Search results for: performance optimization

Authors: Umar Hayatu Sidik

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Application of liquid base petroleum fuel (petrol and diesel) for transportation fuel causes emissions of greenhouse gases (GHGs), while natural gas (NG) reduces the emissions of greenhouse gases (GHGs). At present, compression and liquefaction are the most matured technology used for transportation system. For transportation use, compression requires high pressure (200–300 bar) while liquefaction is impractical. A relatively low pressure of 30-40 bar is achievable by adsorbed natural gas (ANG) to store nearly compressed natural gas (CNG). In this study, adsorbents for high-pressure adsorption of methane (CH4) was prepared from coconut shells and polyetheretherketone (PEEK) using potassium hydroxide (KOH) and microwave-assisted activation. Design expert software version 7.1.6 was used for optimization and prediction of preparation conditions of the adsorbents for CH₄ adsorption. Effects of microwave power, activation time and quantity of PEEK on the adsorbents performance toward CH₄ adsorption was investigated. The adsorbents were characterized by Fourier transform infrared spectroscopy (FTIR), thermogravimetric (TG) and derivative thermogravimetric (DTG) and scanning electron microscopy (SEM). The ideal CH4 adsorption capacities of adsorbents were determined using volumetric method at pressures of 5, 17, and 35 bar at an ambient temperature and 5 oC respectively. Isotherm and kinetics models were used to validate the experimental results. The optimum preparation conditions were found to be 15 wt% amount of PEEK, 3 minutes activation time and 300 W microwave power. The highest CH4 uptake of 9.7045 mmol CH4 adsorbed/g adsorbent was recorded by M33P15 (300 W of microwave power, 3 min activation time and 15 wt% amount of PEEK) among the sorbents at an ambient temperature and 35 bar. The CH4 equilibrium data is well correlated with Sips, Toth, Freundlich and Langmuir. Isotherms revealed that the Sips isotherm has the best fit, while the kinetics studies revealed that the pseudo-second-order kinetic model best describes the adsorption process. In all scenarios studied, a decrease in temperature led to an increase in adsorption of both gases. The adsorbent (M33P15) maintained its stability even after seven adsorption/desorption cycles. The findings revealed the potential of coconut shell-PEEK as CH₄ adsorbents.

Keywords: adsorption, desorption, activated carbon, coconut shells, polyetheretherketone

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Authors: A. J. Francisco, K. C. Gallosa, R. J. Gasacao, J. R. Ros, B. J. Viado

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The study focuses on the use of quality indicators (QI)s based on the standards made by the (IFCC), that could effectively identify and minimize errors occurring throughout the total testing process (TTP), in order to improve patient safety. The study was conducted through a survey questionnaire that was given to a random sample of 19 respondents (eight privately-owned and eleven government-owned hospitals), mainly CMTs, MTs, and Supervisors from UST-affiliated hospitals. The pre-analytical laboratory errors, which include misidentification errors, transcription errors, sample collection errors and sample handling and transportation errors, were considered as variables according to the IFCC WG-LEPS. Data gathered were analyzed using the Mann-Whitney U test, Percentile, Linear Regression, Percentage, and Frequency. The laboratory performance of both hospitals is High level. There is no significant difference between the laboratory performance between the two stated variables. Moreover, among the four QIs, sample handling and transportation errors contributed most to the difference between the two variables. Outcomes indicate satisfactory performance between both variables. However, in order to ensure high-quality and efficient laboratory operation, constant vigilance and improvements in pre-analytical QI are still needed. Expanding the coverage of the study, the inclusion of other phases, utilization of parametric tests are recommended.

