Search results for: Multi-parameter logistic regression model

Authors: Jaroslav Polec, Viliam Hirner, Michal Martinovič, Kvetoslava Kotuliaková

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In this paper we present a novel error model for packet loss and subsequent error description. The proposed model simulates the error performance of wireless communication link. The model is designed as two independent Markov chains, where the first one is used for packet generation and the second one generates correctly and incorrectly transmitted bits for received packets from the first chain. The statistical analyses of real communication on the wireless link are used for determination of model-s parameters. Using the obtained parameters and the implementation of the generator, we collected generated traffic. The obtained results generated by proposed model are compared with the real data collection.

Keywords: Wireless channel, error model, Markov chain, Elliot model, Gilbert model, generator, IEEE 802.11.

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Authors: Wenzhe Li, Xiaoyu Ying, Grace Ding

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Architecture plane form is an important consideration in the design of green buildings due to its significant impact on energy performance. The most effective method to consider energy performance in the early design stages is parametric modelling. This paper presents a methodology to program plane forms using MATLAB language, generating 16 kinds of plane forms by changing four designed parameters. DesignBuilder (an energy consumption simulation software) was proposed to simulate the energy consumption of the generated planes. A regression mathematical model was established to study the relationship between the plane forms and their energy consumption. The main finding of the study suggested that there was a cubic function relationship between the depth-ratio of U-shaped buildings and energy consumption, and there is also a cubic function relationship between the width-ratio and energy consumption. In the design, the depth-ratio of U-shaped buildings should not be less than 2.5, and the width-ratio should not be less than 2.

Keywords: Graphic parameterization, green building design, mathematical model, U-shaped buildings.

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Authors: Tomoya Okubo, Kuninori Nakamura, Shin-ichi Mayekawa

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In this research, a latent class vector model for pairwise data is formulated. As compared to the basic vector model, this model yields consistent estimates of the parameters since the number of parameters to be estimated does not increase with the number of subjects. The result of the analysis reveals that the model was stable and could classify each subject to the latent classes representing the typical scales used by these subjects.

Keywords: finite mixture models, latent class analysis, Thrustone's paired comparison method, vector model

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Authors: T. N. Mac, B. Shahbodaghkhan, N. Khalili

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A new elastic-viscoplastic (EVP) constitutive model is proposed for the analysis of time-dependent behavior of clay. The proposed model is based on the bounding surface plasticity and the concept of viscoplastic consistency framework to establish continuous transition from plasticity to rate dependent viscoplasticity. Unlike the overstress based models, this model will meet the consistency condition in formulating the constitutive equation for EVP model. The procedure of deriving the constitutive relationship is also presented. Simulation results and comparisons with experimental data are then presented to demonstrate the performance of the model.

Keywords: Bounding surface, consistency theory, constitutive model, viscosity.

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Authors: Salwa Aftab, Sehrish Riaz

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The objective of this study was to check the impact of grade sensitivity on learning motivation and academic performance of students and to remove the degree of difference that exists among students regarding the cause of their learning motivation and also to gain knowledge about this matter since it has not been adequately researched. Data collection was primarily done through the academic sector of Pakistan and was depended upon the responses given by students solely. A sample size of 208 university students was selected. Both paper and online surveys were used to collect data from respondents. The results of the study revealed that grade sensitivity has a positive relationship with the learning motivation of students and their academic performance. These findings were carried out through systematic correlation and regression analysis.

Keywords: Academic performance, correlation, grade sensitivity, learning motivation, regression.

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Authors: Nazrina Aziz, Dong Q. Wang

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There have been various methods created based on the regression ideas to resolve the problem of data set containing censored observations, i.e. the Buckley-James method, Miller-s method, Cox method, and Koul-Susarla-Van Ryzin estimators. Even though comparison studies show the Buckley-James method performs better than some other methods, it is still rarely used by researchers mainly because of the limited diagnostics analysis developed for the Buckley-James method thus far. Therefore, a diagnostic tool for the Buckley-James method is proposed in this paper. It is called the renovated Cook-s Distance, (RD* i ) and has been developed based on the Cook-s idea. The renovated Cook-s Distance (RD* i ) has advantages (depending on the analyst demand) over (i) the change in the fitted value for a single case, DFIT* i as it measures the influence of case i on all n fitted values Yˆ∗ (not just the fitted value for case i as DFIT* i) (ii) the change in the estimate of the coefficient when the ith case is deleted, DBETA* i since DBETA* i corresponds to the number of variables p so it is usually easier to look at a diagnostic measure such as RD* i since information from p variables can be considered simultaneously. Finally, an example using Stanford Heart Transplant data is provided to illustrate the proposed diagnostic tool.

