Search results for: performance and quality

Authors: Janeth Chepkemoi, Richard Onwonga, Noel Templer, Elkana Kipkoech, Angela Gitau

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Conventional agriculture is one of the leading causes of land degradation, threatening the sustainability of food production. Organic farming promotes practices that have the potential of feeding the world while also promoting ecological health. A study was therefore carried out with the aim of conceptualizing how such farming systems are contributing to ecological health in Trans Nzoia County. 71 farmers were interviewed and data was collected on parameters such as land preparation, agroforestry, soil fertility management, soil and water conservation, and pests and diseases. A soil sample was also collected from each farm for laboratory analysis. Data collected were analyzed using Microsoft Excel and SPSS version 21. Results showed that 66% of the respondents practiced organic farming whereas 34% practiced conventional farming. Intercropping and crop rotations were the most common cropping systems and the most preferred land preparation tools among both organic and conventional farmers were tractors and hand hoes. Organic farms fared better in agroforestry, organic soil amendments, land and water conservation, and soil chemical properties. Pests and disease, however, affected organic farms more than conventional. The average nitrogen (%), K (Cmol/ kg and P (ppm) of organic soils were 0.26, 0.7 and 26.18 respectively, conventional soils were 0.21, 0.66 and 22.85. Soil organic carbon content of organic farms averaged a higher percentage of 2.07% as compared to 1.91 for the conventional. In conclusion, most farmers in Trans Nzoia County had transitioned into ecologically friendly farming practices that improved the quality and health of the soil and therefore promoted its sustainability.

Keywords: organic farming, conventional farming, ecological health, soil health

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Authors: Liang-Hsuan Chen, Sheng-Shing Nien

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This study aims to develop approaches to formulate intuitionistic fuzzy regression (IFR) models for many decision-making applications in the fuzzy environments using intuitionistic fuzzy observations. Intuitionistic fuzzy numbers (IFNs) are used to characterize the fuzzy input and output variables in the IFR formulation processes. A mathematical programming problem (MPP) is built up to optimally determine the IFR parameters. Each parameter in the MPP is defined as a couple of alternative numerical variables with opposite signs, and an intuitionistic fuzzy error term is added to the MPP to characterize the uncertainty of the model. The IFR model is formulated based on the distance measure to minimize the total distance errors between estimated and observed intuitionistic fuzzy responses in the MPP resolution processes. The proposed approaches are simple/efficient in the formulation/resolution processes, in which the sign of parameters can be determined so that the problem to predetermine the sign of parameters is avoided. Furthermore, the proposed approach has the advantage that the spread of the predicted IFN response will not be over-increased, since the parameters in the established IFR model are crisp. The performance of the obtained models is evaluated and compared with the existing approaches.

Keywords: fuzzy sets, intuitionistic fuzzy number, intuitionistic fuzzy regression, mathematical programming method

Procedia PDF Downloads 142

Authors: Jamileh Darsareh, Mohammad Nikafrooz

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Some teachers and e-content producers, based on their experiences, try to produce educational videos using screen recording software. There are many challenges that they may encounter while producing screen-recorded videos. These are in the domains of technical and pedagogical challenges like designing the roadmap, preparing the screen, setting the recording software and recording the screen, editing, etc. This study is a descriptive study and tries to present some procedures for producing acceptable and well-made videos. These procedures are presented in the form of an algorithm for producing screen-recorded video. This algorithm presents the main producing phases, including design, pre-production, production, post-production, and distribution. These phases consist of some steps which are supported by several technical and pedagogical considerations. Following these phases and steps according to the suggested order helps the producers to produce their intended and desired video by saving time and also facing fewer technical problems. It is expected that by using this algorithm, e-content producers and teachers gain better performance in producing educational videos.

Keywords: e-content producing algorithm, screen-recorded videos, screen recording software, technical and pedagogical considerations

Procedia PDF Downloads 200

Authors: Valentina Colonnello, Paolo Maria Russo

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Living kidney donation requires psychological evaluation and ongoing follow-up. A crucial aspect of this evaluation is assessing the social functioning of donors after donation. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we conducted a review of quantitative and qualitative studies on the psychological assessment of living kidney donors' social functioning. The majority of quantitative studies examining the long-term social health post-donation have primarily utilized the Short Form Health Survey (SF) and the World Health Organization Quality of Life-BREF (WHOQoL-BREF) questionnaires. These studies have indicated that donors' social functioning and relationships either remained stable post-donation or returned to pre-donation levels. In some instances, donors' social functioning even surpassed that of the general population. Qualitative studies, conducted through interviews and focus groups, have revealed donors' experiences and emotional concerns that are often overlooked in quantitative analyses. Specifically, qualitative analysis has identified two main themes: "connecting to others" and "acknowledgment and social support." Our review highlights that the majority of published quantitative studies on donors have employed measures of social functioning that may not fully capture donors' experiences and needs. It underscores the importance of further investigation in quantitative studies to assess donors' actual social health and psychological needs accurately. Overall, this review provides valuable insights into specific constructs that warrant deeper exploration in quantitative studies concerning the assessment of donors' social health and psychological well-being.