Keywords: pre-analytical phase, quality indicators, laboratory performance, pre-analytical error

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Authors: Thanduxolo Elford Fana

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Rationale and Purpose: Performance management and development system are central to effective and efficient service delivery, especially in highly labour intensive sectors such as South African public health. Performance management and development systems seek to ensure that good employee performance is rewarded accordingly, while those who underperform are developed so that they can reach their full potential. An effective and efficiently implemented performance management system motivates and improves employee engagement. The purpose of this study is to examine the implementation of the performance management and development system and the challenges that are encountered during its implementation in the Eastern Cape Provincial Department of Health. Methods: A qualitative research approach and a case study design was adopted in this study. The primary data were collected through observations, focus group discussions with employees, a group interview with shop stewards, and in-depth interviews with supervisors and managers, from April 2019 to September 2019. There were 45 study participants. In-depth interviews were held with 10 managers at facility level, which included chief executive officer, chief medical officer, assistant director’s in human resources management, patient admin, operations, finance, and two area manager and two operation managers nursing. A group interview was conducted with five shop stewards and an in-depth interview with one shop steward from the group. Five focus group discussions were conducted with clinical and non-clinical staff. The focus group discussions were supplemented with an in-depth interview with one person from each group in order to counter the group effect. Observations included moderation committee, contracting, and assessment meetings. Findings: The study shows that the performance management and development system was not properly implemented. There was non-compliance to performance management and development system policy guidelines in terms of time lines for contracting, evaluation, payment of incentives to good performers, and management of poor performance. The study revealed that the system is ineffective in raising the performance of employees and unable to assist employees to grow. The performance bonuses were no longer paid to qualifying employees. The study also revealed that lack of capacity and commitment, poor communication, constant policy changes, financial constraints, weak and highly bureaucratic management structures, union interference were challenges that were encountered during the implementation of the performance management and development system. Lastly, employees and supervisors were rating themselves three irrespective of how well or bad they performed. Conclusion: Performance management is regarded as vital to improved performance of the health workforce and healthcare service delivery among populations. Effective implementation of performance management and development system depends on well-capacitated and unbiased management at facility levels. Therefore, there is an urgent need to improve communication, link performance management to rewards, and capacitate staff on performance management and development system, as it is key to improved public health sector outcomes or performance.

Keywords: challenges, implementation, performance management and development system, public hospital

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Authors: Timna Mayer

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This paper explores the vast potential of self-directed learning in violin pedagogy. Based in practice and drawing on concepts from neuropsychology, the author, a violinist and teacher, outlines five learning principles. Self-directed learning is defined as an ongoing process based on problem detection, definition, and resolution. The traditional roles of teacher and student are reimagined within this context. A step-by-step guide to applied self-directed learning suggests a model for both teachers and students that realizes student independence in the classroom, leading to higher-level understanding and more robust performance. While the value of self-directed learning is well-known in general pedagogy, this paper is novel in applying the approach to the study of musical performance, a field which is currently dominated by habit and folklore, rather than informed by science.

Keywords: neuropsychology and musical performance, self-directed learning, strategic problem solving, violin pedagogy

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Authors: Bhim Kumar Dahal

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Transportation network development in the developing country is in rapid pace. The majority of the network belongs to railway and expressway which passes through diverse topography, landform and geological conditions despite the avoidance principle during route selection. Construction of such networks demand many low to high embankment which required improvement in the foundation soil. This paper is mainly focused on the various advanced ground improvement techniques used to improve the soft soil, modelling approach and its predictability for embankments construction. The ground improvement techniques can be broadly classified in to three groups i.e. densification group, drainage and consolidation group and reinforcement group which are discussed with some case studies.  Various methods were used in modelling of the embankments from simple 1-dimensional to complex 3-dimensional model using variety of constitutive models. However, the reliability of the predictions is not found systematically improved with the level of sophistication.  And sometimes the predictions are deviated more than 60% to the monitored value besides using same level of erudition. This deviation is found mainly due to the selection of constitutive model, assumptions made during different stages, deviation in the selection of model parameters and simplification during physical modelling of the ground condition. This deviation can be reduced by using optimization process, optimization tools and sensitivity analysis of the model parameters which will guide to select the appropriate model parameters.

Keywords: cement, improvement, physical properties, strength

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Authors: S. Ivanova, K. Ivanov

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Bemitil (2-ethylthiobenzimidazole hydrobromide) is a synthetic adaptogen and actoprotector, with wide-ranging pharmacological activities such as nootropic, antihypoxic, antioxidant, immunostimulant. The intake of Bemitil increases mental and physical performance and could be applied under either normal or extreme conditions. Until 2017 Bemitil was not considered as doping and was used by professional athletes more than 30 years because of its high efficiency and safety. The drug was included in WADA monitoring programme for 2018, and most likely it would be included in WADA Prohibited List for 2019. Usually, a substance/method is included in WADA Prohibited List if it meets any two of the following three criteria: the potential to enhance or enhances sports performance/ potential health risk to the athlete/ violates the spirit of sport. Bemitil has high performance-enhancing potential, but it is also safe- it is controversial whether it should be considered as doping.