Keywords: Buckley-James estimators, censored regression, censored data, diagnostic analysis, product-limit estimator, renovated Cook's Distance.

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Authors: S. Raissi

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Response surface methodology (RSM) is a very efficient tool to provide a good practical insight into developing new process and optimizing them. This methodology could help engineers to raise a mathematical model to represent the behavior of system as a convincing function of process parameters. Through this paper the sequential nature of the RSM surveyed for process engineers and its relationship to design of experiments (DOE), regression analysis and robust design reviewed. The proposed four-step procedure in two different phases could help system analyst to resolve the parameter design problem involving responses. In order to check accuracy of the designed model, residual analysis and prediction error sum of squares (PRESS) described. It is believed that the proposed procedure in this study can resolve a complex parameter design problem with one or more responses. It can be applied to those areas where there are large data sets and a number of responses are to be optimized simultaneously. In addition, the proposed procedure is relatively simple and can be implemented easily by using ready-made standard statistical packages.

Keywords: Response Surface Methodology (RSM), Design of Experiments (DOE), Process modeling, Process setting, Process optimization.

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Authors: Rana Khalid Naeem, Asif Mansoor

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The hydrologic time series data display periodic structure and periodic autoregressive process receives considerable attention in modeling of such series. In this communication long term record of monthly waste flow of Lyari river is utilized to quantify by using PAR modeling technique. The parameters of model are estimated by using Frances & Paap methodology. This study shows that periodic autoregressive model of order 2 is the most parsimonious model for assessing periodicity in waste flow of the river. A careful statistical analysis of residuals of PAR (2) model is used for establishing goodness of fit. The forecast by using proposed model confirms significance and effectiveness of the model.

Keywords: Diagnostic checks, Lyari river, Model selection, Monthly waste flow, Periodicity, Periodic autoregressive model.

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Authors: Eva Kotlánová

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After recession that began in 2007 in the United States and subsequently spilled over the Europe we could expect recovery of economic growth. According to the last estimation of economic progress of European countries, this recovery is not strong enough. Among others, it will depend on economic policy, where and in which way, the economic indicators will proceed. Economic theories postulate that the economic subjects prefer stably, continual economic policy without repeated and strong fluctuations. This policy is perceived as support of economic growth. Mostly in crises period, when the government must cope with consequences of recession, the economic policy becomes unpredictable for many subjects and economic policy uncertainty grows, which have negative influence on economic growth. The aim of this paper is to use panel regression to prove or disprove this hypothesis on the example of five largest European economies in the period 2008–2012.

Keywords: Economic Crises in Europe, Economic Policy, Uncertainty, Panel Analysis Regression.

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Authors: Teka Haile, Behailu Hawulte, Solomon Alemayehu

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Background: HIV virological failure still remains a problem in HV/AIDS treatment and care. This study aimed to describe the prevalence and identify the factors associated with viral non-suppression among HIV-positive adult patients on antiretroviral therapy in Woliso Town, Oromia, Ethiopia. Methods: A retrospective cross-sectional study was conducted among 424 HIV-positive patient’s attending antiretroviral therapy (ART) in Woliso Town during the period from August 25, 2020 to August 30, 2020. Data collected from patient medical records were entered into Epi Info version 2.3.2.1 and exported to SPSS version 21.0 for analysis. Logistic regression analysis was done to identify factors associated with viral load non-suppression, and statistical significance of odds ratios were declared using 95% confidence interval and p-value < 0.05. Results: A total of 424 patients were included in this study. The mean age (± SD) of the study participants was 39.88 (± 9.995) years. The prevalence of HIV viral load non-suppression was 55 (13.0%) with 95% CI (9.9-16.5). Second-line ART treatment regimen (Adjusted Odds Ratio (AOR) = 8.98, 95% Confidence Interval (CI): 2.64, 30.58) and routine viral load testing (AOR = 0.01, 95% CI: 0.001, 0.02) were significantly associated with virological non-suppression. Conclusion: Virological non-suppression was high, which hinders the achievement of the third global 95 target. The second-line regimen and routine viral load testing were significantly associated with virological non-suppression. It suggests the need to assess the effectiveness of antiretroviral drugs for epidemic control. It also clearly shows the need to decentralize third-line ART treatment for those patients in need.

