Search results for: multi regression analysis

Authors: Aydin Teymourifar, Gurkan Ozturk

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In this paper, a hybrid Tabu Search (TS) algorithm is suggested for the multi-objective job shop scheduling problems (MO-JSSPs). The algorithm integrates several shifting bottleneck based neighborhood structures with the Giffler & Thompson algorithm, which improve efficiency of the search. Diversification and intensification are provided with local and global left shift algorithms application and also new semi-active, active, and non-delay schedules creation. The suggested algorithm is tested in the MO-JSSPs benchmarks from the literature based on the Pareto optimality concept. Different performances criteria are used for the multi-objective algorithm evaluation. The proposed algorithm is able to find the Pareto solutions of the test problems in shorter time than other algorithm of the literature.

Keywords: tabu search, heuristics, job shop scheduling, multi-objective optimization, Pareto optimality

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Authors: Naman Solanki, Souraj Mondal

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With the world moving towards online communication, the video datastore has exploded in the past few years. Consequently, it has become crucial to analyse participant’s engagement levels in online communication videos. Engagement prediction of people in videos can be useful in many domains, like education, client meetings, dating, etc. Video-level or frame-level prediction of engagement for a user involves the development of robust models that can capture facial micro-emotions efficiently. For the development of an engagement prediction model, it is necessary to have a widely-accepted standard dataset for engagement analysis. DAiSEE is one of the datasets which consist of in-the-wild data and has a gold standard annotation for engagement prediction. Earlier research done using the DAiSEE dataset involved training and testing standard models like CNN-based models, but the results were not satisfactory according to industry standards. In this paper, a multi-level classification approach has been introduced to create a more robust model for engagement analysis using the DAiSEE dataset. This approach has recorded testing accuracies of 0.638, 0.7728, 0.8195, and 0.866 for predicting boredom level, engagement level, confusion level, and frustration level, respectively.

Keywords: computer vision, engagement prediction, deep learning, multi-level classification

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Authors: Zijian Zhang, Yangyang Dong

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Synchronization is of great importance to ensure the multi-arm robot to complete the task. Therefore, a synchronous controller is designed to coordinate task space motion of the multi-arm in the paper. The position error, the synchronous position error, and the coupling position error are all considered in the controller. Besides, an adaptive control method is used to adjust parameters of the controller to improve the effectiveness of coordinated control performance. Simulation in the Matlab shows the effectiveness of the method. At last, a robot experiment platform with two 7-DOF (Degree of Freedom) robot arms has been established and the synchronous controller simplified to control dual-arm robot has been validated on the experimental set-up. Experiment results show the position error decreased 10% and the corresponding frequency is also greatly improved.

Keywords: synchronous control, space robot, task space control, multi-arm robot

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Authors: Festus Epetimehin

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Agriculture remains the dominant sector in the rural areas where over 70% of Nigerian reside and it’s still the backbone of our economy. The observed poor performance of farmers in agricultural productivity is due to the nature of risks and uncertainties in agriculture.Agricultural insurance is one of the mechanisms by which farmers can stabilize farm income and investment. The study examined the relationship between agricultural insurance scheme (AIS) and performance of agribusiness in Nigeria. The study adopted exploratory research design which is an ex-ante research approach. One hundred copies of structured questionnaire were administered for the purpose of the study. Correlation analysis and regression analysis were employed for the study. The correlation analysis of the finding revealed that the independent variable; agricultural insurance scheme (AIS) is positively and significantly correlated with the set of dependent variables; where turnover (ABT)=0.582**, profitability (ABP)=0.321**, solvency (ABS)=0.418**and cost of production (ABC)=0.23** respectively. The regression analysis result also revealed the degree of relationship between the independent variable (AIS) and set of dependent variables where one(1%) percent increase in independent variable will lead to 33.9% (ABT), 9.7% (ABP), 17.5%(ABS) and 1.5%(ABC).The study recommended that the Federal Government in collaboration with the participating Agricultural insurers embark on awareness campaign through to the length and breadth of Nigeria on government support and insurance scheme for farmers. Government should also ensure that the loan and insurance scheme should extend beyond the mechanized farmers and include the intensive subsistence farmers in view of the fact that they are the dominants in most of the farm produce markets.

