Search results for: vector error correction model (VECM)

Authors: Sang Hun Park, Chul Gyu Song

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Artery and vein occlusion changes observed in patients and experimental animals are unexplainable symptoms. As the fat accumulated in cardiovascular ruptures, it causes vascular blocking. Likewise, early detection of cardiovascular disease can be useful for treatment. In this study, we used the mouse femoral occlusion model to observe the arterial and venous occlusion changes without darkroom. We observed the femoral arterial flow pattern changes by proposed fluorescent imaging system using an animal model of thrombosis. We adjusted the near-infrared light source current in order to control the intensity of the fluorescent substance light. We got the clear fluorescent images and femoral artery flow pattern were measured by a 5-minute interval. The result showed that the fluorescent substance flowing in the femoral arteries were accumulated in thrombus as time passed, and the fluorescence of other vessels gradually decreased.

Keywords: thrombus, fluorescence, femoral, arteries

Procedia PDF Downloads 344

Authors: A. Fettahoglu

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Theory of viscoelasticity is used by many researchers to represent the behavior of many materials such as pavements on roads or bridges. Several researches used analytical methods and rheology to predict the material behaviors of simple models. Today, more complex engineering structures are analyzed using Finite Element Method, in which material behavior is embedded by means of three dimensional viscoelastic material laws. As a result, structures of unordinary geometry and domain can be analyzed by means of Finite Element Method and three dimensional viscoelastic equations. In the scope of this study, rheological models embedded in ANSYS, namely, generalized Maxwell model and Prony series, which are two methods used by ANSYS to represent viscoelastic material behavior, are presented explicitly. Afterwards, a guide is illustrated to ease using of viscoelasticity tool in ANSYS.

Keywords: ANSYS, generalized Maxwell model, finite element method, Prony series, viscoelasticity, viscoelastic material curve fitting

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Authors: Avdhesh K. Sharma

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Key, in the development of energy-efficient micro-scale heat exchanger devices, is to select large heat transfer surface to volume ratio without much expanse on re-circulated pumps. The increased interest in short heat exchanger (SHE) is due to accessibility of advanced technologies for manufacturing of micro-tubes in range of 1 micron m - 1 mm. Such SHE using micro-tubes are highly effective for high flux heat transfer technologies. Nanofluids, are used to enhance the thermal conductivity of re-circulated coolant and thus enhances heat transfer rate further. Higher viscosity associated with nanofluid expands more pumping power. Thus, there is a trade-off between heat transfer rate and pressure drop with geometry of micro-tubes. Herein, a novel design of short counter flow heat exchanger (SCFHE) using non-circular micro-tubes flooded with CuO-water nanofluid is conceptualized by varying the ratio of surface area to cross-sectional area of micro-tubes. A framework for comparative analysis of SCFHE using micro-tubes non-circular shape flooded by CuO-water nanofluid is presented. In SCFHE concept, micro-tubes having various geometrical shapes (viz., triangular, rectangular and trapezoidal) has been arranged row-wise to facilitate two aspects: (1) allowing easy flow distribution for cold and hot stream, and (2) maximizing the thermal interactions with neighboring channels. Adequate distribution of rows for cold and hot flow streams enables above two aspects. For comparative analysis, a specific volume or cross-section area is assigned to each elemental cell (which includes flow area and area corresponds to half wall thickness). A specific volume or cross-section area is assumed to be constant for each elemental cell (which includes flow area and half wall thickness area) and variation in surface area is allowed by selecting different geometry of micro-tubes in SCFHE. Effective thermal conductivity model for CuO-water nanofluid has been adopted, while the viscosity values for water based nanofluids are obtained empirically. Correlations for Nusselt number (Nu) and Poiseuille number (Po) for micro-tubes have been derived or adopted. Entrance effect is accounted for. Thermal and hydrodynamic performances of SCFHE are defined in terms of effectiveness and pressure drop or pumping power, respectively. For defining the overall performance index of SCFHE, two links are employed. First one relates heat transfer between the fluid streams q and pumping power PP as (=qj/PPj); while another link relates effectiveness eff and pressure drop dP as (=effj/dPj). For analysis, the inlet temperatures of hot and cold streams are varied in usual range of 20dC-65dC. Fully turbulent regime is seldom encountered in micro-tubes and transition of flow regime occurs much early (i.e., ~Re=1000). Thus, Re is fixed at 900, however, the uncertainty in Re due to addition of nanoparticles in base fluid is quantified by averaging of Re. Moreover, for minimizing error, volumetric concentration is limited to range 0% to ≤4% only. Such framework may be helpful in utilizing maximum peripheral surface area of SCFHE without any serious severity on pumping power and towards developing advanced short heat exchangers.

Keywords: CuO-water nanofluid, non-circular micro-tubes, performance index, short counter flow heat exchanger

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Authors: Linyi Fan, C.J. Schumaker

