Search results for: discrete-time queueing inventory model

Authors: Vijaya Dixit Aasheesh Dixit

Abstract:

Shipbuilding industry operates in Engineer Procure Construct (EPC) context. Product mix of a shipyard comprises of various types of ships like bulk carriers, tankers, barges, coast guard vessels, sub-marines etc. Each order is unique based on the type of ship and customized requirements, which are engineered into the product right from design stage. Thus, to execute every new project, a shipyard needs to upgrade its production expertise. As a result, over the long run, holistic learning occurs across different types of projects which contributes to the knowledge base of the shipyard. Simultaneously, in the short term, during execution of a project comprising of multiple sister ships, repetition of similar tasks leads to learning at activity level. This research aims to capture above learnings of a shipyard and incorporate learning curve effect in project scheduling and materials procurement to improve project performance. Extant literature provides support for the existence of such learnings in an organization. In shipbuilding, there are sequences of similar activities which are expected to exhibit learning curve behavior. For example, the nearly identical structural sub-blocks which are successively fabricated, erected, and outfitted with piping and electrical systems. Learning curve representation can model not only a decrease in mean completion time of an activity, but also a decrease in uncertainty of activity duration. Sister ships have similar material requirements. The same supplier base supplies materials for all the sister ships within a project. On one hand, this provides an opportunity to reduce transportation cost by batching the order quantities of multiple ships. On the other hand, it increases the inventory holding cost at shipyard and the risk of obsolescence. Further, due to learning curve effect the production scheduled of each consequent ship gets compressed. Thus, the material requirement schedule of every next ship differs from its previous ship. As more and more ships get constructed, compressed production schedules increase the possibility of batching the orders of sister ships. This work aims at integrating materials management with project scheduling of long duration projects for manufacturing of multiple sister ships. It incorporates the learning curve effect on progressively compressing material requirement schedules and addresses the above trade-off of transportation cost and inventory holding and shortage costs while satisfying budget constraints of various stages of the project. The activity durations and lead time of items are not crisp and are available in the form of probabilistic distribution. A Stochastic Mixed Integer Programming (SMIP) model is formulated which is solved using evolutionary algorithm. Its output provides ordering dates of items and degree of order batching for all types of items. Sensitivity analysis determines the threshold number of sister ships required in a project to leverage the advantage of learning curve effect in materials management decisions. This analysis will help materials managers to gain insights about the scenarios: when and to what degree is it beneficial to treat a multiple ship project as an integrated one by batching the order quantities and when and to what degree to practice distinctive procurement for individual ship.

Keywords: learning curve, materials management, shipbuilding, sister ships

Procedia PDF Downloads 482

Authors: Yulin Zhang, Kaixi Dong, Guozhen Zhao

Abstract:

Background: Different levels of life satisfaction are associated with some individual differences. Understanding the mechanism between them will help to enhance an individual’s well-being. On the one hand, traditional personality such as extraversion has been considered as the most stable and effective factor in predicting life satisfaction to the author’s best knowledge. On the other, individual emotional difference, such as alexithymia (difficulties identifying and describing one’s own feelings), is also closely related to life satisfaction. With the development of positive psychology, positive personalities such as virtues attract wide attention. And according to the broaden-and-build theory, social connectivity may mediate between emotion and life satisfaction. Therefore, the current study aims to explore the mediating role of social connectivity in the effect of positive personality and alexithymia on life satisfaction. Method: This study was conducted with 318 healthy Chinese college students whose age range from 18 to 30. Positive personality (including interpersonal, vitality, and cautiousness) was measured by the Chinese version of Values in Action Inventory of Strengths (VIA-IS). Alexithymia was measured by the Toronto Alexithymia Scale (TAS), and life satisfaction was measured by Satisfaction With Life Scale (SWLS). And social connectivity was measured by six items which have been used in previous studies. Each scale showed high reliability and validity. The mediating model was examined in Mplus 7.2 within a structural equation modeling (SEM) framework. Findings: The model fitted well and results revealed that both positive personality (95% confidence interval of indirect effect was [0.023, 0.097]) and alexithymia (95% confidence interval of indirect effect was [-0.270, -0.089]) predicted life satisfaction level significantly through social connectivity. Also, only positive personality significantly and directly predicted life satisfaction compared to alexithymia (95% confidence interval of direct effect was [0.109, 0.260]). Conclusion: Alexithymia predicts life satisfaction only through social connectivity, which emphasizes the importance of social bonding in enhancing the well-being of Chinese college students with alexithymia. And the positive personality can predict life satisfaction directly or through social connectivity, which provides implications for enhancing the well-being of Chinese college students by cultivating their virtue and positive psychological quality.

