Search results for: carrying cost

Authors: Yousuf Nasser Al Khamisi

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Purpose: This paper presents a Knowledge Transfer (KT) Framework in healthcare sectors by applying a systematic literature review process to the healthcare organizations domain to identify enablers and barriers of KT in Healthcare. Methods: The paper conducted a systematic literature search of peer-reviewed papers that described key elements of KT using four databases (Medline, Cinahl, Scopus, and Proquest) for a 10-year period (1/1/2008–16/10/2017). The results of the literature review were used to build a conceptual framework of KT in healthcare organizations. The author used a systematic review of the literature, as described by Barbara Kitchenham in Procedures for Performing Systematic Reviews. Findings: The paper highlighted the impacts of using Knowledge Management (KM) concept at a healthcare organization in controlling infectious diseases in hospitals, improving family medicine performance and enhancing quality improvement practices. Moreover, it found that good-coding performance is analytically linked with a knowledge sharing network structure rich in brokerage and hierarchy rather than in density. The unavailability or ignored of the latest evidence on more cost-effective or more efficient delivery approaches leads to increase the healthcare costs and may lead to unintended results. Originality: Search procedure produced 12,093 results, of which 3523 were general articles about KM and KT. The titles and abstracts of these articles had been screened to segregate what is related and what is not. 94 articles identified by the researchers for full-text assessment. The total number of eligible articles after removing un-related articles was 22 articles.

Keywords: healthcare organisation, knowledge management, knowledge transfer, KT framework

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Authors: Jin Fan, M. Ala Saadeghvaziri

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Unmanned aerial vehicles (UAVs), also referred to as drones, equipped with various kinds of advanced detecting or surveying systems, are effective and low-cost in data acquisition, data delivery and sharing, which can benefit the building of infrastructures. This paper will give an overview of applications of drones in planning, designing, construction and maintenance of infrastructures. The drone platform, detecting and surveying systems, and post-data processing systems will be introduced, followed by cases with details of the applications. Challenges from different aspects will be addressed. Opportunities of drones in infrastructure include but not limited to the following. Firstly, UAVs equipped with high definition cameras or other detecting equipment are capable of inspecting the hard to reach infrastructure assets. Secondly, UAVs can be used as effective tools to survey and map the landscape to collect necessary information before infrastructure construction. Furthermore, an UAV or multi-UVAs are useful in construction management. UVAs can also be used in collecting roads and building information by taking high-resolution photos for future infrastructure planning. UAVs can be used to provide reliable and dynamic traffic information, which is potentially helpful in building smart cities. The main challenges are: limited flight time, the robustness of signal, post data analyze, multi-drone collaboration, weather condition, distractions to the traffic caused by drones. This paper aims to help owners, designers, engineers and architects to improve the building process of infrastructures for higher efficiency and better performance.

Keywords: bridge, construction, drones, infrastructure, information

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Authors: Ainur Bulasheva

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During the last decade, the dual learning system (DLS) has been actively introduced in various industries in Kazakhstan, including both vocational, post-secondary, and higher education levels. It is a relatively new practice-oriented approach to training qualified personnel in Kazakhstan, officially introduced in 2012. Dual learning was integrated from the German vocational education and training system, combining practical training with part-time work in production and training in an educational institution. The policy of DLS has increasingly focused on decreasing youth unemployment and the shortage of mid-level professionals by providing incentives for employers to involve in this system. By participating directly in the educational process, the enterprise strives to train its future personnel to meet fast-changing market demands. This study examines the effectiveness of DLS from the perspective of employers to understand the motivations of businesses to participate (invest) in this program. The human capital theory of Backer, which predicts that employers will invest in training their workers (in our case, dual students) when they expect that the return on investment will be greater than the cost - acts as a starting point. Further extensionists of this theory will be considered to understand investing intentions of businesses. By comparing perceptions of DLS employers and non-dual practices, this study determines the efficiency of promoted training approach for enterprises in the Kazakhstan agri-food industry.

Keywords: vocational and technical education, dualeducation, human capital theory, argi-food industry

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Authors: Omid Ataei Nia, Karim Salahshoor

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In this paper, a new precise and reliable sensor network methodology is introduced for unit processes and operations using the Constriction Coefficient Particle Swarm Optimization (CPSO) method. CPSO is introduced as a new search engine for optimal sensor network design purposes. Furthermore, a Square Root Unscented Kalman Filter (SRUKF) algorithm is employed as a new data reconciliation technique to enhance the stability and accuracy of the filter. The proposed design procedure incorporates precision, cost, observability, reliability together with importance-of-variables (IVs) as a novel measure in Instrumentation Criteria (IC). To the best of our knowledge, no comprehensive approach has yet been proposed in the literature to take into account the importance of variables in the sensor network design procedure. In this paper, specific weight is assigned to each sensor, measuring a process variable in the sensor network to indicate the importance of that variable over the others to cater to the ultimate sensor network application requirements. A set of distinct scenarios has been conducted to evaluate the performance of the proposed methodology in a simulated Continuous Stirred Tank Reactor (CSTR) as a highly nonlinear process plant benchmark. The obtained results reveal the efficacy of the proposed method, leading to significant improvement in accuracy with respect to other alternative sensor network design approaches and securing the definite allocation of sensors to the most important process variables in sensor network design as a novel achievement.