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Background: Biomedical efforts to treat Alzheimer’s disease (AD) have typically produced mixed to poor results, while more lifestyle-focused treatments such as exercise may fare better than existing biomedical treatments. A few promising studies have indicated that activities of daily life (ADL) may be a useful way of predicting AD. However, the existing cross-sectional studies fail to show how functional-related issues such as ADL in early years predict AD and how social factors influence health either in addition to or in interaction with individual risk factors. This study would helpbetterscreening and early treatments for the elderly population and healthcare practice. The findings have significance academically and practically in terms of creating positive social change. Methodology: The purpose of this quantitative historical, correlational study was to examine the relationship between early years’ ADL and the development of AD in later years. The studyincluded 4,526participantsderived fromRAND HRS dataset. The Health and Retirement Study (HRS) is a longitudinal household survey data set that is available forresearchof retirement and health among the elderly in the United States. The sample was selected by the completion of survey questionnaire about AD and dementia. The variablethat indicates whether the participant has been diagnosed with AD was the dependent variable. The ADL indices and changes in ADL were the independent variables. A four-step multilevel regression model approach was utilized to address the research questions. Results: Amongst 4,526 patients who completed the AD and dementia questionnaire, 144 (3.1%) were diagnosed with AD. Of the 4,526 participants, 3,465 (76.6%) have high school and upper education degrees,4,074 (90.0%) were above poverty threshold. The model evaluatedthe effect of ADL and change in ADL on onset of AD in late years while allowing the intercept of the model to vary by level of education. The results suggested that the only significant predictor of the onset of AD was changes in early years’ ADL (b = 20.253, z = 2.761, p < .05). However, the result of the sensitivity analysis (b = 7.562, z = 1.900, p =.058), which included more control variables and increased the observation period of ADL, are not supported this finding. The model also estimated whether the variances of random effect vary by Level-2 variables. The results suggested that the variances associated with random slopes were approximately zero, suggesting that the relationship between early years’ ADL were not influenced bysociodemographic factors. Conclusion: The finding indicated that an increase in changes in ADL leads to an increase in the probability of onset AD in the future. However, this finding is not support in a broad observation period model. The study also failed to reject the hypothesis that the sociodemographic factors explained significant amounts of variance in random effect. Recommendations were then made for future research and practice based on these limitations and the significance of the findings.

Keywords: alzheimer’s disease, epidemiology, moderation, multilevel modeling

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Authors: Tanmay Bisen, Aastha Shayla, Susham Biswas

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Oil spills from tankers can cause significant harm to the environment and local communities, as well as have economic consequences. Early predictions of oil spills can help to minimize these impacts. Our proposed system uses machine learning and neural networks to predict potential oil spills by monitoring data from ship Automatic Identification Systems (AIS). The model analyzes ship movements, speeds, and changes in direction to identify patterns that deviate from the norm and could indicate a potential spill. Our approach not only identifies anomalies but also predicts spills before they occur, providing early detection and mitigation measures. This can prevent or minimize damage to the reputation of the company responsible and the country where the spill takes place. The model's performance on the MV Wakashio oil spill provides insight into its ability to detect and respond to real-world oil spills, highlighting areas for improvement and further research.

Keywords: Anomaly Detection, Oil Spill Prediction, Machine Learning, Image Processing, Graph Neural Network (GNN)

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Authors: M. Yoneda

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It is known that stationary human occupants act as dynamic mass-spring-damper systems and can change the modal properties of civil engineering structures. This paper describes the full scale measurement to explain the tuned mass damper effects of stationary people on structural damping of footbridge with center span length of 33 m. A human body can be represented by a lumped system consisting of masses, springs, and dashpots. Complex eigenvalue calculation is also conducted by using ISO5982:1981 human model (two degree of freedom system). Based on experimental and analytical results for the footbridge with the stationary people in the standing position, it is demonstrated that stationary people behave as a tuned mass damper and that ISO5982:1981 human model can explain the structural damping characteristics measured in the field.

Keywords: dynamic interaction, footbridge, stationary people, structural damping

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Authors: Arnault Morisson

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Innovation districts are being implemented as urban regeneration strategies in cities as diverse as Barcelona (Spain), Boston (Massachusetts), Chattanooga (Tennessee), Detroit (Michigan), Medellin (Colombia), and Montréal (Canada). Little, however, is known about the concept. This paper aims to provide a framework to define innovation districts. The research methodology is based on a qualitative approach using 22@ Barcelona as a case study. 22@ Barcelona was the first innovation district ever created and has been a model for the innovation districts of Medellin (Colombia) and Boston (Massachusetts) among others. Innovation districts based on the 22@ Barcelona’s model can be defined as top-down urban innovation ecosystems designed around four multilayered and multidimensional models of innovation: urban planning, productive, collaborative, and creative, all coordinated under strong leadership, with the ultimate objectives to accelerate the innovation process and competitiveness of a locality. Innovation districts aim to respond to a new economic paradigm in which economic production flows back to cities.

Keywords: innovation ecosystem, governance, technology park, urban planning, urban policy, urban regeneration

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Authors: So Hyun Ahn, Geu Rim Seo, Byungsoo Shin, Kwang-Won Yu, Hyung Joo Suh, Sung Hee Han

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We investigated the effects of GOS, lactulose and DuOligo in loperamide-induced constipation rat model. Dual-Oligo saccharide (DuOligo) was composed with galacto-oligosaccharide (GOS) and lactulose. GOS is an important dietary prebiotics that affects intestinal microbiota and barrier functions to have beneficial effect and lactulose is used as a laxative to treat constipation. To study the DuOligo, after adaptation period of four weeks of Spraque-Dawley rats, loperamide (5 mg/kg, twice per day) was injected to induce constipation for 1 week. DuOligo increased the fecal pellet amount, fecal weight, and water content of feces in rats with loperamide-induced constipation. DuOligo groups tended to produce more total fatty acid than that of observed for the control group. Gastrointestinal transit ratio and length and area of intestinal mucosa increased after treatment with DuOligo in loperamide-induced rats. These results showed that oral administration of DuOligo significantly modulated intestinal peristalsis.