Keywords: alexithymia, life satisfaction, positive personality, social connectivity

Procedia PDF Downloads 147

Authors: I. C. Tolias, A. G. Venetsanos, N. Markatos

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In the present work, CFD simulations of a large scale open deflagration experiment are performed. Stoichiometric hydrogen-air mixture occupies a 20 m hemisphere. Two combustion models are compared and are evaluated against the experiment. The Eddy Dissipation Model and a Multi-physics combustion model which is based on Yakhot’s equation for the turbulent flame speed. The values of models’ critical parameters are investigated. The effect of the turbulence model is also examined. k-ε model and LES approach were tested.

Keywords: CFD, deflagration, hydrogen, combustion model

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Authors: J. Rhodes, V. Cheng, P. Lok

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The aim of this study is to develop a parsimonious model that explains the effect of different stimulus on a tourist’s intention to visit a new destination. The model consists of destination trust and interest as the mediating variables. The model was tested using two different types of stimulus; both studies empirically supported the proposed model. Furthermore, the first study revealed that advertising has a stronger effect than positive online reviews. The second study found that the peripheral route of the elaboration likelihood model has a stronger influence power than the central route in this context.

Keywords: advertising, electronic word-of-mouth, elaboration likelihood model, intention to visit, trust

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Authors: Ahmad Sarfaraz, Raiyad Herwies

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In this paper, a multi-criteria decision making analysis is used to help any organization selects the best KM tool that fits and serves its needs. The AHP model is used based on a previous study to highlight and identify the main criteria and sub-criteria that are incorporated in the selection process. Different KM tools alternatives with different criteria are compared and weighted accurately to be incorporated in the GP model. The main goal is to combine the GP model with the AHP model to ensure that selecting the KM tool considers the resource constraints. Two important issues are discussed in this paper: how different factors could be taken into consideration in forming the AHP model, and how to incorporate the AHP results into the GP model for better results.

Keywords: knowledge management, analytical hierarchy process, goal programming, multi-criteria decision making

Procedia PDF Downloads 356

Authors: Lu Zhao, Nadir Farhi, Yeltsin Valero, Zoi Christoforou, Nadia Haddadou

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In this paper, a long short-term memory (LSTM) neural network model is proposed to replicate simultaneously car-following and lane-changing behaviors in road networks. By combining two kinds of LSTM layers and three input designs of the neural network, six variants of the LSTM model have been created. These models were trained and tested on the NGSIM 101 dataset, and the results were evaluated in terms of longitudinal speed and lateral position, respectively. Then, we compared the LSTM model with a classical car-following model (the intelligent driving model (IDM)) in the part of speed decision. In addition, the LSTM model is compared with a model using classical neural networks. After the comparison, the LSTM model demonstrates higher accuracy than the physical model IDM in terms of car-following behavior and displays better performance with regard to both car-following and lane-changing behavior compared to the classical neural network model.

Keywords: traffic modeling, neural networks, LSTM, car-following, lane-change

Procedia PDF Downloads 224

Authors: Roya Yumul, Chse, Ofelia Loani Elvir Lazo, David Chernobylsky, Omar Durra

Abstract:

Background: Preoperative anxiety has been shown to be caused by the fear associated with surgical and anesthetic complications; however, the current gold standard for assessing patient anxiety, the STAI, is problematic to use in the preoperative setting given the duration and concentration required to complete the 40-item extensive questionnaire. Our primary aim in the study is to investigate the correlation of the Visual Facial Anxiety Scale (VFAS) and Numerical Verbal Rating Scale (NVRS) to State-Trait Anxiety Inventory (STAI) to determine the optimal anxiety scale to use in the perioperative setting. Methods: A clinical study of patients undergoing various surgeries was conducted utilizing each of the preoperative anxiety scales. Inclusion criteria included patients undergoing elective surgeries, while exclusion criteria included patients with anesthesia contraindications, inability to comprehend instructions, impaired judgement, substance abuse history, and those pregnant or lactating. 293 patients were analyzed in terms of demographics, anxiety scale survey results, and anesthesia data via Spearman Coefficients, Chi-Squared Analysis, and Fischer’s exact test utilized for comparison analysis. Results: Statistical analysis showed that VFAS had a higher correlation to STAI than NVRS (rs=0.66, p<0.0001 vs. rs=0.64, p<0.0001). The combined VFAS-Categorization Scores showed the highest correlation with the gold standard (rs=0.72, p<0.0001). Subgroup analysis showed similar results. STAI evaluation time (247.7 ± 54.81 sec) far exceeds VFAS (7.29 ± 1.61 sec), NVRS (7.23 ± 1.60 sec), and Categorization scales (7.29 ± 1.99 sec). Patients preferred VFAS (54.4%), Categorization (11.6%), and NVRS (8.8%). Anesthesiologists preferred VFAS (63.9%), NVRS (22.1%), and Categorization Scales (14.0%). Of note, the top five causes of preoperative anxiety were determined to be waiting (56.5%), pain (42.5%), family concerns (40.5%), no information about surgery (40.1%), or anesthesia (31.6%). Conclusions: Combined VFAS-Categorization Score (VCS) demonstrates the highest correlation to the gold standard, STAI. Both VFAS and Categorization tests also take significantly less time than STAI, which is critical in the preoperative setting. Among both patients and anesthesiologists, VFAS was the most preferred scale. This forms the basis of the Yumul FACES Anxiety Scale, designed for quick quantization and assessment in the preoperative setting while maintaining a high correlation to the golden standard. Additional studies using the formulated Yumul FACES Anxiety Scale are merited.

