Search results for: General Linear Model

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

Procedia PDF Downloads 369

Authors: Avishkar Gawade, Omkar Bansode, Ketan Bhambure, Bhargav Deore

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In recent year wide range of business intelligence technology have been applied to different area in order to support decision making process BI enables extraction of knowledge from data store. BI tools usually used in public health field for financial and administrative purposes.BI uses a dashboard in presentation stage to deliver information to information to end users.In this paper,we intend to analyze some open source BI tools on the market and their applicability in the clinical sphere taking into consideration the general characteristics of the clinical environment.A pervasive BI platform was developed using a real case in order to prove the tool viability.Analysis of various BI Tools in done with the help of several parameters such as data security,data integration,data quality reporting and anlaytics,performance,scalability and cost effectivesness.

Keywords: CDSS, EHR, business intelliegence, tools

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Authors: Abdelhamid Louliej, Younes Jabrane

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Satellites are becoming indispensable assets to fifth-generation (5G) new radio architecture, complementing wireless and terrestrial communication links. The combination of satellites and 5G architecture allows consumers to access all next-generation services anytime, anywhere, including scenarios, like traveling to remote areas (without coverage). Nevertheless, this solution faces several challenges, such as a significant propagation delay, Doppler frequency shift, and high Peak-to-Average Power Ratio (PAPR), causing signal distortion due to the non-linear saturation of the High-Power Amplifier (HPA). To compensate for HPA non-linearity in 5G satellite transmission, an efficient pre-distorter scheme using Neural Networks (NN) is proposed. To assess the proposed NN pre-distorter, two types of HPA were investigated: Travelling Wave Tube Amplifier (TWTA) and Solid-State Power Amplifier (SSPA). The results show that the NN pre-distorter design presents EVM improvement by 95.26%. NMSE and ACPR were reduced by -43,66 dB and 24.56 dBm, respectively. Moreover, the system suffers no degradation of the Bit Error Rate (BER) for TWTA and SSPA amplifiers.

Keywords: satellites, 5G, neural networks, HPA, TWTA, SSPA, EVM, NMSE, ACPR

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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: Rym Ghariani, Younes Boujelbene

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In contemporary times, global technological advancements, particularly those in the realm of digital technology, have emerged as pivotal instruments for enterprises in fostering viable partnerships and forging meaningful alliances with other firms. The advent of these digital innovations is poised to revolutionize nearly every facet and operation within corporate entities. The primary objective of this study is to explore the correlation between digitization, integration of supply chains, and the financial efficacy of the agro-industrial sector in Tunisia. To accomplish this, data collection employed a questionnaire as the primary research instrument. Subsequently, the research queries were addressed, and hypotheses were examined by subjecting the gathered data to principal component analysis and linear regression modeling, facilitated by the utilization of SPSS26 software. The findings revealed that digitalization within the supply chain, along with external supply chain integration, exerted discernible impacts on the financial performance of the organization.

Keywords: digitalization, supply chain integration, financial performance, Tunisian agro-industrial sector