Keywords: constipation, DuOligo, GOS, lactulose

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Authors: K. A. Ibe, J. I. Mbonu, G. K. Umukoro

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The effects of wood ash on the ignition point of five common tropical woods in Nigeria were investigated. The ash and moisture contents of the wood saw dust from Mahogany (Khaya ivorensis), Opepe (Sarcocephalus latifolius), Abura (Hallealedermannii verdc), Rubber (Heavea brasilensis) and Poroporo (Sorghum bicolour) were determined using a furnace (Vecstar furnaces, model ECF2, serial no. f3077) and oven (Genlab laboratory oven, model MINO/040) respectively. The metal contents of the five wood sawdust ash samples were determined using a Perkin Elmer optima 3000 dv atomic absorption spectrometer while the ignition points were determined using Vecstar furnaces model ECF2. Poroporo had the highest ash content, 2.263 g while rubber had the least, 0.710 g. The results for the moisture content range from 2.971 g to 0.903 g. Magnesium metal had the highest concentration of all the metals, in all the wood ash samples; with mahogany ash having the highest concentration, 9.196 ppm while rubber ash had the least concentration of magnesium metal, 2.196 ppm. The ignition point results showed that the wood ashes from mahogany and opepe increased the ignition points of the test wood samples when coated on them while the ashes from poroporo, rubber and abura decreased the ignition points of the test wood samples when coated on them. However, Opepe saw dust ash decreased the ignition point in one of the test wood samples, suggesting that the metal content of the test wood sample was more than that of the Opepe saw dust ash. Therefore, Mahogany and Opepe saw dust ashes could be used in the surface treatment of wood to enhance their fire resistance or retardancy. However, the caution to be exercised in this application is that the metal content of the test wood samples should be evaluated as well.

Keywords: ash, fire, ignition point, retardant, wood saw dust

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Authors: Lokendra Kumar Devangan, Ajay Mishra

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This paper describes the implementation of a large-scale SAS/OR model with significant pre-processing, scenario analysis, and post-processing work done using SAS. A large cement manufacturer with ten geographically distributed manufacturing plants for two variants of cement, around 400 warehouses serving as transshipment points, and several thousand distributor locations generating demand needed to optimize this multi-echelon, multi-modal transport supply chain separately for planning and allocation purposes. For monthly planning as well as daily allocation, the demand is deterministic. Rail and road networks connect any two points in this supply chain, creating tens of thousands of such connections. Constraints include the plant’s production capacity, transportation capacity, and rail wagon batch size constraints. Each demand point has a minimum and maximum for shipments received. Price varies at demand locations due to local factors. A large mixed integer programming model built using proc OPTMODEL decides production at plants, demand fulfilled at each location, and the shipment route to demand locations to maximize the profit contribution. Using base SAS, we did significant pre-processing of data and created inputs for the optimization. Using outputs generated by OPTMODEL and other processing completed using base SAS, we generated several reports that went into their enterprise system and created tables for easy consumption of the optimization results by operations.

Keywords: production planning, mixed integer optimization, network model, network optimization

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Authors: M. S. Meon, M. N. Rao, K-U. Schröder

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Mechanical fasteners especially bolting is commonly used in joining carbon-fiber reinforced polymer (CFRP) composite structures due to their good joinability and easy for maintenance characteristics. Since this approach involves with notching, a proper progressive damage model (PDM) need to be implemented and verified to capture existence of damages in the structure. A three dimensional (3D) failure criteria of Puck is established to predict the ultimate bearing failure of such joint. The failure criteria incorporated with degradation scheme are coded based on user subroutine executed in Abaqus. Single lap joint (SLJ) of composite bolted joint is used as target configuration. The results revealed that the PDM adopted here could sufficiently predict the behaviour of composite bolted joint up to ultimate bearing failure. In addition, mesh refinement near holes increased the accuracy of predicted strength as well as computational effort.

Keywords: bearing strength, bolted joint, degradation scheme, progressive damage model

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Authors: Guoliang Fan, Aiping Li, Xuemei Liu, Liyun Xu

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The performance of the tightening equipment will decline with the working process in manufacturing system. The main manifestations are the randomness and discretization degree increasing of the tightening performance. To evaluate the degradation tendency of the tightening performance accurately, a complexity measurement approach based on Kolmogorov entropy is presented. At first, the states of performance index are divided for calibrating the discrete degree. Then the complexity measurement model based on Kolmogorov entropy is built. The model describes the performance degradation tendency of tightening equipment quantitatively. At last, a study case is applied for verifying the efficiency and validity of the approach. The research achievement shows that the presented complexity measurement can effectively evaluate the degradation tendency of the tightening equipment. It can provide theoretical basis for preventive maintenance and life prediction of equipment.

Keywords: complexity measurement, Kolmogorov entropy, manufacturing system, performance evaluation, tightening equipment

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Authors: M. H. Kazemi, D. Salac

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A semi-implicit phase field method for droplet evolution is proposed. Using the phase field Cahn-Hilliard equation, we are able to track the interface in multiphase flow. The idea of a semi-implicit finite difference scheme is reviewed and employed to solve two nonlinear equations, including the Navier-Stokes and the Cahn-Hilliard equations. The use of a semi-implicit method allows us to have larger time steps compared to explicit schemes. The governing equations are coupled and then solved by a GMRES solver (generalized minimal residual method) using modified Gram-Schmidt orthogonalization. To show the validity of the method, we apply the method to the simulation of a rising droplet, a leaky dielectric drop and the coalescence of drops. The numerical solutions to the phase field model match well with existing solutions over a defined range of variables.

Keywords: coalescence, leaky dielectric, numerical method, phase field, rising droplet, semi-implicit method

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Authors: Ahmed Shuhaiber

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The explosion of the World Wide Web and the electronic trend of university teaching have transformed the learning style to become more learner-centred, Which has popularized the digital delivery of mediated lectures as an alternative or an adjunct to traditional lectures. Despite its potential and popularity, virtual lectures have not been adopted yet in Jordanian universities. This research aimed to fill this gap by studying the factors that influence student’s willingness to accept virtual lectures in one Jordanian University. A quantitative approach was followed by obtaining 216 survey responses and statistically applying the UTAUT model with some modifications. Results revealed that performance expectancy, effort expectancy, social influences and self-efficacy could significantly influence student’s attitudes towards virtual lectures. Additionally, facilitating conditions and attitudes towards virtual lectures were found with significant influence on student’s intention to take virtual lectures. Research implications and future work were specified afterwards.