Keywords: numerical verbal anxiety scale, preoperative anxiety, state-trait anxiety inventory, visual facial anxiety scale

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Authors: Pegah Farokhzad

Abstract:

Family has a crucial role in maintaining the physical, social and mental health of the children. Most of the mental and anxiety problems of children reflects the complex interpersonal situations among family members, especially parents. In other words, anxiety problems of the children is correlated with deficit relationships of family members and improper child rearing styles. The parental child rearing styles leads to positive and negative consequences which affect the children’s mental health. Therefore, the present research was aimed to compare the parental child rearing styles and anxiety of children with stuttering and normal population. It was also aimed to study the relationship between parental child rearing styles and anxiety of children. The research sample included 54 boys with stuttering and 54 normal boys who were selected from the children (boys) of Tehran, Iran in the age range of 5 to 8 years in 2013. In order to collect data, Baumrind Child rearing Styles Inventory and Spence Parental Anxiety Inventory were used. Appropriate descriptive statistical methods and multivariate variance analysis and t test for independent groups were used to test the study hypotheses. Statistical data analyses demonstrated that there was a significant difference between stuttering boys and normal boys in anxiety (t = 7.601, p< 0.01); But there was no significant difference between stuttering boys and normal boys in parental child rearing styles (F = 0.129). There was also not found significant relationship between parental child rearing styles and children anxiety (F = 0.135, p< 0.05). It can be concluded that the influential factors of children’s society are parents, school, teachers, peers and media. So, parental child rearing styles are not the only influential factors on anxiety of children, and other factors including genetic, environment and child experiences are effective in anxiety as well. Details are discussed.

Keywords: child rearing styles, anxiety, stuttering, Iran

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Authors: Coskun Serefoglu

Abstract:

The study aims to analyse how a traditional sector such as agri-food could be mobilized through regional innovation strategies. A principal component analysis as well as qualitative information, such as in-depth interviews, focus group and surveys, were employed to find the priority sectors. An agri-food model was developed which includes both a linear model and interactive model. The model consists of two main components, one of which is technological integration and the other one is agricultural extension which is based on Land-grant university approach of U.S. which is not a common practice in Turkey.

Keywords: regional innovation strategy, interactive model, agri-food sector, local development, planning, regional development

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Authors: Sasiporn Rattanasupha, Settapat Chinviriyasit

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The treatment function adopts a continuous and differentiable function which can describe the effect of delayed treatment when the number of infected individuals increases and the medical condition is limited. In this paper, the SEIR epidemic model with treatment function is studied to investigate the dynamics of the model due to the effect of treatment. It is assumed that the treatment rate is proportional to the number of infective patients. The stability of the model is analyzed. The model is simulated to illustrate the analytical results and to investigate the effects of treatment on the spread of infection.

Keywords: basic reproduction number, local stability, SEIR epidemic model, treatment function

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Authors: Ramesh K. Adsul, V. R. Shinde, S. S. Jadhav

