Search results for: multivariate control chart

Authors: Sanam Haseen, Abdul Bari

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In this paper a three stage multivariate programming problem with random survey cost and variances as random variables has been formulated as a non-linear stochastic programming problem. The problem has been converted into an equivalent deterministic form using chance constraint programming and modified E-modeling. An empirical study of the problem has been done at the end of the paper using R-simulation.

Keywords: chance constraint programming, modified E-model, stochastic programming, stratified sample surveys, three stage sample surveys

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Authors: Muqaddas Javed, Muhammad Hanif

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The generalized multivariate ratio and regression type estimators for population mean are suggested under multi-phase stratified systematic sampling (MPSSS) using multi auxiliary information. Estimators are developed under the two different situations of availability of auxiliary information. The expressions of bias and mean square error (MSE) are developed. Special cases of suggested estimators are also discussed and simulation study is conducted to observe the performance of estimators.

Keywords: generalized estimators, multi-phase sampling, stratified random sampling, systematic sampling

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Authors: William Elnemer, Nauman Hussain, Samir Al-Ali, Henry Shu, Diane Ghanem, Babar Shafiq

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Introduction: The incidence of infection in open tibial shaft injuries varies depending on the severity of the injury, with rates ranging from 1.8% for Gustilo-Anderson type I to 42.9% for type IIIB fractures. The timely administration of antibiotics upon presentation to the emergency department (ED) is an essential component of fracture management, and evidence indicates that prompt delivery of antibiotics is associated with improved outcomes. The objective of this study is to identify factors that contribute to the expedient administration of antibiotics. Methods: This is a retrospective study of open tibial shaft fractures at an academic Level I trauma center. Current Procedural Terminology (CPT) codes identified all patients treated for open tibial shaft fractures between 2015 and 2021. Open fractures were identified by reviewing ED and provider notes, and with ballistic fractures were considered open. Chart reviews were performed to extract demographics, fracture characteristics, postoperative outcomes, time to operative room, time to antibiotic order, and delivery. Univariate statistical analysis compared patients who received early antibiotics (EA), which were delivered within one hour of ED presentation, and those who received late antibiotics (LA), which were delivered outside of one hour of ED presentation. A multivariate analysis was performed to investigate patient, fracture, and transport/ED characteristics contributing to faster delivery of antibiotics. The multivariate analysis included the dependent variables: ballistic fracture, activation of Delta Trauma, Gustilo-Andersen (Type III vs. Type I and II), AO-OTA Classification (Type C vs. Type A and B), arrival between 7 am and 11 pm, and arrival via Emergency Medical Services (EMS) or walk-in. Results: Seventy ED patients with open tibial shaft fractures were identified. Of these, 39 patients (55.7%) received EA, while 31 patients (44.3%) received LA. Univariate analysis shows that the arrival via EMS as opposed to walk-in (97.4% vs. 74.2%, respectively, p = 0.01) and activation of Delta Trauma (89.7% vs. 51.6%, respectively, p < 0.001) was significantly higher in the EA group vs. the LA group. Additionally, EA cases had significantly shorter intervals between the antibiotic order and delivery when compared to LA cases (0.02 hours vs. 0.35 hours, p = 0.007). No other significant differences were found in terms of postoperative outcomes or fracture characteristics. Multivariate analysis shows that a Delta Trauma Response, arrival via EMS, and presentation between 7 am and 11 pm were independent predictors of a shorter time to antibiotic administration (Odds Ratio = 11.9, 30.7, and 5.4, p = 0.001, 0.016, and 0.013, respectively). Discussion: Earlier antibiotic delivery is associated with arrival to the ED between 7 am and 11 pm, arrival via EMS, and a coordinated Delta Trauma activation. Our findings indicate that in cases where administering antibiotics is critical to achieving positive outcomes, it is advisable to employ a coordinated Delta Trauma response. Hospital personnel should be attentive to the rapid administration of antibiotics to patients with open fractures who arrive via walk-in or during late-night hours.

Keywords: antibiotics, emergency department, fracture management, open tibial shaft fractures, orthopaedic surgery, time to or, trauma fractures

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Authors: H. Heidari-Bafroui, B. Ribeiro, A. Charbaji, C. Anagnostopoulos, M. Faghri

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In this paper, we report the development of a portable and inexpensive infrared lightbox for improving the detection limits of paper-based phosphate devices. Commercial paper-based devices utilize the molybdenum blue protocol to detect phosphate in the environment. Although these devices are easy to use and have a long shelf life, their main deficiency is their low sensitivity based on the qualitative results obtained via a color chart. To improve the results, we constructed a compact infrared lightbox that communicates wirelessly with a smartphone. The system measures the absorbance of radiation for the molybdenum blue reaction in the infrared region of the spectrum. It consists of a lightbox illuminated by four infrared light-emitting diodes, an infrared digital camera, a Raspberry Pi microcontroller, a mini-router, and an iPhone to control the microcontroller. An iPhone application was also developed to analyze images captured by the infrared camera in order to quantify phosphate concentrations. Additionally, the app connects to an online data center to present a highly scalable worldwide system for tracking and analyzing field measurements. In this study, the detection limits for two popular commercial devices were improved by a factor of 4 for the Quantofix devices (from 1.3 ppm using visible light to 300 ppb using infrared illumination) and a factor of 6 for the Indigo units (from 9.2 ppm to 1.4 ppm) with repeatability of less than or equal to 1.2% relative standard deviation (RSD). The system also provides more granular concentration information compared to the discrete color chart used by commercial devices and it can be easily adapted for use in other applications.

