Search results for: ANOVA score model

Authors: Y. Sunecher, N. Mamode Khan, V. Jowaheer

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This paper considers the modelling of a non-stationary bivariate integer-valued autoregressive moving average of order one (BINARMA(1,1)) with correlated Poisson innovations. The BINARMA(1,1) model is specified using the binomial thinning operator and by assuming that the cross-correlation between the two series is induced by the innovation terms only. Based on these assumptions, the non-stationary marginal and joint moments of the BINARMA(1,1) are derived iteratively by using some initial stationary moments. As regards to the estimation of parameters of the proposed model, the conditional maximum likelihood (CML) estimation method is derived based on thinning and convolution properties. The forecasting equations of the BINARMA(1,1) model are also derived. A simulation study is also proposed where BINARMA(1,1) count data are generated using a multivariate Poisson R code for the innovation terms. The performance of the BINARMA(1,1) model is then assessed through a simulation experiment and the mean estimates of the model parameters obtained are all efficient, based on their standard errors. The proposed model is then used to analyse a real-life accident data on the motorway in Mauritius, based on some covariates: policemen, daily patrol, speed cameras, traffic lights and roundabouts. The BINARMA(1,1) model is applied on the accident data and the CML estimates clearly indicate a significant impact of the covariates on the number of accidents on the motorway in Mauritius. The forecasting equations also provide reliable one-step ahead forecasts.

Keywords: non-stationary, BINARMA(1, 1) model, Poisson innovations, conditional maximum likelihood, CML

Procedia PDF Downloads 123

Authors: Ramin Zargarbashi, Hamid Rabie, Behnam Panjavi, Hooman Kamran, Seyedarad Mosalamiaghili, Zohre Erfani, Seyed Peyman Mirghaderi, Maryam Salimi

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Background: Posterior shoulder dislocation is one of the disabling complications of brachial plexus birth injury (BPBI), and various treatment options, including capsule and surrounding muscles release for open reduction, humeral derotational osteotomy, and tendon transfers, have been recommended to manage it. In the present study, we aimed to determine the clinical outcome of open reduction with soft tissue release, tendon transfer, and glenoid osteotomy inpatients with BPBI and posterior shoulder dislocation or subluxation. Methods: From 2018 to 2020, 33 patients that underwent open reduction, glenoid osteotomy, and tendon transfer were included. The glenohumeral deformity was classified according to the Waters radiographic classification. Functional assessment was performed using the Mallet grading system before and at least two years after the surgery. Results: The patients were monitored for 26.88± 5.47 months. Their average age was 27.5±14 months. Significant improvement was seen in the overall Mallet score (from 13.5 to 18.91 points) and its segments, including hand to mouth, hand to the neck, global abduction, global external rotation, abduction degree, and external rotation degree. Hand-to-back score and the presence of trumpet sign were significantly decreased in the post-operation phase (all p values<0.001). The above-mentioned variables significantly changed for both infantile and non-infantile dislocations. Conclusion: Our study demonstrated that open reduction along with glenoid osteotomy improves retroversion, and muscle strengthening with different muscle transfers is an effective technique for BPBI.

Keywords: birth injuries, nerve injury, brachial plexus birth palsy, Erb palsy, tendon transfer

Procedia PDF Downloads 92

Authors: Jana Gutierez Chvalkovska, Michal Mejstrik, Matej Urban

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There are pending discussions over the mapping of country export potential in order to refocus export strategy of firms and its evidence-based promotion by the Export Credit Agencies (ECAs) and other permitted vehicles of governments. In this paper we develop our version of an applied model that offers “stepwise” elimination of unattractive markets. We modify and calibrate the model for the particular features of the Czech Republic and specific pilot cases where we apply an individual approach to each sector.

Keywords: export strategy, modeling export, calibration, export promotion

Procedia PDF Downloads 494

Authors: Enrique Barbieri

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The basic disease-spread model described by three states denoting the susceptible (S), infectious (I), and removed (recovered and deceased) (R) sub-groups of the total population N, or SIR model, has been considered. Heuristic mitigating action profiles of the pharmaceutical and non-pharmaceutical types may be developed in a control design setting for the purpose of reducing the transmission rate or improving the recovery rate parameters in the model. Even though the transmission and recovery rates are not control inputs in the traditional sense, a linear observer and feedback controller can be tuned to generate an asymptotic estimate of the transmission rate for a linearized, discrete-time version of the SIR model. Then, a set of mitigating actions is suggested to steer the basic reproduction number toward unity, in which case the disease does not spread, and the infected population state does not suffer from multiple waves. The special case of piecewise constant transmission rate is described and applied to a seventh-order SEIQRDP model, which segments the population into four additional states. The offline simulations in discrete time may be used to produce heuristic policies implemented by public health and government organizations.