Keywords: Virological non-suppression, HIV-positive, ART, Woliso Town, Ethiopia.

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Authors: G. Baskar, C. Muthukumaran, S. Renganathan

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Enzymatic hydrolysis of starch from natural sources finds potential application in commercial production of alcoholic beverage and bioethanol. In this study the effect of starch concentration, temperature, time and enzyme concentration were studied and optimized for hydrolysis of cassava (Manihot esculenta) starch powder (of mesh 80/120) into glucose syrup by immobilized (using Polyacrylamide gel) a-amylase using central composite design. The experimental result on enzymatic hydrolysis of cassava starch was subjected to multiple linear regression analysis using MINITAB 14 software. Positive linear effect of starch concentration, enzyme concentration and time was observed on hydrolysis of cassava starch by a-amylase. The statistical significance of the model was validated by F-test for analysis of variance (p < 0.01). The optimum value of starch concentration temperature, time and enzyme concentration were found to be 4.5% (w/v), 45oC, 150 min, and 1% (w/v) enzyme. The maximum glucose yield at optimum condition was 5.17 mg/mL.

Keywords: Enzymatic hydrolysis, Alcoholic beverage, Centralcomposite design, Polynomial model, glucose yield.

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Authors: A. I. Dounis, P. Tiropanis, D. Tseles, G. Nikolaou, G. P. Syrcos

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The prediction of meteorological parameters at a meteorological station is an interesting and open problem. A firstorder linear dynamic model GM(1,1) is the main component of the grey system theory. The grey model requires only a few previous data points in order to make a real-time forecast. In this paper, we consider the daily average ambient temperature as a time series and the grey model GM(1,1) applied to local prediction (short-term prediction) of the temperature. In the same case study we use a fuzzy predictive model for global prediction. We conclude the paper with a comparison between local and global prediction schemes.

Keywords: Fuzzy predictive model, grey model, local andglobal prediction, meteorological forecasting, time series.

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Authors: Ali Faal Ghayoumi, Mahmoud Dehghan Nayeri, Manouchehre Ansari, Taha Raeesi

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This study aims to investigate empirically the valuerelevance of accounting information to domestic investors in Tehran stock exchange from 1999 to 2006. During the present research impacts of two factors, including positive vs. negative earnings and the firm size are considered as well. The authors used earnings per share and annual change of earnings per share as the income statement indices, and book value of equity per share as the balance sheet index. Return and Price models through regression analysis are deployed in order to test the research hypothesis. Results depicted that accounting information is value-relevance to domestic investors in Tehran Stock Exchange according to both studied models. However, income statement information has more value-relevance than the balance sheet information. Furthermore, positive vs. negative earnings and firm size seems to have significant impact on valuerelevance of accounting information.

Keywords: Value-Relevance of Accounting Information, Iranianstock exchange, Return Model, Price Model

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Authors: Takashi Kaburagi, Masashi Takenaka, Yosuke Kurihara, Takashi Matsumoto

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Major depressive disorder (MDD) is one of the most common mental illnesses today. It is believed to be caused by a combination of several factors, including stress. Stress can be quantitatively evaluated using the State-Trait Anxiety Inventory (STAI), one of the best indices to evaluate anxiety. Although STAI scores are widely used in applications ranging from clinical diagnosis to basic research, the scores are calculated based on a self-reported questionnaire. An objective evaluation is required because the subject may intentionally change his/her answers if multiple tests are carried out. In this article, we present a modified index called the “multi-channel Laterality Index at Rest (mc-LIR)” by recording the brain activity from a wider area of the frontal lobe using multi-channel functional near-infrared spectroscopy (fNIRS). The presented index aims to measure multiple positions near the F_pz defined by the international 10-20 system positioning. Using 24 subjects, the dependencies on the number of measuring points used to calculate the mc-LIR and its correlation coefficients with the STAI scores are reported. Furthermore, a simple linear regression was performed to estimate the STAI scores from mc-LIR. The cross-validation error is also reported. The experimental results show that using multiple positions near the Fpz will improve the correlation coefficients and estimation than those using only two positions.