Keywords: infrared lightbox, paper-based device, phosphate detection, smartphone colorimetric analyzer

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Authors: Panpan Xu, Qiying Zhang, Hui Qian

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Groundwater is main source of water supply in the Guanzhong Basin, China. To investigate the quality of groundwater for agricultural purposes in Jiaokou Irrigation District located in the east of the Guanzhong Basin, 141 groundwater samples were collected for analysis of major ions (K⁺, Na⁺, Mg²⁺, Ca²⁺, SO₄^2-, Cl^-, HCO₃^-, and CO₃^2-), pH, and total dissolved solids (TDS). Sodium percentage (Na%), residual sodium carbonate (RSC), magnesium hazard (MH), and potential salinity (PS) were applied for irrigation water quality assessment. In addition, multivariate statistical techniques were used to identify the underlying hydrogeochemical processes. Results show that the content of TDS mainly depends on Cl^-, Na⁺, Mg²⁺, and SO₄^2-, and the HCO₃^- content is generally high except for the eastern sand area. These are responsible for complex hydrogeochemical processes, such as dissolution of carbonate minerals (dolomite and calcite), gypsum, halite, and silicate minerals, the cation exchange, as well as evaporation and concentration. The average evaluation levels of Na%, RSC, MH, and PS for irrigation water quality are doubtful, good, unsuitable, and injurious to unsatisfactory, respectively. Therefore, it is necessary for decision makers to comprehensively consider the indicators and thus reasonably evaluate the irrigation water quality.

Keywords: irrigation water quality, multivariate statistical analysis, groundwater, hydrogeochemical process

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Authors: Hyun-Woo Cho

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The monitoring of industrial production quality has to be implemented to alarm early warning for unusual operating conditions. Furthermore, identification of their assignable causes is necessary for a quality control purpose. For such tasks many multivariate statistical techniques have been applied and shown to be quite effective tools. This work presents a process data-based monitoring scheme for production processes. For more reliable results some additional steps of noise filtering and preprocessing are considered. It may lead to enhanced performance by eliminating unwanted variation of the data. The performance evaluation is executed using data sets from test processes. The proposed method is shown to provide reliable quality control results, and thus is more effective in quality monitoring in the example. For practical implementation of the method, an on-line data system must be available to gather historical and on-line data. Recently large amounts of data are collected on-line in most processes and implementation of the current scheme is feasible and does not give additional burdens to users.

Keywords: detection, filtering, monitoring, process data

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Authors: Jeong Hong Kim, Ju Wan Kang

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Objective: Histamine skin prick testing is most commonly used to diagnose immunoglobulin E (IgE)-mediated allergic diseases, and histamine reactivity is used as a standardized positive control in the interpretation of a skin prick test. However, reactivity to histamine differs among individuals for reasons that are poorly understood. The present study aimed to evaluate the potential association between body mass index (BMI) and histamine skin reactivity in children. Methods: A total of 451 children (246 boys, 205 girls) aged 7–8 years were enrolled in this study. The skin prick test was performed with 26 aeroallergens commonly found in Korea. Other information was collected, including sex, age, BMI, parental allergy history, and parental smoking status. Multivariate analysis was used to confirm the association between histamine skin reactivity and BMI. Results: The histamine wheal size was revealed to be associated with BMI (Spearman's Rho 0.161, p < 0.001). This association was confirmed by multivariate analysis, after adjusting for sex, age, parental allergy history, parental smoking status, and allergic sensitization (coefficient B 0.071, 95% confidence interval 0.030–0.112). Conclusions: Skin responses to histamine were primarily correlated with increased BMI. Further studies are needed to understand the clinical implication of BMI when interpreting the results of skin prick test.

Keywords: allergy, body mass index, histamine, skin prick test

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Authors: Parimalakrishnan Sundararjan, Madheswaran Murugan, Dhanya Dharman, Yatindra Kumar, Sudhir Singh Gangwar, Guru Prasad Mohanta

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Antibiotic resistance AR is a global issue, India started to redress the issues of antibiotic resistance late and it plans to have: active surveillance of microbial resistance and promote appropriate use of antibiotics. The present study attempted to achieve appropriate use of antibiotics through pharmacists’ intervention at practice point. In a quasi-experimental prospective cohort study, the cases with bacteremia from four hospitals were identified during 2015 and 2016 for intervention. The pharmacists centered intervention: active screening of each prescription and comparing with the selection of antibiotics with susceptibility of the bacteria. Wherever irrationality noticed, it was brought to the notice of the treating physician for making changes. There were two groups: intervention group and control group without intervention. The active screening and intervention in 915 patients has reduced therapeutic regimen time in patients with bacteremia. The intervention group showed the decreased duration of hospital stay 3.4 days from 5.1 days. Further, multivariate modeling of patients who were in control group showed that patients in the intervention group had a significant decrease in both duration of hospital stay and infection-related mortality. Unlike developed countries, pharmacists are not active partners in patient care in India. This unique attempt of pharmacist’ invention was planned in consultation with hospital authorities which proved beneficial in terms of reducing the duration of treatment, hospital stay, and infection-related mortality. This establishes the need for a collaborative decision making among the health workforce in patient care at least for promoting rational use of antibiotics, an attempt to combat resistance.