Keywords: reported outcomes, personalized medicine, individual differences, emotions, psychological assessment

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Authors: Maha Hammami, Olfa Benouda Sioud

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This study investigates the reliability of management earnings forecasts with reference to these two ingredients: verifiability and neutrality. Specifically, we examine the biasedness (or accuracy) of management earnings forecasts and company specific characteristics that can be associated with accuracy. Based on sample of 102 IPO prospectuses published for admission on NYSE Euronext Paris from 2002 to 2010, we found that these forecasts are on average optimistic and two of the five test variables, earnings variability and financial leverage are significant in explaining ex post bias. Acknowledging the possibility that the bias is the result of the managers’ forecasting behavior, we then examine whether managers decide to under-predict, over-predict or forecast accurately for self-serving purposes. Explicitly, we examine the role of financial distress, operating performance, ownership by insiders and the economy state in influencing managers’ forecasting preferences. We find that managers of distressed firms seem to over-predict future earnings. We also find that when managers are given more stock options, they tend to under-predict future earnings. Finally, we conclude that the management earnings forecasts are affected by an intentional bias due to managers’ forecasting preferences.

Keywords: intentional bias, management earnings forecasts, neutrality, verifiability

Procedia PDF Downloads 238

Authors: Anand Kishore Kola, G. Uday Bhaskar Babu, Kotturi Ajay Kumar

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The modern dynamic systems used in industries are complex in nature and hence the fractional order controllers have been contemplated as a fresh approach to control system design that takes the complexity into account. Traditional integer order controllers use integer derivatives and integrals to control systems, whereas fractional order controllers use fractional derivatives and integrals to regulate memory and non-local behavior. This study provides a method based on the maximumsensitivity (Ms) methodology to discover all resilient fractional filter Internal Model Control - proportional integral derivative (IMC-PID) controllers that stabilize the closed-loop system and deliver the highest performance for a time delay system with a Smith predictor configuration. Additionally, it helps to enhance the range of PID controllers that are used to stabilize the system. This study also evaluates the effectiveness of the suggested controller approach for minimum phase system in comparison to those currently in use which are based on Integral of Absolute Error (IAE) and Total Variation (TV).

Keywords: modern dynamic systems, fractional order controllers, maximum-sensitivity, IMC-PID controllers, Smith predictor, IAE and TV

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Authors: A. Peyvan, D. Li, J. Komperda, F. Mashayek

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Turbulence can be observed in a variety fluid motions in nature and industrial applications. Recent investment in high-speed aircraft and propulsion systems has revitalized fundamental research on turbulent flows. In these systems, capturing chaotic fluid structures with different length and time scales is accomplished through the Direct Numerical Simulation (DNS) approach since it accurately simulates flows down to smallest dissipative scales, i.e., Kolmogorov’s scales. The discontinuous spectral element method (DSEM) is a high-order technique that uses spectral functions for approximating the solution. The DSEM code has been developed by our research group over the course of more than two decades. Recently, the code has been improved to run large cases in the order of billions of solution points. Running big simulations requires a considerable amount of RAM. Therefore, the DSEM code must be highly parallelized and able to start on multiple computational nodes on an HPC cluster with distributed memory. However, some pre-processing procedures, such as determining global element information, creating a global face list, and assigning global partitioning and element connection information of the domain for communication, must be done sequentially with a single processing core. A separate code has been written to perform the pre-processing procedures on a local machine. It stores the minimum amount of information that is required for the DSEM code to start in parallel, extracted from the mesh file, into text files (pre-files). It packs integer type information with a Stream Binary format in pre-files that are portable between machines. The files are generated to ensure fast read performance on different file-systems, such as Lustre and General Parallel File System (GPFS). A new subroutine has been added to the DSEM code to read the startup files using parallel MPI I/O, for Lustre, in a way that each MPI rank acquires its information from the file in parallel. In case of GPFS, in each computational node, a single MPI rank reads data from the file, which is specifically generated for the computational node, and send them to other ranks on the node using point to point non-blocking MPI communication. This way, communication takes place locally on each node and signals do not cross the switches of the cluster. The read subroutine has been tested on Argonne National Laboratory’s Mira (GPFS), National Center for Supercomputing Application’s Blue Waters (Lustre), San Diego Supercomputer Center’s Comet (Lustre), and UIC’s Extreme (Lustre). The tests showed that one file per node is suited for GPFS and parallel MPI I/O is the best choice for Lustre file system. The DSEM code relies on heavily optimized linear algebra operation such as matrix-matrix and matrix-vector products for calculation of the solution in every time-step. For this, the code can either make use of its matrix math library, BLAS, Intel MKL, or ATLAS. This fact and the discontinuous nature of the method makes the DSEM code run efficiently in parallel. The results of weak scaling tests performed on Blue Waters showed a scalable and efficient performance of the code in parallel computing.