Keywords: agribusiness, agricultural insurance, performance, turnover, solvency, agricultural risks

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Authors: Tahir Nawaz Cheema, Dumitru Baleanu, Ali Raza

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In this research work, we design intelligent computing through Bayesian Regularization artificial neural networks (BRANNs) introduced to solve the mathematical modeling of infectious diseases (Covid-19). The dynamical transmission is due to the interaction of people and its mathematical representation based on the system's nonlinear differential equations. The generation of the dataset of the Covid-19 model is exploited by the power of the explicit Runge Kutta method for different countries of the world like India, Pakistan, Italy, and many more. The generated dataset is approximately used for training, testing, and validation processes for every frequent update in Bayesian Regularization backpropagation for numerical behavior of the dynamics of the Covid-19 model. The performance and effectiveness of designed methodology BRANNs are checked through mean squared error, error histograms, numerical solutions, absolute error, and regression analysis.

Keywords: mathematical models, beysian regularization, bayesian-regularization backpropagation networks, regression analysis, numerical computing

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Authors: Liwei Liu, Shuguo Pan, Wang Gao

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In order to take full advantages of the BDS-3 penta-frequency signals in the long-baseline RTK positioning, a long-baseline RTK positioning method based on the BDS-3 penta-frequency ionospheric-reduced (IR) combinations is proposed. First, the low noise and weak ionospheric delay characteristics of the multi-frequency combined observations of BDS-3is analyzed. Second, the multi-frequency extra-wide-lane (EWL)/ wide-lane (WL) combinations with long-wavelengths are constructed. Third, the fixed IR EWL combinations are used to constrain the IR WL, then constrain narrow-lane (NL)ambiguityies and start multi-epoch filtering. There is no need to consider the influence of ionospheric parameters in the third step. Compared with the estimated ionospheric model, the proposed method reduces the number of parameters by half, so it is suitable for the use of multi-frequency and multi-system real-time RTK. The results using real data show that the stepwise fixed model of the IR EWL/WL/NL combinations can realize long-baseline instantaneous cimeter-level positioning.

Keywords: penta-frequency, ionospheric-reduced (IR), RTK positioning, long-baseline

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Authors: Yaolin Tian, Shanxiong Chen, Fujia Zhao, Xiaoyu Lin, Hailing Xiong

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Ancient books are significant culture inheritors and their background textures convey the potential history information. However, multi-style texture recovery of ancient books has received little attention. Restricted by insufficient ancient textures and complex handling process, the generation of ancient textures confronts with new challenges. For instance, training without sufficient data usually brings about overfitting or mode collapse, so some of the outputs are prone to be fake. Recently, image generation and style transfer based on deep learning are widely applied in computer vision. Breakthroughs within the field make it possible to conduct research upon multi-style texture recovery of ancient books. Under the circumstances, we proposed a network of layout analysis and image fusion system. Firstly, we trained models by using Deep Convolution Generative against Networks (DCGAN) to synthesize multi-style ancient textures; then, we analyzed layouts based on the Position Rearrangement (PR) algorithm that we proposed to adjust the layout structure of foreground content; at last, we realized our goal by fusing rearranged foreground texts and generated background. In experiments, diversified samples such as ancient Yi, Jurchen, Seal were selected as our training sets. Then, the performances of different fine-turning models were gradually improved by adjusting DCGAN model in parameters as well as structures. In order to evaluate the results scientifically, cross entropy loss function and Fréchet Inception Distance (FID) are selected to be our assessment criteria. Eventually, we got model M8 with lowest FID score. Compared with DCGAN model proposed by Radford at el., the FID score of M8 improved by 19.26%, enhancing the quality of the synthetic images profoundly.