Keywords: Stress, functional near-infrared spectroscopy, frontal lobe, state-trait anxiety inventory score.

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Authors: Anthropometric, Physical Fitness Ability Profile of Elite, Non-Elite Boxers of Manipur

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Background: Boxing is one of the oldest combat sports where different anthropological and fitness ability parameters determine performance. It is characterized by short duration, high intensity bursts of activity. The purpose of this research was to determine anthropometric and physical fitness profile of male elite and non-elite boxers of Manipur and to compare the two groups. Materials and Methods: Nineteen subjects were selected as elite boxers and twenty-four were non-elite boxers of Manipur. A cross-sectional study was conducted on anthropometric measurements and physical fitness ability tests on 33 subjects (elite and non-elite boxers). Statistical analysis was done using descriptive statistics, t-test and logistic regression with the help of SPSS version 15 software. Results: Results showed elite boxers have significantly reduced neck girth and calf girth as compare to non-elite boxers. Elite boxers have significantly lower sub scapular skin fold (SSF) and supra iliac skin fold (SISF) than their counterparts. Higher stature, larger BTB and lower percent fat are associated with higher performance in boxing. Sit ups (SU), standing Broad Jump (SBJ), Plat taping (PT), Sit and reach (SAR) and Harvard Step Test (HST) are predicted as most contributing factors enhancing performance level among the physical fitness components. Elite boxers are found to have more functional strength (sit ups), higher explosive strength (SBJ), more agility (PT), cardio-vascular endurance and flexibility (SAR) than non-elite boxers. Conclusion: In conclusion, lower fat, higher lean body mass, larger bi-trochantric breadth, high explosive strength, agility and flexibility are significantly associated with higher performance and chance of becoming elite boxers.

Keywords: Anthropometry, elite and non-elite boxers, Manipur, physical fitness.

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Authors: A. Kumar, V. Devadas

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India has the most year-round favorable sunny conditions along with the second-highest solar irradiation in the world, the country holds the potential to become the global solar hub. The solar and wind-based generation capacity has skyrocketed in India with the successful effort of the Ministry of Renewable Energy, whereas the potential of rooftop based solar power generation has yet to be explored for proposed solar cities in India. The research aims to analyze the gap in the energy scenario in Jodhpur City and proposes interventions of solar energy generation systems as a catalyst for urban development. The research is based on the system concept which deals with simulation between the city system as a whole and its interactions between different subsystems. A system-dynamics based mathematical model is developed by identifying the control parameters using regression and correlation analysis to assess the gap in energy sector. The base model validation is done using the past 10 years timeline data collected from secondary sources. Further, energy consumption and solar energy generation-based projection are made for testing different scenarios to conclude the feasibility for maintaining the city level energy independence till 2031.

Keywords: City, consumption, energy, generation.

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Authors: Nadeem Akhtar, Shan Bo

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This article illustrates that how non similar culture become a cause of constant anxiety among international students in China. For that, a survey was carried out among international students of Wuhan University, China. The association among non similar culture, non familiarity of Chinese culture, self finance students and food problem is looked at through a regression line, and in the light of empirical results, a model is anticipated which elucidates these results. Some suggestions were directed at the end which will help to mitigate the anxiety among prospective students in Chinese universities.