Keywords: doping, bemitil, sport, actoprotector

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Authors: Stepan Kuchar, Martin Golasowski, Radim Vavrik, Michal Podhoranyi, Boris Sir, Jan Martinovic

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The main goal of this article is to describe the online flood monitoring and prediction system Floreon+ primarily developed for the Moravian-Silesian region in the Czech Republic and the basic process it uses for running automatic rainfall-runoff and hydrodynamic simulations along with their calibration and uncertainty modeling. It takes a long time to execute such process sequentially, which is not acceptable in the online scenario, so the use of high-performance computing environment is proposed for all parts of the process to shorten their duration. Finally, a case study on the Ostravice river catchment is presented that shows actual durations and their gain from the parallel implementation.

Keywords: flood prediction process, high performance computing, online flood prediction system, parallelization

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Authors: Mohamad Abdullah

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Recent Advancements in technology have stimulated deep change in the language learning classroom. Flipped classroom as a new pedagogical method is at the center of this change. It turns the classroom into a student-centered environment and promotes interactive and autonomous learning. The present study is an attempt to examine the effectiveness of the Flipped Classroom Model (FCM) on students’ motivation level in English speaking performance. This study was carried out with 27 undergraduate female English majors who enrolled in the course of Advanced Communication Skills (ENGL 154) at Buraimi University College (BUC). Data was collected through Motivation in English Speaking Performance Questionnaire (MESPQ) which has been distributed among the participants of this study pre and post the implementation of FCM. SPSS was used for analyzing data. The Paired T-Test which was carried out on the pre-post of (MESPQ) showed a significant difference between them (p < .009) that revealed participants’ tendency to increase their motivation level in English speaking performance after the application of FCM. In addition, respondents of the current study reported positive views about the implementation of FCM.

Keywords: english speaking performance, motivation, flipped classroom model, learner-contentedness

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Authors: Federico Pittino, Thomas Arnold

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The shredding of waste materials is a key step in the recycling process towards the circular economy. Industrial shredders for waste processing operate in very harsh operating conditions, leading to the need for frequent maintenance of critical components. Maintenance optimization is particularly important also to increase the machine’s efficiency, thereby reducing the operational costs. In this work, a monitoring system has been developed and deployed on an industrial shredder located at a waste recycling plant in Austria. The machine has been monitored for one year, and methods for predictive maintenance have been developed for two key components: the cutting knives and the drive belt. The large amount of collected data is leveraged by statistical machine learning techniques, thereby not requiring very detailed knowledge of the machine or its live operating conditions. The results show that, despite the wide range of operating conditions, a reliable estimate of the optimal time for maintenance can be derived. Moreover, the trade-off between the cost of maintenance and the increase in power consumption due to the wear state of the monitored components of the machine is investigated. This work proves the benefits of real-time monitoring system for the efficient operation of industrial shredders.

Keywords: predictive maintenance, circular economy, industrial shredder, cost optimization, statistical machine learning

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Authors: M. Graus, K. Westhoff, X. Xu

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The climate change causes a change in all aspects of society. While the expansion of renewable energies proceeds, industry could not be convinced based on general studies about the potential of demand side management to reinforce smart grid considerations in their operational business. In this article, a procedure model for a case-specific data-driven decision support for industrial energy management based on a holistic data analytics approach is presented. The model is executed on the example of the strategic decision problem, to integrate the aspect of renewable energies into industrial energy management. This question is induced due to considerations of changing the electricity contract model from a standard rate to volatile energy prices corresponding to the energy spot market which is increasingly more affected by renewable energies. The procedure model corresponds to a data analytics process consisting on a data model, analysis, simulation and optimization step. This procedure will help to quantify the potentials of sustainable production concepts based on the data from a factory. The model is validated with data from a printer in analogy to a simple production machine. The overall goal is to establish smart grid principles for industry via the transformation from knowledge-driven to data-driven decisions within manufacturing companies.

