Search results for: resource estimation

Authors: Ahmed Rouili

Abstract:

Cantilever L-shaped walls are known to be relatively economical as retaining solution. The design starts by proportioning the wall dimensions for which the stability is checked for. A ratio between the lengths of the base and the stem, falling between 0,5 to 0,7, ensure the stability requirements in most cases. However, the displacement pattern of the wall in terms of rotations and translations, and the lateral pressure profile, do not have the same figure for all wall’s proportioning, as it is usually assumed. In the present work, the results of a numerical analysis are presented, different wall geometries were considered. The results show that the proportioning governs the equilibrium between the instantaneous rotation and the translation of the wall-toe, also, the lateral pressure estimation based on the average value between the at-rest and the active pressure, recommended by most design standards, is found to be not applicable for all walls.

Keywords: cantilever wall, proportioning, numerical analysis, lateral pressure estimation

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Authors: Hamed Zolfaghari, Mojtaba Kord

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After feasibility study the design phase is started and the rest of other phases are highly dependent on this phase. forecasting the duration of design phase could do a miracle and would save a lot of time. This study provides a fast and accurate Machine learning (ML) and optimization framework, which allows a quick duration estimation of project design phase, hence improving operational efficiency and competitiveness of a design construction company. 3 data sets of three years composed of daily time spent for different design projects are used to train and validate the ML models to perform multiple projects. Our study concluded that Artificial Neural Network (ANN) performed an accuracy of 0.94.

Keywords: time estimation, machine learning, Artificial neural network, project design phase

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Authors: Hao-Hsi Tseng, Hsin-Yun Lee, Yu-Cheng Kuo

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In order to understand whether there is a better than the learning function of learning methods and improve the CAD Courses for enterprise’s design human resource development, this research is applied in learning practical learning computer graphics software. In this study, Revit building information model for learning content, design of two different modes of learning curriculum to learning, learning functions, respectively, and project learning. Via a post-test, questionnaires and student interviews, etc., to study the effectiveness of a comparative analysis of two different modes of learning. Students participate in a period of three weeks after a total of nine-hour course, and finally written and hands-on test. In addition, fill in the questionnaire response by the student learning, a total of fifteen questionnaire title, problem type into the base operating software, application software and software-based concept features three directions. In addition to the questionnaire, and participants were invited to two different learning methods to conduct interviews to learn more about learning students the idea of two different modes. The study found that the ad hoc short-term courses in learning, better learning outcomes. On the other hand, functional style for the whole course students are more satisfied, and the ad hoc style student is difficult to accept the ad hoc style of learning.

Keywords: development, education, human resource, learning

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Authors: Z. Masoumi, B. Moaveni

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This article is about first step of structural health monitoring by identifying structural system in the presence of unknown input. In the structural system identification, identification of structural parameters such as stiffness and damping are considered. In this study, the Kalman filter (KF) design for structural systems with unknown excitation is expressed. External excitations, such as earthquakes, wind or any other forces are not measured or not available. The purpose of this filter is its strengths to estimate the state variables of the system in the presence of unknown input. Also least squares estimation (LSE) method with unknown input is studied. Estimates of parameters have been adopted. Finally, using two examples advantages and drawbacks of both methods are studied.

Keywords: Kalman filter (KF), least square estimation (LSE), structural health monitoring (SHM), structural system identification

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Authors: Néstor Álvarez-Díaz, Pino Caballero-Gil, Héctor Reboso-Morales, Francisco Martín-Fernández

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The recent tendency of "Internet of Things" (IoT) has developed in the last years, causing the emergence of innovative communication methods among multiple devices. The appearance of Bluetooth Low Energy (BLE) has allowed a push to IoT in relation to smartphones. In this moment, a set of new applications related to several topics like entertainment and advertisement has begun to be developed but not much has been done till now to take advantage of the potential that these technologies can offer on many business areas and in everyday tasks. In the present work, the application of BLE technology and smartphones is proposed on some business areas related to the optimization of resource allocation in huge facilities like airports. An indoor location system has been developed through triangulation methods with the use of BLE beacons. The described system can be used to locate all employees inside the building in such a way that any task can be automatically assigned to a group of employees. It should be noted that this system cannot only be used to link needs with employees according to distances, but it also takes into account other factors like occupation level or category. In addition, it has been endowed with a security system to manage business and personnel sensitive data. The efficiency of communications is another essential characteristic that has been taken into account in this work.