Keywords: constriction coefficient PSO, importance of variable, MRMSE, reliability, sensor network design, square root unscented Kalman filter

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Authors: Gabrielle Peck, Ryan Hayes

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The use of a phi meter allows for definition of equivalence ratio during a fire test. Previous phi meter designs have used expensive catalysts and had restricted portability due to the large furnace and requirement for pure oxygen. The new design of the phi meter did not require the use of a catalyst. The furnace design was based on the existing micro-scale combustion calorimetry (MCC) furnace and operating conditions based on the secondary oxidizer furnace used in the steady state tube furnace (SSTF). Preliminary tests were conducted to study the effects of varying furnace temperatures on combustion efficiency. The SSTF was chosen to validate the phi meter measurements as it can both pre-set and independently quantify the equivalence ratio during a test. The data were in agreement with the data obtained on the SSTF. It was also validated by a comparison of CO2 yields obtained from the SSTF oxidizer and those obtained by the phi meter. The phi meter designed and constructed in this work was proven to work effectively on a bench-scale. The phi meter was then used to measure the equivalence ratio on a series of large-scale ISO 9705 tests for numerous fire conditions. The materials used were a range of non-homogenous materials such as polyurethane. The measurements corresponded accurately to the data collected, showing the novel design can be used from bench to large-scale tests to measure equivalence ratio. This cheaper, more portable, safer and easier to use phi meter design will enable more widespread use and the ability to quantify fire conditions of tests, allowing for better understanding of flammability and smoke toxicity.

Keywords: phi meter, smoke toxicity, fire condition, ISO9705, novel equipment

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Authors: Sujit Kumar Pradhan, Anil Kumar, Vijay Kumar

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The testing process of the software during the software development time is a crucial step as it makes the software more efficient and dependable. To estimate software’s reliability through the mean value function, many software reliability growth models (SRGMs) were developed under the assumption that operating and testing environments are the same. Practically, it is not true because when the software works in a natural field environment, the reliability of the software differs. This article discussed an SRGM comprising change-point and imperfect debugging in a simulated testing environment. Later on, we extended it in a multi-release direction. Initially, the software was released to the market with few features. According to the market’s demand, the software company upgraded the current version by adding new features as time passed. Therefore, we have proposed a generalized multi-release SRGM where change-point and imperfect debugging concepts have been addressed in a simulated testing environment. The failure-increasing rate concept has been adopted to determine the change point for each software release. Based on nine goodness-of-fit criteria, the proposed model is validated on two real datasets. The results demonstrate that the proposed model fits the datasets better. We have also discussed the optimal release time of the software through a cost model by assuming that the testing and debugging costs are time-dependent.

Keywords: software reliability growth models, non-homogeneous Poisson process, multi-release software, mean value function, change-point, environmental factors

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Authors: Bhanu Pant, Sanjay H. Upadhyay

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Frequently, the upper stage of high-performance launch vehicles utilizes cryogenic tank-submerged pressurization gas bottles with high volume-to-weight efficiency to achieve a direct gain in the satellite payload. Titanium alloys, owing to their high specific strength coupled with excellent compatibility with various fluids, are the materials of choice for these applications. Amongst the Titanium alloys, there are two alloys suitable for cryogenic applications, namely Ti6Al4V-ELI and Ti5Al2.5Sn-ELI. The two-phase alpha-beta alloy Ti6Al4V-ELI is usable up to LOX temperature of 90K, while the single-phase alpha alloy Ti5Al2.5Sn-ELI can be used down to LHe temperature of 4 K. The high-pressure gas bottles submerged in the LH2 (20K) can store more amount of gas in as compared to those submerged in LOX (90K) bottles the same volume. Thus, the use of these alpha alloy gas bottles stored at 20K gives a distinct advantage with respect to the need for a lesser number of gas bottles to store the same amount of high-pressure gas, which in turn leads to a one-to-one advantage in the payload in the satellite. The cost advantage to the tune of 15000$/ kg of weight is saved in the upper stages, and, thereby, the satellite payload gain is expected by this change. However, the processing of alpha Ti5Al2.5Sn-ELI alloy gas bottles poses challenges due to the lower forgeability of the alloy and mode of qualification for the critical severe application environment. The present paper describes the processing and challenges/ solutions during the development of these advanced gas bottles for LH2 (20K) applications.