Keywords: deep learning, image fusion, image generation, layout analysis

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Authors: A.N. Moulay Khatir, A. Guen-Bouazza, B. Bouazza

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SOI-Multifin-FET shows excellent transistor characteristics, ideal sub-threshold swing, low drain induced barrier lowering (DIBL) without pocket implantation and negligible body bias dependency. In this work, we analyzed this combination by a three-dimensional numerical device simulator to investigate the influence of fins number on corner effect by analyzing its electrical characteristics and potential distribution in the oxide and the silicon in the section perpendicular to the flow of the current for SOI-single-fin FET, three-fin and five-fin, and we provide a comparison with a Trigate SOI Multi-FinFET structure.

Keywords: SOI, FinFET, corner effect, dual-gate, tri-gate, Multi-Fin FET

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Authors: Ayman M. Mansour

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In this paper, we propose a multi-agent intelligent system that is used for monitoring the health conditions of elderly people. Monitoring the health condition of elderly people is a complex problem that involves different medical units and requires continuous monitoring. Such expert system is highly needed in rural areas because of inadequate number of available specialized physicians or nurses. Such monitoring must have autonomous interactions between these medical units in order to be effective. A multi-agent system is formed by a community of agents that exchange information and proactively help one another to achieve the goal of elderly monitoring. The agents in the developed system are equipped with intelligent decision maker that arms them with the rule-based reasoning capability that can assist the physicians in making decisions regarding the medical condition of elderly people.

Keywords: fuzzy logic, inference system, monitoring system, multi-agent system

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Authors: Shahadut Hossain, Jacek Wesolowski, Zahirul Hoque

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In many epidemiological and environmental studies covariate measurements are subject to the detection limit. In most applications, covariate measurements are usually truncated from below which is known as left-truncation. Because the measuring device, which we use to measure the covariate, fails to detect values falling below the certain threshold. In regression analyses, it causes inflated bias and inaccurate mean squared error (MSE) to the estimators. This paper suggests a response-based regression calibration method to correct the deleterious impact introduced by the covariate detection limit in the estimators of the parameters of simple logistic regression model. Compared to the maximum likelihood method, the proposed method is computationally simpler, and hence easier to implement. It is robust to the violation of distributional assumption about the covariate of interest. In producing correct inference, the performance of the proposed method compared to the other competing methods has been investigated through extensive simulations. A real-life application of the method is also shown using data from a population-based case-control study of non-Hodgkin lymphoma.

Keywords: environmental exposure, detection limit, left truncation, bias, ad-hoc substitution

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Authors: Manish Pandey, Gurinderjit Kaur, Meenu Talwar, Sachin Chauhan, Jagbir Gill

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Health-care management systems are a unit of nice connection as a result of the supply a straightforward and fast management of all aspects relating to a patient, not essentially medical. What is more, there are unit additional and additional cases of pathologies during which diagnosing and treatment may be solely allotted by victimization medical imaging techniques. With associate ever-increasing prevalence, medical pictures area unit directly acquired in or regenerate into digital type, for his or her storage additionally as sequent retrieval and process. Data Mining is the process of extracting information from large data sets through using algorithms and Techniques drawn from the field of Statistics, Machine Learning and Data Base Management Systems. Forecasting may be a prediction of what's going to occur within the future, associated it's an unsure method. Owing to the uncertainty, the accuracy of a forecast is as vital because the outcome foretold by foretelling the freelance variables. A forecast management should be wont to establish if the accuracy of the forecast is within satisfactory limits. Fuzzy regression strategies have normally been wont to develop shopper preferences models that correlate the engineering characteristics with shopper preferences relating to a replacement product; the patron preference models offer a platform, wherever by product developers will decide the engineering characteristics so as to satisfy shopper preferences before developing the merchandise. Recent analysis shows that these fuzzy regression strategies area units normally will not to model client preferences. We tend to propose a Testing the strength of Exponential Regression Model over regression toward the mean Model.