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Authors: Po-Chien Li

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Despite the extant literature has hosted a wide-range of knowledge about trade shows, this knowledge base deserves to be further expanded and extended because there exist many unclear issues and overlooked topics. One area that needs much research attention is regarding the behavior and performance of booth workers at the exhibition site. Booth staffs play many key roles in interacting with booth visitors. Their exhibiting-related attitudes and motivations might have significant consequences on a firm’s exhibition results. However, to date, little research, if any, has studied how booth workers are affected and behave in the context of trade fair. The primary purpose of the current study is to develop and test a research model, derived from role theory and resource-based viewpoint, that depicts the effects of a firm’s pre-exhibition resource investment behavior on booth staff’s role perceptions and work behavior during the exhibition period. The author collects data with two survey questionnaires at two trade shows in 2016. One questionnaire is given to the booth head of an exhibiting company, asking about the firm’s resource commitment behavior prior to the exhibition period. In contrast, another questionnaire is provided for a booth worker of the same firm, requesting the individual staff to report his/her own role perceptions, degree of exhibition goal acceptance, and level of work effort during the exhibition period. The study has utilized the following analytic methods, including descriptive statistics, exploratory factor analysis, reliability analysis, and regression analysis. The results of a set of regression analyses show that a firm’s pre-exhibition resource investment behavior has significant effects on a booth staff’s exhibiting perceptions and attitudes. Specifically, an exhibitor’s resource investment behavior has impacts on the factors of booth staff’s role clarity and role conflict. In addition, a booth worker’s role clarity is related to the degree of exhibition goal acceptance, but his/her role conflict is not. Finally, a booth worker’s exhibiting effort is significantly related to the individual’s role clarity, role conflict and goal acceptance. In general, the major contribution of the current research is that it offers insight into and early evidence on the links between an exhibiting firm’s resource commitment behavior and the work perceptions and attitudes of booth staffs during the exhibition period. The current research’s results can benefit the extant literature of exhibition marketing.

Keywords: exhibition resource investment, role perceptions, goal acceptance, work effort

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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: Duchduen Bhanthumnavin

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One of the most important characteristics to increase competitive ability in undergraduate students after post COVID-19 era is goal setting and self-control. This correlational study aimes at investigating the influence of psycho-social antecedents on goal setting and self-control in 550 Thai university students. Results from multiple regression analysis revealed that the important predictors of this characteristic were reasoning ability, psychological immunity, attitudes toward competition, core self-evaluation, and family nurture, which yielded 54.28 predictive percentage in the total sample. Moreover, the analysis identified three at-risk groups, namely, male students, low GPA students, and students with siblings. Discussion and implications in general and for specific purposes for the at-risk groups were offered.

Keywords: antecedents, plan and self-control, predictors, university students

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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

Procedia PDF Downloads 278

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

Procedia PDF Downloads 186

Authors: Emad A. Mohammed

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The concept of hydraulic flow units (HFU) has been used for decades in the petroleum industry to improve the prediction of permeability. This concept is strongly related to the flow zone indicator (FZI) which is a function of the reservoir rock quality index (RQI). Both indices are based on reservoir porosity and permeability of core samples. It is assumed that core samples with similar FZI values belong to the same HFU. Thus, after dividing the porosity-permeability data based on the HFU, transformations can be done in order to estimate the permeability from the porosity. The conventional practice is to use the power law transformation using conventional HFU where percentage of error is considerably high. In this paper, neural network technique is employed as a soft computing transformation method to predict permeability instead of power law method to avoid higher percentage of error. This technique is based on HFU identification where Amaefule et al. (1993) method is utilized. In this regard, Kozeny and Carman (K–C) model, and modified K–C model by Hasan and Hossain (2011) are employed. A comparison is made between the two transformation techniques for the two porosity-permeability models. Results show that the modified K-C model helps in getting better results with lower percentage of error in predicting permeability. The results also show that the use of artificial intelligence techniques give more accurate prediction than power law method. This study was conducted on a heterogeneous complex carbonate reservoir in Oman. Data were collected from seven wells to obtain the permeability correlations for the whole field. The findings of this study will help in getting better estimation of permeability of a complex reservoir.

Keywords: permeability, hydraulic flow units, artificial intelligence, correlation

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Authors: Sulaiman B. Ali Alharbi, Bassam H. Mashat, Naif Abdullah Al-Harbi, Milton Wainwright, Abeer S. Aloufi, Sulamain Alnaimat

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Bismuth salicylate was found to inhibit the growth of a range of bacteria and yeast, Candida albican. In general the growth of bacteria did not result in the increase in bismuth solubilisation, in contrast, bismuth solubilisation increased following the growth of C. albicans. A significant increase in the biomass (dry weight) of Aspergillus niger and Aspergillus oryzae occurred in vitro when these fungi were grown in the presence of bismuth salicylate. Biomass increase occurred over a range of bismuth compound additions, which in the case of A. oryzae was associated with the increase in the solubilisation of the insoluble bismuth compounds.