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The main aim of the present study was to explore the effect of various levels of parental acceptance – avoidance attitude on various areas of adjustment of urban and rural junior college students. It was hypothesized that 1. There exists no significant effect of various levels of parental acceptance attitude on adjustment of urban and rural junior college students. 2. There exists no significant effect of various levels of parental avoidance attitude on adjustment of urban and rural junior college students. 3. There would be no significant difference between urban and rural Junior College students on various areas of (home, health, social, and emotional) adjustment. The 847 students (427 boys and 420 girls) studying in 11th class of various Junior colleges in Sangli ,Satara and Kolhapur districts of Maharashtra State, India were selected by random sampling method. Study was conducted by using two psychological tests namely 1. Family Relationship Inventory. 2.Bell’s Adjustment Inventory. One way ANOVA was employed to find out the effect of parental acceptance – avoidance attitude and adjustment in various areas of urban and rural junior college students. ‘t’ test was used to find out the difference between urban and rural students on various areas of adjustment. The results of the study indicate that (1) It is observed that three groups of parental acceptance attitude (PA) are significantly varied on home and social adjustment. It means that PA affects home and social adjustment of adolescents. High PA creates excellent adjustment and low PA creates poor adjustment in adolescents. (2) Study revealed that PV significantly affects adjustment of adolescents. High PV significantly creates poor adjustment in adolescents than average and low PV. (3) There is significant difference between urban and rural adolescents on adjustment. Urban adolescents have better adjustment than rural adolescents.

Keywords: parental acceptance, avoidance attitude, adjustment, urban-rural student

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Authors: Rakesh Kumar Mishra, Tarun Kumar Dan

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Lead-Lag based Internal Model Control method is proposed based on Internal Model Control (IMC) strategy. In this paper, we have designed the Lead-Lag based Internal Model Control for binary distillation column for SISO process (considering only bottom product). The transfer function has been taken from Wood and Berry model. We have find the composition control and disturbance rejection using Lead-Lag based IMC and comparing with the response of simple Internal Model Controller.

Keywords: SISO, lead-lag, internal model control, wood and berry, distillation column

Procedia PDF Downloads 618

Authors: Malgorzata Sekulowicz, Krystyna Boron-Krupinska, Paulina Morga, Blazej Cieslik

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Burnout is highly prevalent in health care employees, especially in physicians. It significantly reduces the efficiency of these employees, which can have negative consequences for both physicians and patients. Resilience and mindfulness enhancing positive emotions, leading to sustainable development and personal commitment, can have a significant impact on burnout. Therefore, the aim of this study was to determine the relationship between burnout symptoms and mindfulness and resilience among physicians. The authors conducted a cross-sectional survey study among seventy-four polish physicians. Participants filled out the following psychometric tools: the Maslach Burnout Inventory - Human Services Survey (MBI-HSS), Five Facet Mindfulness Questionnaire (FFMQ), Areas of Work-Life Survey (AWS), International Personality Item Pool (IPIP), the Resilience Assessment Scale (SPP-25) and the Mini-COPE Inventory. The relationship between burnout and resilience and mindfulness was assessed with path analysis. Analyzing the relationship between MBI-HSS components and mindfulness, a significant negative correlation of the FFMQ score with emotional exhaustion (-0.50, p < 0.05) and depersonalization (-0.43, p < 0.05) and a positive correlation with personal accomplishment (0.50, p < 0.05) was demonstrated. Analyzing resilience, a statistically significant relationship of SPP-25 with all tested components of MBI-HSS was demonstrated: emotional exhaustion (-0.54, p < 0.05), depersonalization (-0.31, p < 0.05) and personal accomplishment (0.35, p < 0.05). In the group of medical doctors, the higher the level of mindfulness and resilience, the lower the risk of burnout. Furthermore, the more frequently used active coping strategies (planning, acceptance), the lower the risk of burnout, while the use of passive, evasive strategies increases the risk of burnout. It may be worth considering implementing mindfulness intervention to effectively manage burnout symptoms in this group.

Keywords: burnout, medical doctors, mindfulness, physicians, resilience

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Authors: H. Namazi, H. T. N. Kuan

Abstract:

It is known that in humans, the adaptation to a given odor occurs within a quite short span of time (typically one minute) after the odor is presented to the brain. Different models of human olfaction have been developed by scientists but none of these models consider the diffusion phenomenon in olfaction. A novel microscopic model of the human olfaction is presented in this paper. We develop this model by incorporating the transient diffusivity. In fact, the mathematical model is written based on diffusion of the odorant within the mucus layer. By the use of the model developed in this paper, it becomes possible to provide quantification of the objective strength of odor.