Keywords: titanium alloys, cryogenic gas bottles, alpha titanium alloy, alpha-beta titanium alloy

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Authors: Sebastian Kohlstädt, Michael Vynnycky, Stephan Goeke, Jan Jäckel, Andreas Gebauer-Teichmann

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This paper summarizes the progress in the latest computational fluid dynamics research towards the modeling in of lost core viability in high-pressure die casting. High-pressure die casting is a process that is widely employed in the automotive and neighboring industries due to its advantages in casting quality and cost efficiency. The degrees of freedom are however somewhat limited as it has been so far difficult to use lost cores in the process. This is right now changing and the deployment of lost cores is considered a future growth potential for high-pressure die casting companies. The use of this technology itself is difficult though. The strength of the core material, as chiefly salt is used, is limited and experiments have shown that the cores will not hold under all circumstances and process designs. For this purpose, the publicly available CFD library foam-extend (OpenFOAM) is used, and two additional fluid models for incompressible and compressible two-phase flow are implemented as fluid solver models into the FSI library. For this purpose, the volume-of-fluid (VOF) methodology is used. The necessity for the fluid-structure interaction (FSI) approach is shown by a simple CFD model geometry. The model is benchmarked against analytical models and experimental data. Sufficient agreement is found with the analytical models and good agreement with the experimental data. An outlook on future developments concludes the paper.

Keywords: CFD, fluid-structure interaction, high-pressure die casting, multiphase flow

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Authors: Luay Alsalmi

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Background: Facial filler is the most common type of cosmetic surgery next to botox. Permanent filler is preferred nowadays due to the low cost brought about by non-recurring injection appointments. However, such fillers pose a higher risk for complications, with even greater adverse effects when the procedure is done using unknown dermal filler injections. AIM: This study aimed to establish an algorithm to categorize and manage patients that receive permanent fillers. Materials and Methods: Twelve participants were presented to the service through emergency or as outpatient from November 2015 to May 2021. Demographics such as age, sex, date of injection, time of onset, and types of complications were collected. After examination, all cases were managed based on an algorithm established. FACE-Q was used to measure overall satisfaction and psychological well-being. Results: The algorithm to diagnose and manage these patients effectively with a high satisfaction rate was established in this study. All participants were non-smoker females with no known medical comorbidities. The algorithm presented determined the treatment plan when faced with complications. Results revealed high appearance-related psychosocial distress was observed prior to surgery, while it significantly dropped after surgery. FACE-Q was able to establish evidence of satisfactory ratings among patients prior to and after surgery. Conclusion: This treatment algorithm can guide the surgeon in formulating a suitable plan with fewer complications and a high satisfaction rate.

Keywords: facial filler, FACE-Q, psycho-social stress, botox, treatment algorithm

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Authors: Iván Rivet, Narges Dialami, Miguel Cervera, Michele Chiumenti

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Process parameters in Additive Manufacturing (AM) play a critical role in the mechanical performance of the final component. In order to find the input configuration that guarantees the optimal performance of the printed part, the process-performance relationship must be found. Fused Filament Fabrication (FFF) is the selected demonstrative AM technology due to its great popularity in the industrial manufacturing world. A material model that considers the different printing patterns present in a FFF part is used. A voxelized mesh is built from the manufacturing toolpaths described in the G-Code file. An Adaptive Mesh Refinement (AMR) based on the octree strategy is used in order to reduce the complexity of the mesh while maintaining its accuracy. High-fidelity and cost-efficient Finite Element (FE) simulations are performed and the influence of key process parameters in the mechanical performance of the component is analyzed. A robust optimization process based on appropriate failure criteria is developed to find the printing direction that leads to the optimal mechanical performance of the component. The Tsai-Wu failure criterion is implemented due to the orthotropy and heterogeneity constitutive nature of FFF components and because of the differences between the strengths in tension and compression. The optimization loop implements a modified version of an Anomaly Detection (AD) algorithm and uses the computed metrics to obtain the optimal printing direction. The developed methodology is verified with a case study on an industrial demonstrator.

Keywords: additive manufacturing, optimization, printing direction, mechanical performance, voxelization

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Authors: Abdollah Sobhani, Hossein Vaseghi-Dodaran

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Proteomics is defined as the study of the component of a cell, tissue and biological fluid. This technique has the potential to identify protein biomarkers of a disease states. In this study which was performed on bovine ovarian follicular cysts (BOFC), eight proteins are over expressed in BOFC that these proteins could be useful biomarkers for BOFC. The difference between serum proteome pattern cows affected by postpartum endometritis with healthy cows revealed that concentrations orosomucoid was decreased in endometritis. The comparison proteome of brucella abortus between laboratory adapted strains and clinical isolates could be useful to better understand this disease and vaccine development. Proteomics experiments identified new proteins and pathways that may be important in future hypothesis-driven studies of glucocorticoid-induced immunosuppression. Understanding the molecular mechanisms of effective parameters on male fertility is essential for obtaining high reproductive efficiency by decreasing cost and time. The investigations on proteome of high fertility spermatozoa indicated that expression of some proteins such as casein kinase 2 (CKII) prime poly peptide and tyrosine kinase in high fertility spermatozoa was higher compared to low fertility spermatozoa. Also, some evidence has indicated that variation in protein types and amounts in seminal fluid regulates fertility indexes in dairy bull. In conclusion, proteomics is a useful technique for discovering drugs, vaccine development, and diagnosis disease by biomarkers and improvement of reproduction efficiency.