Keywords: bluetooth low energy, indoor location, resource assignment, smartphones

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Authors: Tadashi Watanabe, Jinya Katsuyama, Akihiro Mano

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The estimation of leak flow rates through narrow cracks in structures is of importance for nuclear reactor safety, since the leak flow could be detected before occurrence of loss-of-coolant accidents. The two-phase critical leak flow rates are calculated using the system analysis code, and two representative non-homogeneous critical flow models, Henry-Fauske model and Ransom-Trapp model, are compared. The pressure decrease and vapor generation in the crack, and the leak flow rates are found to be larger for the Henry-Fauske model. It is shown that the leak flow rates are not affected by the structural temperature, but affected largely by the roughness of crack surface.

Keywords: crack, critical flow, leak, roughness

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Authors: Muhammad Ashraf

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It is experimentally conceded reality that education not just promotes social and intellectual abilities yet, in addition, the incomes of people. The present study is directed to investigate the connection between education level and student income. Data of different education levels is acquired from 300 students through field review from four public sector Universities; two from upper Punjab (University of Gujarat and Government college university-Lahore) and two from lower Punjab (Islamia University-Bahawalpur and The University of Sahiwal). Two-phase estimation is based on the Mincerian human capital model. The first stage presents statistical/descriptive investigation, which shows positive linkage among higher education and income of the students. Econometric estimation is estimated in the second stage by applying Ordinary least Square Method (OLS). Econometric examination reaffirms the importance of higher education as the impact of higher education on students’ incomes accelerates as we move from lower-level education to higher-level education. Educational levels, experience, and working hours are sure and noteworthy with student’s income. Econometric estimation additionally investigated that M. Phil and Ph.D. students have a higher income than bachelor students. Concerning the students, the income profile study commended that the Government ought to give part-time jobs or internships to students as indicated to labor market demand.

Keywords: education, student’s income, experience, universities

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Authors: Md. Shakhawat Hossain, Jimma Hossain, Md. Naushad Ali

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Acute pancreatitis is a dangerous medical emergency in the practice of gastroenterology. Management of acute pancreatitis needs multidisciplinary approach with support starts from emergency to ICU. So, there is a chance of mismanagement in every steps, especially in low resource settings. Other factors such as patient’s financial condition, education, social custom, transport facility, referral system from periphery may also challenge the current guidelines for management. The present study is intended to determine the clinico-pathological profile, severity assessment and challenges of management of acute pancreatitis in a government laid tertiary care hospital to image the real scenario of management in a low resource place. A total 100 patients of acute pancreatitis were studied in this prospective study, held in the Department of Gastroenterology, Rangpur medical college hospital, Bangladesh from July 2017 to July 2018 within one year. Regarding severity, 85 % of the patients were mild, whereas 13 were moderately severe, and 2 had severe acute pancreatitis according to the revised Atlanta criteria. The most common etiologies of acute pancreatitis in our study were gall stone (15%) and biliary sludge (15%), whereas 54% were idiopathic. The most common challenges we faced were delay in hospital admission (59%) and delay in hospital diagnosis (20%). Others are non-adherence of patient party, and lack of investigation facility, physician’s poor knowledge about current guidelines. We were able to give early aggressive fluid to only 18% of patients as per current guideline. Conclusion: Management of acute pancreatitis as per guideline is challenging when optimum facility is lacking. So, modified guidelines for assessment and management of acute pancreatitis should be prepared for low resource setting.