Keywords: health-care management systems, fuzzy regression, data mining, forecasting, fuzzy membership function

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Authors: Manthan Patel, Vinit Ahlawat, Anshh Singh Claire, Pijush Samui

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This paper focuses on the analysis of quicksand condition for a dam foundation. The quicksand condition occurs in cohesion less soil when effective stress of soil becomes zero. In a dam, the saturated sediment may appear quite solid until a sudden change in pressure or shock initiates liquefaction. This causes the sand to form a suspension and lose strength hence resulting in failure of dam. A soil profile shows different properties at different points and the values obtained are uncertain thus reliability analysis is performed. The reliability is defined as probability of safety of a system in a given environment and loading condition and it is assessed as Reliability Index. The reliability analysis of dams under quicksand condition is carried by Gaussian Process Regression (GPR). Reliability index and factor of safety relating to liquefaction of soil is analysed using GPR. The results of reliability analysis by GPR is compared to that of conventional method and it is demonstrated that on applying GPR the probabilistic analysis reduces the computational time and efforts.

Keywords: factor of safety, GPR, reliability index, quicksand

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Authors: Hao Chen, Bo Guo, Ping Jiang

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Residual life (RL) estimation based on multi-phase nonlinear Wiener process was studied in this paper, which is significant for complicated products with small samples. Firstly, nonlinear Wiener model with random parameter was introduced and multi-phase nonlinear Wiener model was proposed to model degradation process of products that were nonlinear and separated into different phases. Then the multi-phase RL probability density function based on the presented model was derived approximately in a closed form and parameters estimation was achieved with the method of maximum likelihood estimation (MLE). Finally, the method was applied to estimate the RL of high voltage plus capacitor. Compared with the other three different models by log-likelihood function (Log-LF) and Akaike information criterion (AIC), the results show that the proposed degradation model can capture degradation process of high voltage plus capacitors in a better way and provide a more reliable result.

Keywords: multi-phase nonlinear wiener process, residual life estimation, maximum likelihood estimation, high voltage plus capacitor

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Authors: Nabilah Filzah Mohd Radzuan, Andi Putra, Zalinda Othman, Azuraliza Abu Bakar, Abdul Razak Hamdan

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Precipitation forecast is important to avoid natural disaster incident which can cause losses in the involved area. This paper reviews three techniques logistic regression, decision tree, and random forest which are used in making precipitation forecast. These combination techniques through the vector auto-regression (VAR) model help in finding the advantages and strengths of each technique in the forecast process. The data-set contains variables of the rain’s domain. Adaptation of artificial intelligence techniques involved in rain domain enables the forecast process to be easier and systematic for precipitation forecast.

Keywords: logistic regression, decisions tree, random forest, VAR model

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Authors: Miguel Cañon, Darwin Mena, Ivan Cabeza

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In this work was compared and evaluated the applicability of statistical methods for the estimation of missing precipitations data in the basin of the river Lenguazaque located in the departments of Cundinamarca and Boyacá, Colombia. The methods used were the method of simple linear regression, distance rate, local averages, mean rates, correlation with nearly stations and multiple regression method. The analysis used to determine the effectiveness of the methods is performed by using three statistical tools, the correlation coefficient (r2), standard error of estimation and the test of agreement of Bland and Altmant. The analysis was performed using real rainfall values removed randomly in each of the seasons and then estimated using the methodologies mentioned to complete the missing data values. So it was determined that the methods with the highest performance and accuracy in the estimation of data according to conditions that were counted are the method of multiple regressions with three nearby stations and a random application scheme supported in the precipitation behavior of related data sets.