Keywords: antibiotics resistance, intervention, bacteremia, multivariate modeling

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Authors: Elahe Memari, Ahmad Aslizadeh, Ahmad Memari

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Today strategic planning is counted as the most important duties of senior directors in each organization. Strategic planning allows the organizations to implement compiled strategies and reach higher competitive benefits than their competitors. The present research work tries to prepare and rank the strategies form effective factors on strategic planning in fulfillment of the State Road Management and Transportation Organization in order to indicate the role of organizational factors in efficiency of the process to organization managers. Connection between six main factors in fulfillment of State Road Management and Transportation Organization were studied here, including Improvement of Strategic Thinking in senior managers, improvement of the organization business process, rationalization of resources allocation in different parts of the organization, coordination and conformity of strategic plan with organization needs, adjustment of organization activities with environmental changes, reinforcement of organizational culture. All said factors approved by implemented tests and then ranked using fuzzy multivariate decision-making technique.

Keywords: Fuzzy TOPSIS, improvement of organization business process, multivariate decision-making, strategic planning

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Authors: Faisal G. Khamis, Ghaleb A. El-Refae

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Many researchers have studied socioeconomic, health, and security variables in the developed countries; however, very few studies used multivariate analysis in developing countries. The current study contributes to the scarce literature about the determinants of the variance in socioeconomic, health, and security factors. Questions raised were whether the independent variables (IVs) of governorate and year impact the socioeconomic, health, and security dependent variables (DVs) in Jordan, whether the marginal mean of each DV in each governorate and in each year is significant, which governorates are similar in difference means of each DV, and whether these DVs vary. The main objectives were to determine the source of variances in DVs, collectively and separately, testing which governorates are similar and which diverge for each DV. The research design was time series and cross-sectional analysis. The main hypotheses are that IVs affect DVs collectively and separately. Multivariate and univariate analyses of variance were carried out to test these hypotheses. The population of 12 governorates in Jordan and the available data of 15 years (2000–2015) accrued from several Jordanian statistical yearbooks. We investigated the effect of two factors of governorate and year on the four DVs of divorce rate, mortality rate, unemployment percentage, and crime rate. All DVs were transformed to multivariate normal distribution. We calculated descriptive statistics for each DV. Based on the multivariate analysis of variance, we found a significant effect in IVs on DVs with p < .001. Based on the univariate analysis, we found a significant effect of IVs on each DV with p < .001, except the effect of the year factor on unemployment was not significant with p = .642. The grand and marginal means of each DV in each governorate and each year were significant based on a 95% confidence interval. Most governorates are not similar in DVs with p < .001. We concluded that the two factors produce significant effects on DVs, collectively and separately. Based on these findings, the government can distribute its financial and physical resources to governorates more efficiently. By identifying the sources of variance that contribute to the variation in DVs, insights can help inform focused variation prevention efforts.

Keywords: ANOVA, crime, divorce, governorate, hypothesis test, Jordan, MANOVA, means, mortality, unemployment, year

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Authors: Sunghoon Park, Hank Kim, Jinwon An, Sungzoon Cho

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Internet of Things allows one to collect data from facilities which are then used to monitor them and even predict malfunctions in advance. Conventional quality control methods focus on setting a normal range on a sensor value defined between a lower control limit and an upper control limit, and declaring as an anomaly anything falling outside it. However, interactions among sensor values are ignored, thus leading to suboptimal performance. We propose a multivariate approach which takes into account many sensor values at the same time. In particular Gaussian Mixture Model is used which is trained to maximize likelihood value using Expectation-Maximization algorithm. The number of Gaussian component distributions is determined by Bayesian Information Criterion. The negative Log likelihood value is used as an anomaly score. The actual usage scenario goes like a following. For each instance of sensor values from a facility, an anomaly score is computed. If it is larger than a threshold, an alarm will go off and a human expert intervenes and checks the system. A real world data from Building energy system was used to test the model.