Keywords: Anxiety, international students, non similar culture, Wuhan University

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Authors: Luay A. Fraiwan, Natheer Y. Khaswaneh, Khaldon Y. Lweesy

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Sleep stage scoring is the process of classifying the stage of the sleep in which the subject is in. Sleep is classified into two states based on the constellation of physiological parameters. The two states are the non-rapid eye movement (NREM) and the rapid eye movement (REM). The NREM sleep is also classified into four stages (1-4). These states and the state wakefulness are distinguished from each other based on the brain activity. In this work, a classification method for automated sleep stage scoring based on a single EEG recording using wavelet packet decomposition was implemented. Thirty two ploysomnographic recording from the MIT-BIH database were used for training and validation of the proposed method. A single EEG recording was extracted and smoothed using Savitzky-Golay filter. Wavelet packets decomposition up to the fourth level based on 20th order Daubechies filter was used to extract features from the EEG signal. A features vector of 54 features was formed. It was reduced to a size of 25 using the gain ratio method and fed into a classifier of regression trees. The regression trees were trained using 67% of the records available. The records for training were selected based on cross validation of the records. The remaining of the records was used for testing the classifier. The overall correct rate of the proposed method was found to be around 75%, which is acceptable compared to the techniques in the literature.

Keywords: Features selection, regression trees, sleep stagescoring, wavelet packets.

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Authors: A. Rezazadeh, N. Omidvar, H. Eini-Zinab

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Food insecurity (FI) influences may result in poor physical and mental health outcomes. Minor ethnic group may experience higher level of FI, and this situation may be related with higher depression prevalence. The aim of this study was to determine the association of depression with food security status in major (Azeri) and minor (Kurdish) ethnicity living in Urmia, West Azerbaijan, north of Iran. In this cross-sectional study, 723 participants (427 women and 296 men) aged 20–64 years old, from two ethnic groups (445 Azeri and 278 Kurdish), were selected through a multi stage cluster systematic sampling. Depression rate was assessed by “Beck” short form questionnaire (validated in Iranians) through interviews. Household FI status (HFIS) was measured using adapted HFI access scale through face-to-face interviews at homes. Multinomial logistic regression was used to estimate odds ratios (OR) of depression across HFIS. Higher percent of Kurds had moderate and severe depression in comparison with Azeri group (73 [17.3%] vs. 86 [27.9%]). There were not any significant differences between the two ethnicities in mild depression. Also, of all the subjects, moderate-to-sever FI was more prevalent in Kurds (28.5%), compared to Azeri group (17.3%) [P < 0.01]. Kurdish ethnic group living in food security or mild FI households had lower chance to have symptom of severe depression in comparison to those with sever FI (OR=0.097; 95% CI: 0.02-0.47). However, there was no significant association between depression and HFI in Azeri group. Findings revealed that the severity of HFI was related with severity depression in minor studied ethnic groups. However, in Azeri ethnicity as a major group, other confounders may have influence on the relation with depression and FI, that were not studied in the present study.

Keywords: Depression, ethnicity, food security status, Iran.

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Authors: Eunji Choi, Borang Park, Youngjae Choi, Jinwoo Moon

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In this study, a predictive model for estimating the metabolism (MET) of human body was developed for the optimal control of indoor thermal environment. Human body images for indoor activities and human body joint coordinated values were collected as data sets, which are used in predictive model. A deep learning algorithm was used in an initial model, and its number of hidden layers and hidden neurons were optimized. Lastly, the model prediction performance was analyzed after the model being trained through collected data. In conclusion, the possibility of MET prediction was confirmed, and the direction of the future study was proposed as developing various data and the predictive model.

Keywords: Deep learning, indoor quality, metabolism, predictive model.

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Authors: Irtaza M. Syed, Kaamran Raahemifar

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This paper presents modeling of an Alternating Current (AC) Photovoltaic (PV) module using Matlab/Simulink. The proposed AC-PV module model is simple, realistic, and application oriented. The model is derived on module level as compared to cell level directly from the information provided by the manufacturer data sheet. DC-PV module, MPPT control, BC, VSI and LC filter, all were treated as a single unit. The model accounts for changes in variations of both irradiance and temperature. The AC-PV module proposed model is simulated and the results are compared with the datasheet projected numbers to validate model’s accuracy and effectiveness. Implementation and results demonstrate simplicity and accuracy, as well as reliability of the model.

Keywords: AC PV Module, Datasheet, Matlab/Simulink, PV modeling.