Keywords: diffusion, microscopic model, mucus layer, olfaction

Procedia PDF Downloads 487

Authors: Yanshuang Zhang, Byungho Jeong

Abstract:

There exists some time lag between the consumption of inputs and the production of outputs. This time lag effect should be considered in calculating efficiency of decision making units (DMU). Recently, a couple of DEA models were developed for considering time lag effect in efficiency evaluation of research activities. However, these models can’t discriminate efficient DMUs because of the nature of basic DEA model in which efficiency scores are limited to ‘1’. This problem can be resolved a super-efficiency model. However, a super efficiency model sometimes causes infeasibility problem. This paper suggests an output oriented super-efficiency model for efficiency evaluation under the consideration of time lag effect. A case example using a long term research project is given to compare the suggested model with the MpO model

Keywords: DEA, Super-efficiency, Time Lag, research activities

Procedia PDF Downloads 635

Authors: Ofelia Loani Elvir Lazo, Roya Yumul, David Chernobylsky, Omar Durra

Abstract:

Background: It is crucial to detect the patient’s existing anxiety to assist patients in a perioperative setting which is to be caused by the fear associated with surgical and anesthetic complications. However, the current gold standard for assessing patient anxiety, the STAI, is problematic to use in the preoperative setting, given the duration and concentration required to complete the 40-item questionnaire. Our primary aim in the study is to investigate the correlation of the Yumul Visual Facial Anxiety Scale (VFAS) and Numerical Verbal Rating Scale (NVRS) to State-Trait Anxiety Inventory (STAI) to determine the optimal anxiety scale to use in the perioperative setting. Methods: A clinical study of patients undergoing various surgeries was conducted utilizing each of the preoperative anxiety scales. Inclusion criteria included patients undergoing elective surgeries, while exclusion criteria included patients with anesthesia contraindications, inability to comprehend instructions, impaired judgement, substance abuse history, and those pregnant or lactating. 293 patients were analyzed in terms of demographics, anxiety scale survey results, and anesthesia data via Spearman Coefficients, Chi-Squared Analysis, and Fischer’s exact test utilized for comparative analysis. Results: Statistical analysis showed that VFAS had a higher correlation to STAI than NVRS (rs=0.66, p<0.0001 vs. rs=0.64, p<0.0001). The combined VFAS-Categorization Scores showed the highest correlation with the gold standard (rs=0.72, p<0.0001). Subgroup analysis showed similar results. STAI evaluation time (247.7 ± 54.81 sec) far exceeds VFAS (7.29 ± 1.61 sec), NVRS (7.23 ± 1.60 sec), and Categorization scales (7.29 ± 1.99 sec). Patients preferred VFAS (54.4%), Categorization (11.6%), and NVRS (8.8%). Anesthesiologists preferred VFAS (63.9%), NVRS (22.1%), and Categorization Scales (14.0%). Of note, the top five causes of preoperative anxiety were determined to be waiting (56.5%), pain (42.5%), family concerns (40.5%), no information about surgery (40.1%), or anesthesia (31.6%). Conclusıons: Both VFAS and Categorization tests also take significantly less time than STAI, which is critical in the preoperative setting. Combined VFAS-Categorization Score (VCS) demonstrates the highest correlation to the gold standard, STAI. Among both patients and anesthesiologists, VFAS was the most preferred scale. This forms the basis of the Yumul Faces Anxiety Scale, designed for quick quantization and assessment in the preoperative setting while maintaining a high correlation to the golden standard. Additional studies using the formulated Yumul Faces Anxiety Scale are merited.

Keywords: numerical verbal anxiety scale, preoperative anxiety, state-trait anxiety inventory, visual facial anxiety scale

Procedia PDF Downloads 95

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

Abstract:

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

Keywords: validation, verification, formal, theorem prover

Procedia PDF Downloads 488

Authors: Matthew C. Best

Abstract:

Linear Multi-Input Multi-Output (MIMO) dynamic models can be identified, with no a priori knowledge of model structure or order, using a new Generalised Identifying Filter (GIF). Based on an Extended Kalman Filter, the new filter identifies the model iteratively, in a continuous modal canonical form, using only input and output time histories. The filter’s self-propagating state error covariance matrix allows easy determination of convergence and conditioning, and by progressively increasing model order, the best fitting reduced-order model can be identified. The method is shown to be resistant to noise and can easily be extended to identification of smoothly nonlinear systems.

Keywords: system identification, Kalman filter, linear model, MIMO, model order reduction

Procedia PDF Downloads 571

Authors: Tejush Badal, Sanaa Alwidian

Abstract:

Class diagrams are useful tools within the Unified Modelling Language (UML) to model and visualize the relationships between, and properties of objects within a system. As a system evolves over time and space (e.g., products), a series of models with several commonalities and variabilities create what is known as a model family. In circumstances where there are several versions of a model, examining each model individually, becomes expensive in terms of computation resources. To avoid performing redundant operations, this paper proposes an approach for representing a family of class diagrams into Union Models to represent model families using a single generic model. The paper aims to analyze and reason about a family of class diagrams using union models as opposed to individual analysis of each member model in the family. The union algorithm provides a holistic view of the model family, where the latter cannot be otherwise obtained from an individual analysis approach, this in turn, enhances the analysis performed in terms of speeding up the time needed to analyze a family of models together as opposed to analyzing individual models, one model at a time.