Keywords: E-learning, student willingness, UTAUT, virtual Lectures, web-based learning systems

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Authors: Chaiyakrit Raoupatham, Ram Hari Dhakal, Chalermchai Wanichlamlert

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This paper is aimed to introduce the solution of concrete slump recovery using chemical admixture type-F (superplasticizer, naphthalene base) to the practice, in order to solve unusable concrete problem due to concrete loss its slump, especially for those tropical countries that have faster slump loss rate. In the other hand, randomly adding superplasticizer into concrete can cause concrete to segregate. Therefore, this paper also develops the estimation model used to calculate amount of second dose of superplasticizer need for concrete slump recovery. Fresh properties of ordinary Portland cement concrete with volumetric ratio of paste to void between aggregate (paste content) of 1.1-1.3 with water-cement ratio zone of 0.30 to 0.67 and initial superplasticizer (naphthalene base) of 0.25%- 1.6% were tested for initial slump and slump loss for every 30 minutes for one and half hour by slump cone test. Those concretes with slump loss range from 10% to 90% were re-dosed and successfully recovered back to its initial slump. Slump after re-dosed was tested by slump cone test. From the result, it has been concluded that, slump loss was slower for those mix with high initial dose of superplasticizer due to addition of superplasticizer will disturb cement hydration. The required second dose of superplasticizer was affected by two major parameter, which were water-cement ratio and paste content, where lower water-cement ratio and paste content cause an increase in require second dose of superplasticizer. The amount of second dose of superplasticizer is higher as the solid content within the system is increase, solid can be either from cement particles or aggregate. The data was analyzed to form an equation use to estimate the amount of second dosage requirement of superplasticizer to recovery slump to its original.

Keywords: estimation model, second superplasticizer dosage, slump loss, slump recovery

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Authors: T. Praveenkumar, Kulpreet Singh, Divy Bhanpuriya, M. Saimurugan

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This study analysed the classification accuracy for gearbox faults using Machine Learning Techniques. Gearboxes are widely used for mechanical power transmission in rotating machines. Its rotating components such as bearings, gears, and shafts tend to wear due to prolonged usage, causing fluctuating vibrations. Increasing the dependability of mechanical components like a gearbox is hampered by their sealed design, which makes visual inspection difficult. One way of detecting impending failure is to detect a change in the vibration signature. The current study proposes various machine learning algorithms, with aid of these vibration signals for obtaining the fault classification accuracy of an automotive 4-Speed synchromesh gearbox. Experimental data in the form of vibration signals were acquired from a 4-Speed synchromesh gearbox using Data Acquisition System (DAQs). Statistical features were extracted from the acquired vibration signal under various operating conditions. Then the extracted features were given as input to the algorithms for fault classification. Supervised Machine Learning algorithms such as Support Vector Machines (SVM) and unsupervised algorithms such as Deep Feed Forward Neural Network (DFFNN), Deep Belief Networks (DBN) algorithms are used for fault classification. The fusion of DBN & DFFNN classifiers were architected to further enhance the classification accuracy and to reduce the computational complexity. The fault classification accuracy for each algorithm was thoroughly studied, tabulated, and graphically analysed for fused and individual algorithms. In conclusion, the fusion of DBN and DFFNN algorithm yielded the better classification accuracy and was selected for fault detection due to its faster computational processing and greater efficiency.

Keywords: deep belief networks, DBN, deep feed forward neural network, DFFNN, fault diagnosis, fusion of algorithm, vibration signal

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Authors: Mariana L. de Araújo, Pedro P. M. Menezes

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Research on strategic human resource management (SHRM) has made progress in the last few decades, showing a relationship between policies and practices of human resource management (HRM) and improving organizational results. That's because demonstrating the effectiveness of any HRM or other organizational practice, which means the extent that this can operate as a tool to achieve organizational performance, is a complex and arduous task to execute. Even today, there isn't consensus about "effectiveness," and the tools to measure the effectiveness are disconnected and not convincing. It is not different from the performance management system (PMS) effectiveness. A disproportionate focus on specific criteria adopted and an accumulation of studies that don't relate to the others, which damages the development of the field. Therefore, it aimed to evaluate the effectiveness of the PMS through models, dimensions, criteria, and measures. The objective of this study is to propose a theoretical-integrative model for evaluating PMS based on the literature in the PMS field. So, the PRISMA protocol was applied to carry out a systematic review, resulting in 57 studies. After performing the content analysis, we identified six dimensions: learning, societal impact, reaction, financial results, operational results and transfer, and 22 categories. In this way, a theoretical-integrative model for assessing the effectiveness of PMS was proposed based on the findings of this study, in which it was possible to confirm that the effectiveness construct is somewhat complex when viewing that most of the reviewed studies considered multiple dimensions in their assessment. In addition, we identified that the most immediate and proximal results of PMS are the most adopted by the studies; conversely, the studies adopted less distal outcomes to assess the effectiveness of PMS. Another finding of this research is that the reviewed studies predominantly analyze from the individual or psychological perspective, even when it comes to criteria whose phenomena are at an organizational level. Therefore, this study converges with a trend recently identified when referring to a process of "psychologization" in which GP studies, in general, have demonstrated macro results of the GP system from an individual perspective. Therefore, given the identification of a methodological pattern, the predominant influence of individual and psychological aspects in studies on HRM in administration is highlighted, demonstrated by the reflection on the practically absolute way of measuring the effectiveness of PMS from perceptual and subjective measures. Therefore, based on the recognition of the patterns identified, the model proposed to promote studies on the subject more broadly and profoundly to broaden and deepen the perspective of the field of management's interests so that the evaluation of the effectiveness of PMS can promote inputs on the impact of the PMS system in organizational performance. Finally, the findings encourage reflections on assessing the effectiveness of PMS through the theoretical-integrative model developed so that the field can promote new theoretical and practical perspectives.