Keywords: statistical comparison, precipitation data, river subbasin, Bland and Altmant

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Authors: Ali A. Abdollahi

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During the last several decades, scientists have consistently applied Multiple Criteria Decision-Making methods in making decisions about multi-faceted, complicated subjects. While making such decisions and in order to achieve more accurate evaluations, they have regularly used a variety of criteria instead of applying just one Optimum Evaluation Criterion. The method presented here utilizes both ‘quantity’ and ‘quality’ to assess the function of the Multiple-Criteria method. Applying Data envelopment analysis (DEA), weighted aggregated sum product assessment (WASPAS), Weighted Sum Approach (WSA), Analytic Network Process (ANP), and Charnes, Cooper, Rhodes (CCR) methods, we have analyzed thirteen parks in Kerman city. It further indicates that the functions of WASPAS and WSA are compatible with each other, but also that their deviation from DEA is extensive. Finally, the results for the CCR technique do not match the results of the DEA technique. Our study indicates that the ANP method, with the average rate of 1/51, ranks closest to the DEA method, which has an average rate of 1/49.

Keywords: multiple criteria decision making, Data envelopment analysis (DEA), Charnes Cooper Rhodes (CCR), Weighted Sum Approach (WSA)

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Authors: Gelareh Changizi, Mahsa Khajavi, Ladan Shahhosseini

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Corporate-level strategy, or simply ‘parent strategy’, is a topic that has received much attention since the very early days of the strategic planning field. Since the multi level enterprises have different sub enterprises which deal with different business environments, we cannot define the same strategic perspective for all of them. Therefore, the determination of a perspective to manage and deal with affiliates of such enterprises is the main challenge. The parent strategy in mother enterprises' level has been analyzed in this research. A case study has been carried to comprehensively describe the proposed model.

Keywords: parent strategy, multi-business companies, performance evaluation, lifecycle

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Authors: R. B. Adegbola, K. F. Oyedele, L. Adeoti

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We present a method that utilizes Multi-channel Analysis of Surface Waves, which was used to measure shear wave velocities with a view to establishing the probable causes of road failure, subsidence and weakening of structures in some Local Government Area, Lagos, Nigeria. Multi channel Analysis of Surface waves (MASW) data were acquired using 24-channel seismograph. The acquired data were processed and transformed into two-dimensional (2-D) structure reflective of depth and surface wave velocity distribution within a depth of 0–15m beneath the surface using SURFSEIS software. The shear wave velocity data were compared with other geophysical/borehole data that were acquired along the same profile. The comparison and correlation illustrates the accuracy and consistency of MASW derived-shear wave velocity profiles. Rigidity modulus and N-value were also generated. The study showed that the low velocity/very low velocity are reflective of organic clay/peat materials and thus likely responsible for the failed, subsidence/weakening of structures within the study areas.

Keywords: seismograph, road failure, rigidity modulus, N-value, subsidence

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Authors: Jan Doutreloigne

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The main goal of this paper is to develop a switching amplifier with optimized power efficiency for analog signals with a very high crest factor such as audio or DSL signals. Theoretical calculations show that a switching amplifier architecture based on multi-level pulse width modulation outperforms all other types of linear or switching amplifiers in that respect. Simulations on a 2 W multi-level switching audio amplifier, designed in a 50 V 0.35 mm IC technology, confirm its superior performance in terms of power efficiency. A real silicon implementation of this audio amplifier design is currently underway to provide experimental validation.

Keywords: audio amplifier, multi-level switching amplifier, power efficiency, pulse width modulation, PWM, self-oscillating amplifier

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Authors: Anvi Kumar

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This paper explores the attitudes and awareness of multiple generations ranging from Boomers I to GenZ (i.e. from 1954 to 2012) towards mental health issues. A convenient sample of 191 people was gathered in India aged 11-77. 20 people each were considered from 5 generational cohorts, namely- Boomers I, Boomers II, Gen X, Millennials, and Gen Z. The study tool comprised a survey that included demographic questions and the Community Attitude towards Mental Illness (CAMI) scale by Taylor & Dear (1981). Descriptive statistics, ANOVA, and Bonferonni’s post-hoc analysis have been used to perform the analysis. The findings reveal that the level of kindness towards those who struggle with mental health varies through certain age groups. An overall sense of exclusion of those struggling with mental health is prevalent among all age groups. GenZ’s awareness of mental health issues is primarily via social media, as against the rest of the generations seeking it from close relatives and friends. The study’s findings suggest a need to investigate further the quality of mental health knowledge content and its consumption pattern. Understanding the dynamics of information sharing and the potential for biases requires further discovery.