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Authors: Ondruska Marek

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The article presents the whole model of IS/IT architecture exception governance. As first, the assumptions of presented model are set. As next, there is defined a generic governance model that serves as a basis for the architecture exception governance. The architecture exception definition and its attributes follow. The model respects well known approaches to the area that are described in the text, but it adopts higher granularity in description and expands the process view with all the next necessary governance components as roles, principles and policies, tools to enable the implementation of the model into organizations. The architecture exception process is decomposed into a set of processes related to the architecture exception lifecycle consisting of set of phases and architecture exception states. Finally, there is information about my future research related to this area.

Keywords: Architecture, dispensation, exception, governance, model

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Authors: Arsalan Jabbar, Wajiha Javed, Nelofer Mehboob, Zahid Memon

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Introduction: There are multiple social, individual and cultural factors that influence an individual’s decision to adopt family planning methods especially among non-users in patriarchal societies like Pakistan. Non-users, if targeted efficiently, can contribute significantly to country’s CPR. A research study showed that nonusers if convinced to adopt lactational amenorrhea method can shift to long term methods in future. Research shows that if non users are targeted efficiently a 59% reduction in unintended pregnancies in Saharan Africa and South-Central and South-East Asia is anticipated. Methods: We did secondary data analysis on Pakistan Demographic Heath Survey (2012-13) dataset. Use of contraception (never-use/ever-use) was the outcome variable. At univariate level Chi-square/Fisher Exact test was used to assess relationship of baseline covariates with contraception use. Then variables to be incorporated in the model were checked for multicollinearity, confounding and interaction. Then binary logistic regression (with an urban-rural stratification) was done to find relationship between contraception use and baseline demographic and social variables. Results: The multivariate analyses of the study showed that younger women (≤ 29 years)were more prone to be never users as compared to those who were >30 years and this trend was seen in urban areas (AOR 1.92, CI 1.453-2.536) as well as rural areas (AOR 1.809, CI 1.421-2.303). While looking at regional variation, women from urban Sindh (AOR 1.548, CI 1.142-2.099) and urban Balochistan (AOR 2.403, CI 1.504-3.839) had more never users as compared to other urban regions. Women in the rich wealth quintile were more never users and this was seen both in urban and rural localities (urban (AOR 1.106 CI .753-1.624); rural areas (AOR 1.162, CI .887-1.524)) even though these were not statistically significant. Women idealizing more children (>4) are more never users as compared to those idealizing less children in both urban (AOR 1.854, CI 1.275-2.697) and rural areas (AOR 2.101, CI 1.514-2.916). Women who never lost a pregnancy were more inclined to be nonusers in rural areas (AOR 1.394, CI 1.127-1.723) .Women familiar with only traditional or no method had more never users in rural areas (AOR 1.717, CI 1.127-1.723) but in urban areas it wasn’t significant. Women unaware of Lady Health Worker’s presence in their area were more never users especially in rural areas (AOR 1.276, CI 1.014-1.607). Women who did not visit any care provider were more never users (urban (AOR 11.738, CI 9.112-15.121) rural areas (AOR 7.832, CI 6.243-9.826)). Discussion/Conclusion: This study concluded that government, policy makers and private sector family planning programs should focus on the untapped pool of never users (younger women from underserved provinces, in higher wealth quintiles, who desire more children.). We need to make sure to cover catchment areas where there are less LHWs and less providers as ignorance to modern methods and never been visited by an LHW are important determinants of never use. This all is in sync with previous literate from similar developing countries.

Keywords: Contraception, Demographic and Health Survey, Family Planning, Never users.

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Authors: Zainab M. Musa, Nordin M. A. Rahman, Julaily A. Jusoh

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The web services applications for digital reference service (WSDRS) of LIS model is an informal model that claims to reduce the problems of digital reference services in libraries. It uses web services technology to provide efficient way of satisfying users’ needs in the reference section of libraries. The formal WSDRS model consists of the Z specifications of all the informal specifications of the model. This paper discusses the formal validation of the Z specifications of WSDRS model. The authors formally verify and thus validate the properties of the model using Z/EVES theorem prover.

Keywords: Validation, verification, formal, theorem proving.

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Authors: Hirohide Ushida

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This paper discusses an artificial mind model and its applications. The mind model is based on some theories which assert that emotion is an important function in human decision making. An artificial mind model with emotion is built, and the model is applied to action selection of autonomous agents. In three examples, the agents interact with humans and their environments. The examples show the proposed model effectively work in both virtual agents and real robots.