Keywords: computational fluid dynamics, direct numerical simulation, spectral element, turbulent flow

Procedia PDF Downloads 137

Authors: Tae Gwan Kim, Hyun Kyu Cho, Young Hoon Lee, Young Chul Park

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Foam monitors are devices that are installed on cargo tank decks to suppress cargo area fires in oil tankers or hazardous chemical ship cargo ships. In general, the main design parameter of the foam monitor is the distance of the projection through the foam monitor. In this study, the relationship between flow characteristics and projection distance, depending on the shape was examined. Numerical techniques for fluid analysis of foam monitors have been developed for prediction. The flow pattern of the fluid varies depending on the shape of the flow path of the foam monitor, as the flow losses affecting projection distance were calculated through numerical analysis. The basic shape of the foam monitor was an L shape designed by N Company. The modified model increased the length of the flow path and used the S shape model. The calculation result shows that the L shape, which is the basic shape, has a problem that the force is directed to one side and the vibration and noise are generated there. In order to solve the problem, S-shaped model, which is a change model, was used. As a result, the problem is solved, and the projection distance from the nozzle is improved.

Keywords: CFD, foam monitor, projection distance, moment

Procedia PDF Downloads 346

Authors: Mahfoodh Saleh Al Sabbagh, Amitabh Mishra, Anwar Al Sheyadi

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A tremendous transformation is taking place in the state of education in Sultanate of Oman. The vision 2040 for Higher Education focuses on both academic and technical sides of education aims at improving the quality of education as per higher international standards with emphasis on learning and innovation, creativity and scientific research. The objective is to achieve a proficient education system that keeps abreast of the recent development, the essentials of sustainable development and enhancing the national identity. Higher Education Institutes have contributed immensely to the growth of education in Oman, in this context; Business Organization represents the most complex social structure known today due to its dynamic nature. Employees are considered as one of the dynamic resources of the organization and through their commitment and involvement organization becomes competitive. Organization Culture can be promoted to facilitate the achievement of job satisfaction and employees commitment. The purpose of the research is to explore the impact of Higher Educational Institutions Culture on employee satisfaction, and commitment. Based on primary data, the study was conducted in Higher Education Institutions in the Sultanate of Oman. Data was collected through questionnaire consisting of 60 questions related to culture, satisfaction, and commitment. The sample consisted of 330 employees of leading Higher Education Institutes in the Sultanate of Oman. Structural Equation Modeling was carried out on the data through SPSS and AMOS. Results indicate that culture of organization is significantly related with employees’ satisfaction and commitment both in direct and indirect ways. Significant theoretical and practical implications are driven from the outcomes of the study.

Keywords: organization culture, employee satisfaction and commitment, higher education, Sultanate of Oman

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Authors: Boualem Chetti, Samir Zahaf

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This paper presents the steady-state performance analysis of a four-lobe journal bearing lubricated with a couple stress fluids operating in the turbulent regime, following Constantinescu’s turbulent lubrication theory. The modified Reynolds equation is solved numerically using the finite difference method taking into consideration the effects of the turbulence and the couple stress. In this analysis, the steady-state parameters in terms of the attitude angle, load carrying capacity, side leakage and friction coefficient are determined at various values of eccentricities ratio. The computed results show that the turbulence increases the load carrying capacity, the attitude angle and the friction coefficient for a journal bearing lubricated with a Newtonian or a couple stress fluids. It is found that the turbulence has strongly influence on the steady-state performances of the four-lobe journal bearing lubricated with Newtonian fluids or a couple stress fluids.

Keywords: Four-lobe journal bearings, static characteristics, couple-stress fluids, turbulent flow

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Authors: Kamellia Reshadi, Pranav Ragji, Theodoros Soldatos

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Recent advancements in cloud computing and storage, along with rapid progress in artificial intelligence (AI), have transformed approaches to developing efficient, scalable applications. However, integrating AI with cloud computing poses challenges as these fields are often disjointed, and many advancements remain difficult to access, obscured in complex documentation or scattered across research reports. For this reason, we share experiences from prototype projects combining these technologies. Specifically, we focus on Google Cloud Platform (GCP) functionalities and describe vision and speech activities applied to labeling, subtitling, and urban traffic flow tasks. We describe challenges, pricing, architecture, and other key features, considering the goal of real-time performance. We hope our demonstrations provide not only essential guidelines for using these functionalities but also enable more similar approaches.