Keywords: data analytics, green production, industrial energy management, optimization, renewable energies, simulation

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Authors: Fatiha Naaoui-Outini

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Purpose – The purpose of this paper is to shed light on how a Downstream Supply Chain facilitated the Customer Service Performance (BTB) by more collaborative practices between the different stakeholders in the chain. Methodology/approach – The paper developed a theoretical framework and conducted a qualitative exploratory study approach based on six semi-structured interviews with two international groups in the distribution sector with the aim of understanding and analyzing how companies have changed their supply chains to ensure optimal customer service. Findings/Implications – The study contributes to the Global Supply Chain Management and Collaboration literature by integrating the role of the downstream supply chain into research that may actually influence customer service performance on BTB. Our findings also provide firms with some guidelines on building successful downstream supply chain collaboration and a significant influence on customer service performance in BTB. Because of the exploratory nature of the study approach, the research results are limited to the data collected, and these preliminary findings require further confirmation.

Keywords: customer service performance (B2B), global supply chain, downstream supply collaboration, qualitative case study

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Authors: F. Hamidi, N. Amiri, H. Mishmast Nehi

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The Bilevel Programming (BP) model has been presented for a decision making process that consists of two decision makers in a hierarchical structure. In fact, BP is a model for a static two person game (the leader player in the upper level and the follower player in the lower level) wherein each player tries to optimize his/her personal objective function under dependent constraints; this game is sequential and non-cooperative. The decision making variables are divided between the two players and one’s choice affects the other’s benefit and choices. In other words, BP consists of two nested optimization problems with two objective functions (upper and lower) where the constraint region of the upper level problem is implicitly determined by the lower level problem. In real cases, the coefficients of an optimization problem may not be precise, i.e. they may be interval. In this paper we develop an algorithm for solving interval bilevel linear fractional programming problems. That is to say, bilevel problems in which both objective functions are linear fractional, the coefficients are interval and the common constraint region is a polyhedron. From the original problem, the best and the worst bilevel linear fractional problems have been derived and then, using the extended Charnes and Cooper transformation, each fractional problem can be reduced to a linear problem. Then we can find the best and the worst optimal values of the leader objective function by two algorithms.

Keywords: best and worst optimal solutions, bilevel programming, fractional, interval coefficients

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Authors: Behzad Behnia, Noah LaRussa-Trott

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In recent years, fibers have been successfully used as an additive to reinforce asphalt concrete materials and to enhance the sustainability and resiliency of transportation infrastructure. Roads covered with fiber-reinforced asphalt concrete (FRAC) require less frequent maintenance and tend to have a longer lifespan. The present work investigates the application of sasobit-coated aramid fibers in asphalt pavements and employs machine learning to develop prediction models to evaluate the cracking performance of FRAC materials. For the experimental part of the study, the effects of several important parameters such as fiber content, fiber length, and testing temperature on fracture characteristics of FRAC mixtures were thoroughly investigated. Two mechanical performance tests, i.e., the disk-shaped compact tension [DC(T)] and indirect tensile [ID(T)] strength tests, as well as the non-destructive acoustic emission test, were utilized to experimentally measure the cracking behavior of the FRAC material in both macro and micro level, respectively. The experimental results were used to train the supervised machine learning approach in order to establish prediction models for fracture performance of the FRAC mixtures in the field. Experimental results demonstrated that adding fibers improved the overall fracture performance of asphalt concrete materials by increasing their fracture energy, tensile strength and lowering their 'embrittlement temperature'. FRAC mixtures containing long-size fibers exhibited better cracking performance than regular-size fiber mixtures. The developed prediction models of this study could be easily employed by pavement engineers in the assessment of the FRAC pavements.