Keywords: facility anomaly detection, gaussian mixture model, anomaly score, expectation maximization algorithm

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Authors: Ayten Ekin Meşe, Selahattin Şentürk, Melike Duvanoğlu

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Petroleum refineries are a highly complex process industry with continuous production and high operating costs. Physical separation of crude oil starts with the crude oil distillation unit, continues with various conversion and purification units, and passes through many stages until obtaining the final product. To meet the desired product specification, process parameters are strictly followed. To be able to ensure the quality of distillates, routine analyses are performed in quality control laboratories based on appropriate international standards such as American Society for Testing and Materials (ASTM) standard methods and European Standard (EN) methods. The cut point of distillates in the crude distillation unit is very crucial for the efficiency of the upcoming processes. In order to maximize the process efficiency, the determination of the quality of distillates should be as fast as possible, reliable, and cost-effective. In this sense, an alternative study was carried out on the crude oil distillation unit that serves the entire refinery process. In this work, studies were conducted with three different crude oil distillates which are Light Straight Run Naphtha (LSRN), Heavy Straight Run Naphtha (HSRN), and Kerosene. These products are named after separation by the number of carbons it contains. LSRN consists of five to six carbon-containing hydrocarbons, HSRN consist of six to ten, and kerosene consists of sixteen to twenty-two carbon-containing hydrocarbons. Physical properties of three different crude distillation unit products (LSRN, HSRN, and Kerosene) were determined using Near-Infrared Spectroscopy with multivariate calibration. The absorbance spectra of the petroleum samples were obtained in the range from 10000 cm⁻¹ to 4000 cm⁻¹, employing a quartz transmittance flow through cell with a 2 mm light path and a resolution of 2 cm⁻¹. A total of 400 samples were collected for each petroleum sample for almost four years. Several different crude oil grades were processed during sample collection times. Extended Multiplicative Signal Correction (EMSC) and Savitzky-Golay (SG) preprocessing techniques were applied to FT-NIR spectra of samples to eliminate baseline shifts and suppress unwanted variation. Two different multivariate calibration approaches (Partial Least Squares Regression, PLS and Genetic Inverse Least Squares, GILS) and an ensemble model were applied to preprocessed FT-NIR spectra. Predictive performance of each multivariate calibration technique and preprocessing techniques were compared, and the best models were chosen according to the reproducibility of ASTM reference methods. This work demonstrates the developed models can be used for routine analysis instead of conventional analytical methods with over 90% accuracy.

Keywords: crude distillation unit, multivariate calibration, near infrared spectroscopy, data preprocessing, refinery

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Authors: S. Benchelha, H. C. Aoudjehane, M. Hakdaoui, R. El Hamdouni, H. Mansouri, T. Benchelha, M. Layelmam, M. Alaoui

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The logistic regression (LR) and multivariate adaptive regression spline (MarSpline) are applied and verified for analysis of landslide susceptibility map in Oudka, Morocco, using geographical information system. From spatial database containing data such as landslide mapping, topography, soil, hydrology and lithology, the eight factors related to landslides such as elevation, slope, aspect, distance to streams, distance to road, distance to faults, lithology map and Normalized Difference Vegetation Index (NDVI) were calculated or extracted. Using these factors, landslide susceptibility indexes were calculated by the two mentioned methods. Before the calculation, this database was divided into two parts, the first for the formation of the model and the second for the validation. The results of the landslide susceptibility analysis were verified using success and prediction rates to evaluate the quality of these probabilistic models. The result of this verification was that the MarSpline model is the best model with a success rate (AUC = 0.963) and a prediction rate (AUC = 0.951) higher than the LR model (success rate AUC = 0.918, rate prediction AUC = 0.901).

Keywords: landslide susceptibility mapping, regression logistic, multivariate adaptive regression spline, Oudka, Taounate

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Authors: Jose Flores, Nadia Gamboa

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A proper water quality management requires the establishment of a monitoring network. Therefore, evaluation of the efficiency of water quality monitoring networks is needed to ensure high-quality data collection of critical quality chemical parameters. Unfortunately, in some Latin American countries water quality monitoring programs are not sustainable in terms of recording historical data or environmentally representative sites wasting time, money and valuable information. In this study, multivariate statistical techniques, such as principal components analysis (PCA) and hierarchical cluster analysis (HCA), are applied for identifying the most significant monitoring sites as well as critical water quality parameters in the monitoring network of the Jequetepeque River basin, in northern Peru. The Jequetepeque River basin, like others in Peru, shows socio-environmental conflicts due to economical activities developed in this area. Water pollution by trace elements in the upper part of the basin is mainly related with mining activity, and agricultural land lost due to salinization is caused by the extensive use of groundwater in the lower part of the basin. Since the 1980s, the water quality in the basin has been non-continuously assessed by public and private organizations, and recently the National Water Authority had established permanent water quality networks in 45 basins in Peru. Despite many countries use multivariate statistical techniques for assessing water quality monitoring networks, those instruments have never been applied for that purpose in Peru. For this reason, the main contribution of this study is to demonstrate that application of the multivariate statistical techniques could serve as an instrument that allows the optimization of monitoring networks using least number of monitoring sites as well as the most significant water quality parameters, which would reduce costs concerns and improve the water quality management in Peru. Main socio-economical activities developed and the principal stakeholders related to the water management in the basin are also identified. Finally, water quality management programs will also be discussed in terms of their efficiency and sustainability.