Keywords: analysis, class diagram, model family, unified modeling language, union model

Procedia PDF Downloads 52

Authors: Katharina Eberhardt, Florian Klaus Kaiser, Frank Schultmann

Abstract:

Last-mile distribution is one of the most critical parts of a disaster relief operation. Various uncertainties, such as infrastructure conditions, resource availability, and fluctuating beneficiary demand, render last-mile distribution challenging in disaster relief operations. The need to balance critical performance criteria like response time, meeting demand and cost-effectiveness further complicates the task. The occurrence of disasters cannot be controlled, and the magnitude is often challenging to assess. In summary, these uncertainties create a need for additional flexibility, agility, and preparedness in logistics operations. As a result, strategic planning and efficient network design are critical for an effective and efficient response. Furthermore, the increasing frequency of disasters and the rising cost of logistical operations amplify the need to provide robust and resilient solutions in this area. Therefore, we formulate a scenario-based bi-objective optimization model that integrates pre-positioning, allocation, and distribution of relief supplies extending the general form of a covering location problem. The proposed model aims to minimize underlying logistics costs while maximizing demand coverage. Using a set of disruption scenarios, the model allows decision-makers to identify optimal network solutions to address the risk of disruptions. We provide an empirical case study of the public authorities’ emergency food storage strategy in Germany to illustrate the potential applicability of the model and provide implications for decision-makers in a real-world setting. Also, we conduct a sensitivity analysis focusing on the impact of varying stockpile capacities, single-site outages, and limited transportation capacities on the objective value. The results show that the stockpiling strategy needs to be consistent with the optimal number of depots and inventory based on minimizing costs and maximizing demand satisfaction. The strategy has the potential for optimization, as network coverage is insufficient and relies on very high transportation and personnel capacity levels. As such, the model provides decision support for public authorities to determine an efficient stockpiling strategy and distribution network and provides recommendations for increased resilience. However, certain factors have yet to be considered in this study and should be addressed in future works, such as additional network constraints and heuristic algorithms.

Keywords: humanitarian logistics, bi-objective optimization, pre-positioning, last mile distribution, decision support, disaster relief networks

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Authors: T. Arshad

Abstract:

A correlation study was done to explore the relationship of intrusiveness, appraisal and thought control strategies in patients with Obsessive Compulsive Disorder. Theoretical frame work for the present study was Salkovskis (1985) cognitive model of obsessive compulsive disorder. Sample of 100 patients (men=48, women=52) of age 14-62 years (M=32.13, SD=10.37) was recruited from hospitals of Lahore, Pakistan. Revised Obsessional Intrusion Inventory, Stress Appraisal Measure, Thought Control Questionnaire and Symptoms Checklist-R were self-administered. Findings revealed that intrusiveness is correlated with appraisals (controllable by self, controllable by others, uncontrollable, stressfulness) and thought control strategy (punishment). Furthermore, appraisals (uncontrollable, stressfulness, controllable by others) were emerged as strong predictors for different through control strategies (distraction, punishment and social control). Moreover, men have higher frequency of intrusion, whereas women were frequently using social control as thought control strategy. Results implied that intrusiveness, appraisals (controllable by others, uncontrollable, stressfulness) and thought control strategy (punishment) are related which maintains the disorder.

Keywords: appraisal, intrusiveness, obsessive compulsive disorder, thought control strategies

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Authors: Soumiya Bhattacharjee, P. K. Champati Ray, Shovan L. Chattoraj, Mrinmoy Dhara

Abstract:

The entire Himalayan range is globally renowned for rainfall-induced landslides. The prime focus of the study is to determine rainfall based threshold for initiation of landslides that can be used as an important component of an early warning system for alerting stake holders. This research deals with temporal dimension of slope failures due to extreme rainfall events along the National Highway-58 from Karanprayag to Badrinath in the Garhwal Himalaya, India. Post processed 3-hourly rainfall intensity data and its corresponding duration from daily rainfall data available from Tropical Rainfall Measuring Mission (TRMM) were used as the prime source of rainfall data. Landslide event records from Border Road Organization (BRO) and some ancillary landslide inventory data for 2013 and 2014 have been used to determine Intensity Duration (ID) based rainfall threshold. The derived governing threshold equation, I= 4.738D^-0.025, has been considered for prediction of landslides of the study region. This equation was validated with an accuracy of 70% landslides during August and September 2014. The derived equation was considered for further prediction of landslides of the study region. From the obtained results and validation, it can be inferred that this equation can be used for initiation of landslides in the study area to work as a part of an early warning system. Results can significantly improve with ground based rainfall estimates and better database on landslide records. Thus, the study has demonstrated a very low cost method to get first-hand information on possibility of impending landslide in any region, thereby providing alert and better preparedness for landslide disaster mitigation.