Keywords: acute pancreatitis, challenges of management, severity, prognosis

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Authors: Seyed Esmail Seyedi Bariran, Khairul Salleh Mohamed Sahari

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In robotics literature, the simultaneous localization and mapping (SLAM) is commonly associated with a priori-posteriori problem. The autonomous vehicle needs a neutral map to spontaneously track its local position, i.e., “localization” while at the same time a precise path estimation of the environment state is required for effective route planning and obstacle avoidance. On the other hand, the environmental noise factors can significantly intensify the inherent uncertainties in using odometry information and measurements obtained from the robot’s exteroceptive sensor which in return directly affect the overall performance of the corresponding SLAM. Therefore, the current work is primarily dedicated to provide a diagnostic analysis of six SLAM algorithms including FastSLAM, L-SLAM, GraphSLAM, Grid SLAM and DP-SLAM. A SLAM simulated environment consisting of two sets of landmark locations and robot waypoints was set based on modified EKF and UKF in MATLAB using two separate maps for indoor and outdoor route planning subject to natural and artificial obstacles. The simulation results are expected to provide an unbiased platform to compare the estimation performances of the five SLAM models as well as on the reliability of each SLAM model for indoor and outdoor applications.

Keywords: route planning, obstacle, estimation performance, FastSLAM, L-SLAM, GraphSLAM, Grid SLAM, DP-SLAM

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Authors: Md Habibul Ansary, Chandan Garai, Ranjan Dasgupta

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Utilization of resources is always a great challenge for any allocation problem, particularly when resource availability is dynamic in nature. In this work VM allocation mechanism has been augmented by providing resources in a combined manner. This approach has some inherent advantages in terms of reduction of wait state for the pending jobs of some users and better utilization of unused resources from the service providers’ point of view. Moreover the algorithm takes care of released resources from the finished jobs as soon as those become available. The proposed algorithm has been explained by suitable example to make the work complete.

Keywords: Bid ratio, cloud service, virtualization, VM allocation problem

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Authors: Md. Abud Darda

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Different options for natural gas production in wide geographic areas may be described through diffusion of innovation models. This type of modeling approach provides an indirect estimate of an ultimately recoverable resource, URR, capture the quantitative effects of observed strategic interventions, and allow ex-ante assessments of future scenarios over time. In order to ensure a sustainable energy policy, it is important to forecast the availability of this natural resource. Considering a finite life cycle, in this paper we try to investigate the natural gas production of Myanmar and Algeria, two important natural gas provider in the world energy market. A number of homogeneous and heterogeneous diffusion models, with convenient extensions, have been used. Models validation has also been performed in terms of prediction capability.

Keywords: diffusion models, energy forecast, natural gas, nonlinear production

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Authors: Müberra Yüksel, Ömer Faruk Görçün

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The purpose of the present study is to investigate the role of strategic human resource management (SHRM) in constructing "employer branding" in logistics. Prior research does not focus on internal stakeholders, that is, employees. Despite the fact that logistic sector has become customer-oriented, the focus is solely on service quality as the unique aspect of logistic companies for competitive advantage. With an increasing interest lately in internal marketing of the employer brand, the emphasis is on the value that human capital brings to the firm which cannot be imitated. `Employer branding` has been the application of branding and relationship marketing principles for competitive advantage in SHRM. Employer branding is an organizing framework for human resource managers since it represents an organization’s efforts to promote, both within and outside, a coherent view of what makes the firm different and desirable as an employer, i.e., the distinct “employer brand personality” and "employee value propositions" (EVP) offered. The presumption of employer branding enhanced by internal marketing is to make customer-conscious employees to handle services better by being aligned with business mission and goals. Starting from internal customers and analyzing the gaps of EVP by using analytical hierarchy process methodology (AHP) and inquiring whether these brand values are communicated and conceived well may be the initial steps in our proposal for employer branding in logistics sector. This empirical study aims to fill this research gap within the context of an emergent market- Turkey, which is located at a hub of transportation and logistics.

Keywords: Strategic Human Resource Management (SHRM), employer branding, Employee Value Propositions (EVP), Analytical Hierarchy Process (AHP), logistics

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Authors: Charawee Butbumrung

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The purpose of this study is to evaluate the monetary worthiness of investment and the usefulness of risk estimation as a tool employed by a production section of an electronic factory. This study employed the case study of accidents occurring in production areas. Data is collected from interviews with six production of safety coordinators and collect the information from the relevant section. The study will present the ratio of benefits compared with the operation costs for investment. The result showed that it is worthwhile for investment with the safety measures. In addition, the organizations must be able to analyze the causes of accidents about the benefits of investing in protective working process. They also need to quickly provide the manual for the staff to learn how to protect themselves from accidents and how to use all of the safety equipment.