Keywords: artificial intelligence, cloud computing, real-time applications, case studies, knowledge management, research and development, text labeling, video annotation, urban traffic analysis, public safety, prototyping, Google Cloud Platform

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Authors: S. M. Samkeyat Shohan

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This study is mainly focused on the determination and analysis of the photolysis rate of atmospheric, specifically tropospheric, ozone as function of cloud properties through-out the year 2007. The observational basis for ozone concentrations and cloud properties are the measurement data set of the Global Ozone Monitoring Experiment-2 (GOME-2) sensor on board the polar orbiting Metop-A satellite. Two different spectral ranges are used; ozone total column are calculated from the wavelength window 325 – 335 nm, while cloud properties, such as cloud top height (CTH) and cloud optical thick-ness (COT) are derived from the absorption band of molecular oxygen centered at 761 nm. Cloud fraction (CF) is derived from measurements in the ultraviolet, visible and near-infrared range of GOME-2. First, ozone concentrations above clouds are derived from ozone total columns, subtracting the contribution of stratospheric ozone and filtering those satellite measurements which have thin and low clouds. Then, the values of ozone photolysis derived from observations are compared with theoretical modeled results, in the latitudinal belt 5˚N-5˚S and 20˚N - 20˚S, as function of CF and COT. In general, good agreement is found between the data and the model, proving both the quality of the space-borne ozone and cloud properties as well as the modeling theory of ozone photolysis rate. The found discrepancies can, however, amount to approximately 15%. Latitudinal seasonal changes of photolysis rate of ozone are found to be negatively correlated to changes in upper-tropospheric ozone concentrations only in the autumn and summer months within the northern and southern tropical belts, respectively. This fact points to the entangled roles of temperature and nitrogen oxides in the ozone production, which are superimposed on its sole photolysis induced by thick and high clouds in the tropics.

Keywords: cloud properties, photolysis rate, stratospheric ozone, tropospheric ozone

Procedia PDF Downloads 215

Authors: Gladys Abiemwense Ibhaze, Anthony Henry Ekeocha, Adebowale Noah Fajemisin, Tope Oke, Caroline Tosin Alade,

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The study was conducted to evaluate the silage quality and acceptability of ensiled avocado pear skin (APS) with cassava peel (CSP) and brewers’ grain (BG) using eighteen (18) West African Dwarf goats with an average weight of 7.0±1.5 kg. The experimental diets; 1) 50% cassava peel+ 50% brewers’ grain, 2) 50% brewers’ grain+ 50% avocado pear skin, 3) 50% cassava peel +25% brewers’ grain+ 25% avocado pear skin were ensiled for 21 days. The experimental design was a completely randomized design (CRD). The chemical composition of the diets was investigated. The acceptability of the diets was evaluated for twelve (12) days. Results obtained showed that the crude protein content ranged from 12.18 – 12.47%, crude fiber (15.99-22.67%). Results obtained showed that diet 1 had the least pH value (4.0), followed by diet 3 (4.5) and diet 2 (5.2). All diets were firm in texture and maintained their initial color. The temperature ranged from 27-29 ⁰C with diet 2 having the highest temperature of 29 ⁰C. Acceptability of experimental diets varied (p < 0.05) significantly. Dry matter intake ranged from (426.22-686.73g/day) with animals on a diet one recording the highest dry matter intake. The coefficient of preference and percentage preference, also differed (p <0.05) significantly among the diets. Diet 1 had a coefficient of preference greater than unity. However, this was not significantly (p>0.05) different from diet two but differed from diet 3. Conclusively, APS could be included in goats’ diets in the absence of CSP during feed scarcity provided a rich source of protein is available.

Keywords: avocado pear skin, Brewers' grain, Cassava peel, preference

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Authors: Jae-Yong Lee, Gyu-Hyun Bae, Yun-Soo Chung, Dae-Sub Kim, Jae-Sung Bae

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In general, fabric is heat-treated using a stenter machine in order to dry and fix its shape. It is important to shape before the heat treatment because it is difficult to revert back once the fabric is formed. To produce the product of right shape, camera type weft straightener has been applied recently to capture and process fabric images quickly. It is more powerful in determining the final textile quality rather than photo-sensor. Positioning in front of a stenter machine, weft straightener helps to spread fabric evenly and control the angle between warp and weft constantly as right angle by handling skew and bow rollers. To process this tricky procedure, the structural analysis should be carried out in advance, based on which, its control technology can be drawn. A structural analysis is to figure out the specific contact/slippage characteristics between fabric and roller. We already examined the applicability of camera type weft straightener to plain weave fabric and found its possibility and the specific working condition of machine and rollers. In this research, we aimed to explore another applicability of camera type weft straightener. Namely, we tried to figure out camera type weft straightener can be used for fabrics. To find out the optimum condition, we increased the number of rollers. The analysis is done by ANSYS software using Finite Element Analysis method. The control function is demonstrated by experiment. In conclusion, the structural analysis of weft straightener is done to identify a specific characteristic between roller and fabrics. The control of skew and bow roller is done to decrease the error of the angle between warp and weft. Finally, it is proved that camera type straightener can also be used for the special fabrics.