Keywords: performance management, strategic human resource management, effectiveness, organizational performance

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Authors: G. Sandhya Devi, G. Suvarna Kumar, S. Chandini

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This research work aims to develop a system that will analyze and identify students who indulge in malpractices/suspicious activities during the course of an academic offline examination. Automated Video Surveillance provides an optimal solution which helps in monitoring the students and identifying the malpractice event immediately. This work is organized into three modules. The first module deals with performing an impersonation check using a PCA-based face recognition method which is done by cross checking his profile with the database. The presence or absence of the student is even determined in this module by implementing an image registration technique wherein a grid is formed by considering all the images registered using the frontal camera at the determined positions. Second, detecting such facial malpractices in which a student gets involved in conversation with another, trying to obtain unauthorized information etc., based on the threshold range evaluated by considering his/her mouth state whether open or closed. The third module deals with identification of unauthorized material or gadgets used in the examination hall by training the positive samples of the object through various stages. Here, a top view camera feed is analyzed to detect the suspicious activities. The system automatically alerts the administration when any suspicious activities are identified, thereby reducing the error rate caused due to manual monitoring. This work is an improvement over our previous work published in identifying suspicious activities done by examinees in an offline examination.

Keywords: impersonation, image registration, incrimination, object detection, threshold evaluation

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Authors: Chin-Chih Chang

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Many manufacturing systems suffer failures due to complex degradation processes and various environment conditions such as random shocks. Consider an operating system is subject to random shocks and works at random times for successive jobs. When successive jobs often result in production losses and performance deterioration, it would be better to do maintenance or replacement at a planned time. A preventive replacement (PR) policy is presented to replace the system before a failure occurs at a continuous time T. In such a policy, the failure characteristics of the system are designed as follows. Each job would cause a random amount of additive damage to the system, and the system fails when the cumulative damage has exceeded a failure threshold. Suppose that the deteriorating system suffers one of the two types of shocks with age-dependent probabilities: type-I (minor) shock is rectified by a minimal repair, or type-II (catastrophic) shock causes the system to fail. A corrective replacement (CR) is performed immediately when the system fails. In summary, a generalized maintenance model to scheduling replacement plan for an operating system is presented below. PR is carried out at time T, whereas CR is carried out when any type-II shock occurs and the total damage exceeded a failure level. The main objective is to determine the optimal continuous schedule time of preventive replacement through minimizing the mean cost rate function. The existence and uniqueness of optimal replacement policy are derived analytically. It can be seen that the present model is a generalization of the previous models, and the policy with preventive replacement outperforms the one without preventive replacement.

Keywords: preventive replacement, working time, cumulative damage model, minimal repair, imperfect maintenance, optimization

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Authors: Ririh Rahma Ratinghayu, Jayu Pramudya, Nur Aini Masruroh, Shi-Woei Lin

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This research studies pricing strategy in cooperative setting of hotel duopoly selling perishable product under fixed capacity constraint by using the perspective of managers. In hotel revenue management, competitor’s average room rate and occupancy rate should be taken into manager’s consideration in determining pricing strategy to generate optimum revenue. This information is not provided by business intelligence or available in competitor’s website. Thus, Information Sharing (IS) among players might result in improved performance of pricing strategy. IS is widely adopted in the logistics industry, but IS within hospitality industry has not been well-studied. This research put IS as one of cooperative game schemes, besides Mutual Price Setting (MPS) scheme. In off-peak season, hotel manager arranges pricing strategy to offer promotion package and various kinds of discounts up to 60% of full-price to attract customers. Competitor selling homogenous product will react the same, then triggers a price war. Price war which generates lower revenue may be avoided by creating collaboration in pricing strategy to optimize payoff for both players. In MPS cooperative game, players collaborate to set a room rate applied for both players. Cooperative game may avoid unfavorable players’ payoff caused by price war. Researches on horizontal cooperative game in logistics show better performance and payoff for the players, however, horizontal cooperative game in hotel revenue management has not been demonstrated. This paper aims to develop hotel revenue management models under duopoly cooperative schemes (IS & MPS), which are compared to models under non-cooperative scheme too. Each scheme has five models, Capacity Allocation Model; Demand Model; Revenue Model; Optimal Price Model; and Equilibrium Price Model. Capacity Allocation Model and Demand Model employs self-hotel and competitor’s full and discount price as predictors under non-linear relation. Optimal price is obtained by assuming revenue maximization motive. Equilibrium price is observed by interacting self-hotel’s and competitor’s optimal price under reaction equation. Equilibrium is analyzed using game theory approach. The sequence applies for three schemes. MPS Scheme differently aims to optimize total players’ payoff. The case study in which theoretical models are applied observes two hotels offering homogenous product in Indonesia during a year. The Capacity Allocation, Demand, and Revenue Models are built using multiple regression and statistically tested for validation. Case study data confirms that price behaves within demand model in a non-linear manner. IS Models can represent the actual demand and revenue data better than Non-IS Models. Furthermore, IS enables hotels to earn significantly higher revenue. Thus, duopoly hotel players in general, might have reasonable incentives to share information horizontally. During off-peak season, MPS Models are able to predict the optimal equal price for both hotels. However, Nash equilibrium may not always exist depending on actual payoff of adhering or betraying mutual agreement. To optimize performance, horizontal cooperative game may be chosen over non-cooperative game. Mathematical models can be used to detect collusion among business players. Empirical testing can be used as policy input for market regulator in preventing unethical business practices potentially harming society welfare.