Keywords: Artificial mind, emotion, interactive agent, pet robot

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Authors: Vanessa Matias Leite, Jandira Guenka Palma, Flávio Henrique de Oliveira

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This paper presents a model-oriented development approach to software development in the Model-View-Controller (MVC) architectural standard. This approach aims to expose a process of extractions of information from the models, in which through rules and syntax defined in this work, assists in the design of the initial model and its future conversions. The proposed paper presents a syntax based on the natural language, according to the rules agreed in the classic grammar of the Portuguese language, added to the rules of conversions generating models that follow the norms of the Object Management Group (OMG) and the Meta-Object Facility MOF.

Keywords: Model driven architecture, model-view-controller, bnf syntax, model, transformation, UML.

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Authors: Shuh Liang

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This article provides empirical evidence on the effect of domestic and international factors on the U.S. current account deficit. Linear dynamic regression and vector autoregression models are employed to estimate the relationships during the period from 1986 to 2011. The findings of this study suggest that the current and lagged private saving rate and foreign current account for East Asian economies have played a vital role in affecting the U.S. current account. Additionally, using Granger causality tests and variance decompositions, the change of the productivity growth and foreign domestic demand are determined to influence significantly the change of the U.S. current account. To summarize, the empirical relationship between the U.S. current account deficit and its determinants is sensitive to alternative regression models and specifications.

Keywords: Current account deficit, productivity growth, foreign demand, vector autoregression.

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Authors: Hina Gull, Farooque Azam, Wasi Haider Butt, Sardar Zafar Iqbal

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The software system goes through a number of stages during its life and a software process model gives a standard format for planning, organizing and running a project. The article presents a new software development process model named as “Divide and Conquer Process Model", based on the idea first it divides the things to make them simple and then gathered them to get the whole work done. The article begins with the backgrounds of different software process models and problems in these models. This is followed by a new divide and conquer process model, explanation of its different stages and at the end edge over other models is shown.

Keywords: Process Model, Waterfall, divide and conquer, Requirements.

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Authors: Gorazd Karer, Igor Skrjanc, Borut Zupancic

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The complex hybrid and nonlinear nature of many processes that are met in practice causes problems with both structure modelling and parameter identification; therefore, obtaining a model that is suitable for MPC is often a difficult task. The basic idea of this paper is to present an identification method for a piecewise affine (PWA) model based on a fuzzy clustering algorithm. First we introduce the PWA model. Next, we tackle the identification method. We treat the fuzzy clustering algorithm, deal with the projections of the fuzzy clusters into the input space of the PWA model and explain the estimation of the parameters of the PWA model by means of a modified least-squares method. Furthermore, we verify the usability of the proposed identification approach on a hybrid nonlinear batch reactor example. The result suggest that the batch reactor can be efficiently identified and thus formulated as a PWA model, which can eventually be used for model predictive control purposes.

Keywords: Batch reactor, fuzzy clustering, hybrid systems, identification, nonlinear systems, PWA systems.

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Authors: Sotirios Raptis

Abstract:

Linking social needs to social classes using different criteria may lead to social services misuse. The paper discusses using ML and Neural Networks (NNs) in linking public services in Scotland in the long term and advocates, this can result in a reduction of the services cost connecting resources needed in groups for similar services. The paper combines typical regression models with clustering and cross-correlation as complementary constituents to predict the demand. Insurance companies and public policymakers can pack linked services such as those offered to the elderly or to low-income people in the longer term. The work is based on public data from 22 services offered by Public Health Services (PHS) Scotland and from the Scottish Government (SG) from 1981 to 2019 that are broken into 110 years series called factors and uses Linear Regression (LR), Autoregression (ARMA) and 3 types of back-propagation (BP) Neural Networks (BPNN) to link them under specific conditions. Relationships found were between smoking related healthcare provision, mental health-related health services, and epidemiological weight in Primary 1(Education) Body Mass Index (BMI) in children. Primary component analysis (PCA) found 11 significant factors while C-Means (CM) clustering gave 5 major factors clusters.

Keywords: Probability, cohorts, data frames, services, prediction.

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