Keywords: camera type weft straightener, structure analysis, control, skew and bow roller

Procedia PDF Downloads 293

Authors: Qasem Drmosh, Zain Yamai, Amar Mohamedkhair, Abdulmajid Hendi

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In recent years, there has been a growing interest in the reduction of the nitrogen oxides NOx (NO2, NO) gases resulting from automotive or combustion emissions. Recently, metal additives in nanometer dimension onto the surface of SnO2 nanorods, nanowires and nanotubes sensitizer to further increase the sensor response have been used. In contrast, there is a lack study focused on modifying the surface of SnO2 thin films by nanoparticles. The challenge in case of thin films is how to fabricate these nanoparticles on the surfaces in cost-effective method, high purity as well as without hampering electrical and topographical properties. Here in this report, a simple and facile strategy has been demonstrated to acquire high sensitive and fast response NO2 gas sensor. Structural, electrical, morphological, optical, and compositional properties of the fabricated sensors were investigated through different analytical technique including X-ray diffraction (XRD), Field emission scanning emission microscope (FESEM) and X-ray photoelectron spectroscopy (XPS). The sensing performance of the prepared sensors are studied at different temperatures for various concentrations of NO2 and compared with pristine SnO2 film.

Keywords: NO2 sensor, SnO2, sputtering, thin films

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Authors: E. Behmanesh, J. Pannek

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Logistics network design is known as one of the strategic decision problems. As these kinds of problems belong to the category of NP-hard problems, traditional ways are failed to find an optimal solution in short time. In this study, we attempt to involve reverse flow through an integrated design of forward/reverse supply chain network that formulated into a mixed integer linear programming. This Integrated, multi-stages model is enriched by three different delivery path which makes the problem more complex. To tackle with such an NP-hard problem a revised random path direct encoding method based memetic algorithm is considered as the solution methodology. Each algorithm has some parameters that need to be investigate to reveal the best performance. In this regard, Taguchi method is adapted to identify the optimum operating condition of the proposed memetic algorithm to improve the results. In this study, four factors namely, population size, crossover rate, local search iteration and a number of iteration are considered. Analyzing the parameters and improvement in results are the outlook of this research.

Keywords: integrated logistics network, flexible path, memetic algorithm, Taguchi method

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Authors: E. Asadollahi-Yazdi, J. Gardan, P. Lafon

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Nowadays, manufactures are encountered with production of different version of products due to quality, cost and time constraints. On the other hand, Additive Manufacturing (AM) as a production method based on CAD model disrupts the design and manufacturing cycle with new parameters. To consider these issues, the researchers utilized Design For Manufacturing (DFM) approach for AM but until now there is no integrated approach for design and manufacturing of product through the AM. So, this paper aims to provide a general methodology for managing the different production issues, as well as, support the interoperability with AM process and different Product Life Cycle Management tools. The problem is that the models of System Engineering which is used for managing complex systems cannot support the product evolution and its impact on the product life cycle. Therefore, it seems necessary to provide a general methodology for managing the product’s diversities which is created by using AM. This methodology must consider manufacture and assembly during product design as early as possible in the design stage. The latest approach of DFM, as a methodology to analyze the system comprehensively, integrates manufacturing constraints in the numerical model in upstream. So, DFM for AM is used to import the characteristics of AM into the design and manufacturing process of a hybrid product to manage the criteria coming from AM. Also, the research presents an integrated design method in order to take into account the knowledge of layers manufacturing technologies. For this purpose, the interface model based on the skin and skeleton concepts is provided, the usage and manufacturing skins are used to show the functional surface of the product. Also, the material flow and link between the skins are demonstrated by usage and manufacturing skeletons. Therefore, this integrated approach is a helpful methodology for designer and manufacturer in different decisions like material and process selection as well as, evaluation of product manufacturability.

Keywords: additive manufacturing, 3D printing, design for manufacturing, integrated design, interoperability

Procedia PDF Downloads 319

Authors: B. Hekner, J. Myalski, P. Wrzesniowski

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This study presents aluminum matrix composites reinforced by glassy carbon (GC) and titanium (Ti). In the first step, the heterophase (GC+Ti), spatial form (similar to skeleton) of reinforcement was obtained via own method. The polyurethane foam (with spatial, open-cells structure) covered by suspension of Ti particles in phenolic resin was pyrolyzed. In the second step, the prepared heterogeneous foams were infiltrated by aluminium alloy. The manufactured composites are designated to industrial application, especially as a material used in tribological field. From this point of view, the glassy carbon was applied to stabilise a coefficient of friction on the required value 0.6 and reduce wear. Furthermore, the wear can be limited due to titanium phase application, which reveals high mechanical properties. Moreover, fabrication of thin titanium layer on the carbon skeleton leads to reduce contact between aluminium alloy and carbon and thus aluminium carbide phase creation. However, the main modification involves the manufacturing of reinforcement in the form of 3D, skeleton foam. This kind on reinforcement reveals a few important advantages compared to classical form of reinforcement-particles: possibility to control homogeneity of reinforcement phase in composite material; low-advanced technique of composite manufacturing- infiltration; possibility to application the reinforcement only in required places of material; strict control of phase composition; High quality of bonding between components of material. This research is founded by NCN in the UMO-2016/23/N/ST8/00994.