Keywords: proteomics, reproduction, biomarker, immunity

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Authors: F. C. Amadi, G. C. Enyi, G. Nasr

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Relative permeabilities are practical factors that are used to correct the single phase Darcy’s law for application to multiphase flow. For effective characterisation of large-scale multiphase flow in hydrocarbon recovery, relative permeability and capillary pressures are used. These parameters are acquired via special core flooding experiments. Special core analysis (SCAL) module of reservoir simulation is applied by engineers for the evaluation of these parameters. But, core flooding experiments in shale core sample are expensive and time consuming before various flow assumptions are achieved for instance Darcy’s law. This makes it imperative for the application of coreflooding simulations in which various analysis of relative permeabilities and capillary pressures of multiphase flow can be carried out efficiently and effectively at a relative pace. This paper presents a Sendra software simulation of core flooding to achieve to relative permeabilities and capillary pressures using different correlations. The approach used in this study was three steps. The first step, the basic petrophysical parameters of Marcellus shale sample such as porosity was determined using laboratory techniques. Secondly, core flooding was simulated for particular scenario of injection using different correlations. And thirdly the best fit correlations for the estimation of relative permeability and capillary pressure was obtained. This research approach saves cost and time and very reliable in the computation of relative permeability and capillary pressures at steady or unsteady state, drainage or imbibition processes in oil and gas industry when compared to other methods.

Keywords: relative permeabilty, porosity, 1-D black oil simulator, capillary pressures

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Authors: Kausar Alam, Mohammad Yazdi, Peiman Zogh, Ramin Motamed

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An earthquake is an unpredictable natural disaster. It induces liquefaction, which causes considerable damage to the structure, life support, and piping systems because of ground settlement. As a result, people are incredibly concerned about how to resolve the situation. Previous researchers adopted different ground improvement techniques to reduce the settlement of the structure during earthquakes. This study evaluates the effectiveness of lowering the water table as a technique to mitigate foundation settlement in liquefiable soil. The performance will be evaluated based on foundation settlement and the reduction of excessive pore water pressure. In this study, a scaled model was prepared based on a full-scale shale table experiment conducted at the University of California, San Diego (UCSD). The model ground consists of three soil layers having a relative density of 55%, 45%, and 90%, respectively. A shallow foundation is seated over an unsaturated crust layer. After preparation of the model ground, the water table was measured to be at 45, 40, and 35 cm (from the bottom). Then, the input motions were applied for 10 seconds, with a peak acceleration of 0.25g and a constant frequency of 2.73 Hz. Based on the experimental results, the effectiveness of the lowering water table in reducing the foundation settlement and excess pore water pressure was evident. The foundation settlement was reduced from 50 mm to 5 mm. In addition, lowering the water table as a mitigation measure is a cost-effective way to decrease liquefaction-induced building settlement.

Keywords: foundation settlement, ground water table, liquefaction, hake table test

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Authors: U. S. Babuga, A. H. Danwanka, A. Garba

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The research was carried out to compare the yield of respondents before and after access to extension services on crop production technologies in the study area. Data were collected from the study area through questionnaires administered to seventy-five randomly selected respondents. Data were analyzed using descriptive statistics, t-test and regression models. The result disclosed that majority (97%) of the respondent attended one form of school or the other. The majority (78.67%) of the respondents had farm size ranging between 1-3 hectares. The majority of the respondent adopt improved variety of crops, plant spacing, herbicide, fertilizer application, land preparation, crop protection, crop processing and storage of farm produce. The result of the t-test between the yield of respondents before and after access to extension services shows that there was a significant (p<0.001) difference in yield before and after access to extension. It also indicated that farm size was significant (p<0.001) while household size, years of farming experience and extension contact were significant at (p<0.005). The major constraint to adoption of crop production technologies were shortage of extension agents, high cost of technology and lack of access to credit facility. The major pre-requisite for the improvement of extension service are employment of more extension agents or workers and adequate training. Adequate agricultural credit to farmers at low interest rates will enhance their adoption of crop production technologies.

Keywords: comparative, analysis, yield, access, extension

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Authors: Rohit Gupta, Ravinder Agarwal

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Surface electromyographic (sEMG) signal has the potential to identify the human activities and intention. This potential is further exploited to control the artificial limbs using the sEMG signal from residual limbs of amputees. The paper deals with the development of multichannel cost efficient sEMG signal interface for research application, along with evaluation of proposed class dependent statistical approach of the feature selection method. The sEMG signal acquisition interface was developed using ADS1298 of Texas Instruments, which is a front-end interface integrated circuit for ECG application. Further, the sEMG signal is recorded from two lower limb muscles for three locomotions namely: Plane Walk (PW), Stair Ascending (SA), Stair Descending (SD). A class dependent statistical approach is proposed for feature selection and also its performance is compared with 12 preexisting feature vectors. To make the study more extensive, performance of five different types of classifiers are compared. The outcome of the current piece of work proves the suitability of the proposed feature selection algorithm for locomotion recognition, as compared to other existing feature vectors. The SVM Classifier is found as the outperformed classifier among compared classifiers with an average recognition accuracy of 97.40%. Feature vector selection emerges as the most dominant factor affecting the classification performance as it holds 51.51% of the total variance in classification accuracy. The results demonstrate the potentials of the developed sEMG signal acquisition interface along with the proposed feature selection algorithm.