Keywords: bacterial inhibition, fungal growth stimulation, medical uses of bismuth, yeast inhibition

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Authors: Xiping Guo, Jing Li

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The microstructure of an Si-Al-Y co-deposition coating prepared on an Nb-Si based ultra high temperature alloy by pack cementation process at 1250°C for eight hours was studied. The results showed that the coating was composed of a (Nb,X)Si₂ (X represents Ti, Cr and Hf elements) outer layer, a (Ti,Nb)₅Si₄ middle layer and an Al, Cr-rich inner layer. For comparison, the oxidation behaviors of the coating at 800, 1050 and 1350°C were investigated respectively. Linear oxidation kinetics was found with the parabolic rate constants of 5.29×10⁻², 9×10⁻²and 5.81 mg² cm⁻⁴ h⁻¹, respectively. Catastrophic pesting oxidation has not been found at 800°C even for 100 h. The surface of the scale was covered by compact glassy SiO₂ film. The coating was able to effectively protect the Nb-Si based alloy from oxidation at 1350°C for at least 100 h. The formation process of the scale was testified following an epitaxial growth mechanism. The mechanism responsible for the oxidation behavior of the Si-Al-Y co-deposition coating at 800, 1050 and 1350°C was proposed.

Keywords: Nb-Si based ultra high temperature alloy, oxidation resistance, pack cementation, silicide coating, Al and Y modified

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Authors: Francois Brambati, Daniele Ruscio, Federica Biassoni, Rebecca Hueting, Alessandra Tedeschi

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This research, in the frame of social acceptance of renewable energies and community-based production and consumption models, aims at (1) supporting a data-driven approachable to dealing with climate change and (2) identifying & quantifying the psycho-sociological dimensions and factors that could support the transition from a technology-driven approach to a consumer-driven approach throughout the emerging “prosumer business models.” In addition to the existing Social Acceptance dimensions, this research tries to identify a purely individual psychological fourth dimension to understand processes and factors underling individual acceptance and adoption of renewable energy business models, realizing a Prosumer Acceptance Index. Questionnaire data collection has been performed throughout an online survey platform, combining standardized and ad-hoc questions adapted for the research purposes. To identify the main factors (individual/social) influencing the relation with renewable energy technology (RET) adoption, a Factorial Analysis has been conducted to identify the latent variables that are related to each other, revealing 5 latent psychological factors: Factor 1. Concern about environmental issues: global environmental issues awareness, strong beliefs and pro-environmental attitudes rising concern on environmental issues. Factor 2. Interest in energy sharing: attentiveness to solutions for local community’s collective consumption, to reduce individual environmental impact, sustainably improve the local community, and sell extra energy to the general electricity grid. Factor 3. Concern on climate change: environmental issues consequences on climate change awareness, especially on a global scale level, developing pro-environmental attitudes on global climate change course and sensitivity about behaviours aimed at mitigating such human impact. Factor 4. Social influence: social support seeking from peers. With RET, advice from significant others is looked for internalizing common perceived social norms of the national/geographical region. Factor 5. Impact on bill cost: inclination to adopt a RET when economic incentives from the behaviour perception affect the decision-making process could result in less expensive or unvaried bills. Linear regression has been conducted to identify and quantify the factors that could better predict behavioural intention to become a prosumer. An overall scale measuring “acceptance of a renewable energy solution” was used as the dependent variable, allowing us to quantify the five factors that contribute to measuring: awareness of environmental issues and climate change; environmental attitudes; social influence; and environmental risk perception. Three variables can significantly measure and predict the scores of the “Acceptance in becoming a prosumer” ad hoc scale. Variable 1. Attitude: the agreement to specific environmental issues and global climate change issues of concerns and evaluations towards a behavioural intention. Variable 2. Economic incentive: the perceived behavioural control and its related environmental risk perception, in terms of perceived short-term benefits and long-term costs, both part of the decision-making process as expected outcomes of the behaviour itself. Variable 3. Age: despite fewer economic possibilities, younger adults seem to be more sensitive to environmental dimensions and issues as opposed to older adults. This research can facilitate policymakers and relevant stakeholders to better understand which relevant psycho-sociological factors are intervening in these processes and what and how specifically target when proposing change towards sustainable energy production and consumption.