Keywords: horizontal cooperative game theory, hotel revenue management, information sharing, mutual price setting

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Authors: Kothuri Sriraman, Mattupalli Komal Teja

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In this paper, a novel algorithm is proposed for the recognition of hulls in a hand written images that might be irregular or digit or character shape. Identification of objects and internal objects is quite difficult to extract, when the structure of the image is having bulk of clusters. The estimation results are easily obtained while going through identifying the sub-regional objects by using the SASK algorithm. Focusing mainly to recognize the number of internal objects exist in a given image, so as it is shadow-free and error-free. The hard clustering and density clustering process of obtained image rough set is used to recognize the differentiated internal objects, if any. In order to find out the internal hull regions it involves three steps pre-processing, Boundary Extraction and finally, apply the Hull Detection system. By detecting the sub-regional hulls it can increase the machine learning capability in detection of characters and it can also be extend in order to get the hull recognition even in irregular shape objects like wise black holes in the space exploration with their intensities. Layered hulls are those having the structured layers inside while it is useful in the Military Services and Traffic to identify the number of vehicles or persons. This proposed SASK algorithm is helpful in making of that kind of identifying the regions and can useful in undergo for the decision process (to clear the traffic, to identify the number of persons in the opponent’s in the war).

Keywords: chain code, Hull regions, Hough transform, Hull recognition, Layered Outline Extraction, SASK algorithm

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Authors: G. Martino, F. Silva, E. Marchal

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The control over delivered iron ore blend characteristics is one of the most important aspects of the mining business. The iron ore price is a function of its composition, which is the outcome of the beneficiation process. So, end-to-end integrated planning of mine operations can reduce risks of penalties on the iron ore price. In a standard iron mining company, the production chain is composed of mining, ore beneficiation, and client supply. When mine planning and client supply decisions are made uncoordinated, the beneficiation plant struggles to deliver the best blend possible. Technological improvements in several fields allowed bridging the gap between departments and boosting integrated decision-making processes. Clusterization and classification algorithms over historical production data generate reasonable previsions for quality and volume of iron ore produced for each pile of run-of-mine (ROM) processed. Mathematical modeling can use those deterministic relations to propose iron ore blends that better-fit specifications within a delivery schedule. Additionally, a model capable of representing the whole production chain can clearly compare the overall impact of different decisions in the process. This study shows how flexibilization combined with a planning optimization model between the mine and the ore beneficiation processes can reduce risks of out of specification deliveries. The model capabilities are illustrated on a hypothetical iron ore mine with magnetic separation process. Finally, this study shows ways of cost reduction or profit increase by optimizing process indicators across the production chain and integrating the different plannings with the sales decisions.

Keywords: clusterization and classification algorithms, integrated planning, mathematical modeling, optimization, penalty minimization

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Authors: Cecile Edel, Sandrine Giscard D'Estaing, Elsa Labrune, Jacqueline Lornage, Mehdi Benchaib

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Introduction: The use of incubator equipped with time-lapse technology in Artificial Reproductive Technology (ART) allows a continuous surveillance. With morphocinetic parameters, algorithms are available to predict the potential outcome of an embryo. However, the different proposed time-lapse algorithms do not take account the missing data, and then some embryos could not be classified. The aim of this work is to construct a predictive model even in the case of missing data. Materials and methods: Patients: A retrospective study was performed, in biology laboratory of reproduction at the hospital ‘Femme Mère Enfant’ (Lyon, France) between 1 May 2013 and 30 April 2015. Embryos (n= 557) obtained from couples (n=108) were cultured in a time-lapse incubator (Embryoscope®, Vitrolife, Goteborg, Sweden). Time-lapse incubator: The morphocinetic parameters obtained during the three first days of embryo life were used to build the predictive model. Predictive model: A quadratic regression was performed between the number of cells and time. N = a. T² + b. T + c. N: number of cells at T time (T in hours). The regression coefficients were calculated with Excel software (Microsoft, Redmond, WA, USA), a program with Visual Basic for Application (VBA) (Microsoft) was written for this purpose. The quadratic equation was used to find a value that allows to predict the blastocyst formation: the synthetize value. The area under the curve (AUC) obtained from the ROC curve was used to appreciate the performance of the regression coefficients and the synthetize value. A cut-off value has been calculated for each regression coefficient and for the synthetize value to obtain two groups where the difference of blastocyst formation rate according to the cut-off values was maximal. The data were analyzed with SPSS (IBM, Il, Chicago, USA). Results: Among the 557 embryos, 79.7% had reached the blastocyst stage. The synthetize value corresponds to the value calculated with time value equal to 99, the highest AUC was then obtained. The AUC for regression coefficient ‘a’ was 0.648 (p < 0.001), 0.363 (p < 0.001) for the regression coefficient ‘b’, 0.633 (p < 0.001) for the regression coefficient ‘c’, and 0.659 (p < 0.001) for the synthetize value. The results are presented as follow: blastocyst formation rate under cut-off value versus blastocyst rate formation above cut-off value. For the regression coefficient ‘a’ the optimum cut-off value was -1.14.10-3 (61.3% versus 84.3%, p < 0.001), 0.26 for the regression coefficient ‘b’ (83.9% versus 63.1%, p < 0.001), -4.4 for the regression coefficient ‘c’ (62.2% versus 83.1%, p < 0.001) and 8.89 for the synthetize value (58.6% versus 85.0%, p < 0.001). Conclusion: This quadratic regression allows to predict the outcome of an embryo even in case of missing data. Three regression coefficients and a synthetize value could represent the identity card of an embryo. ‘a’ regression coefficient represents the acceleration of cells division, ‘b’ regression coefficient represents the speed of cell division. We could hypothesize that ‘c’ regression coefficient could represent the intrinsic potential of an embryo. This intrinsic potential could be dependent from oocyte originating the embryo. These hypotheses should be confirmed by studies analyzing relationship between regression coefficients and ART parameters.