Keywords: control of SIR, observer, SEIQRDP, disease spread

Procedia PDF Downloads 102

Authors: Anastasis D. Petrou

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Innovation and strategy discussions do highlight open innovation as a new paradigm in business. Yet, a number of stumbling blocks in the form of closed innovation principles weaved into the fabric of a traditional business model stand in the way of the new paradigm’s momentum to increase value in various business contexts. The paper argues that businesses considering an engagement with the open innovation paradigm would need to take steps to improve their multiplicative, absorptive and relational capabilities, respectively. The needed improvements would amount to a business model evolutionary transformation and eventually bring about a paradigm overhaul in business. The transformation is worth staging over time to ensure that open innovation is developed across interconnected and partnered areas of strategic importance. This article develops an open innovation strategy (OIS) capabilities model, and employs examples from different industries to briefly discuss OIS’s potential to augment business value in a number of suggested areas for future research.

Keywords: close innovation, open innovation paradigm, open innovation strategy (OIS) paradigm, OIS capabilities model, multiplicative capability, absorptive capability, relational capability

Procedia PDF Downloads 514

Authors: T. Yılmaz, Ş. Tavman

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In this study, optimization of ultrasound assisted extraction (UAE) of hemicellulose based polysaccharides from plant waste material has been studied. Selected material is hazelnut skin. Extraction variables for the operation are extraction time, amplitude and application temperature. Optimum conditions have been evaluated depending on responses such as amount of wet crude polysaccharide, total carbohydrate content and dried sample. Pretreated hazelnut skin powders were used for the experiments. 10 grams of samples were suspended in 100 ml water in a jacketed vessel with additional magnetic stirring. Mixture was sonicated by immersing ultrasonic probe processor. After the extraction procedures, ethanol soluble and insoluble sides were separated for further examinations. The obtained experimental data were analyzed by analysis of variance (ANOVA). Second order polynomial models were developed using multiple regression analysis. The individual and interactive effects of applied variables were evaluated by Box Behnken Design. The models developed from the experimental design were predictive and good fit with the experimental data with high correlation coefficient value (R2 more than 0.95). Extracted polysaccharides from hazelnut skin are assumed to be pectic polysaccharides according to the literature survey of Fourier Transform Spectrometry (FTIR) analysis results. No more change can be observed between spectrums of different sonication times. Application of UAE at optimized condition has an important effect on extraction of hemicellulose from plant material by satisfying partial hydrolysis to break the bounds with other components in plant cell wall material. This effect can be summarized by varied intensity of microjets and microstreaming at varied sonication conditions.

Keywords: hazelnut skin, optimization, polysaccharide, ultrasound assisted extraction

Procedia PDF Downloads 324

Authors: Xian Li, Qing-Guo Wang, Jiangshuai Huang, Jidong Liu, Ming Yu, Tan Kok Poh

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In power industry, accurate electricity demand forecasting for a certain leading time is important for system operation and control, etc. In this paper, we investigate the modeling and forecasting of Singapore’s electricity demand. Several standard models, such as HWT exponential smoothing model, the ARMA model and the ANNs model have been proposed based on historical demand data. We applied them to Singapore electricity market and proposed three refinements based on simulation to improve the modeling accuracy. Compared with existing models, our refined model can produce better forecasting accuracy. It is demonstrated in the simulation that by adding forecasting error into the forecasting equation, the modeling accuracy could be improved greatly.

Keywords: power industry, electricity demand, modeling, forecasting

Procedia PDF Downloads 636

Authors: B. Van Kessel, P. T. Kockelkorn, T. R. Speelman, T. C. Wierikx, C. Mai Van, T. A. Bogaard

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Saltwater intrusion is a common problem in estuaries around the world, as it could hinder the freshwater supply of coastal zones. This problem is likely to grow due to climate change and sea-level rise. The influence of these factors on the saltwater intrusion was investigated for the Cai River in the Khanh Hoa province in Vietnam. In addition, the Cai River has high seasonal fluctuations in discharge, leading to increased saltwater intrusion during the dry season. Sea level rise, river discharge changes, river mouth widening and a proposed saltwater intrusion prevention dam can have influences on the saltwater intrusion but have not been quantified for the Cai River estuary. This research used both an analytical and numerical model to investigate the effect of the aforementioned factors. The analytical model was based on a model proposed by Savenije and was calibrated using limited in situ data. The numerical model was a 3D hydrodynamic model made using the Delft3D4 software. The analytical model and numerical model agreed with in situ data, mostly for tidally average data. Both models indicated a roughly similar dependence on discharge, also agreeing that this parameter had the most severe influence on the modeled saltwater intrusion. Especially for discharges below 10 m/s3, the saltwater was predicted to reach further than 10 km. In the models, both sea-level rise and river widening mainly resulted in salinity increments up to 3 kg/m3 in the middle part of the river. The predicted sea-level rise in 2070 was simulated to lead to an increase of 0.5 km in saltwater intrusion length. Furthermore, the effect of the saltwater intrusion dam seemed significant in the model used, but only for the highest position of the gate.