Keywords: classifiers, feature selection, locomotion, sEMG

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Authors: Tebogo Emma Makaba, Barnabas Ndlovu Gatsheni

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The cities of Johannesburg and Pretoria both located in the Gauteng province are separated by a distance of 58 km. The traffic queues on the Ben Schoeman freeway which connects these two cities can stretch for almost 1.5 km. Vehicle traffic congestion impacts negatively on the business and the commuter’s quality of life. The goal of this paper is to identify variables that influence the flow of traffic and to design a vehicle traffic prediction model, which will predict the traffic flow pattern in advance. The model will unable motorist to be able to make appropriate travel decisions ahead of time. The data used was collected by Mikro’s Traffic Monitoring (MTM). Multi-Layer perceptron (MLP) was used individually to construct the model and the MLP was also combined with Bagging ensemble method to training the data. The cross—validation method was used for evaluating the models. The results obtained from the techniques were compared using predictive and prediction costs. The cost was computed using combination of the loss matrix and the confusion matrix. The predicted models designed shows that the status of the traffic flow on the freeway can be predicted using the following parameters travel time, average speed, traffic volume and day of month. The implications of this work is that commuters will be able to spend less time travelling on the route and spend time with their families. The logistics industry will save more than twice what they are currently spending.

Keywords: bagging ensemble methods, confusion matrix, multi-layer perceptron, vehicle traffic flow

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Authors: Van-Thanh Ho, Hyoungsoon Lee, Jaiyoung Ryu

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Efficient pressure distribution within soft robotic systems, specifically to the pneumatic artificial muscle (PAM) regions, is essential to minimize energy consumption. This optimization involves adjusting reservoir pressure, pipe diameter, and branching network layout to reduce flow speed and pressure drop while enhancing flow efficiency. The outcome of this optimization is a lightweight power source and reduced mechanical impedance, enabling extended wear and movement. To achieve this, a branching network system was created by combining pipe components and intricate cross-sectional area variations, employing the principle of minimal work based on a complete virtual human exosuit. The results indicate that modifying the cross-sectional area of the branching network, gradually decreasing it, reduces velocity and enhances momentum compensation, preventing flow disturbances at separation regions. These optimized designs achieve uniform velocity distribution (uniformity index > 94%) prior to entering the connection pipe, with a pressure drop of less than 5%. The design must also consider the length-to-diameter ratio for fluid dynamic performance and production cost. This approach can be utilized to create a comprehensive PAM system, integrating well-designed tube networks and complex pneumatic models.

Keywords: pneumatic artificial muscles, pipe networks, pressure drop, compressible turbulent flow, uniformity flow, murray's law

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Authors: S. F. H. Tasfy, N. A. M. Zabidi, M.-S. Shaharun

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Utilization of CO2 as a carbon source to produce valuable chemicals is one of the important ways to reduce the global warming caused by increasing CO2 in the atmosphere. Supported metal catalysts are crucial for the production of clean and renewable fuels and chemicals from the stable CO2 molecules. The catalytic conversion of CO2 into methanol is recently under increased scrutiny as an opportunity to be used as a low-cost carbon source. Therefore, series of the bimetallic Cu/ZnO-based catalyst supported by SBA-15 were synthesized via impregnation technique with different total metal loading and tested in the catalytic hydrogenation of CO2 to methanol. The morphological and textural properties of the synthesized catalysts were determined by transmission electron microscopy (TEM), temperature programmed desorption, reduction, oxidation and pulse chemisorption (TPDRO), and N2-adsorption. The CO2 hydrogenation reaction was performed in microactivity fixed-bed system at 250 °C, 2.25 MPa, and H2/CO2 ratio of 3. Experimental results showed that the catalytic structure and performance was strongly affected by the loading of the active site. Where, the catalytic activity, methanol selectivity as well as the space-time yield increased with increasing the metal loading until it reaches the maximum values at a metal loading of 15 wt% while further addition of metal inhibits the catalytic performance. The higher catalytic activity of 14 % and methanol selectivity of 92 % were obtained over Cu/ZnO-SBA-15 catalyst with total bimetallic loading of 15 wt%. The excellent performance of 15 wt% Cu/ZnO-SBA-15 catalyst is attributed to the presence of well disperses active sites with small particle size, higher Cu surface area, and lower catalytic reducibility.

Keywords: hydrogenation of carbon dioxide, methanol synthesis, metal loading, Cu/ZnO-SBA-15 catalyst

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Authors: Hiba S. Ahmed, Abbas A. Allawi, Riyadh A. Hindi

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Pultruded materials made of fiber-reinforced polymer (FRP) come in a broad range of shapes, such as bars, I-sections, C-sections, and other structural sections. These FRP materials are starting to compete with steel as structural materials because of their great resistance, low self-weight, and cheap maintenance costs-especially in corrosive conditions. This study aimed to evaluate the effectiveness of Glass Fiber Reinforced Polymer (GFRP) of the hybrid columns built by combining (GFRP) profiles with concrete columns because of their low cost and high structural efficiency. To achieve the aims of this study, nine circular columns with a diameter of (150 mm) and a height of (1000mm) were cast using normal concrete with compression strength equal to (35 MPa). The research involved three different types of reinforcement: hybrid circular columns type (IG) with GFRP I-section and 1% of the reinforcement ratio of steel bars, hybrid circular columns type (IS) with steel I-section and 1% of the reinforcement ratio of steel bars, (where the cross-section area of I-section for GFRP and steel was the same), compared with reference column (R) without I-section. To investigate the ultimate capacity, axial and lateral deformation, strain in longitudinal and transverse reinforcement, and failure mode of the circular column under different loading conditions (concentric and eccentric) with eccentricities of 25 mm and 50 mm, respectively. In the second part, an analytical finite element model will be performed using ABAQUS software to validate the experimental results.