Keywords: behavioural intention, environmental risk perception, prosumer, renewable energy technology, social acceptance

Procedia PDF Downloads 109

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: Eunice Chiamaka Allen-Ngbale

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Cargo claims are brought by cargo interests against carriers when the goods are not delivered or delivered short or mis-delivered or delivered damaged. The objective of the cargo claimant is to seek recovery for the loss suffered through the award of damages against the carrier by a court of competent jurisdiction. Moreover, whether the vessel on which the goods were carried is or is not under charter, the bill of lading plays a central role in the cargo claim. Since the bill of lading is an important international transport document, this paper examines, by chronicling the progress of a cargo claim as governed by the English law of contract. It finds that other than by contract, there are other modes of recovery available to a consignee or endorsee of a bill of lading to obtain a remedy under the sui generis contract of carriage contained in or evidenced by a bill of lading.

Keywords: bill of lading, cargo interests, carriage contract, transfer of right of suit

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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

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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

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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

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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: 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

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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

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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

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Authors: Izabella Szollosi, Klara Marton

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Aphasia can be defined as a weakness in accessing linguistic information. Accessing linguistic information is strongly related to information processing, which in turn is associated with the cognitive control system. According to the literature, a deficit in the cognitive control system interferes with language processing and contributes to non-fluent speech performance. The aim of our study was to explore this hypothesis by investigating how cognitive control interacts with language performance in participants with non-fluent aphasia. Cognitive control is a complex construct that includes working memory (WM) and the ability to resist proactive interference (PI). Based on previous research, we hypothesized that impairments in domain-general (DG) cognitive control abilities have negative effects on language processing. In contrast, better DG cognitive control functioning supports goal-directed behavior in language-related processes as well. Since stroke itself might slow down information processing, it is important to examine its negative effects on both cognitive control and language processing. Participants (N=52) in our study were individuals with non-fluent Broca’s aphasia (N = 13), with transcortical motor aphasia (N=13), individuals with stroke damage without aphasia (N=13), and unimpaired speakers (N = 13). All participants performed various computer-based tasks targeting cognitive control functions such as WM and resistance to PI in both linguistic and non-linguistic domains. Non-linguistic tasks targeted primarily DG functions, while linguistic tasks targeted more domain specific (DS) processes. The results showed that participants with Broca’s aphasia differed from the other three groups in the non-linguistic tasks. They performed significantly worse even in the baseline conditions. In contrast, we found a different performance profile in the linguistic domain, where the control group differed from all three stroke-related groups. The three groups with impairment performed more poorly than the controls but similar to each other in the verbal baseline condition. In the more complex verbal PI condition, however, participants with Broca’s aphasia performed significantly worse than all the other groups. Participants with Broca’s aphasia demonstrated the most severe language impairment and the highest vulnerability in tasks measuring DG cognitive control functions. Results support the notion that the more severe the cognitive control impairment, the more severe the aphasia. Thus, our findings suggest a strong interaction between cognitive control and language. Individuals with the most severe and most general cognitive control deficit - participants with Broca’s aphasia - showed the most severe language impairment. Individuals with better DG cognitive control functions demonstrated better language performance. While all participants with stroke damage showed impaired cognitive control functions in the linguistic domain, participants with better language skills performed also better in tasks that measured non-linguistic cognitive control functions. The overall results indicate that the level of cognitive control deficit interacts with the language functions in individuals along with the language spectrum (from severe to no impairment). However, future research is needed to determine any directionality.