Keywords: fiber reinforced asphalt concrete, machine learning, cracking performance tests, prediction model

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Authors: Shoumodip Roy, Ankit Singhania, M. K. G. Choudhury, Santanu Mallick, M. K. Agarwal, R. V. Ramna, Uttam Singh

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One of the key corporate goals of Tata Steel company is to demonstrate Environment Leadership. Decreasing specific CO₂ emission is one of the key steps to achieve the stated corporate goal. At any Blast Furnace, specific CO₂ emission is directly proportional to fuel intake. To reduce the fuel intake at G Blast Furnace, an initial benchmarking exercise was carried out with international and domestic Blast Furnaces to determine the potential for improvement. The gap identified during the exercise revealed that the benchmark Blast Furnaces operated with superior raw material quality than that in G Blast Furnace. However, since the raw materials to G Blast Furnace are sourced from the captive mines, improvement in the raw material quality was out of scope. Therefore, trials were taken with different operating regimes, to identify the key process parameters, which on optimization could significantly reduce the fuel intake in G Blast Furnace. The key process parameters identified from the trial were the Stoichiometric Oxygen Ratio, Melting Capacity ratio and the burden distribution inside the furnace. These identified process parameters were optimized to bridge the gap in fuel intake at G Blast Furnace, thereby reducing specific CO₂ emission to benchmark levels. This paradigm shift enabled to lower the fuel intake by 70kg per ton of liquid iron produced, thereby reducing the specific CO₂ emission by 15 percent.

Keywords: benchmark, blast furnace, CO₂ emission, fuel rate

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Authors: Nour Wehbe

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The Lebanese electricity sector is at the heart of a deep crisis. Electricity in Lebanon is supplied by Électricité du Liban (EdL) which has to suffer from technical and financial deficiencies for decades and proved to be insufficient and deficient as the demand still exceeds the supply. As a result, backup generation is widespread throughout Lebanon. The sector costs massive government resources and, on top of it, consumers pay massive additional amounts for satisfying their electrical needs. While the developed countries have been investing in renewable energy for the past two decades, the Lebanese government realizes the importance of adopting such energy sourcing strategies for the upgrade of the electricity sector in the country. The diversification of the national electricity generation mix has increased considerably in Lebanon's energy planning agenda, especially that a detailed review of the energy potential in Lebanon has revealed a great potential of solar and wind energy resources, a considerable potential of biomass resource, and an important hydraulic potential in Lebanon. This paper presents a review of the energy status of Lebanon, and illustrates a detailed review of the EDL structure with the existing problems and recommended solutions. In addition, scenarios reflecting implementation of policy projects are presented, and conclusions are drawn on the usefulness of a proposed evaluation methodology and the effectiveness of the adopted new energy policy for the electrical sector in Lebanon.

Keywords: EdL Electricite du Liban, portfolio optimization, electricity generation mix, mean-variance approach

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Authors: Bhavesh Dadhich, Fenil Bamnoliya, Akshita Swaminathan

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This project aims to design a system to generate energy from flowing wind due to the motion of a vehicle on the road or from the flow of wind in compact areas to utilize the wasteful energy into a useful one. It is envisaged through a design and aerodynamic performance improvement of a Savonius vertical axis wind turbine rotor and used in an integrated system with a Triboelectric Nanogenerator (TENG) that can generate a good amount of electrical energy. Aerodynamic calculations are performed numerically using Computational Fluid Dynamics software, and TENG's performance is evaluated analytically. The Turbine's coefficient of power is validated with published results for an inlet velocity of 7 m/s with a Tip Speed Ratio of 0.75 and found to reasonably agree with that of experiment results. The baseline design is modified with a new blade arc angle and rotor position angle based on the recommended parameter ranges suggested by previous researchers. Simulations have been performed for different T.S.R. values ranging from 0.25 to 1.5 with an interval of 0.25 with two applicable free stream velocities of 5 m/s and 7m/s. Finally, the newly designed VAWT CFD performance results are used as input for the analytical performance prediction of the triboelectric nanogenerator. The results show that this approach could be feasible and useful for small power source applications.

Keywords: savonius turbine, power, overlap ratio, tip speed ratio, TENG

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Authors: N. Guo, C. Xu, Z. C. Yang

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In order to ensure the high reliability of an aircraft, the accurate structural dynamics analysis has become an indispensable part in the design of an aircraft structure. Therefore, the structural finite element model which can be used to accurately calculate the structural dynamics and their transfer relations is the prerequisite in structural dynamic design. A dynamic finite element model updating method is presented to correct the uncertain parameters of the finite element model of a structure using measured modal parameters. The coordinate modal assurance criterion is used to evaluate the correlation level at each coordinate over the experimental and the analytical mode shapes. Then, the weighted summation of the natural frequency residual and the coordinate modal assurance criterion residual is used as the objective function. Moreover, the hybrid pattern search (HPS) optimization technique, which synthesizes the advantages of pattern search (PS) optimization technique and genetic algorithm (GA), is introduced to solve the dynamic FE model updating problem. A numerical simulation and a model updating experiment for GARTEUR aircraft model are performed to validate the feasibility and effectiveness of the present dynamic model updating method, respectively. The updated results show that the proposed method can be successfully used to modify the incorrect parameters with good robustness.