Keywords: composite, columns, reinforced concrete, GFRP, axial load

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Authors: Shivaram P. Arunachalam, Mustafa Y. Sir, Andy Boggust, David M. Nestler, Thomas R. Hellmich, Kalyan S. Pasupathy

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Emergency departments (EDs) provide urgent care to patients throughout the day in a complex and chaotic environment. Real-time location systems (RTLS) are increasingly being utilized in healthcare settings, and have shown to improve safety, reduce cost, and increase patient satisfaction. Radio Frequency Identification Device (RFID) data in an ED has been shown to compute variables such as patient-provider contact time, which is associated with patient outcomes such as 30-day hospitalization. These variables can provide avenues for improving ED operational efficiency. A major challenge with ED financial operations is under-coding of critical care services due to physicians’ difficulty reporting accurate times for critical care provided under Current Procedural Terminology (CPT) codes 99291 and 99292. In this work, the authors propose a framework to optimize ED critical care billing using RFID data. RFID estimated physician-patient contact times could accurately quantify direct critical care services which will help model a data-driven approach for ED critical care billing. This paper will describe the framework and provide insights into opportunities to prevent under coding as well as over coding to avoid insurance audits. Future work will focus on data analytics to demonstrate the feasibility of the framework described.

Keywords: critical care billing, CPT codes, emergency department, RFID

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Authors: Aderonke Oluseun Akinwumi, Olusola A. Komolaf

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This paper gives information about the wide array of challenges facing both the electric utilities and consumers in the distribution system in developing countries, using Obafemi Awolowo University, Ile-Ife Nigeria as a case study. It also proffers cost-effective solution through remote monitoring, diagnostic and operation of distribution networks without compromising the system reliability. As utilities move from manned and unintelligent networks to completely unmanned smart grids, switching activities at substations and feeders will be managed and controlled remotely by dedicated systems hence this design. The Substation Remote Diagnostic and Operation Solution (sRDOs) would remotely monitor the load on Medium Voltage (MV) and Low Voltage (LV) feeders as well as distribution transformers and allow the utility disconnect non-paying customers with absolutely no extra resource deployment and without interrupting supply to paying customers. The aftermath of the implementation of this design improved the lifetime of key distribution infrastructure by automatically isolating feeders during overload conditions and more importantly erring consumers. This increased the ratio of revenue generated on electricity bills to total network load.

Keywords: electric utility, consumers, remote monitoring, diagnostic, system reliability, manned and unintelligent networks, unmanned smart grids, switching activities, medium voltage, low voltage, distribution transformer

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Authors: Ramin Rostamkhani, Thurasamy Ramayah

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One of the most important topics of today’s industrial organizations is the challenging issue of supply chain management. In this field, scientists and researchers have published numerous practical articles and models, especially in the last decade. In this research, to our best knowledge, the discussion of data modeling of supply chain management components using well-known statistical distribution functions has been considered. The world of science owns mathematics, and showing the behavior of supply chain data based on the characteristics of statistical distribution functions is innovative research that has not been published anywhere until the moment of doing this research. In an analytical process, describing different aspects of functions including probability density, cumulative distribution, reliability, and failure function can reach the suitable statistical distribution function for each of the components of the supply chain management. It can be applied to predict the behavior data of the relevant component in the future. Providing a model to adapt the best statistical distribution function in the supply chain management components will be a big revolution in the field of the behavior of the supply chain management elements in today's industrial organizations. Demonstrating the final results of the proposed model by introducing the process capability indices before and after implementing it alongside verifying the approach through the relevant assessment as an acceptable verification is a final step. The introduced approach can save the required time and cost to achieve the organizational goals. Moreover, it can increase added value in the organization.

Keywords: analyzing, process capability indices, statistical distribution functions, supply chain management components

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Authors: Gurjeet Singh, M. K. Pradhan, Ajay Verma

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The plastic industry plays very important role in the economy of any country. It is generally among the leading share of the economy of the country. Since metals and their alloys are very rarely available on the earth. So to produce plastic products and components, which finds application in many industrial as well as household consumer products is beneficial. Since 50% plastic products are manufactured by injection moulding process. For production of better quality product, we have to control quality characteristics and performance of the product. The process parameters plays a significant role in production of plastic, hence the control of process parameter is essential. In this paper the effect of the parameters selection on injection moulding process has been described. It is to define suitable parameters in producing plastic product. Selecting the process parameter by trial and error is neither desirable nor acceptable, as it is often tends to increase the cost and time. Hence optimization of processing parameter of injection moulding process is essential. The experiments were designed with Taguchi’s orthogonal array to achieve the result with least number of experiments. Here Plastic material polypropylene is studied. Tensile strength test of material is done on universal testing machine, which is produced by injection moulding machine. By using Taguchi technique with the help of MiniTab-14 software the best value of injection pressure, melt temperature, packing pressure and packing time is obtained. We found that process parameter packing pressure contribute more in production of good tensile plastic product.