Keywords: cost and benefit, enterprises in Thailand, investment in safety and health, risk estimation

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Authors: M. Khalid, G. N. Singh

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In this paper, we have considered the problems of estimation for the population mean on current (second) occasion in two-occasion successive sampling under random non-response situations. Some modified exponential type estimators have been proposed and their properties are studied under the assumptions that the number of sampling unit follows a discrete distribution due to random non-response situations. The performances of the proposed estimators are compared with linear combinations of two estimators, (a) sample mean estimator for fresh sample and (b) ratio estimator for matched sample under the complete response situations. Results are demonstrated through empirical studies which present the effectiveness of the proposed estimators. Suitable recommendations have been made to the survey practitioners.

Keywords: modified exponential estimator, successive sampling, random non-response, auxiliary variable, bias, mean square error

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Authors: Youngsun Moon, Yeong-Ju Go, Jong-Soo Choi

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Most drones that currently have surveillance/reconnaissance missions are basically equipped with optical equipment, but we also need to use a microphone array to estimate the location of the acoustic source. This can provide additional information in the absence of optical equipment. The purpose of this study is to estimate Direction of Arrival (DOA) based on Time Difference of Arrival (TDOA) estimation of the acoustic source in the drone. The problem is that it is impossible to measure the clear target acoustic source because of the drone noise. To overcome this problem is to separate the drone noise and the target acoustic source using Blind Source Separation(BSS) based on Independent Component Analysis(ICA). ICA can be performed assuming that the drone noise and target acoustic source are independent and each signal has non-gaussianity. For maximized non-gaussianity each signal, we use Negentropy and Kurtosis based on probability theory. As a result, we can improve TDOA estimation and DOA estimation of the target source in the noisy environment. We simulated the performance of the DOA algorithm applying BSS algorithm, and demonstrated the simulation through experiment at the anechoic wind tunnel.

Keywords: aeroacoustics, acoustic source detection, time difference of arrival, direction of arrival, blind source separation, independent component analysis, drone

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Authors: Hamza Benzerrouk, Alexander Nebylov

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In classical GNSS/INS integration designs, the loosely coupled approach uses the GNSS derived position and the velocity as the measurements vector. This design is suboptimal from the standpoint of preventing GNSSoutliers/outages. The tightly coupled GPS/INS navigation filter mixes the GNSS pseudo range and inertial measurements and obtains the vehicle navigation state as the final navigation solution. The ultra‐tightly coupled GNSS/INS design combines the I (inphase) and Q(quadrature) accumulator outputs in the GNSS receiver signal tracking loops and the INS navigation filter function intoa single Kalman filter variant (EKF, UKF, SPKF, CKF and HCKF). As mentioned, EKF and UKF are the most used nonlinear filters in the literature and are well adapted to inertial navigation state estimation when integrated with GNSS signal outputs. In this paper, it is proposed to move a step forward with more accurate filters and modern approaches called Cubature and High Degree cubature Kalman Filtering methods, on the basis of previous results solving the state estimation based on INS/GNSS integration, Cubature Kalman Filter (CKF) and High Degree Cubature Kalman Filter with (HCKF) are the references for the recent developed generalized Cubature rule based Kalman Filter (GCKF). High degree cubature rules are the kernel of the new solution for more accurate estimation with less computational complexity compared with the Gauss-Hermite Quadrature (GHQKF). Gauss-Hermite Kalman Filter GHKF which is not selected in this work because of its limited real-time implementation in high-dimensional state-spaces. In ultra tightly or a deeply coupled GNSS/INS system is dynamics EKF is used with transition matrix factorization together with GNSS block processing which is well described in the paper and assumes available the intermediary frequency IF by using a correlator samples with a rate of 500 Hz in the presented approach. GNSS (GPS+GLONASS) measurements are assumed available and modern SPKF with Cubature Kalman Filter (CKF) are compared with new versions of CKF called high order CKF based on Spherical-radial cubature rules developed at the fifth order in this work. Estimation accuracy of the high degree CKF is supposed to be comparative to GHKF, results of state estimation are then observed and discussed for different initialization parameters. Results show more accurate navigation state estimation and more robust GNSS receiver when Ultra Tightly Coupled approach applied based on High Degree Cubature Kalman Filter.