Keywords: metal matrix composites, MMC, glassy carbon, heterophase composites, tribological application

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Authors: Hatem Diaf, Patrice Melinon, Antonio Pereira, Bernard Moine, Nicholas Blanchard, Florent Bourquard, Florence Garrelie, Christophe Donnet

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Glassy carbon exhibits excellent biological compatibility with live tissues meaning it has high potential for applications in life science. Moreover, glassy carbon has interesting properties including 'high temperature resistance', hardness, low density, low electrical resistance, low friction, and low thermal resistance. The structure of glassy carbon has long been a subject of debate. It is now admitted that glassy carbon is 100% sp2. This term is a little bit confusing as long sp2 hybridization defined from quantum chemistry is related to both properties: threefold configuration and pi bonding (parallel pz orbitals). Using plasma laser deposition of carbon clusters combined with pulsed nano/femto laser annealing, we are able to synthesize thin films of glassy carbon of good quality (probed by G band/ D disorder band ratio in Raman spectroscopy) without thermal post annealing. A careful inspecting of Raman signal, plasmon losses and structure performed by HRTEM (High Resolution Transmission Electron Microscopy) reveals that both properties (threefold and pi orbitals) cannot coexist together. The structure of the films is compared to models including schwarzites based from negatively curved surfaces at the opposite of onions or fullerene-like structures with positively curved surfaces. This study shows that a huge collection of porous carbon named vitreous carbon with different structures can coexist.

Keywords: glassy carbon, cluster deposition, coating, electronic structure

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Authors: Fedili Benamar, Beloulou Mohamed Lamine, Ouahes Hassane, Ghattas Samir

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 Background and aims: Peripheral regional anesthesia has been integrated into most analgesia protocols for total knee arthroplasty which considered among the most painful surgeries with a huge potential for chronicization. The adductor canal block (ACB) has gained popularity. Similarly, the IPACK block has been described to provide analgesia of the posterior knee capsule. This study aimed to evaluate the analgesic efficacy of this block in patients undergoing primary PTG. Methods: 90 patients were randomized to receive either an IPACK, an anterior sciatic block, or a sham block (30 patients in each group + multimodal analgesia and a catheter in the KCA adductor canal). GROUP 1 KCA GROUP 2 KCA+BSA GROUP 3 KCA+IPACK The analgesic blocks were done under echo-guidance preoperatively respecting the safety rules, the dose administered was 20 cc of ropivacaine 0.25% was used. We were to assess posterior knee pain 6 hours after surgery. Other endpoints included quality of recovery after surgery, pain scores, opioid requirements (PCA morphine)(EPI info 7.2 analysis). Results: -groups were matched -A predominance of women (4F/1H). -average age: 68 +/-7 years -the average BMI =31.75 kg/m2 +/- 4. -70% of patients ASA2 ,20% ASA3. -The average duration of the intervention: 89 +/- 19 minutes. -Morphine consumption (PCA) significantly higher in group 1 (16mg) & group 2 (8mg) group 3 (4mg) - The groups were matched . -There was a correlation between the use of the ipack block and postoperative pain Conclusions :In a multimodal analgesic protocol, the addition of IPACK block decreased pain scores and morphine consumption ,

Keywords: regional anesthesia, analgesia, total knee arthroplasty, the adductor canal block (acb), the ipack block, pain

Procedia PDF Downloads 79

Authors: Abdulkader Helwan

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Rheumatoid joint inflammation is characterized as a perpetual incendiary issue which influences the joints by hurting body tissues Therefore, there is an urgent need for an effective intelligent identification system of knee Rheumatoid arthritis especially in its early stages. This paper is to develop a new intelligent system for the identification of Rheumatoid arthritis of the knee utilizing image processing techniques and neural classifier. The system involves two principle stages. The first one is the image processing stage in which the images are processed using some techniques such as RGB to gryascale conversion, rescaling, median filtering, background extracting, images subtracting, segmentation using canny edge detection, and features extraction using pattern averaging. The extracted features are used then as inputs for the neural network which classifies the X-ray knee images as normal or abnormal (arthritic) based on a backpropagation learning algorithm which involves training of the network on 400 X-ray normal and abnormal knee images. The system was tested on 400 x-ray images and the network shows good performance during that phase, resulting in a good identification rate 97%.