Keywords: attitude, behaviour, mental illness, Gen Z, millennials, Gen Y, multi-generations, generational differences

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Authors: Mahnaz Motamedi, Mohammad Shahbazi, Shahrzad Rahimi-Naghani, Mehrdad Salehi

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Introduction and Aim: This study assessed sexual behaviours among men and women aged 15 to 49 years in Tehran. Material and Methods: This was a cross-sectional study conducted on 755 men and women aged 15 to 49 years who were residents of Tehran. To select the participants, a multistage, cluster, random sampling method was used and included different regions of Tehran. The data were collected using the WHO-endorsed Questionnaire of Sexual and Reproductive Health. Descriptive, bivariate, and multivariate analyses were conducted using SPSS version 20. Sexual and reproductive health (SRH) behaviours was a scale variable that was constructed from items of six sections: sexual experiences, characteristics of the first sexual partner, characteristics of the first intercourse, next sexual contact and the consequences of the first sexual contact, homosexual experiences and the causes of sexual abstinence. Results: The mean age at the time of sexual intercourse with penetration (vaginal, anal) was 19.88 in men and 21.82 in women. Multivariate analysis using linear regression showed that by controlling for other variables, gender had a significant relationship with having sexual experience, mean age of first sexual intercourse, and being multi-partner. Thus, women with sexual experience were 0.158 units less than men. The mean age of first intercourse in women was 1.57 units higher than men and being a multi-partner in women was 0.247 less than men (P < 0.001). Sexual experience in very religious and relatively religious individuals was 0.332 and 0.218 units less than those for whom religion did not matter (P < 0.001). 25.6% of men and 40.7% of women who did not have sexual experience at the time of the study stated that their reason for abstinence was their unwillingness to have sex (P < 0.05). 35.9% of men and 16.5% of women stated that the reason for abstinence was not providing a suitable opportunity (P < 0.001). 4.7% of men and 1.7% of women had sexual attraction to the same sex. The difference between men and women was significant (P < 0.001). Conclusion: Sexual relation is also present in singles and younger groups and is not limited to married or final marriage candidates. Therefore, more evaluation should be done in national research and interventions for sexual and reproductive health services should be done at the macro level of policy making.

Keywords: sexual behaviours, Iranian men and women, Iran, cross-sectional study

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Authors: Jui-Chen Huang

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This research used artificial intelligence method to explore elderly’s opinions on the reuse of telecare, its effect on their service quality, satisfaction and the relationship between customer perceived value and intention to reuse. This study conducted a questionnaire survey on the elderly. A total of 124 valid copies of a questionnaire were obtained. It adopted Backpropagation Network (BPN) to propose an effective and feasible analysis method, which is different from the traditional method. Two third of the total samples (82 samples) were taken as the training data, and the one third of the samples (42 samples) were taken as the testing data. The training and testing data RMSE (root mean square error) are 0.022 and 0.009 in the BPN, respectively. As shown, the errors are acceptable. On the other hand, the training and testing data RMSE are 0.100 and 0.099 in the regression model, respectively. In addition, the results showed the service quality has the greatest effects on the intention to reuse, followed by the satisfaction, and perceived value. This result of the Backpropagation Network method is better than the regression analysis. This result can be used as a reference for future research.

Keywords: artificial intelligence, backpropagation network (BPN), elderly, reuse, telecare

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Authors: Nurullah Ekmekci, Ömer Akkaya, Kazım Karaboğa, Mahmut Tekin

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Job selection is one of the most important decisions that affect their lives in the name of being more useful to themselves and the society. There are many criteria to consider in the job selection. The amount of criteria in the job selection makes it a multi-criteria decision-making (MCDM) problem. In this study; job selection has been discussed as multi-criteria decision-making problem and has been solved by Analytic Hierarchy Process (AHP), one of the multi-criteria decision making methods. A survey, contains 5 different job selection criteria (finding a job friendliness, salary status, job , social security, work in the community deems reputation and business of the degree of difficulty) within many job selection criteria and 4 different job alternative (being academician, working at the civil service, working at the private sector and working at in their own business), has been conducted to the students of Selcuk University Faculty of Economics and Administrative Sciences. As a result of pairwise comparisons, the highest weighted criteria in the job selection and the most coveted job preferences were identified.