Keywords: Cai River, hydraulic models, river discharge, saltwater intrusion, tidal barriers

Procedia PDF Downloads 105

Authors: Omar Alzeley, Sergey Utev

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Minimizing a constrained multivariate function is the fundamental of Machine learning, and these algorithms are at the core of data mining and data visualization techniques. The decision function that maps input points to output points is based on the result of optimization. This optimization is the central of learning theory. One approach to complex systems where the dynamics of the system is inferred by a statistical analysis of the fluctuations in time of some associated observable is time series analysis. The purpose of this paper is a mathematical transition from the autoregressive model of classical time series to the matrix formalization of quantum theory. Firstly, we have proposed a quantum time series model (QTS). Although Hamiltonian technique becomes an established tool to detect a deterministic chaos, other approaches emerge. The quantum probabilistic technique is used to motivate the construction of our QTS model. The QTS model resembles the quantum dynamic model which was applied to financial data. Secondly, various statistical methods, including machine learning algorithms such as the Kalman filter algorithm, are applied to estimate and analyses the unknown parameters of the model. Finally, simulation techniques such as Markov chain Monte Carlo have been used to support our investigations. The proposed model has been examined by using real and simulated data. We establish the relation between quantum statistical machine and quantum time series via random matrix theory. It is interesting to note that the primary focus of the application of QTS in the field of quantum chaos was to find a model that explain chaotic behaviour. Maybe this model will reveal another insight into quantum chaos.

Keywords: machine learning, simulation techniques, quantum probability, tensor product, time series

Procedia PDF Downloads 465

Authors: Lely A. Luengas, Pedro R. Vizcaya, Giovanni Sánchez

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In this paper, a methodology is presented to obtain the Static Alignment Model for any transtibial amputee person. The proposed methodology starts from experimental data collected on the Hospital Militar Central, Bogotá, Colombia. The effects of transtibial prosthesis malalignment on amputees were measured in terms of joint angles, center of pressure (COP) and weight distribution. Some statistical tools are used to obtain the model parameters. Mathematical predictive models of prosthetic alignment were created. The proposed models are validated in amputees and finding promising results for the prosthesis Static Alignment. Static alignment process is unique to each subject; nevertheless the proposed methodology can be used in each transtibial amputee.

Keywords: information theory, prediction model, prosthetic alignment, transtibial prosthesis

Procedia PDF Downloads 251

Authors: Zhilin Wang, Zhihao Zheng, Linxin Liu

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This study proposes a low-code model-building approach that aims to simplify the development and deployment of artificial intelligence (AI) models. With an intuitive way to drag and drop and connect components, users can easily build complex models and integrate multiple algorithms for training. After the training is completed, the system automatically generates a callable model service API. This method not only lowers the technical threshold of AI development and improves development efficiency but also enhances the flexibility of algorithm integration and simplifies the deployment process of models. The core strength of this method lies in its ease of use and efficiency. Users do not need to have a deep programming background and can complete the design and implementation of complex models with a simple drag-and-drop operation. This feature greatly expands the scope of AI technology, allowing more non-technical people to participate in the development of AI models. At the same time, the method performs well in algorithm integration, supporting many different types of algorithms to work together, which further improves the performance and applicability of the model. In the experimental part, we performed several performance tests on the method. The results show that compared with traditional model construction methods, this method can make more efficient use, save computing resources, and greatly shorten the model training time. In addition, the system-generated model service interface has been optimized for high availability and scalability, which can adapt to the needs of different application scenarios.

Keywords: low-code, model building, artificial intelligence, algorithm integration, model deployment

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Authors: Safak Akdemir

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The main purpose of this research is to evaluate the relationships between childhood traumas and dissociative experiences, self-perceptions and early maladaptive schemas in male convicts convicted of sexual assault crimes in prison. In our study, male convicts in prison for the crime of sexual assault constitute the experimental group, and the participants matched with this experimental group in terms of education, age and gender constitute the control group. The experimental group of the research consists of 189 male individuals who are convicted in the Ministry of Justice, General Directorate of Prisons, Istanbul/Maltepe L Type Closed Prison. The control group of this study consists of 147 adult males matched with the experimental group in terms of age, gender and education parameters. A total of 336 adult male individuals are included in the sample of this study. 46% of the experimental group were convicted of only sexual assault, 54% of them were convicted of both sexual assault and murder, injury and drug crimes. Total of five data collection tools, namely the Personal Information Form created by S. A. & E. O., Childhood Trauma Questionnaire (CTQ), the Dissociative Experiences Scale (DES), the Rosenberg Self-Esteem Scale (RSES), and the Young Schema Questionnaire-Short Form (YSQ-SF3), were completed. DES cut-off score of 99 (52.39%) of 189 convicts in the experimental group and 12 (8.17%) of 147 people in the control group was found to be 30 and above, and this result indicates the presence of pathological dissociative experiences. 180 (95.23%) of the sexual assault convicts in the experimental group had at least one childhood trauma, 154 (81.48%) were emotional neglect, 140 (74.07%) were emotional abuse, 121 (64.02%) were physical neglect, 91 (4814%) physical abuse and 70 (37.03%) sexual abuse. 168 (88.88%) of the experimental group reported multiple type of trauma and 12 (6.34%) reported single type of trauma. While the childhood traumas, isolation, abandonment and emotional deprivation schema levels of the convicts with a DES cut-off score of 30 and above are higher than the convicts with a DES cut-off score of 30 and above, their self-esteem is lower than this group. Experimental group while childhood traumas, dissociative experiences and early maladaptive schemas are higher than the control group, their self-esteem levels are lower. Dissociative experiences, abandonment and emotional deprivation early maladaptive schemas are more common in convicts aged between 18-30 years compared to convicts aged 31 and over. In addition, dissociative experiences and early maladaptive schemas of male convicts who reported physical and sexual abuse were higher than those who did not report physical and sexual abuse, while their self-esteem was at a lower level. As a result, in terms of psychotraumatology and clinical forensic psychology, dissociative disorders developed under the influence of chronic childhood traumas, with clinical interviews and psychometric measurements to be made in terms of forensic psychiatry; it is of fundamental importance to evaluate it in terms of neurosis-psychosis distinction, disability retirement, custody, malpractice, criminal and legal capacity criteria.