Keywords: injection moulding, tensile strength, poly-propylene, Taguchi

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Authors: M. López-Moreno, L. Lugo Avilés, F. Román, J. Lugo Rosas, J. Hernández-Viezcas Jr., Peralta-Videa, J. Gardea-Torresdey

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Degradation of agricultural soils has increased rapidly during the last 20 years due to the indiscriminate use of pesticides and other anthropogenic activities. Currently, there is an urgent need of soil restoration to increase agricultural production. Utilization of sewage sludge or municipal solid waste is an important way to recycle nutrient elements and improve soil quality. With these amendments, nutrient availability in the aqueous phase might be increased and production of healthier crops can be accomplished. This research project aimed to achieve sustainable management of tropical agricultural soils, specifically in Puerto Rico, through the amendment of water treatment plant sludge’s. This practice avoids landfill disposal of sewage sludge and at the same time results cost-effective practice for recycling solid waste residues. Coriander sativum was cultivated in a compost-soil-sludge mixture at different proportions. Results showed that Coriander grown in a mixture of 25% compost+50% Voladora soi+25% sludge had the best growth and development. High chlorophyll content (33.01 ± 0.8) was observed in Coriander plants cultivated in 25% compost+62.5% Coloso soil+ 12.5% sludge compared to plants grown with no sludge (32.59 ± 0.7). ICP-OES analysis showed variations in mineral element contents (macro and micronutrients) in coriander plant grown I soil amended with sludge and compost.

Keywords: compost, Coriandrum sativum, nutrients, waste sludge

Procedia PDF Downloads 382

Authors: Volker Koch, Sigrid Swobodnik, Bernd M. Zunk

Abstract:

The success of companies on globalized markets is significantly influenced by the performance of purchasing departments and, of course, the individuals employed as professional purchasers. Nonetheless, this is generally accepted in practice, in literature as well as in empirical research, only insufficient attention was given to the assessment of this relationship between the personality of professional purchasers and their individual performance. This paper aims to describe the relationship against the background of the 'Big Five Inventory'. Based on the five dimensions of a personality (openness to experience, conscientiousness, extraversion, agreeableness, and neuroticism) a research model was designed. The research model divides the individual performance of professional purchasers into two major dimensions: operational and strategic. The operational dimension consists of the items 'cost', 'quality delivery' and 'flexibility'; the strategic dimension comprises the positions 'innovation', 'supplier satisfaction' as wells as 'purchasing and supply management integration in the organization'. To test the research model, a survey study was performed, and an online questionnaire was sent out to purchasing professionals in Austrian companies. The data collected from 78 responses was used to test the research model applying a group comparison. The comparison points out that there is (i) an influence of the purchasers’ personality on the individual performance of professional purchasers and (ii) a link between purchasers’ personality to a high or a low individual performance of professional purchasers. The findings of this study may help human resource managers during staff recruitment processes to identify the 'right performing personality' for an operational and/or a strategic position in purchasing departments.

Keywords: big five inventory, individual performance, personality, purchasing professionals

Procedia PDF Downloads 152

Authors: Ayobami Solomon Popoola, Victor N. Enujiugha

Abstract:

Production of soy-yogurt by fermentation of soymilk with lactic acid bacteria isolated from soymilk was studied. Soymilk was extracted from dehulled soybean seeds and pasteurized at 95 °C for 15 min. The soymilk was left to naturally ferment (temperature 40 °C; time 8 h) and lactic acid bacteria were isolated, screened and selected for yogurt production. Freshly prepared soymilk was pasteurized (95 °C, 15 min), inoculated with the lactic acid bacteria isolated (3% w/v starter culture) and incubated at 40 °C for 8 h. The yogurt produced was stored at 4 °C. Investigations were carried out with the aim of improving the sensory qualities and acceptability of soy yogurt. Commercial yogurt was used as a control. The percentage of soymilk inoculated was 70% of the broth. Soy-yoghurt samples produced were subsequently subjected to biochemical and microbiological assays which included total viable counts of fresh milk and soy-based yoghurt; proximate composition of functional soy-based yoghurt fermented with Lactobacillus plantarum; changes in pH, Titratable acidity, and lactic acid bacteria during a 14 day period of storage; as well as morphological and biochemical characteristics of lactic acid bacteria isolated. The results demonstrated that using Lactobacillus plantarum to inoculate soy milk for yogurt production takes about 8 h. The overall acceptability of the soy-based yogurt produced was not significantly different from that of the control sample. The use of isolate from soymilk had the added advantage of reducing the cost of yogurt starter culture, thereby making soy-yogurt, a good source of much desired good quality protein. However, more experiments are needed to improve the sensory qualities such as beany or astringent flavor and color.

Keywords: soy, soymilk, yoghurt, starter culture

Procedia PDF Downloads 235

Authors: Umar D. M., Aminu A. M., Izaddeen K. Y.