Keywords: PCA, HCA, Jequetepeque, multivariate statistical

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Authors: Dwi Kartika Rukmi, Miftafu Darussalam

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Background: The disclosure of women’s HIV status toward their sexual partners is an important issue that should be regarded as one of the efforts to prevent and control the spread of HIV. Research on the disclosure of seropositive HIV status as well as women-related factors in Indonesia, especially Yogyakarta is only a few. Methods: This is a correlational descriptive research along with its cross-sectional approach on 329 women with HIV/AIDS at the Victory Plus NGO from June to July 2016. This research used a purposive sampling method and a questionnaire as the data collection technique. The bivariate analysis test was undertaken by using a chi-square and multivariate test along with a logistic regression. Result: The multivariate analysis and logistic regression show five independent variables related to the disclosure of seropositive HIV status of women with HIV/AIDS toward their sexual partners, namely ethnicity (aOR = 36,859; 95% CI; (6,544-207,616)) religion (aOR =0,255; 95%CI; (0,075-0,868)), discussion with partners prior to the HIV test (aOR =0,069; 95%CI; (0,065-0,438)) , types of sexual partners (aOR = 0.191; 95% CI; (0.082-0,445)) and knowledge on the partners’ HIV status (aOR = 0.036; 95% CI; (0.008-0.160)). The highest level of reason for seropositive HIV women not to be open about their partners’ status is the fear of being rejected by their partners and the environmental stigma of HIV AIDS disease. Conclusion: The disclosure of seropositive HIV status in women with HIV/AIDS in the Victory Plus NGO of Yogyakarta was 79.4% or classified as a high category with some related factors such as ethnicity, religion, discussion with partners prior to the HIV test, types of partners and knowledge on the partners’ HIV status.

Keywords: women, HIV, disclosure, sexual partner

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Authors: Achut Manandhar, Kenneth D. Morton, Peter A. Torrione, Leslie M. Collins

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The current trends in affect recognition research are to consider continuous observations from spontaneous natural interactions in people using multiple feature modalities, and to represent affect in terms of continuous dimensions, incorporate spatio-temporal correlation among affect dimensions, and provide fast affect predictions. These research efforts have been propelled by a growing effort to develop affect recognition system that can be implemented to enable seamless real-time human-computer interaction in a wide variety of applications. Motivated by these desired attributes of an affect recognition system, in this work a multi-dimensional affect prediction approach is proposed by integrating multivariate Relevance Vector Machine (MVRVM) with a recently developed Output-associative Relevance Vector Machine (OARVM) approach. The resulting approach can provide fast continuous affect predictions by jointly modeling the multiple affect dimensions and their correlations. Experiments on the RECOLA database show that the proposed approach performs competitively with the OARVM while providing faster predictions during testing.

Keywords: dimensional affect prediction, output-associative RVM, multivariate regression, fast testing

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Authors: Maryam Mousavi Nik, Sara Pasandian

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The aim of the current research was to determine the effectiveness of Cognitive-Behavioral Group Therapy (G-CBT) on stress, illness anxiety and obsessions-compulsion caused by the coronavirus crisis in adolescents (14-18-Year-olds) in Tehran, Iran. This research was carried out in the form of a semi-experimental study with a control group and in the framework of a pre-test and post-test design for both experimental and control groups. The statistical population of this research consisted of all high schools in Tehran in 2022. The sample size includes 32 Adolescents (14-18-Year-olds) who were selected using a cluster sampling method, and then they were randomly replaced in two experimental (n=16) and control (n=16) groups. In this research, an adolescent stress questionnaire (ASQ-N) with an emphasis on the impact of Coronavirus, Coronavirus disease anxiety (CDAS) and The Children's Yale-Brown Obsessive Compulsive Symptom Scale (CY-BOCS) emphasis on the Coronavirus were used, and group therapy intervention with The cognitive-behavioral approach was conducted for 8 sessions of 90 minutes in the experimental group. The research data were analyzed by Multivariate analysis of covariance (MANCOVA) and covariance (ANCVA) tests. The results of multivariate covariance analysis showed that group therapy intervention with a cognitive-behavioral approach had a significant effect on at least one of the variables of stress, illness anxiety and obsession-compulsion at the level (P<0.01, F=94.772) in the post-test stage. Also, the results of covariance analysis of one variable showed that group therapy intervention with a cognitive-behavioral approach in the level of (P<0.01, F=106.377) stress, in the level of (P<0.01, F=48.147) disease anxiety and in the level (P>0.01, F=17.033) of obsession-compulsion had a significant effect in the post-test stage. The results showed that The treatment with GCBT can be effective in decreasing stress, illness anxiety and obsessions and compulsion caused by the coronavirus crisis in Adolescents (15-20-Year-olds) and may be considered as an alternative to either individual cognitive-behavioral therapy or medication.

Keywords: stress, disease anxiety, obsession-compulsion, coronavirus (Covid-19) crisis, and cognitive-behavioral therapy

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Authors: Prozorkevitch D., Mishurov A., Sokolov K., Karsakov L., Pestrikova L.

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The current body of knowledge about the marine environment and the dynamics of marine ecosystems includes a huge amount of heterogeneous data collected over decades. It generally includes a wide range of hydrological, biological and fishery data. Marine researchers collect these data and analyze how and why the ecosystem changes from past to present. Based on these historical records and linkages between the processes it is possible to predict future changes. Multivariate analysis of trends and their interconnection in the marine ecosystem may be used as an instrument for predicting further ecosystem evolution. A wide range of information about the components of the marine ecosystem for more than 50 years needs to be used to investigate how these arrays can help to predict the future.