Keywords: GNSS, INS, Kalman filtering, ultra tight integration

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Authors: Safa Lazzem, Faouzi Jilani

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The aim of this research is to investigate the impact of diversification strategy on the nature of the relationship between leverage and accrual-based earnings management through panel-estimation techniques based on a sample of 162 nonfinancial French firms indexed in CAC All-Tradable during the period from 2006 to 2012. The empirical results show that leverage increases encourage managers to manipulate earnings management. Our findings prove that the diversification strategy provides the needed context for this accounting practice to be possible in highly diversified firms. In addition, the results indicate that diversification moderates the relationship between leverage and accrual-based earnings management by changing the nature and the sign of this relationship.

Keywords: diversification, earnings management, leverage, panel-estimation techniques

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Authors: Parichehr Sharifi, Konrad Reschke, Hans-Liudger Dienel

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Psychological intervention generally targets changes in attitudes and behavior. Working with DUIs is part of traffic psychologists’ work. The primary goal of this field is to reduce the probability of re-conspicuous of the delinquent driver. One of these measurements in Germany is IFT courses for DUI s. The IFT course was designed by the Institute for Therapy Research. Participants are drivers who have fallen several times or once with a blood alcohol concentration of 1.6 per mill and who have completed a medical-psychological assessment (MPU) with the result of the course recommendation. The course covers four sessions of 3.5 hours each (1 hour / 60 m) and in a period of 3 to 4 weeks in the group discussion. This work analyzes interventions for the rehabilitation of DUI (Drunk Drivers offenders) offenders in groups under the aspect of activating psychological resources. From the aspect of sustainability, they should also have long-term consequences for the maintenance of unproblematic driving behavior in terms of the activation of resources. It is also addressing a selected consistency-theory-based intervention effect, activating psychological resources. So far, this has only been considered in the psychotherapeutic field but never in the field of traffic psychology. The methodology of this survey is one qualitative and three quantitative. In four sub-studies, it will be examined which measurements can determine the resources and how traffic psychological interventions can strengthen resources. The results of the studies have the following implications for traffic psychology research and practice: (1) In the field of traffic psychology intervention for the restoration of driving fitness, it can be stated that aspects of resource activation in this work have been investigated for the first time by qualitative and quantitative methods. (2) The resource activation could be confirmed based on the determined results as an effective factor of traffic psychological intervention. (3) Two sub-studies show a range of resources and resource activation options that must be given greater emphasis in traffic psychology interventions: - Social resource activation - improvement of the life skills of participants - Reactivation of existing social support options - Re-experiencing self-esteem, self-assurance, and acceptance of traffic-related behaviors. (4) In revising the IFT-§70 course, as well as other courses on recreating aptitude for DUI, new traffic-specific resource-enabling interventions against alcohol abuse should be developed to further enhance the courses through motivational, cognitive, and behavioral effects of resource activation, Resource-activating interventions can not only be integrated into behavioral group interventions but can also be applied in psychodynamic, psychodynamic (individual psychological) and other contexts of individual traffic psychology. The results are indicative but clearly show that personal resources can be strengthened through traffic psychology interventions. In the research, practice, training, and further education of traffic psychology, the aspect of primary resource activation (Grawe, 1999), therefore, always deserves the greatest attention for the rehabilitation of DUIs and Traffic safety.

Keywords: traffic safety, psychological resources, activating of resources, intervention programs for alcohol offenders, empowerment