Abstract:

Deployments of mini macrocell base stations also referred to as femtocells, improve the quality of service of indoor and outdoor users. Nevertheless, mobility management remains a key issue with regards to their deployment. This paper is leaned towards this issue, with an in-depth focus on the most important aspect of mobility management -handover. In handover management, making a handover decision in the LTE two-tier macrocell femtocell network is a crucial research area. Decision algorithms in this research are classified and comparatively analyzed according to received signal strength, user equipment speed, cost function, and interference. However, it was observed that most of the discussed decision algorithms fail to consider cell selection with hybrid access policy in a single macrocell multiple femtocell scenario, another observation was a majority of these algorithms lack the incorporation of user equipment residence parameter. Not including this parameter boosts the number of unnecessary handover occurrence. To deal with these issues, a sophisticated handover decision algorithm is proposed. The proposed algorithm considers the user’s velocity, received signal strength, residence time, as well as the femtocell base station’s access policy. Simulation results have shown that the proposed algorithm reduces the number of unnecessary handovers when compared to conventional received signal strength-based handover decision algorithm.

Keywords: user-equipment, radio signal service, long term evolution, mobility management, handoff

Procedia PDF Downloads 108

Authors: J. S. Dhillon, K. K. Dhaliwal

Abstract:

In almost all the digital filtering applications the digital infinite impulse response (IIR) filters are preferred over finite impulse response (FIR) filters because they provide much better performance, less computational cost and have smaller memory requirements for similar magnitude specifications. However, the digital IIR filters are generally multimodal with respect to the filter coefficients and therefore, reliable methods that can provide global optimal solutions are required. The artificial bee colony (ABC) algorithm is one such recently introduced meta-heuristic optimization algorithm. But in some cases it shows insufficiency while searching the solution space resulting in a weak exchange of information and hence is not able to return better solutions. To overcome this deficiency, the opposition based learning strategy is incorporated in ABC and hence a modified version called oppositional artificial bee colony (OABC) algorithm is proposed in this paper. Duplication of members is avoided during the run which also augments the exploration ability. The developed algorithm is then applied for the design of optimal and stable digital IIR filter structure where design of low-pass (LP) and high-pass (HP) filters is carried out. Fuzzy theory is applied to achieve maximize satisfaction of minimum magnitude error and stability constraints. To check the effectiveness of OABC, the results are compared with some well established filter design techniques and it is observed that in most cases OABC returns better or atleast comparable results.

Keywords: digital infinite impulse response filter, artificial bee colony optimization, opposition based learning, digital filter design, multi-parameter optimization

Procedia PDF Downloads 454

Authors: Nishant Rodrigues, Nicole Spanedda, Chilukuri K. Mohan, Arindam Chakraborty

Abstract:

A crucial objective in quantum chemistry is the computation of the energy levels of chemical systems. This task requires electron-repulsion integrals as inputs, and the steep computational cost of evaluating these integrals poses a major numerical challenge in efficient implementation of quantum chemical software. This work presents a moment-based machine-learning approach for the efficient evaluation of electron-repulsion integrals. These integrals were approximated using linear combinations of a small number of moments. Machine learning algorithms were applied to estimate the coefficients in the linear combination. A random forest approach was used to identify promising features using a recursive feature elimination approach, which performed best for learning the sign of each coefficient but not the magnitude. A neural network with two hidden layers were then used to learn the coefficient magnitudes along with an iterative feature masking approach to perform input vector compression, identifying a small subset of orbitals whose coefficients are sufficient for the quantum state energy computation. Finally, a small ensemble of neural networks (with a median rule for decision fusion) was shown to improve results when compared to a single network.

Keywords: quantum energy calculations, atomic orbitals, electron-repulsion integrals, ensemble machine learning, random forests, neural networks, feature extraction

Procedia PDF Downloads 85

Authors: M. Shahadat Hossain

Abstract:

People experiencing economic disadvantages have limited access to justice system. Employment status is a key indicator of economic disadvantage. There is a link between employment status and vulnerability to legal problems. This paper addresses the obstacles unemployed people experience to secure justice in Australia. This paper further explores exiting services for economically disadvantaged people to secure justice where these unemployment people can get access. It reveals that unemployed people are vulnerable to multifaced crime and violence. Due to high cost of legal services, these unemployed people are unable to afford legal services to access justice. They are often found higher levels of nonactions in terms of access to justice also due to lack of their initiatives. This paper further reveals that legal aid commissions are state and territory statutory agencies in Australia which provide free legal information, advice, duty lawyers, and legal representation services. Community legal centres are independent, non-profit government organizations with a focus of early advice, problem solving, and working with other agencies to address connected, financial, and health problems. Moreover, the private profession helps people who cannot afford to pay for a lawyer in several ways. But there are problems of shortage of funding for these legal services and making available to economically disadvantaged people. However, this paper argues that people experiencing long-term unemployment face barriers to secure justice due to their economic disadvantages. It further argues that services available for them to access to justice is inadequate.

Keywords: economic disadvantages, unemployment, access to justice, Australia

Procedia PDF Downloads 115