Keywords: barents sea ecosystem, abiotic, biotic, data sets, trends, prediction

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Authors: Nannapus Saramad, Rewwadee Petsirasan, Jom Suwanno

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Background: This retrospective study design was to describe average blood pressure, blood pressure level, target blood pressure control rate post-stroke BP control in the year following discharge from Sichon hospital, Sichon District, Nakhon Si Thammarat province. The secondary data analysis was employed from the patient’s health records with patient or caregiver interview. A total of 232 eligible post-acute ischemic strokes in the year following discharge (2017-2018) were recruited. Methods: Data analyses were applied to identify the relationship values of single variables were determined through univariate analyses: The Chi-square test, Fisher exact test, the variables found to have a p-value < 0.2 were analyzed by the binary logistic regression Results: Most of the patients in this study were men 61.6%, an average age of 65.4 ± 14.8 years. Systolic blood pressure levels were in the grade 1-2 hypertension and diastolic pressure at optimal and normal at all times during the initial treatment through the present. The results revealed 25% among the groups under the age of 60 achieved BP control; 36.3% for older than 60 years group; and 27.9% for diabetic group. The multivariate analysis revealed the final relationship of four significant variables: 1) receiving calcium-channel blocker (p =.027); 2) medication adherence of antihypertensive (p = .024) 3) medication adherence of antiplatelet ( p = .020); and 4) medication behavior ( p = . 010) . Conclusion: The medical nurse and health care provider should promote their adherence to behavior to improve their blood pressure control.

Keywords: acute ischemic stroke, target blood pressure control, medication adherence, recurrence stroke

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Authors: Azadeh Golshan, Craig Evans, Phillip Geary, Abigail Morrow, Zoe Rogers, Marcel Maeder

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22 physicochemical variables have been determined in water samples collected weekly from January to December in 2013 from three sampling stations located within a major drinking water reservoir. Classical Multivariate Curve Resolution Alternating Least Squares (MCR-ALS) analysis was used to investigate the environmental factors associated with the physico-chemical variability of the water samples at each of the sampling stations. Matrix augmentation MCR-ALS (MA-MCR-ALS) was also applied, and the two sets of results were compared for interpretative clarity. Links between these factors, reservoir inflows and catchment land-uses were investigated and interpreted in relation to chemical composition of the water and their resolved geographical distribution profiles. The results suggested that the major factors affecting reservoir water quality were those associated with agricultural runoff, with evidence of influence on algal photosynthesis within the water column. Water quality variability within the reservoir was also found to be strongly linked to physical parameters such as water temperature and the occurrence of thermal stratification. The two methods applied (MCR-ALS and MA-MCR-ALS) led to similar conclusions; however, MA-MCR-ALS appeared to provide results more amenable to interpretation of temporal and geological variation than those obtained through classical MCR-ALS.

Keywords: drinking water reservoir, multivariate analysis, physico-chemical parameters, water quality

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Authors: Nida Rizvi, Deeksha Katyal, Varun Joshi

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River Hindon is an important river catering the demand of highly populated rural and industrial cluster of western Uttar Pradesh, India. Water quality of river Hindon is deteriorating at an alarming rate due to various industrial, municipal and agricultural activities. The present study aimed at identifying the pollution sources and quantifying the degree to which these sources are responsible for the deteriorating water quality of the river. Various water quality parameters, like pH, temperature, electrical conductivity, total dissolved solids, total hardness, calcium, chloride, nitrate, sulphate, biological oxygen demand, chemical oxygen demand and total alkalinity were assessed. Water quality data obtained from eight study sites for one year has been subjected to the two multivariate techniques, namely, principal component analysis and cluster analysis. Principal component analysis was applied with the aim to find out spatial variability and to identify the sources responsible for the water quality of the river. Three Varifactors were obtained after varimax rotation of initial principal components using principal component analysis. Cluster analysis was carried out to classify sampling stations of certain similarity, which grouped eight different sites into two clusters. The study reveals that the anthropogenic influence (municipal, industrial, waste water and agricultural runoff) was the major source of river water pollution. Thus, this study illustrates the utility of multivariate statistical techniques for analysis and elucidation of multifaceted data sets, recognition of pollution sources/factors and understanding temporal/spatial variations in water quality for effective river water quality management.

Keywords: cluster analysis, multivariate statistical techniques, river Hindon, water quality

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Authors: A. Oukaci, R. Toufouti, D. Dib, l. Atarsia

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This article presents a multitude of alternative techniques to control the vector control, namely the nonlinear control and sliding mode control. Moreover, the implementation of their control law applied to the high-performance to the induction motor with the objective to improve the tracking control, ensure stability robustness to parameter variations and disturbance rejection. Tests are performed numerical simulations in the Matlab/Simulink interface, the results demonstrate the efficiency and dynamic performance of the proposed strategy.