Keywords: cognitive control, information processing, language performance, non-fluent aphasia

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Authors: Maassoumeh Bemani Naeini

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Studies on interlanguage have long been engaged in describing the phenomenon of variation in SLA. Pursuing the same goal and particularly addressing the role of linguistic features, this study describes the use of Persian morphology in the interlanguage of two adult English-speaking learners of Persian L2. Taking the general approach of a combination of contrastive analysis, error analysis and interlanguage analysis, this study focuses on the identification and prediction of some possible instances of transfer from English L1 to Persian L2 across six elicitation tasks aiming to investigate whether any of contextual features may variably influence the learners’ order of morpheme accuracy in the areas of copula, possessives, articles, demonstratives, plural form, personal pronouns, and genitive cases.  Results describe the existence of task variation in the interlanguage system of Persian L2 learners.

Keywords: English L1, Interlanguage Analysis, Persian L2, SLA variation

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Authors: N. Zarikian

Abstract:

Comparative analysis of the fauna of two families of butterflies (Lepidoptera: Rhopalocera) – Hesperiidae and Nymphalidae were carried out. In general, 122 species of the families are recorded. among these 33 species belong to Hesperiidae and 89 to Nymphalidae. The numbers by countries are as follows: 72 species are found in Syria (including 24 Hesperiidae and 48 Nymphalidae) and 97 in Armenia (26 and 71 species, respectively). Two species of Hesperiidae are reported for Syrian fauna for the first time and one species is newly recorded for Armenia. From the species above mentioned 38 are common both for Syria and Armenia. For estimation of the similarity of faunas studied were used the Jaccard index. By families the index is rather different, consisting for Hesperiidae 0.5151 and for Nymphalidae 0.337.

Keywords: Armenia, fauna, Hesperiidae, Nymphalidae, (Rhopalocera: Lepidoptera), Syria

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Authors: Thidathit Prachanukool, Chaiyaporn Yuksen, Welawat Tienpratarn, Sorravit Savatmongkorngul, Panvilai Tangkulpanich, Chetsadakon Jenpanitpong, Yuranan Phootothum, Malivan Phontabtim, Promphet Nuanprom

Abstract:

Background: Ruptured appendicitis has a high morbidity and mortality and requires immediate surgery. The Alvarado Score is used as a tool to predict the risk of acute appendicitis, but there is no such score for predicting rupture. This study aimed to developed the prediction score to determine the likelihood of ruptured appendicitis in an Asian population. Methods: This study was diagnostic, retrospectively cross-sectional and exploratory model at the Emergency Medicine Department in Ramathibodi Hospital between March 2016 and March 2018. The inclusion criteria were age >15 years and an available pathology report after appendectomy. Clinical factors included gender, age>60 years, right lower quadrant pain, migratory pain, nausea and/or vomiting, diarrhea, anorexia, fever>37.3°C, rebound tenderness, guarding, white blood cell count, polymorphonuclear white blood cells (PMN)>75%, and the pain duration before presentation. The predictive model and prediction score for ruptured appendicitis was developed by multivariable logistic regression analysis. Result: During the study period, 480 patients met the inclusion criteria; of these, 77 (16%) had ruptured appendicitis. Five independent factors were predictive of rupture, age>60 years, fever>37.3°C, guarding, PMN>75%, and duration of pain>24 hours to presentation. A score > 6 increased the likelihood ratio of ruptured appendicitis by 3.88 times. Conclusion: Using the Ramathibodi Welawat Ruptured Appendicitis Score. (RAMA WeRA Score) developed in this study, a score of > 6 was associated with ruptured appendicitis.

Keywords: predictive model, risk score, ruptured appendicitis, emergency room

Procedia PDF Downloads 154