Keywords: ART procedure, blastocyst formation, time-lapse incubator, quadratic model

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Authors: Tingyu Zhang

Abstract:

This paper utilizes the Super-SBM model to assess water resources green efficiency (WRGE) among provinces in China and investigate its spatial and temporal features, based on the characteristic framework of “economy-environment-society.” The social network analysis is employed to examine the network pattern and spatial interaction of WRGE. Further, the quadratic assignment procedure method is utilized for examining the influencing factors of the spatial association of WRGE regarding “relationship.” The study reveals that: (1) the spatial distribution of WRGE demonstrates a distribution pattern of Eastern>Western>Central; (2) a remarkable spatial association exists among provinces; however, no strict hierarchical structure is observed. The internal structure of the WRGE network is characterized by the feature of "Eastern strong and Western weak". The block model analysis discovers that the members of the “net spillover” and “two-way spillover” blocks are mostly in the eastern and central provinces; “broker” block, which plays an intermediary role, is mostly in the central provinces; and members of the “net beneficiary” block are mostly in the western region. (3) Differences in economic development, degree of urbanization, water use environment, and water management have significant impacts on the spatial connection of WRGE. This study is dedicated to the realization of regional linkages and synergistic enhancement of WRGE, which provides a meaningful basis for building a harmonious society of human and water coexistence.

Keywords: water resources green efficiency, super-SBM model, social network analysis, quadratic assignment procedure

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Authors: Yao Wu

Abstract:

In the context of financial globalization, China has put forward the policy goal of high-quality development, and the digital economy, with its advantage of information resources, is driving China's export trade to achieve high-quality development. Due to the long-standing financing constraints of small and medium-sized export enterprises, how to expand the export scale of small and medium-sized enterprises has become a major threshold for the development of China's export trade. This paper firstly adopts the hierarchical analysis method to establish the evaluation system of high-quality development of China's export trade; secondly, the panel data of 30 provinces in China from 2011 to 2018 are selected for empirical analysis to establish the impact model of digital inclusive finance on the high-quality development of China's export trade; based on the analysis of heterogeneous enterprise trade model, a mediating effect model is established to verify the mediating role of credit constraint in the development of high-quality export trade in China. Based on the above analysis, this paper concludes that inclusive digital finance, with its unique digital and inclusive nature, alleviates the credit constraint problem among SMEs, enhances the binary marginal effect of SMEs' exports, optimizes their export scale and structure, and promotes the high-quality development of regional and even national export trade. Finally, based on the findings of this paper, we propose insights and suggestions for inclusive digital finance to promote the high-quality development of export trade.

Keywords: digital inclusive finance, high-quality development of export trade, fixed effects, binary marginal effects

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Authors: Zdzislaw Kaminski, Zbigniew Czyz, Tytus Tulwin

Abstract:

This paper describes the geometrical model, algorithm and CFD simulation of an airflow around a Vertical Axis Wind Turbine rotor. A solver, ANSYS Fluent, was applied for the numerical simulation. Numerical simulation, unlike experiments, enables us to validate project assumptions when it is designed to avoid a costly preparation of a model or a prototype for a bench test. This research focuses on the rotor designed according to patent no PL 219985 with its blades capable of modifying their working surfaces, i.e. absorbing wind kinetic energy. The operation of this rotor is based on a regulation of blade angle α between the top and bottom parts of blades mounted on an axis. If angle α increases, the working surface which absorbs wind kinetic energy also increases. CFD calculations enable us to compare aerodynamic characteristics of forces acting on rotor working surfaces and specify rotor operation parameters like torque or turbine assembly power output. This paper is part of the research to improve an efficiency of a rotor assembly and it contains investigation of the impact of a blade angle of wind turbine working blades on the power output as a function of rotor torque, specific rotational speed and wind speed. The simulation was made for wind speeds ranging from 3.4 m/s to 6.2 m/s and blade angles of 30°, 60°, 90°. The simulation enables us to create a mathematical model to describe how aerodynamic forces acting each of the blade of the studied rotor are generated. Also, the simulation results are compared with the wind tunnel ones. This investigation enables us to estimate the growth in turbine power output if a blade angle changes. The regulation of blade angle α enables a smooth change in turbine rotor power, which is a kind of safety measures if the wind is strong. Decreasing blade angle α reduces the risk of damaging or destroying a turbine that is still in operation and there is no complete rotor braking as it is in other Horizontal Axis Wind Turbines. This work has been financed by the Polish Ministry of Science and Higher Education.

Keywords: computational fluid dynamics, mathematical model, numerical analysis, power, renewable energy, wind turbine

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Authors: Jiayuan Wu. Lu Hu

Abstract:

With the development of the sharing economy and mobile technology, carsharing becomes more popular. In this paper, we focus on the joint optimization of one-way station-based carsharing systems. We model the problem as an integer linear program with six elements: station locations, station capacity, fleet size, initial vehicle allocation, vehicle relocation, and demand selection. A greedy-based heuristic is proposed to address the model. Firstly, initialization based on the location variables relaxation using Gurobi solver is conducted. Then, according to the profit margin and demand satisfaction of each station, the number of stations is downsized iteratively. This method is applied to real data from Chengdu, Sichuan taxi data, and it’s efficient when dealing with a large scale of candidate stations. The result shows that with vehicle relocation and demand selection, the profit and demand satisfaction of carsharing systems are increased.