Keywords: crime, sexual assault, criminology, rape crimes, dissocitative disorders, maladative schemas

Procedia PDF Downloads 63

Authors: Christopher Deekia Nwimae, Nigel Simms, Liyun Lao

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Erosion in pipe bends caused by particles is a major obstacle in the oil and gas fields and might cause the breakdown of production equipment. This work studied the effects imposed by flow velocity and impact of solid particles diameter in an elbow; erosion rate was verified with experimental data using the computational fluid dynamics (CFD) approach. Two-way coupled Euler-Lagrange and discrete phase model was employed to calculate the air/solid particle flow in an elbow. One erosion model and three-particle rebound models were used to predict the erosion rate on the 90° elbows. The generic erosion model was used in the CFD-based erosion model, and after comparing it with experimental data, results showed agreement with the CFD-based predictions as observed.

Keywords: erosion, prediction, elbow, computational fluid dynamics

Procedia PDF Downloads 149

Authors: Siamak Yaghoubi, Vahideh Rashtchi, Marzieh Khezri, Hamid Kayalha, Monadi Hamidfar

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Background and objectives: Effective postoperative pain management in abdominal surgeries, which are painful procedures, plays an important role in reducing postoperative complications and increasing patient’s satisfaction. There are many techniques for pain control, one of which is Patient-Controlled Analgesia (PCA). The aim of this study was to compare the analgesic effects of morphine, paracetamol and ketorolac in the patients undergoing open cholecystectomy, using PCA method. Material and Methods: This randomized controlled trial was performed on 330 ASA (American Society of Anesthesiology) I-II patients ( three equal groups, n=110) who were scheduled for elective open cholecystectomy in Shahid Rjaee hospital of Qazvin, Iran from August 2013 until September 2015. All patients were managed by general anesthesia with TIVA (Total Intra Venous Anesthesia) technique. The control group received morphine with maximum dose of 0.02mg/kg/h, the paracetamol group received paracetamol with maximum dose of 1mg/kg/h, and the ketorolac group received ketorolac with maximum daily dose of 60mg using IV-PCA method. The parameters of pain, nausea, hemodynamic variables (BP and HR), pruritus, arterial oxygen desaturation, patient’s satisfaction and pain score were measured every two hours for 8 hours following operation in all groups. Results: There were no significant differences in demographic data between the three groups. there was a statistically significant difference with regard to the mean pain score at all times between morphine and paracetamol, morphine and ketorolac, and paracetamol and ketorolac groups (P<0.001). Results indicated a reduction with time in the mean level of postoperative pain in all three groups. At all times the mean level of pain in ketorolac group was less than that in the other two groups (p<0.001). Conclusion: According to the results of this study ketorolac is more effective than morphine and paracetamol in postoperative pain control in the patients undergoing open cholecystectomy, using PCA method.

Keywords: analgesia, cholecystectomy, ketorolac, morphine, paracetamol

Procedia PDF Downloads 193

Authors: Yoshimoto Kurihara, Tad Gonsalves

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Currently, in the field of object posture estimation, there is research on estimating the position and angle of an object by storing a 3D model of the object to be estimated in advance in a computer and matching it with the model. However, in this research, we have succeeded in creating a module that is much simpler, smaller in scale, and faster in operation. Our 6D pose estimation model consists of two different networks – a classification network and a regression network. From a single RGB image, the trained model estimates the class of the object in the image, the coordinates of the object, and its rotation angle in 3D space. In addition, we compared the estimation accuracy of each camera position, i.e., the angle from which the object was captured. The highest accuracy was recorded when the camera position was 75°, the accuracy of the classification was about 87.3%, and that of regression was about 98.9%.

Keywords: 6D posture estimation, image recognition, deep learning, AlexNet

Procedia PDF Downloads 148

Authors: Mohammad Y. Badiee, Saeed Golestani, Mir Saman Pishvaee

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In recent years consumers and governments have been pushing companies to design their activities in such a way as to reduce negative environmental impacts by producing renewable product or threat free disposal policy more and more. It is therefore important to focus more accurate to the optimization of various aspect of total supply chain. Modeling a supply chain can be a challenging process due to the fact that there are a large number of factors that need to be considered in the model. The use of multi-objective optimization can lead to overcome those problems since more information is used when designing the model. Uncertainty is inevitable in real world. Considering uncertainty on parameters in addition to use multi-objectives are ways to give more flexibility to the decision making process since the process can take into account much more constraints and requirements. In this paper we demonstrate a stochastic scenario based robust model to cope with uncertainty in a closed-loop multi-objective supply chain. By applying the proposed model in a real world case, the power of proposed model in handling data uncertainty is shown.