Keywords: model updating, modal parameter, coordinate modal assurance criterion, hybrid genetic/pattern search

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Authors: Desierin Rodrin, Magdalena Alcantara, Cristina Olo

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The increase in environmental temperatures brought about by climate change impacts negatively the growth performance of broilers that may be solved by manipulating the diet of the animals. Hence, this study was conducted to evaluate the effects of different vitamin supplements on the growth performance of broiler chickens subjected to ambient (31°C) and heat stress (34°C) temperatures. The treatments were: I- Control (no vitamin supplement), II- Vitamin A (4.5 mg/kg of feed), III- Vitamin C (250 mg/kg of feed), IV- Vitamin E (250 mg/kg of feed), V- Vitamin C and E (250 mg/kg of feed and 250 mg/kg of feed), VI- Vitamin A and E (4.5 mg/kg of feed and 250 mg/kg of feed), VII- Vitamin A and C (4.5 mg/kg of feed and 250 mg/kg of feed), and VIII- Vitamin A, C and E (4.5 mg/kg of feed, 250 mg/kg of feed and 250 mg/kg of feed). The birds (n=240) were distributed randomly into eight treatments replicated three times, with each replicates having five birds. Ambient temperature was maintained using a 25 watts bulb for every 20 birds, while heat stress condition was sustained at 34°C for about 9 hours daily by using a 50 watts bulb per 5 birds. The interaction of vitamin supplements and temperatures did not significantly (P>0.05) affected body weight, average daily gain, feed consumption and feed conversion efficiency throughout the growing period. Similarly, supplementation of different vitamins did not improve (P>0.05) the overall production performance of birds throughout the rearing period. Birds raised in heat stress (34°C) condition had significantly lower ((P<0.05) body weight, average daily gain, and feed consumption compared to birds raised in ambient temperature at weeks 3, 4 and 5 of rearing. Supplementation of vitamins A, C, and E in the diet of broilers did not alleviate the effect of heat stress in the growth performance of broilers.

Keywords: broiler growth performance, heat stress, vitamin supplementation, vitamin A, vitamin C, vitamin E

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Authors: Sarah Nasr, Maha M. A. Nasra, Ossama Y. Abdallah

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The present work aimed to prepare Silymarin loaded MCM-41 type mesoporous silica nanoparticles (MSNs) and to assess the system’s solubility enhancement ability on the pharmacodynamic performance of Silymarin as a hepatoprotective agent. MSNs prepared by soft-templating technique, were loaded with Silymarin, characterized for particle size, zeta potential, surface properties, DSC and XRPD. DSC and specific surface area data confirmed deposition of Silymarin in an amorphous state in MSNs’ pores. In-vitro drug dissolution testing displayed enhanced dissolution rate of Silymarin upon loading on MSNs. High dose Acetaminophen was then used to inflict hepatic injury upon albino male Wistar rats simultaneously receiving either free Silymarin, Silymarin loaded MSNs or blank MSNs. Plasma AST, ALT, albumin and total protein and liver homogenate content of TBARs or LDH as measures of antioxidant drug action were assessed for all animal groups. Results showed a significant superiority of Silymarin loaded MSNs to free drug in almost all parameters. Meanwhile prolonged administration of blank MSNs had no evident toxicity on rats.