Keywords: Induction Motor (IM), Non-linear Control (NLC), Sliding Mode Control (SMC), nonlinear sliding surface

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Authors: Poonam Magu, Kumud Khanna, P. Seetharaman

Abstract:

A kitchen is a major workplace in any home. A large variety of tasks, mainly related to meal preparation is performed here. The types of activities performed are varied and vast. In a way, it is the activities performed that determine the way the space within the kitchen is going to be utilised. A study was conducted in 510 Indian kitchens belonging to middle-income group families living in Delhi. It was conducted in three phases. In the first phase, 510 non-working homemakers were interviewed and questions pertaining to their personal characteristics, meal preparation and physical aspects related to the kitchen were asked. In the second phase, the technique of Path Process Chart was developed. Subsequently, a sub-sample of 50 homemakers was selected from the larger group. The activity of meal preparation was carried out by the homemakers themselves in their kitchens. A time and motion study was conducted using the technique of Path Process Chart. The results were analysed using the appropriate analysis sheets and conclusions were drawn. It was found that the entire kitchen and more specifically, the counter had been 'divided' into a number of workplaces. These workplaces were being used either for performing operations or for the purpose of storage. In many cases, it was used for both. On the whole, in 50 kitchens studied, 21 workplaces were identified which were used for performing operations related to meal preparation and 17 for storage It was also observed that almost the entire kitchen was used for the purpose of storage of some item or the other. The major workplaces where operations were performed were the range, workplaces to the right and left of range and sink and workplaces to the right or left of the sink. The same workplaces were also used for the purpose of storage. There were some workplaces outside the kitchen too, which were used for operations or storage. These were the dining table, courtyard or balcony, bedroom cupboard. On the whole, the range centre and the sink centre were found to be the two most important centres in an Indian kitchen belonging to urban middle-income group family.

Keywords: kitchen, workplace, meal preparation, path process chart

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Authors: Sunaitan Al Mutairi

Abstract:

A perfect start is a key factor for project completion on time. The study examined the effects of delayed mobilization of resources during the initial phases of the project. This paper mainly highlights the identification and categorization of all delays during the initial construction phase and their root cause analysis with corrective/control measures for the Kuwait Oil Company oil and gas projects. A relatively good percentage of the delays identified during the project execution (Contract award to end of defects liability period) attributed to mobilization/preliminary activity delays. Data analysis demonstrated significant increase in average project delay during the last five years compared to the previous period. Contractors had delays/issues during the initial phase, which resulted in slippages and progressively increased, resulting in time and cost overrun. Delays/issues not mitigated on time during the initial phase had very high impact on project completion. Data analysis of the delays for the past five years was carried out using trend chart, scatter plot, process map, box plot, relative importance index and Pareto chart. Construction of any project inside the Gathering Centers involves complex management skills related to work force, materials, plant, machineries, new technologies etc. Delay affects completion of projects and compromises quality, schedule and budget of project deliverables. Works executed as per plan during the initial phase and start-up duration of the project construction activities resulted in minor slippages/delays in project completion. In addition, there was a good working environment between client and contractor resulting in better project execution and management. Mainly, the contractor was on the front foot in the execution of projects, which had minimum/no delays during the initial and construction period. Hence, having a perfect start during the initial construction phase shall have a positive influence on the project success. Our research paper studies each type of delay with some real example supported by statistic results and suggests mitigation measures. Detailed analysis carried out with all stakeholders based on impact and occurrence of delays to have a practical and effective outcome to mitigate the delays. The key to improvement is to have proper control measures and periodic evaluation/audit to ensure implementation of the mitigation measures. The focus of this research is to reduce the delays encountered during the initial construction phase of the project life cycle.

Keywords: construction activities delays, delay analysis for construction projects, mobilization delays, oil & gas projects delays

Procedia PDF Downloads 313

Authors: Yi-Hsiang Pan, Ching-Hsiang Chen, Wei-Ting Hsu

Abstract:

The purpose of this study was to compare the learning effects of the sports education model (SEM) to those of the traditional teaching model (TTM) in physical education classes in terms of students learning motivation, action control, learning strategies, and learning performance. A quasi-experimental design was utilized in this study, and participants included two physical educators and four classes with a total of 94 students in grades 5 and 6 of elementary schools. Two classes implemented the SEM (n=47, male=24, female=23; age=11.89, SD=0.78) and two classes implemented the TTM (n=47, male=25, female=22, age=11.77; SD=0.66). Data were collected from these participants using a self-report questionnaire (including a learning motivation scale, action control scale, and learning strategy scale) and a game performance assessment instrument, and multivariate analysis of covariance was used to conduct statistical analysis. The findings of the study revealed that the SEM was significantly better than the TTM in promoting students learning motivation, action control, learning strategies, and game performance. It was concluded that the SEM could promote the mechanics of students self-regulated learning process, and thereby improve students movement performance.

Keywords: self-regulated learning theory, learning process, curriculum model, physical education

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Authors: Hossein Ilanloo, Sedigheh Ahmadi, Kianoosh Zahrakar

Abstract:

The present study aims at investigating the effectiveness of group counseling of mindfulness-based cognitive therapy on cognitive emotion regulation in high school students. The research design was quasi-experimental and pre-test-post-test type and a two-month follow-up with a control group. The statistical population of the study consisted of all-male high school students in Takestan city in the Academic Year 2020-2021. The sample comprised 30 high school male students selected through the convenience sampling method and randomly assigned to experimental (n=15) and control (n=15) groups. The experimental group then received ten sessions of 90-minute group counseling of mindfulness-based cognitive therapy, and the control group did not receive any intervention. In order to collect data, the author used the Cognitive Emotion Regulation Questionnaire (CERQ). The researcher also used multivariate analysis of covariance, repeated measures, LSD post hoc test, and SPSS-26 software for data analysis.