Keywords: supply chain management, closed-loop supply chain, multi-objective optimization, goal programming, uncertainty, robust optimization

Procedia PDF Downloads 409

Authors: Selin Guney, Andres Riquelme

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The traditional bio-economic method for fisheries modeling uses some estimate of the growth parameters and the system carrying capacity from a biological model for the population dynamics (usually a logistic population growth model) which is then analyzed as a traditional production function. The stock dynamic is transformed into a revenue function and then compared with the extraction costs to estimate the maximum economic yield. In this paper, the logistic population growth model for the population is combined with a forecast of the abundance and location of the stock by using a generalized additive model approach. The paper focuses on the Chilean hake population. This method allows for the incorporation of climatic variables and the interaction with other marine species, which in turn will increase the reliability of the estimates and generate better extraction paths for different conservation objectives, such as the maximum biological yield or the maximum economic yield.

Keywords: bio-economic, fisheries, GAM, production

Procedia PDF Downloads 243

Authors: Michael Zaidman, Naum Simanovsky

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Introduction. Symptomatic tarsal coalition with rigid flat foot often demands operative solution. An isolated coalition resection does not guarantee pain relief; correction of co-existing foot deformity may be required. The objective of the study was to analyze the results of combination of tarsal coalition resection and arthroereisis. Patients and methods. We retrospectively reviewed medical records and radiographs of children operatively treated in our institution for symptomatic calcaneonavicular or talocalcaneal coalition between the years 2019 and 2022. Eight patients (twelve feet), 4 boys and 4 girls with mean age 11.2 years, were included in the study. In six patients (10 feet) calcaneonavicular coalition was diagnosed, two patients (two feet) sustained talonavicular coalition. To quantify degrees of foot deformity, we used calcaneal pitch angle, lateral talar-first metatarsal (Meary's) angle, and talonavicular coverage angle. The clinical results were assessed using the American Orthopaedic Foot and Ankle Society (AOFAS) Ankle Hindfoot Score. Results. The mean follow-up was 28 month. The preoperative mean talonavicular coverage angle was 17,75º as compared with postoperative mean angle of 5.4º. The calcaneal pitch angle improved from mean 6,8º to 16,4º. The mean preoperative Meary’s angle of -11.3º improved to mean 2.8º. The preoperative mean AOFAS score improved from 54.7 to 93.1 points post-operatively. In nine of twelve feet, overall clinical outcome judged by AOFAS scale was excellent (90-100 points), in three feet was good (80-90 points). Six patients (ten feet) obviously improved their subtalar range of motion. Conclusion. For symptomatic stiff or rigid flat feet associated with tarsal coalition, the combination of coalition resection and arthroereisis leads to normalization of radiographic parameters, clinical and functional improvement with good patient’s satisfaction and likely to be more effective than the isolated procedures.

Keywords: rigid flat foot, tarsal coalition resection, arthroereisis, outcome

Procedia PDF Downloads 62

Authors: Ammar Asma, Bouafia Nabiha, Dhahri Meriem, Ben Cheikh Asma, Ezzi Olfa, Chafai Rim, Njah Mansour

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Despite recent advances in treatment of the lung cancer patients, the prognosis remains poor. Information is limited regarding health related quality of life (QOL) status of advanced lung cancer patients. The purposes of this study were: to assess patient reported symptom burden, to measure their QOL, and to identify determinant factors associated with QOL. Materials/Methods: A cross sectional study of 60 patients was carried out from over the period of 03 months from February 1st to 30 April 2016. Patients were recruited in two department of health care: Pneumology department in a university hospital in Sousse and an oncology unit in a University Hospital in Kairouan. Patients with advanced stage (III and IV) of lung cancer who were hospitalized or admitted in the day hospital were recruited by convenience sampling. We used a questionnaire administrated and completed by a trained interviewer. This questionnaire is composed of three parts: demographic, clinical and therapeutic information’s, QOL measurements: based on the SF-36 questionnaire, Symptom’s burden measurement using the Lung Cancer Symptom Scale (LCSS). To assess Correlation between symptoms burden and QOL, we compared the scores of two scales two by two using the Pearson correlation. To identify factors influencing QOL in Lung cancer, a univariate statistical analysis then, a stepwise backward approach, wherein the variables with p< 0.2, were carried out to determine the association between SF-36 scores and different variables. Results: During the study period, 60 patients consented to complete symptom and quality of life questionnaires at a single point time (72% were recruited from day hospital). The majority of patients were male (88%), age ranged from 21 to 79 years with a mean of 60.5 years. Among patients, 48 (80%) were diagnosed as having non-small cell lung carcinoma (NSCLC). Approximately, 60 % (n=36) of patients were in stage IV, 25 % in stage IIIa and 15 % in stage IIIb. For symptom burden, the symptom burden index was 43.07 (Standard Deviation, 21.45). Loss of appetite and fatigue were rated as the most severe symptoms with mean scores (SD): 49.6 (25.7) and 58.2 (15.5). The average overall score of SF36 was 39.3 (SD, 15.4). The physical and emotional limitations had the lowest scores. Univariate analysis showed that factors which influence negatively QOL were: married status (p<0.03), smoking cessation after diagnosis (p<0.024), LCSS total score (p<0.001), LCSS symptom burden index (p<0.001), fatigue (p<0.001), loss of appetite (p<0.001), dyspnea (p<0.001), pain (p<0.002), and metastatic stage (p<0.01). In multivariate analysis, unemployment (p<0.014), smoking cessation after diagnosis (p<0.013), consumption of analgesic (p<0.002) and the indication of an analgesic radiotherapy (p<0.001) are revealed as independent determinants of QOL. The result of the correlation analyses between total LCSS scores and the total and individual domain SF36 scores was significant (p<0.001); the higher total LCSS score is, the poorer QOL is. Conclusion: A built in support of lung cancer patients would better control the symptoms and promote the QOL of these patients.