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Authors: Kvnkc Sharma

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Globalization, coupled with increase in competition is compelling organizations to adopt innovative strategies and identify core competencies in order to distinguish themselves from the competition. The capability of an organization is no longer determined by their products or services alone. The intellectual assets and quality of the human resource are fast emerging as key differentiators. Corporations are now positioning themselves as ‘brands’ not solely to market their products and services, but also to lure and to retain the best talent in the business. This paper identifies leadership as the ‘key element’ in developing an organization’s brand, which has a significant influence on the employee’s eventual perception of this external brand as portrayed by the organization. External branding incorporates innovation, consumer concern, trust, quality and sustainability. The paper contends that employees are indeed an organization’s ‘brand ambassadors. Internal branding involves taking care of these ambassadors of corporate brand i.e. human resource. If employees of an organization are not exposed to the organization’s branding (an ongoing process that functionally aligns, motivates and empower employees at all levels to consistently provide a satisfying customer experience), the external brand could be jeopardized. Internal branding, on the other hand, refers to employee’s perception of the organization’s brand. The current business environment can at best, be termed as volatile. Employees with the right technical and behavioral skills remain a scarce resource and the employers need to be ready to capture the attention, interest and commitment of the best and brightest candidates. This paper attempts to review and understand the relationship between employer branding and employee retention. The paper also seeks to identify potential impact of employer branding across all the factors affecting employees.

Keywords: external branding, human resource, internal branding, leadership

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Authors: Mesias Alfeus, Kirsty Fitzhenry, Alessia Lederer

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The present paper provides empirical studies to estimate defaultable bonds in the South African financial market. The main goal is to estimate the unobservable factors affecting bond yields for South African major banks. The maximum likelihood approach is adopted for the estimation methodology. Extended Kalman filtering techniques are employed in order to tackle the situation that the factors cannot be observed directly. Multi-dimensional Cox-Ingersoll-Ross (CIR)-type factor models are considered. Results show that default risk increased sharply in the South African financial market during COVID-19 and the CIR model with jumps exhibits a better performance.

Keywords: default intensity, unobservable state variables, CIR, α-CIR, extended kalman filtering

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Authors: Ma. Rosario Concepcion O. Ang, Luis Caezar Ian K. Panganiban, Charmyne B. Mamador, Oliver Dan G. De Luna, Michael D. Bausas, Joselito P. Cruz

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PhilSHORE is a multi-site, multi-device and multi-criteria decision support tool designed to support the development of tidal current energy in the Philippines. Its platform is based on Geographic Information Systems (GIS) which allows for the collection, storage, processing, analyses and display of geospatial data. Combining GIS tools with open source web development applications, PhilSHORE becomes a webGIS-based marine spatial planning tool. To date, PhilSHORE displays output maps and graphs of power and energy density, site suitability and site-device analysis. It enables stakeholders and the public easy access to the results of tidal current energy resource assessments and site suitability analyses. Results of the initial development shows PhilSHORE is a promising decision support tool for ORE project developments.

Keywords: gis, site suitability analysis, tidal current energy resource assessment, webgis

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Authors: Ibrahim Elnour Abdelrahman Eltayeb

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Computational modelling is a method used to investigate joint forces during a movement. It can get high accuracy in the joint forces via subject-specific models. However, the construction of subject-specific models remains time-consuming and expensive. The purpose of this paper was to identify what alterations we can make to generic computational models to get a better estimation of the joint forces. It appraised the impact of these alterations on the accuracy of the estimated joint forces. It found different strategies of alterations: joint model, muscle model, and an optimisation problem. All these alterations affected joint contact force accuracy, so showing the potential for improving the model predictions without involving costly and time-consuming medical images.

Keywords: joint force, joint model, optimisation problem, validation

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Authors: A. Majeed, P. Ali

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Before designing an electrical system, the estimation of load is necessary for unit sizing and demand-generation balancing. The system could be a stand-alone system for a village or grid connected or integrated renewable energy to grid connection, especially as there are non–electrified villages in developing countries. In the classical model, the energy demand was found by estimating the household appliances multiplied with the amount of their rating and the duration of their operation, but in this paper, information exists for electrified villages could be used to predict the demand, as villages almost have the same life style. This paper describes a method used to predict the average energy consumed in each two months for every consumer living in a village by Artificial Neural Network (ANN). The input data are collected using a regional survey for samples of consumers representing typical types of different living, household appliances and energy consumption by a list of information, and the output data are collected from administration office of Piramagrun for each corresponding consumer. The result of this study shows that the average demand for different consumers from four villages in different months throughout the year is approximately 12 kWh/day, this model estimates the average demand/day for every consumer with a mean absolute percent error of 11.8%, and MathWorks software package MATLAB version 7.6.0 that contains and facilitate Neural Network Toolbox was used.