Keywords: analytical hierarchy process, job selection, multi-criteria, decision making

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Authors: Malika Elkyal

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We consider an iterative parallel multi-splitting method for differential algebraic equations. The main feature of the proposed idea is to use the asynchronous form. We prove that the multi-splitting technique can effectively accelerate the convergent performance of the iterative process. The main characteristic of an asynchronous mode is that the local algorithm does not have to wait at predetermined messages to become available. We allow some processors to communicate more frequently than others, and we allow the communication delays to be substantial and unpredictable. Accordingly, we note that synchronous algorithms in the computer science sense are particular cases of our formulation of asynchronous one.

Keywords: parallel methods, asynchronous mode, multisplitting, differential algebraic equations

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Authors: Liu Shengnan, Sun Liping, Zhu Jianxun

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Based on three dimensional potential flow theory, hydrodynamic response analysis is carried on the multi floating bodies system composed of FPSO moored with yoke and shuttle tanker. It considered hydrodynamic interaction between FPSO and shuttle tanker, interaction between the hull and yoke mooring systems, hawsers, fenders, and then focuses on hawsers of the side-by-side offloading system. The influence of hawsers parameters on system safety is studied in respects of hawser stiffness, length and arrangement. Through analysis in different environment conditions and two typical loading conditions, it can be found that a better safety performance can be achieved through these three ways including enlarging the number of hawsers as well as the stiffness of hawsers, changing the length and arrangement of hawsers.

Keywords: yoke mooring, side-by-side offloading, multi floating body, hawser, safety

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Authors: Omar Dib, Rita Yaacoub, Luc Eveleigh, Nathalie Locquet, Hussein Dib, Ali Bassal, Christophe B. Y. Cordella

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The potential of front-face fluorescence coupled with chemometric techniques, namely parallel factor analysis (PARAFAC) and multiple linear regression (MLR) as a rapid analysis tool to characterize Lebanese virgin olive oils was investigated. Fluorescence fingerprints were acquired directly on 102 Lebanese virgin olive oil samples in the range of 280-540 nm in excitation and 280-700 nm in emission. A PARAFAC model with seven components was considered optimal with a residual of 99.64% and core consistency value of 78.65. The model revealed seven main fluorescence profiles in olive oil and was mainly associated with tocopherols, polyphenols, chlorophyllic compounds and oxidation/hydrolysis products. 23 MLR regression models based on PARAFAC scores were generated, the majority of which showed a good correlation coefficient (R > 0.7 for 12 predicted variables), thus satisfactory prediction performances. Acid values, peroxide values, and Delta K had the models with the highest predictions, with R values of 0.89, 0.84 and 0.81 respectively. Among fatty acids, linoleic and oleic acids were also highly predicted with R values of 0.8 and 0.76, respectively. Factors contributing to the model's construction were related to common fluorophores found in olive oil, mainly chlorophyll, polyphenols, and oxidation products. This study demonstrates the interest of front-face fluorescence as a promising tool for quality control of Lebanese virgin olive oils.

Keywords: front-face fluorescence, Lebanese virgin olive oils, multiple Linear regressions, PARAFAC analysis