Keywords: rheumatoid arthritis, intelligent identification, neural classifier, segmentation, backpropoagation

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Authors: Steven Ploetz, Andreas Lohmueller, Robert F. Singer

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The outstanding performance of aluminum matrix composites (AMCs) regarding stiffness/weight ratio makes AMCs attractive material for lightweight construction. Low-density boride compounds promise simultaneously an increase in stiffness and decrease in composite density. This is why boron carbide is chosen for composite manufacturing. The composites are fabricated with the stir casting process. To avoid gas entrapment during mixing and ensure nonporous composites, partial vacuum is adapted during particle feeding and stirring. Poor wettability of boron carbide with liquid aluminum hinders particle incorporation, but alloying elements such as magnesium and titanium could improve wettability and thus particle incorporation. Next to alloying elements, adapted stirring parameters and impeller geometries improve particle incorporation and enable homogenous particle distribution and high particle volume fractions of boron carbide. AMCs with up to 15 vol.% of boron carbide particles are produced via melt stirring, resulting in an increase in stiffness and strength.

Keywords: aluminum matrix composites, boron carbide, stiffness, stir casting

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Authors: Nuzhat Sultana M. B.

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Children are high-risk population in terms of food born illnesses. Food safety and security are the most important aspect of the success of midday meal programmes. Improper holding temperatures, cross-contamination and poor personal hygiene of food handlers are the main causes for the prevalence of pathogenic microbes in the food servicing areas. Two hundred and fifty preschool children in the age of 3 to 6 years from urban and rural anganwadies (pre school center) of Beed district were selected. Nutritional status of preschool children were assessed by anthropometrical and clinical measurement. The study assessed the food safety and security with the help of personal hygiene and other safety measures maintained by the food personnel working for midday meal programme, supplying mid meals to children in govt. anganwadies (pre school center). The hygiene level, sanitary condition and microbial quality of food and water, pathological health examination of food handlers were assessed with the help of checklist. A questionnaire was designed to evaluate knowledge, attitude, and practices of food handlers. Results of the study show that the nutritional and health status of rural and urban preschool children was very poor. Many of the food handlers were not aware of general knowledge and hygiene practices to be followed during food preparation areas. An intervention programme of education and importing training at workplaces has shown a positive impact on the outcome of safety and security practices and safe, hygienic practices of food handlers at workplace.

Keywords: food, health, preschool children, safety, security

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Authors: Chen Xiong, Tong Xin, Li Hao, Xu Jin-Sheng

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Experiment and simulation researches on the structural integrity of propellant grain in solid rocket motor (SRM) with high volumetric fraction were conducted. First, by using SRM parametric modeling functions with secondary development tool Python of ABAQUS, the three dimensional parameterized modeling programs of star shaped grain, wheel shaped grain and wing cylindrical grain were accomplished. Then, the mechanical properties under different loads for star shaped grain were obtained with the application of automatically established finite element model in ABAQUS. Next, several optimization algorithms are introduced to optimize the star shaped grain, wheel shaped grain and wing cylindrical grain. After meeting the demands of burning surface changes and volumetric fraction, the optimum three dimensional shapes of grain were obtained. Finally, by means of parametric modeling functions, pressure data of SRM’s cold pressurization test was directly applied to simulation of grain in terms of mechanical performance. The results verify the reliability and practical of parameterized modeling program of SRM.

Keywords: cold pressurization test, ğarametric modeling, structural integrity, propellant grain, SRM

Procedia PDF Downloads 366

Authors: Zhong Ma, Zhuping Wang, Congxin Liu, Xiangzeng Liu

Abstract:

Satellite imagery classification is a challenging problem with many practical applications. In this paper, we designed a deep convolution neural network (DCNN) to classify the satellite imagery. The contributions of this paper are twofold — First, to cope with the large-scale variance in the satellite image, we introduced the inception module, which has multiple filters with different size at the same level, as the building block to build our DCNN model. Second, we proposed a genetic algorithm based method to efficiently search the best hyper-parameters of the DCNN in a large search space. The proposed method is evaluated on the benchmark database. The results of the proposed hyper-parameters search method show it will guide the search towards better regions of the parameter space. Based on the found hyper-parameters, we built our DCNN models, and evaluated its performance on satellite imagery classification, the results show the classification accuracy of proposed models outperform the state of the art method.

Keywords: satellite imagery classification, deep convolution network, genetic algorithm, hyper-parameter optimization

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Authors: S. Anastasiou, C. Nathanailides

Abstract:

There is considerable evidence to suggest that employees participation in the decision-making process of an organisation, has a positive effect on job satisfaction and work performance of the employees. The purpose of the present work was to examine the HRM practices, demographics and the level of job satisfaction of employees in Greek Aquaculture fish farms. A survey of employees (n=86) in 6 Greek Aquaculture Firms was carried out. The results indicate that HRM practices such as recruitment of the personnel and communication between the departments did not vary between different firms. The most frequent method of recruitment was through the professional network or the personal network of the managers. The preferred method of HRM communication was through the line managers and through group meeting. The level of job satisfaction increased with work experience participation and participation in the decision making process. A high percentage of the employees (81,3%±8.39) felt that they frequently participated in the decision making process. The Aquaculture employees exhibited high level of job satisfaction (88,1±6.95). The level of job satisfaction was related with participation in the decision making process (-0.633, P<0.05) but was not related with as age or gender. In terms of the working conditions, employees were mostly satisfied with their work itself, their colleagues and mostly dissatisfied with working hours, salary issues and low prospects of pay rises.