Keywords: quality of life, lung cancer, metastasis, symptoms burden

Procedia PDF Downloads 375

Authors: S. Sonkham, U. Pinsopon, W. Chatlatanagulchai

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This paper presents a method of sliding mode control (SMC) designing and developing for the servo system in a dual-stage actuator (DSA) hard disk drive. Mathematical modelling of hard disk drive actuators is obtained, extracted from measuring frequency response of the voice-coil motor (VCM) and PZT micro-actuator separately. Matlab software tools are used for mathematical model estimation and also for controller design and simulation. A model-reference approach for tracking requirement is selected as a proposed technique. The simulation results show that performance of a model-reference SMC controller design in DSA servo control can be satisfied in the tracking error, as well as keeping the positioning of the head within the boundary of +/-5% of track width under the presence of internal and external disturbance. The overall results of model-reference SMC design in DSA are met per requirement specifications and significant reduction in %off track is found when compared to the single-state actuator (SSA).

Keywords: hard disk drive, dual-stage actuator, track following, hdd servo control, sliding mode control, model-reference, tracking control

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Authors: Shahrokh Barati

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In this paper, we introduced AIDS disease at first, then proposed dynamic model illustrate its progress, after expression of a short history of nonlinear modeling by polynomial phasing systems, we considered the stability conditions of the systems, which contained a huge amount of researches in order to modeling and control of AIDS in dynamic nonlinear form, in this approach using a frame work of control any polynomial phasing modeling system which have been generalized by part of phasing model of T-S, in order to control the system in better way, the stability conditions were achieved based on polynomial functions, then we focused to design the appropriate controller, firstly we considered the equilibrium points of system and their conditions and in order to examine changes in the parameters, we presented polynomial phase model that was the generalized approach rather than previous Takagi Sugeno models, then with using case we evaluated the equations in both open loop and close loop and with helping the controlling feedback, the close loop equations of system were calculated, to simulate nonlinear model of AIDS disease, we used polynomial phasing controller output that was capable to make the parameters of a nonlinear system to follow a sustainable reference model properly.

Keywords: polynomial fuzzy, AIDS, nonlinear AIDS model, fuzzy control systems

Procedia PDF Downloads 462

Authors: Guru Prakash, Revanth Dugalam

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A road’s condition often deteriorates due to harsh loading such as overload due to trucks, and severe environmental conditions such as heavy rain, snow load, and cyclic loading. In absence of proper maintenance planning, this results in potholes, wide cracks, bumps, and increased roughness of roads. In this paper, a data-driven model will be developed to detect these damages using vibration and image signals. The key idea of the proposed methodology is that the road anomaly manifests in these signals, which can be detected by training a machine learning algorithm. The use of various machine learning techniques such as the support vector machine and Radom Forest method will be investigated. The proposed model will first be trained and tested with artificially simulated data, and the model architecture will be finalized by comparing the accuracies of various models. Once a model is fixed, the field study will be performed, and data will be collected. The field data will be used to validate the proposed model and to predict the future road’s health condition. The proposed will help to automate the road condition monitoring process, repair cost estimation, and maintenance planning process.

Keywords: SVM, data-driven, road health monitoring, pot-hole

Procedia PDF Downloads 81

Authors: Babek Erdebilli

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The aim of this study is to develop and describe a new methodology for the Multi-Criteria Decision-Making (MCDM) problem using IFE (Elimination Et Choix Traduisant La Realite (ELECTRE) model. The proposed models enable Decision-Makers (DMs) on the assessment and use Intuitionistic Fuzzy Numbers (IFN). A numerical example is provided to demonstrate and clarify the proposed analysis procedure. Also, an empirical experiment is conducted to validation the effectiveness.