Keywords: artificial neural network, load estimation, regional survey, rural electrification

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Authors: Brenda Margaret Behan

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Kenya is a water-stressed country with highly varied socio-ecological environments in its devolved county system, and is currently implementing a polycentric water governance system; this paper examines the importance of social capital in community-based natural resource management and its role in supporting good water governance systems in the Kenya context. Through a robust literature review of theory and case studies, specific aspects of social capital are examined to determine their importance in the implementation of local community-based water management arrangements which support and complement the more formal institutions outlined in the 2002 and 2016 Water Acts of Kenya. Water is an increasingly important and scarce resource not only for Kenya, but for many communities across the globe, and lessons learned in the Kenya context can be useful for other countries and communities faced with similar challenges. Changing climates, increasing populations, and increased per capita consumption of water is contributing to a situation in which the management of water resources will be vital to community resilience. Community-based natural resource management is widely recognized as a building block and component of wider water resource management systems, and when properly conducted can provide a way to enable sustainable use of resources and empower communities. Greater attention to the social and cultural norms and traditional institutions associated with a community’s social capital can lead to better results for Kenya’s polycentric governance of water. The key findings and recommendations from this research show that in Kenya, traditional institutions need to be understood and integrated into governance systems; social values and cultural norms have a significant impact on the implementation of community-based water management efforts; and social capital is a dynamic concept which influences and is influenced by policies and practices. The community-based water management approach will continue to be a key cornerstone for Kenya’s polycentric water governance structure, especially in the more remote arid and semi-arid lands; thus, the successful integration of social capital aspects into planning and implementation will contribute to a strengthened, sustainable, and more equitable national water governance system. Specific observations and recommendations from this study will help practitioners and policymakers to better craft community-based interventions.

Keywords: community-based natural resource management, social capital, traditional institutions, water governance

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Authors: Muneera Mohammed Al-Dossary, Fatimah Mohammed Al-Dossary, Mashael Al-Shahrani, Amal Al-Tammemi

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Johns Hopkins Aramco Healthcare (JAHA), a joint venture between Saudi Aramco and Johns Hopkins Medicine, delivers comprehensive healthcare services to a diverse patient population. Despite achieving high patient satisfaction rates and surpassing several operational targets, JAHA faces challenges such as appointment delays and resource inefficiencies. These issues highlight the need for an advanced, integrated approach to operational management. This paper proposes a Business Intelligence (BI) framework to address these challenges, leveraging tools such as Epic electronic health records and Tableau dashboards. The framework focuses on data integration, real-time monitoring, and predictive analytics to streamline operations and enhance decision-making. Key outcomes include reduced wait times (e.g., a 23% reduction in specialty clinic wait times) and improved operating room efficiency (from 95.83% to 98% completion rates). These advancements align with JAHA’s strategic objectives of optimizing resource utilization and delivering superior patient care. The findings underscore the transformative potential of BI in healthcare, enabling a shift from reactive to proactive operations management. The success of this implementation lays the foundation for future innovations, including machine learning models for more precise demand forecasting and resource allocation.

Keywords: business intelligence, operational efficiency, healthcare management, predictive analytics, patient care improvement, data integration, real-time monitoring, resource optimization, Johns Hopkins Aramco Healthcare, electronic health records, Tableau dashboards, predictive modeling, efficiency metrics, resource utilization, patient satisfaction

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Authors: Amrane Meriem, Oukid Salyha

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The presence of defects or bugs in software can lead to costly setbacks, operational inefficiencies, and compromised user experiences. The integration of Machine Learning(ML) techniques has emerged to predict and preemptively address software defects. ML represents a proactive strategy aimed at identifying potential anomalies, errors, or vulnerabilities within code before they manifest as operational issues. By analyzing historical data, such as code changes, feature im- plementations, and defect occurrences. This en- ables development teams to anticipate and mitigate these issues, thus enhancing software quality, reducing maintenance costs, and ensuring smoother user interactions. In this work, we used a recommendation system to improve the performance of ML models in terms of predicting the code severity and effort estimation.