Keywords: one-way carsharing, location, vehicle relocation, demand selection, greedy algorithm

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Authors: Hamed Saremi, Shahla Saremi

Abstract:

In today's competitive world, organizations are expected to surpass the competitors and benefit from the resources and benefits. Therefore, organizations need to improve the current performance is felt more than ever that this requires to identify organizational optimal strategies, and consider all strategies simultaneously. In this study, to enhance competitive advantage and according to customer requirements, alignment between business, production and marketing strategies, House of Quality (QFD) approach has been used and zero-one linear programming model has been studied. First, the alignment between production and marketing strategies with business strategy, independent weights of these strategies is calculated. Then with using QFD approach the aligned weights of optimal strategies in each production and marketing field will be obtained and finally the aligned marketing strategies selection with the purpose of allocating budget and specialist human resource to marketing functions will be done that lead to increasing competitive advantage and benefit.

Keywords: marketing strategy, business strategy, strategy alignment, house of quality deployment, production strategy

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Authors: Jhonnatan Eduardo Zamudio Palacios, Oscar Leonardo Mosquera Dussan, Daniel Guzman Perez, Daniel Alfonso Botero Rosas, Oscar Fabian Rubiano Espinosa, Jose Antonio Garcia Torres, Ivan Dario Chavarro, Ivan Ramiro Rodriguez Camacho, Jaime Orlando Rodriguez

Abstract:

The training of cilsitas with some type of disability finds in the technological development an indispensable ally, generating every day advances to contribute to the quality of life allowing to maximize the capacities of the athletes. The performance of a cyclist depends on physiological and biomechanical factors, such as aerodynamic profile, bicycle measurements, connecting rod length, pedaling systems, type of competition, among others. This study particularly focuses on the description of the dynamic model of a transtibial prosthesis for Paralympic cyclists. To make the model, two points are chosen: in the radius centers of rotation of the plate and pinion of the track bicycle. The parametric scheme of the track bike represents a model of 6 degrees of freedom due to the displacement in X - Y of each of the reference points of the angles of the curve profile β, cant of the velodrome α and the angle of rotation of the connecting rod φ. The force exerted on the crank of the bicycle varies according to the angles of the curve profile β, the velodrome cant of α and the angle of rotation of the crank φ. The behavior is analyzed through the Matlab R2015a software. The average strength that a cyclist exerts on the cranks of a bicycle is 1,607.1 N, the Paralympic cyclist must perform a force on each crank about 803.6 N. Once the maximum force associated with the movement has been determined, it is continued to the dynamic modeling of the transtibial prosthesis that represents a model of 6 degrees of freedom with displacement in X - Y in relation to the angles of rotation of the hip π, knee γ and ankle λ. Subsequently, an analysis of the kinematic behavior of the prosthesis was carried out by means of SolidWorks 2017 and Matlab R2015a, which was used to model and analyze the variation of the hip angles π, knee γ and ankle of the λ prosthesis. The reaction forces generated in the prosthesis were performed on the ankle of the prosthesis, performing the summation of forces on the X and Y axes. The same analysis was then applied to the tibia of the prosthesis and the socket. The reaction force of the parts of the prosthesis varies according to the hip angles π, knee γ and ankle of the prosthesis λ. Therefore, it can be deduced that the maximum forces experienced by the ankle of the prosthesis is 933.6 N on the X axis and 2.160.5 N on the Y axis. Finally, it is calculated that the maximum forces experienced by the tibia and the socket of the transtibial prosthesis in high performance competitions is 3.266 N on the X axis and 1.357 N on the Y axis. In conclusion, it can be said that the performance of the cyclist depends on several physiological factors, linked to biomechanics of training. The influence of biomechanical factors such as aerodynamics, bicycle measurements, connecting rod length, or non-circular pedaling systems on the cyclist performance.

Keywords: biomechanics, dynamic model, paralympic cyclist, transtibial prosthesis

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Authors: Hamid Hanifi, Adel Azar, Alireza Booshehri

Abstract:

In order to know about the capability level of R & D units in automotive industry, it is essential that organizations always compare themselves with standard level and higher than themselves so that to be improved continuously. In this research, with respect to the importance of this issue, we have tried to present an assessment model for R & D capabilities having reviewed on new products development in automotive industry of Iran. Iran Khodro Company was selected for the case study. To this purpose, first, having a review on the literature, about 200 indicators effective in R & D capabilities and new products development were extracted. Then, of these numbers, 29 indicators which were more important were selected by industry and academia experts and the questionnaire was distributed among statistical population. Statistical population was consisted of 410 individuals in Iran Khodro Company. We used the 410 questionnaires for exploratory factor analysis and then used the data of 308 questionnaires from the same population randomly for confirmatory factor analysis. The results of exploratory factor analysis led to categorization of dimensions in 9 secondary dimensions. Naming the dimensions was done according to a literature review and the professors’ opinion. Using structural equation modeling and AMOS software, confirmatory factor analysis was conducted and ultimate model with 9 secondary dimensions was confirmed. Meanwhile, 9 secondary dimensions of this research are as follows: 1) Research and design capability, 2) Customer and market capability, 3) Technology capability, 4) Financial resources capability, 5) Organizational chart, 6) Intellectual capital capability, 7) NPD process capability, 8) Managerial capability and 9) Strategy capability.

Keywords: research and development, new products development, structural equations, exploratory factor analysis, confirmatory factor analysis

Procedia PDF Downloads 342