR-C, NMR-H, and NMR-P analyses.

Keywords: α-aminophosphonates, aminophenols, natural acids, aqueous media, Kabachnik-Fields reaction

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Authors: Benjamin Bobbia, Matthias Picard

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In recent years active learning methodologies based on the representativity of the data seems more promising to limit overfitting. The presented query methodology for regression using the Wasserstein distance measuring the representativity of our labelled dataset compared to the global distribution. In this work a crucial use of GroupSort Neural Networks is made therewith to draw a double advantage. The Wasserstein distance can be exactly expressed in terms of such neural networks. Moreover, one can provide explicit bounds for their size and depth together with rates of convergence. However, heterogeneity of the dataset is also considered by weighting the Wasserstein distance with the error of approximation at the previous step of active learning. Such an approach leads to a reduction of overfitting and high prediction performance after few steps of query. After having detailed the methodology and algorithm, an empirical study is presented in order to investigate the range of our hyperparameters. The performances of this method are compared, in terms of numbers of query needed, with other classical and recent query methods on several UCI datasets.

Keywords: active learning, Lipschitz regularization, neural networks, optimal transport, regression

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

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

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

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Authors: O. M. Bamigbola, A. A. Ibrahim

Abstract:

Analysis of real life problems often results in linear systems of equations for which solutions are sought. The method to employ depends, to some extent, on the properties of the coefficient matrix. It is not always feasible to solve linear systems of equations by direct methods, as such the need to use an iterative method becomes imperative. Before an iterative method can be employed to solve a linear system of equations there must be a guaranty that the process of solution will converge. This guaranty, which must be determined a priori, involve the use of some criterion expressible in terms of the entries of the coefficient matrix. It is, therefore, logical that the convergence criterion should depend implicitly on the algebraic structure of such a method. However, in deference to this view is the practice of conducting convergence analysis for Gauss-Seidel iteration on a criterion formulated based on the algebraic structure of Jacobi iteration. To remedy this anomaly, the Gauss-Seidel iteration was studied for its algebraic structure and contrary to the usual assumption, it was discovered that some property of the iteration matrix of Gauss-Seidel method is only diagonally dominant in its first row while the other rows do not satisfy diagonal dominance. With the aid of this structure we herein fashion out an improved version of Gauss-Seidel iteration with the prospect of enhancing convergence and robustness of the method. A numerical section is included to demonstrate the validity of the theoretical results obtained for the improved Gauss-Seidel method.

Keywords: linear algebraic system, Gauss-Seidel iteration, algebraic structure, convergence

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Authors: Chaimongkol Limpianchob

Abstract:

This work addresses the problem of production planning that arises in the production of aromatic coconuts from Samudsakhorn province in Thailand. The planning involves the forwarding of aromatic coconuts from the harvest areas to the factory, which is classified into two groups; self-owned areas and contracted areas, the decisions of aromatic coconuts flow in the plant, and addressing a question of which warehouse will be in use. The problem is formulated as a mixed-integer linear programming model within supply chain management framework. The objective function seeks to minimize the total cost including the harvesting, labor and inventory costs. Constraints on the system include the production activities in the company and demand requirements. Numerical results are presented to demonstrate the feasibility of coconuts supply chain model compared with base case.

Keywords: aromatic coconut, supply chain management, production planning, mixed-integer linear programming

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Authors: Gopal Chandra Saha, Sumanta Daw

Abstract:

Warm-up is an essential component for optimizing performance in various sports before a physical fitness training session. This study investigated the immediate comparative effect of Self-Myofascial Release through vibration rolling (VR), non-vibration rolling (NVR), and static stretching as a part of a warm-up treatment on the functional fitness of young adults. Functional fitness is a classification of training that prepares the body for real-life movements and activities. For the present study 20male physical education students were selected as subjects. The age of the subjects was ranged from 20-25 years. The functional fitness variables undertaken in the present study were flexibility, muscle strength, agility, static and dynamic balance of the lower extremity. Each of the three warm-up protocol was administered on consecutive days, i.e. 24 hr time gap and all tests were administered in the morning. The mean and SD were used as descriptive statistics. The significance of statistical differences among the groups was measured by applying ‘F’-test, and to find out the exact location of difference, Post Hoc Test (Least Significant Difference) was applied. It was found from the study that only flexibility showed significant difference among three types of warm-up exercise. The observed result depicted that VR has more impact on myofascial release in flexibility in comparison with NVR and stretching as a part of warm-up exercise as ‘p’ value was less than 0.05. In the present study, within the three means of warm-up exercises, vibration roller showed better mean difference in terms of NVR, and static stretching exercise on functional fitness of young physical education practitioners, although the results were found insignificant in case of muscle strength, agility, static and dynamic balance of the lower extremity. These findings suggest that sports professionals and coaches may take VR into account for designing more efficient and effective pre-performance routine for long term to improve exercise performances. VR has high potential to interpret into an on-field practical application means.

Keywords: self-myofascial release, functional fitness, foam roller, physical education

Procedia PDF Downloads 132