Keywords: multi-criteria decision-making, IFE, DM’s, fuzzy electre model

Procedia PDF Downloads 643

Authors: Sangwoo Han, Saeed Khaleghi Rahimian, Ying Liu

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Vehicle electrification is gaining momentum, and many car manufacturers promise to deliver more electric vehicle (EV) models to consumers in the coming years. In controlling the battery pack, the battery management system (BMS) must maintain optimal battery performance while ensuring the safety of a battery pack. Tasks related to battery performance include determining state-of-charge (SOC), state-of-power (SOP), state-of-health (SOH), cell balancing, and battery charging. Safety related functions include making sure cells operate within specified, static and dynamic voltage window and temperature range, derating power, detecting faulty cells, and warning the user if necessary. The BMS often utilizes an RC circuit model to model a Li-ion cell because of its robustness and low computation cost among other benefits. Because an equivalent circuit model such as the RC model is not a physics-based model, it can never be a prognostic model to predict battery state-of-health and avoid any safety risk even before it occurs. A physics-based Li-ion cell model, on the other hand, is more capable at the expense of computation cost. To avoid the high computation cost associated with a full-order model, many researchers have demonstrated the use of a single particle model (SPM) for BMS applications. One drawback associated with the single particle modeling approach is that it forces to use the average current density in the calculation. The SPM would be appropriate for simulating drive cycles where there is insufficient time to develop a significant current distribution within an electrode. However, under a continuous or high-pulse electrical load, the model may fail to predict cell voltage or Li⁺ plating potential. To overcome this issue, a multi-particle reduced-order model is proposed here. The use of multiple particles combined with either linear or nonlinear charge-transfer reaction kinetics enables to capture current density distribution within an electrode under any type of electrical load. To maintain computational complexity like that of an SPM, governing equations are solved sequentially to minimize iterative solving processes. Furthermore, the model is validated against a full-order model implemented in COMSOL Multiphysics.

Keywords: battery management system, physics-based li-ion cell model, reduced-order model, single-particle and multi-particle model

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Authors: W. H. Wan Zakiyatussariroh, A. A. Nasuhar, W. Y. Wan Fairos, Z. A. Nazatul Shahreen

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Forecasting dengue incidence in a population can provide useful information to facilitate the planning of the public health intervention. Many studies on dengue cases in Malaysia were conducted but are limited in modeling the outbreak and forecasting incidence. This article attempts to propose the most appropriate time series model to explain the behavior of dengue incidence in Malaysia for the purpose of forecasting future dengue outbreaks. Several seasonal auto-regressive integrated moving average (SARIMA) models were developed to model Malaysia’s number of dengue incidence on weekly data collected from January 2001 to December 2011. SARIMA (2,1,1)(1,1,1)52 model was found to be the most suitable model for Malaysia’s dengue incidence with the least value of Akaike information criteria (AIC) and Bayesian information criteria (BIC) for in-sample fitting. The models further evaluate out-sample forecast accuracy using four different accuracy measures. The results indicate that SARIMA (2,1,1)(1,1,1)52 performed well for both in-sample fitting and out-sample evaluation.

Keywords: time series modeling, Box-Jenkins, SARIMA, forecasting

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Authors: Diana Coyl-Shepherd, Lisa Newland

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Research and theory suggest that parenting and parent-child attachment influence emotional development and well-being. Studies indicate that adolescents often describe differences in relationships with each parent and may form different types of attachment to mothers and fathers. During adolescence and young adulthood, romantic partners may also become attachment figures, influencing well being, and providing a relational context for emotion skill development. Mothers, however, tend to be remain the primary attachment figure; fathers and romantic partners are more likely to be secondary attachment figures. The following hypotheses were tested: 1) participants would rate mothers as more accepting and less rejecting than fathers, 2) participants would rate secure attachment to mothers higher and insecure attachment lower compared to father and romantic partner, 3) parental rejection and insecure attachment would be negatively related to life satisfaction and emotional intelligence, and 4) secure attachment and parental acceptance would be positively related life satisfaction and emotional intelligence. After IRB and informed consent, one hundred fifty adolescents and young adults (ages 11-28, M = 19.64; 71% female) completed an online survey. Measures included parental acceptance, rejection, attachment (i.e., secure, dismissing, and preoccupied), emotional intelligence (i.e., seeking and providing comfort, use, and understanding of self emotions, expressing warmth, understanding and responding to others’ emotional needs), and well-being (i.e., self-confidence and life satisfaction). As hypothesized, compared to fathers’, mothers’ acceptance was significantly higher t (190) = 3.98, p = .000 and rejection significantly lower t (190) = - 4.40, p = .000. Group differences in secure attachment were significant, f (2, 389) = 40.24, p = .000; post-hoc analyses revealed significant differences between mothers and fathers and between mothers and romantic partners; mothers had the highest mean score. Group differences in preoccupied attachment were significant, f (2, 388) = 13.37, p = .000; post-hoc analyses revealed significant differences between mothers and romantic partners, and between fathers and romantic partners; mothers have the lowest mean score. However, group differences in dismissing attachment were not significant, f (2, 389) = 1.21, p = .30; scores for mothers and romantic partners were similar; father means score was highest. For hypotheses 3 and 4 significant negative correlations were found between life satisfaction and dismissing parent, and romantic attachment, preoccupied father and romantic attachment, and mother and father rejection variables; secure attachment variables and parental acceptance were positively correlated with life satisfaction. Self-confidence was correlated only with mother acceptance. For emotional intelligence, seeking and providing comfort were negatively correlated with parent dismissing and mother rejection; secure mother and romantic attachment and mother acceptance were positively correlated with these variables. Use and understanding of self-emotions were negatively correlated with parent and partner dismissing attachment, and parent rejection; romantic secure attachment and parent acceptance were positively correlated. Expressing warmth was negatively correlated with dismissing attachment variables, romantic preoccupied attachment, and parent rejection; whereas attachment secure variables were positively associated. Understanding and responding to others’ emotional needs were correlated with parent dismissing and preoccupied attachment variables and mother rejection; only secure father attachment was positively correlated.