Keywords: mindfulness-based cognitive therapy, cognitive emotion regulation, students, high schools

Procedia PDF Downloads 119

Authors: Plessen Mogens Graf

Abstract:

Within the context of multivariate time series segmentation, this paper proposes a method inspired by a posteriori optimal trading. After a normalization step, time series are treated channelwise as surrogate stock prices that can be traded optimally a posteriori in a virtual portfolio holding either stock or cash. Linear transaction costs are interpreted as hyperparameters for noise filtering. Trading signals, as well as trading signals obtained on the reversed time series, are used for unsupervised channelwise labeling before a consensus over all channels is reached that determines the final segmentation time instants. The method is model-free such that no model prescriptions for segments are made. Benefits of proposed approach include simplicity, computational efficiency, and adaptability to a wide range of different shapes of time series. Performance is demonstrated on synthetic and real-world data, including a large-scale dataset comprising a multivariate time series of dimension 1000 and length 2709. Proposed method is compared to a popular model-based bottom-up approach fitting piecewise affine models and to a recent model-based top-down approach fitting Gaussian models and found to be consistently faster while producing more intuitive results in the sense of segmenting time series at peaks and valleys.

Keywords: time series segmentation, model-free, trading-inspired, multivariate data

Procedia PDF Downloads 130

Authors: H. J. Kim, K. H. Kim, N. H. Park, K. T. Nam, Y. H. Jung, T. H. Kim, J. H. Shin

Abstract:

Underground excavations in an urban area can cause various geotechnical problems such as ground loss and lowering of groundwater level. When the ground loss becomes uncontrollably large, sinkholes can be developed to the ground surface. A sinkhole is commonly known as the natural phenomenon associated with lime rock areas. However, sinkholes in urban areas due to pressurized sewers and/or tunneling are also frequently reported. In this study, mechanism of a sinkhole developed at the site ‘A’ where a tunneling work underwent is investigated. The sinkhole occurred in the sand strata with the high level of groundwater when excavating a tunnel of which diameter is 3.6 m. The sinkhole was progressed in two steps. The first step began with the local failure around the tunnel face followed by tons of groundwater inflow, and the second step was triggered by the TBM (Tunnel Boring Machine) chamber opening which led to the progressive general failure. The possibility of the sinkhole was evaluated by using Limit Equilibrium Method (LEM), and critical height was evaluated by the empirical stability chart. It is found that the lowering of the face pressure and inflow of groundwater into the tunnel face turned to be the main reason for the sinkhole.

Keywords: limit equilibrium method, sinkhole, stability chart, tunneling

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Authors: Ibrahim Suliman Hanaish

Abstract:

Disaggregation daily rainfall using stochastic models formulated based on multivariate approach (MuDRain) is discussed in this paper. Seven rain gauge stations are considered in this study for different distances from the referred station starting from 4 km to 160 km in Peninsular Malaysia. The hourly rainfall data used are covered the period from 1973 to 2008 and July and November months are considered as an example of dry and wet periods. The cross-correlation among the rain gauges is considered for the available hourly rainfall information at the neighboring stations or not. This paper discussed the applicability of the MuDRain model for disaggregation daily rainfall to hourly rainfall for both sources of cross-correlation. The goodness of fit of the model was based on the reproduction of fitting statistics like the means, variances, coefficients of skewness, lag zero cross-correlation of coefficients and the lag one auto correlation of coefficients. It is found the correlation coefficients based on extracted correlations that was based on daily are slightly higher than correlations based on available hourly rainfall especially for neighboring stations not more than 28 km. The results showed also the MuDRain model did not reproduce statistics very well. In addition, a bad reproduction of the actual hyetographs comparing to the synthetic hourly rainfall data. Mean while, it is showed a good fit between the distribution function of the historical and synthetic hourly rainfall. These discrepancies are unavoidable because of the lowest cross correlation of hourly rainfall. The overall performance indicated that the MuDRain model would not be appropriate choice for disaggregation daily rainfall.

Keywords: rainfall disaggregation, multivariate disaggregation rainfall model, correlation, stochastic model

Procedia PDF Downloads 509

Authors: K. Umbleja, M. Ichino, H. Yaguchi

Abstract:

In this paper, we propose a coloring method for multivariate data visualization by using parallel coordinates based on dissimilarity and tree structure information gathered during hierarchical clustering. The proposed method is an extension for proximity-based coloring that suffers from a few undesired side effects if hierarchical tree structure is not balanced tree. We describe the algorithm by assigning colors based on dissimilarity information, show the application of proposed method on three commonly used datasets, and compare the results with proximity-based coloring. We found our proposed method to be especially beneficial for symbolic data visualization where many individual objects have already been aggregated into a single symbolic object.

Keywords: data visualization, dissimilarity-based coloring, proximity-based coloring, symbolic data

Procedia PDF Downloads 165