Keywords: landslide, intensity-duration, rainfall threshold, TRMM, slope, inventory, early warning system

Procedia PDF Downloads 254

Authors: D. Thawinkarn, S. Wongbutlee

Abstract:

The Social Change Leadership model is strongly aligned with administration’s mission. This research aims to examine the elements of social change leadership, build and develop leadership for social change, and evaluate effectiveness of leadership development model for social change. The research operation has 3 phases: model studies by in-depth interviews and survey research; drafting and creating model which verified by the experts; and trial of model in schools. The results showed that administrators and teachers have the elements of leadership for social change in moderate level. These elements are ranged descending from consciousness of self, common purpose, congruence, collaboration, commitment, citizenship, and controversy with civility. Model of leadership for social change is included the principles, objectives, content, process. Workshop process: Results show that the model of leadership development for social change in administrators and teachers leads to higher score in leadership evaluation prior to administering the operation.

Keywords: leadership, social change model, organization, administrators

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Authors: A. Lakrim, D. Tahri

Abstract:

This paper sets out a behavioral macro-model of a Merged PiN and Schottky (MPS) diode based on silicon carbide (SiC). This model holds good for both static and dynamic electrothermal simulations for industrial applications. Its parameters have been worked out from datasheets curves by drawing on the optimization method: Simulated Annealing (SA) for the SiC MPS diodes made available in the industry. The model also adopts the Analog Behavioral Model (ABM) of PSPICE in which it has been implemented. The thermal behavior of the devices was also taken into consideration by making use of Foster’ canonical network as figured out from electro-thermal measurement provided by the manufacturer of the device.

Keywords: SiC MPS diode, electro-thermal, SPICE model, behavioral macro-model

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Authors: Funda Kul, İsmail Gür

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Pension scheme providers have to price mortality risk by accurate mortality forecasting method. There are many mortality-forecasting methods constructed and used in literature. The Lee-Carter model is the first model to consider stochastic improvement trends in life expectancy. It is still precisely used. Mortality forecasting is done by mortality index in the Lee-Carter model. It is assumed that mortality index fits ARIMA time series model. In this paper, we propose and use dynamic normal inverse gaussian distribution to modeling mortality indes in the Lee-Carter model. Using population mortality data for Italy, France, and Turkey, the model is forecasting capability is investigated, and a comparative analysis with other models is ensured by some well-known benchmarking criterions.

Keywords: mortality, forecasting, lee-carter model, normal inverse gaussian distribution

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Authors: Piotr Fiszeder, Marcin Fałdziński, Peter Molnár

Abstract:

The dynamic conditional correlation model of Engle (2002) is one of the most popular multivariate volatility models. However, this model is based solely on closing prices. It has been documented in the literature that the high and low price of the day can be used in an efficient volatility estimation. We, therefore, suggest a model which incorporates high and low prices into the dynamic conditional correlation framework. Empirical evaluation of this model is conducted on three datasets: currencies, stocks, and commodity exchange-traded funds. The utilisation of realized variances and covariances as proxies for true variances and covariances allows us to reach a strong conclusion that our model outperforms not only the standard dynamic conditional correlation model but also a competing range-based dynamic conditional correlation model.

Keywords: volatility, DCC model, high and low prices, range-based models, covariance forecasting

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Authors: Birsel Canan Demirbag, Kıymet Yesilcicek Calik, Hacer Kobya Bulut

Abstract:

Objective: This study was conducted to evaluate the problems of women over 65 with incontinence diagnosis. Methods: This descriptive study was conducted with women over 65 with incontinence diagnosis in four Family Health Centers in a city in Eastern Black Sea region between November 1, and December 20, 2015. 203, 107, 178, 180 women over 65 were registered in these centers and 262 had incontinence diagnosis at least once and had an ongoing complaint. 177 women were volunteers for the study. During home visits and using face-to-face survey methodology, participants were given socio-demographic characteristics survey, Sandvik severity scale, Incontinence Quality of Life Scale, Urogenital Distress Inventory and a questionnaire including challenges experienced due to incontinence developed by the researcher. Data were analyzed with SPSS program using percentages, numbers, Chi-square, Man-Whitney U and t test with 95% confidence interval and a significance level p <0.05. Findings: 67 ± 1.4 was the mean age, 2.05 ± 0.04 was parity, 44.5 ± 2.12 was menopause age, 66.3% were primary school graduates, 45.7% had deceased spouse, 44.4% lived in a large family, 67.2% had their own room, 77.8% had income, 89.2% could meet self- care, 73.2% had a diagnosis of mixed incontinence, 87.5% suffered for 6-20 years % 78.2 had diuretics, antidepressants and heart medicines, 20.5% had urinary fecal cases, 80.5% had bladder training at least once, 90.1% didn’t have bladder diary calendar/control training programs, 31.1% had hysterectomy for prolapse, 97.1'i% was treated with lower urinary tract infection at least once, 66.3% saw a doctor to get drug in the last three months, 76.2 could not go out alone, 99.2 % had at least one chronic disease, 87.6 % had constipation complain, 2.9% had chronic cough., 45.1% fell due to a sudden rise for toilet. Incontinence Impact Questionnaire Average score was (QOL) 54.3 ± 21.1, Sandvik score was 12.1 ± 2.5, Urogenital Distress Inventory was 47.7 ± 9.2. Difficulties experienced due to incontinence were 99.5% feeling of unhappiness, 67.1% constant feeling of urine smell due to failing to change briefs frequently, % 87.2 move away from social life, 89.7 unable to use pad, 99.2% feeling of disturbing households / other individuals, 87.5% feel dizziness/fall due to sudden rise, 87.4% feeling of others’ imperceptions about the situation, % 94.3 insomnia, 78.2 lack of assistance, 84.7% couldn’t afford urine protection briefs. Results: With this study, it was found out that there were a lot of unsolved issues at individual and community level affecting the life quality of women with incontinence. In accordance with this common problem in women, to facilitate daily life it is obvious that regular home care training programs at institutional level in our country will be effective.

Keywords: health problems, incontinence, incontinence quality of life questionnaire, old age, urinary urogenital distress inventory, Sandviken severity, women

Procedia PDF Downloads 300

Authors: C. Shih, J. R. Wang, H. C. Chang, S. W. Chen, S. C. Chiang, T. Y. Yu

Abstract:

After the measurement uncertainty recapture (MUR) power uprates, Kuosheng nuclear power plant (NPP) was uprated the power from 2894 MWt to 2943 MWt. For power upgrade, several codes (e.g., TRACE, RELAP5, etc.) were applied to assess the safety of Kuosheng NPP. Hence, the main work of this research is to establish a RELAP5/MOD3.3 model of Kuosheng NPP with SNAP interface. The establishment of RELAP5/SNAP model was referred to the FSAR, training documents, and TRACE model which has been developed and verified before. After completing the model establishment, the startup test scenarios would be applied to the RELAP5/SNAP model. With comparing the startup test data and TRACE analysis results, the applicability of RELAP5/SNAP model would be assessed.

Keywords: RELAP5, TRACE, SNAP, BWR

Procedia PDF Downloads 407

Authors: Hoda Ghavamipoor, S. Alireza Hashemi Golpayegani

Abstract:

An approach to model the customer interaction with e-commerce websites is presented. Considering the service quality level as a predictive feature, we offer an improved method based on the Customer Behavior Model Graph (CBMG), a state-transition graph model. To derive the Quality of Service sensitive-CBMG (QoS-CBMG) model, process-mining techniques is applied to pre-processed website server logs which are categorized as ‘buy’ or ‘visit’. Experimental results on an e-commerce website data confirmed that the proposed method outperforms CBMG based method.

Keywords: customer behavior model, electronic commerce, quality of service, customer behavior model graph, process mining

Procedia PDF Downloads 389

Authors: Ishit Sheth, Chandrasekhar Jinendran, Chinmaya Ranjan Sahu

Abstract:

A fourteen degree of freedom (DOF) ride and handling control mathematical model is developed for a car using generalized boltzmann hamel equation which will create a basis for design of ride and handling controller. Mathematical model developed yield equations of motion for non-holonomic constrained systems in quasi-coordinates. The governing differential equation developed integrates ride and handling control of car. Model-based systems engineering approach is implemented for simulation using matlab/simulink, vehicle’s response in different DOF is examined and later validated using commercial software (ADAMS). This manuscript involves detailed derivation of full car vehicle model which provides response in longitudinal, lateral and yaw motion to demonstrate the advantages of the developed model over the existing dynamic model. The dynamic behaviour of the developed ride and handling model is simulated for different road conditions.

Keywords: Full Vehicle Model, MBSE, Non Holonomic Constraints, Boltzmann Hamel Equation

Procedia PDF Downloads 192