Keywords: adolescent emotional intelligence, life satisfaction, parent and romantic attachment, parental rejection and acceptance

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Authors: Andrés I. Ávila, Patricia Aros, César San Martín, Elizabeth Kehr, Yovana Leal

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Planning models for fresh products is a very useful tool for improving the net profits. To get an efficient supply chain model, several functions should be considered to get a complete simulation of several operational units. We consider a linear programming model to help farmers to decide if it is convenient to choose what area should be planted for three kinds of export fruits considering their future investment. We consider area, investment, water, productivity minimal unit, and harvest restrictions to develop a monthly based model to compute the average income in five years. Also, conditions on the field as area, water availability, and initial investment are required. Using the Chilean costs and dollar-peso exchange rate, we can simulate several scenarios to understand the possible risks associated to this market. Also, this tool help to support decisions for government and individual farmers.

Keywords: mixed integer problem, fresh fruit production, support decision model, agricultural and biosystems engineering

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Authors: Chamtouri I., Kechida M.

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Background: Evaluation has a prominent role in medical education and graduation. This evaluation has usually done in face-to-face, by written or oral questions. Simulation is increasingly taking a part as a method of evaluation. Due to the Covid-19 pandemic, which disrupted face-to-face evaluation, simulation using serious games (SG) is emerging in the field of training and assessment of medical students. The aim of our study is to compare the results of the evaluation of medical students by virtual simulation by online serious games versus clinical case-multiple choice questions (MCQ) and to assess the degree of satisfaction from these two evaluation methods. Methods: Medical students from the same study level were voluntarily participated in this study. Groupe 1 had an evaluation by SG dealing with “diagnosis and management of ST-segment elevationmyocardialinfarction (STEMI)alreadyprepared on the website www.Mediactiv.com. Groupe 2 were evaluated by clinical case-MCQ having thes same topic as SG. Results of the two groups were compared. Satisfaction questionnaire was filled by the two groups. Satisfaction degree was compared between the two groups. Results. In this study, 64 medical students (G1:31 and G2: 33) were enrolled. Obtaining complete notes in the "questioning" and "clinical examination" parts is significantly more important in-group 1 compared to group 2. No significant difference detected between the two groups in terms of “ECG interpretation” and “diagnosis of STEMI” parts. A greater number of students of group 1 obtained the full note compared to group 2 in “the initial treatment part” (54.8% vs. 39.4%; p = 0.04). Thirty learners (96.8%) in-group 1 obtained a total score ≥ 50% versus 69.7% in-group 2 (p = 0.004). The full score of 100% was obtained in three learners in-group1, while no student scored 100% in-group2 (p = 0.027). Medical evaluation using SG was reported as more innovative, fun, and realistic compared to evaluation by clinical case-MCQ. No significant difference detected between the two methods in terms of stress. Conclusion: Simulation by SG can be considered as an innovative and effective method in evaluating medical students with a higher degree of satisfaction.

Keywords: evaluation, serious games, medical students, satisfaction

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Authors: M. Maleki Sadabad, A. Pointing, N. Marashi

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With respect to the role and increasing importance of technology for countries development, in recent decades technology development has paid attention in a systematic form. Nowadays the markets face with highly complicated and competitive conditions in foreign markets, therefore, evaluation and selection of technology effectiveness and also formulating technology strategy have changed into a vital subject for some organizations. The study introduces the standards of empowerment evaluation and technology attractiveness especially strategic technologies which explain the way of technology evaluation, selection and finally formulating suitable technology strategy in the field of drilling in South Azadegan oil field. The study firstly identifies the key challenges of oil fields in order to evaluate the technologies in field of drilling in South Azadegan oil field through an interview with the experts of industry and then they have been prioritised. In the following, the existing and new technologies were identified to solve the challenges of South Azadegan oil field. In order to explore the ability, availability, and attractiveness of every technology, a questionnaire based on Julie indices has been designed and distributed among the industry elites. After determining the score of ability, availability and attractiveness, every technology which has been obtained by the average of expert’s ideas, the technology package has been introduced by Morin’s model. The matrix includes four areas which will follow the especial strategy. Finally, by analysing the above matrix, the technology options have been suggested in order to select and invest.

Keywords: technology, technology identification, drilling technologies, technology capability

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Authors: Sujit K. Basak

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The aim of this paper is to analyze the impact of literature review software on researchers. The aim of this study was achieved by analyzing models in terms of perceived usefulness, perceived ease of use, and acceptance level. Collected data was analyzed using WarpPLS 4.0 software. This study used two theoretical frameworks namely Technology Acceptance Model and the Training Needs Assessment Model. The study was experimental and was conducted at a public university in South Africa. The results of the study showed that acceptance level has a high impact on research workload and productivity followed by perceived usefulness and perceived ease of use.

Keywords: technology acceptance model, training needs assessment model, literature review software, research productivity

Procedia PDF Downloads 497