Keywords: aquaculture, human resources, job satisfaction

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Authors: Jalal Soleimannejad, Mohammad Asadizeidabadi, Mahmoud Koorki, Mojtaba Azarpira

Abstract:

A significant percentage of production costs is the maintenance costs, and analysis of maintenance costs could to achieve greater productivity and competitiveness. With this is mind, the maintenance of machines and installations is considered as an essential part of organizational functions and applying effective strategies causes significant added value in manufacturing activities. Organizations are trying to achieve performance levels on a global scale with emphasis on creating competitive advantage by different methods consist of RCM (Reliability-Center-Maintenance), TPM (Total Productivity Maintenance) etc. In this study, increasing the capacity of Concentration Plant of Golgohar Iron Ore Mining & Industrial Company (GEG) was examined by using of reliability and maintainability analyses. The results of this research showed that instead of increasing the number of machines (in order to solve the bottleneck problems), the improving of reliability and maintainability would solve bottleneck problems in the best way. It should be mention that in the abovementioned study, the data set of Concentration Plant of GEG as a case study, was applied and analyzed.

Keywords: bottleneck, golgohar iron ore mining & industrial company, maintainability, maintenance costs, reliability

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Authors: Fu Jinyu, Lin Jinguan

Abstract:

This paper introduces a novel approach that unifies two types of models: one is the continuous-time jump-diffusion used to model high-frequency data, and the other is discrete-time GQARCH employed to model low-frequency financial data by embedding the discrete GQARCH structure with jumps in the instantaneous volatility process. This model is named “GQARCH-It\^{o} -Jumps mode.” We adopt the realized range-based threshold estimation for high-frequency financial data rather than the realized return-based volatility estimators, which entail the loss of intra-day information of the price movement. Meanwhile, a quasi-likelihood function for the low-frequency GQARCH structure with jumps is developed for the parametric estimate. The asymptotic theories are mainly established for the proposed estimators in the case of finite activity jumps. Moreover, simulation studies are implemented to check the finite sample performance of the proposed methodology. Specifically, it is demonstrated that how our proposed approaches can be practically used on some financial data.

Keywords: It\^{o} process, GQARCH, leverage effects, threshold, realized range-based volatility estimator, quasi-maximum likelihood estimate

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Authors: Pooya Niksiar, Ali Ashrafizadeh, Mehrzad Shams, Amir Hossein Madani

Abstract:

There are many computationally demanding applications in science and engineering which need efficient algorithms implemented on high performance computers. Recently, Graphics Processing Units (GPUs) have drawn much attention as compared to the traditional CPU-based hardware and have opened up new improvement venues in scientific computing. One particular application area is Computational Fluid Dynamics (CFD), in which mature CPU-based codes need to be converted to GPU-based algorithms to take advantage of this new technology. In this paper, numerical solutions of two classes of discrete fluid flow models via both CPU and GPU are discussed and compared. Test problems include an Eulerian model of a two-dimensional incompressible laminar flow case and a Lagrangian model of a two phase flow field. The CUDA programming standard is used to employ an NVIDIA GPU with 480 cores and a C++ serial code is run on a single core Intel quad-core CPU. Up to two orders of magnitude speed up is observed on GPU for a certain range of grid resolution or particle numbers. As expected, Lagrangian formulation is better suited for parallel computations on GPU although Eulerian formulation represents significant speed up too.

Keywords: CFD, Eulerian formulation, graphics processing units, Lagrangian formulation

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Authors: Ainara Lopez-Ortega, Raquel Bayon, Elena Rodriguez, Amaya Igartua

Abstract:

The materials used in offshore structural applications are continuously subjected to aggressive environmental conditions that accelerate their degradation, thus shortening their useful life. Wear, corrosion and the effect of marine microorganisms are the main processes taking place in marine environments, and whenever they occur simultaneously the durability of materials is strongly reduced. In the present work, the tribocorrosion behaviour of a High-Strength Low-Alloy (HSLA) steel and three coatings commonly used for protecting offshore components has been studied by means of unidirectional tribological tests in synthetic seawater. The coatings were found to enhance the tribological response of the uncoated steel and provide the system with improved corrosion resistance, in terms of smaller material losses and reduction of friction coefficients. The tests were repeated after ageing the materials in a salt-fog cabinet, and the aging process was found to slightly affect the performance of two of the coatings, in terms of higher material losses, meanwhile the third coating was not affected.

Keywords: coatings, corrosion, high-strength low-alloy steel, seawater, tribocorrosion

Procedia PDF Downloads 423