Keywords: software engineering, machine learning, bugs detection, effort estimation

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Authors: Agnieszka Leszczynska

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Flexibility and agility constitute the most dominant features of modern human resource management systems. The former pertains to procedures, practices and competences of human resources, and the latter to the procedures and practices’ effectiveness in dealing with changing conditions in the surrounding environment. The purpose of the paper is to present the relations between the flexibility and agility of human resources and achieving sustainable competitiveness. Based upon hitherto research, we develop a conceptual model that links the constructs together. The conducted study is of theoretical and conceptual nature. Critical literature analysis and the synthesis method were applied. A premise was made that the three dimensions of HR (Human Resources) flexibility (employee skill flexibility, employee behaviour flexibility, and HR practice flexibility) and HR agility affect competitiveness, by increasing the flexibility, creativity of human resources, and improving quality performance, and exert an impact upon the quality of life of employees and social relations. In particular, the agility and flexibility of human resources contribute to the growth of adaptability and strategic orientation, which directly affects the organization's competitiveness. The research results will help to better understand the impact of flexibility and agility related to the HRM (Human Resources Management) system upon the implementation of the concept of sustainable development in the organization.

Keywords: agility, human resource, sustainable competitiveness, sustainable development

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Authors: İbrahi̇m Kara, Seher Arslankaya

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Frequently preferred in the field of engineering in particular, data mining has now begun to be used in the field of health as well since the data in the health sector have reached great dimensions. With data mining, it is aimed to reveal models from the great amounts of raw data in agreement with the purpose and to search for the rules and relationships which will enable one to make predictions about the future from the large amount of data set. It helps the decision-maker to find the relationships among the data which form at the stage of decision-making. In this study, it is aimed to determine the risk of heart attack at the first stage, to control it, and to make its resource planning with the method of data mining. Through the early and correct diagnosis of heart attacks, it is aimed to reveal the factors which affect the diseases, to protect health and choose the right treatment methods, to reduce the costs in health expenditures, and to shorten the durations of patients’ stay at hospitals. In this way, the diagnosis and treatment costs of a heart attack will be scrutinized, which will be useful to determine the risk of the disease at the first stage, to control it, and to make its resource planning.

Keywords: data mining, decision support systems, heart attack, health sector

Procedia PDF Downloads 358

Authors: Bouthiba Amina

Abstract:

The estimation of the statistics bound to the precipitation represents a vast domain, which puts numerous challenges to meteorologists and hydrologists. Sometimes, it is necessary, to approach in value the extreme events for sites where there is little, or no datum, as well as their periods of return. The search for a model of the frequency of the heights of daily rains dresses a big importance in operational hydrology: It establishes a basis for predicting the frequency and intensity of floods by estimating the amount of precipitation in past years. The most known and the most common approach is the statistical approach, It consists in looking for a law of probability that fits best the values observed by the random variable " daily maximal rain " after a comparison of various laws of probability and methods of estimation by means of tests of adequacy. Therefore, a frequent analysis of the annual series of daily maximal rains was realized on the data of 54 pluviometric stations of the pond of high and average. This choice was concerned with five laws usually applied to the study and the analysis of frequent maximal daily rains. The chosen period is from 1970 to 2013. It was of use to the forecast of quantiles. The used laws are the law generalized by extremes to three components, those of the extreme values to two components (Gumbel and log-normal) in two parameters, the law Pearson typifies III and Log-Pearson III in three parameters. In Algeria, Gumbel's law has been used for a long time to estimate the quantiles of maximum flows. However, and we will check and choose the most reliable law.

Keywords: return period, extreme flow, statistics laws, Gumbel, estimation

Procedia PDF Downloads 79

Authors: Kai Jin, Hua Li, Qing Song

Abstract:

Homeland security and border safety is an issue for any country. This paper takes the border security of US as an example to discuss the usage and efficiency of simulation tools in the homeland security application. In this study, available resources and different illegal infiltration parameters are defined, including their individual behavior and objective, in order to develop a model that describes border patrol system. A simulation model is created in Arena. This simulation model is used to study the dynamic activities in the border security. Possible factors that may affect the effectiveness of the border patrol system are proposed. Individual and factorial analysis of these factors is conducted and some suggestions are made.

Keywords: resource optimization, simulation, modeling, border security

Procedia PDF Downloads 519