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Authors: Basan Shrestha

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The relationship between the household size and the poverty is not well understood. Malthus followers advocate that the increasing population add pressure to the dwindling resource base due to increasing demand that would lead to poverty. Others claim that bigger households are richer due to availability of household labour for income generation activities. Facts from Nepal were analyzed to examine the relationship between the household size and poverty rate. The analysis of data from 3,968 Village Development Committee (VDC)/ municipality (MP) located in 75 districts of all five development regions revealed that the average household size had moderate positive correlation with the poverty rate (Karl Pearson's correlation coefficient=0.44). In a regression analysis, the household size determined 20% of the variation in the poverty rate. Higher positive correlation was observed in eastern Nepal (Karl Pearson's correlation coefficient=0.66). The regression analysis showed that the household size determined 43% of the variation in the poverty rate in east. The relation was poor in far-west. It could be because higher incidence of poverty was there irrespective of household size. Overall, the facts revealed that the bigger households were relatively poorer. With the increasing level of awareness and interventions for family planning, it is anticipated that the household size will decrease leading to the decreased poverty rate. In addition, the government needs to devise a mechanism to create employment opportunities for the household labour force to reduce poverty.

Keywords: household size, poverty rate, nepal, regional development

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Authors: Pulak Swain, A. K. Ojha

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Portfolio optimization is based on dealing with the problems of efficient asset allocation. Risk and Expected return are two conflicting criteria in such problems, where the investor prefers the return to be high and the risk to be low. Using multi-objective approach we can solve those type of problems. However the information which we have for the input parameters are generally ambiguous and the input values can fluctuate around some nominal values. We can not ignore the uncertainty in input values, as they can affect the asset allocation drastically. So we use Robust Optimization approach to the problems where the input parameters comes under box uncertainty. In this paper, we solve the multi criteria robust problem with the help of  E- constraint method.

Keywords: portfolio optimization, multi-objective optimization, ϵ - constraint method, box uncertainty, robust optimization

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Authors: Japnoor Garcha, Andrew P. Smith

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There has been a significant increase in the prevalence and estimates of neurodevelopmental disorders specially autism spectrum disorders in the last decade. The literature has seen increasing research on understanding well-being and mental health. The current studies have focused on seeing the impact of mental health and well-being in autism spectrum disorders and ADHD both with and without a diagnosis. To further understand the association and interaction of well-being and mental health with autism and ADHD a survey was given to 560 secondary school students. The survey used the well-being process questionnaire, the autism spectrum quotient, the ADHD self-report scale, and the strengths and difficulties questionnaire. The analysis conducted using SPSS showed that there was a significant correlation between anxiety, depression, AQ and ADHD. Anxiety and depression were also significantly correlated with all well-being and SDQ variables. The regression analysis showed that anxiety was significantly associated with positive well-being, negative well-being, emotional problems and prosocial behaviour whereas depression was significantly associated with positive well-being, negative well-being, physical health, flourishing, conduct problems, emotional problems and peer problems. This interaction led to the formation of a combined variable to see what impact the variables of anxiety, depression, AQ and ADHD would have coupled together. Further analysis showed that the combined variable was significantly correlated with all outcome variables. The regression analysis showed that the Combined variable was significantly correlated with emotional problems, and hyperactivity, stress, negative coping, psychological capital and sleepiness.

Keywords: AQ, adhd, sdq, well-being, combined variable

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Authors: Arindam Roy, Madhushree Das, Apurba Manna, Samir Maity

Abstract:

In this research paper, an algorithmic approach is developed to solve a novel multi-objective four-dimensional traveling salesman problem (MO4DTSP) where different paths with various numbers of conveyances are available to travel between two cities. NSGA-II and Decomposition algorithms are modified to solve MO4DTSP in an IoT-based transport system. This IoT-based transport system can be widely observed, analyzed, and controlled by an extensive distribution of traffic networks consisting of various types of sensors and actuators. Due to urbanization, most of the cities are connected using an intelligent traffic management system. Practically, for a traveler, multiple routes and vehicles are available to travel between any two cities. Thus, the classical TSP is reformulated as multi-route and multi-vehicle i.e., 4DTSP. The proposed MO4DTSP is designed with traveling cost, time, and customer satisfaction as objectives. In reality, customer satisfaction is an important parameter that depends on travel costs and time reflects in the present model.

Keywords: multi-objective four-dimensional traveling salesman problem (MO4DTSP), decomposition, NSGA-II, IoT-based transport system, customer satisfaction

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