Keywords: mesoporous silica nanoparticles, safety, solubility enhancement, silymarin

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Authors: Bilal Liaqat, Muhammad Umar, Zara Bashir, Hassan Rafique, Mohsin Abbasi, Zarak Khan

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Transformational leadership is one of the most studied topics in the organization sciences. However, the impact of transformational leadership on employee’s individual attributes have not yet been studied. Purpose: This research aims to discover the relationship between transformational leadership and employee motivation, performance and creativity. Moreover, the study will also investigate the influence of transformational leadership on employee performance through employee motivation and employee creativity. Design-Methodology-Approach: The data was collected from employees in different organization. This cross-sectional study collected data from employees and the methodology used includes survey data that were collected from employees in organizations. Structured interviews were also conducted to explain the outcomes from the survey. Findings: The results of this study reveal that transformational leadership has a positive impact on employee’s individual attributes. Research Implications: Although this study expands our knowledge about the role of learning orientation between transformational leadership and employee motivation, performance and creativity, the prospects for further research are still present.

Keywords: employee creativity, employee motivation, employee performance, transformational leadership

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Authors: Douglas J. Kube

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At the beginning of the COVID-19 pandemic, the Canadian Red Cross deployed workers into long-term care homes across Canada to support our most vulnerable citizens. It began by recruiting and training small teams of workers to provide non-clinical services for facilities in outbreak. Deployed workers were trained on an approach based on successful Red Cross deployments used with Ebola in which zones were established, levels of protection used, and strict protocols followed to prevent exposure. This paper addresses aspects of human performance through a safety culture lens. The Red Cross deployments highlight valuable insights and are an excellent case study in the principles of human performance and organizational culture. This paper looks at human performance principles, including human fallibility, predictability of error-likely situations, avoiding events by understanding reasons mistakes occur, and the influence on behaviour by organizational factors. This study demonstrates how the Red Cross’s organizational culture and work design positively influenced performance to protect workers and residents/clients. Lastly, this paper shares lessons that can be applied in many workplaces to improve worker health and safety and safety culture. This critical examination is based on the author’s experience as a Senior Occupational Health and Safety Advisor with the Red Cross during the pandemic as part of the team responsible for developing and implementing biological safety practices in long-term care deployments.

Keywords: COVID, human performance, organizational culture, work design

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Authors: I. Martins, A. Martins

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The European Union supports social and civil competencies as being a core element to develop sustainability of organizations, people and regions. These competencies are fundamental for the well-being of the community because they include interpersonal, intrapersonal as well as their civil, active and democratic participation in organizations. The combination of these competencies reveals the organizational socio-emotional maturity and allows relevant levels of performance. It also allows the development of various capitals, namely, human, structural, relational and social, with direct influence on performance. But along this path, the emotional aspect has not been valued as a capital, given that contemporary society is based on knowledge capital and is flooded with information viewed as a capital. The present study, based on the importance of these socio-emotional capitals, aims to show that the competencies of cooperation, interpersonal understanding, empathy, kindness, ability to listen, and tolerance, to mention a few, are strategic in consolidating knowledge within organizations. This implies that the humanizing processes, both inside and outside the organizations, are revitalized. The question is how to go about doing this and its implementation; as well as, where to begin and which guidelines to take on. These are the foci that guide the present study, bearing in mind the directions of the knowledge economy.

Keywords: civil competencies, humanizing, performance, social competencies

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Authors: M. Chobotová, Ž. Rylková

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Time full of changes which is associated with globalization, tougher competition, changes in the structures of markets and economic downturn, that all force companies to think about their competitive advantages. These changes can bring the company a competitive advantage and that can help improve competitive position in the market. Policy of the European Union is focused on the fast growing innovative companies which quickly respond to market demands and consequently increase its competitiveness. To meet those objectives companies need the right conditions and support of their state.

Keywords: innovation, performance, measurements metrics, indices

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Authors: Atilla Bayram

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This paper presents the trajectory tracking control of a spatial redundant hybrid manipulator. This manipulator consists of two parallel manipulators which are a variable geometry truss (VGT) module. In fact, each VGT module with 3-degress of freedom (DOF) is a planar parallel manipulator and their operational planes of these VGT modules are arranged to be orthogonal to each other. Also, the manipulator contains a twist motion part attached to the top of the second VGT module to supply the missing orientation of the endeffector. These three modules constitute totally 7-DOF hybrid (parallel-parallel) redundant spatial manipulator. The forward kinematics equations of this manipulator are obtained, then, according to these equations, the inverse kinematics is solved based on an optimization with the joint limit avoidance. The dynamic equations are formed by using virtual work method. In order to test the performance of the redundant manipulator and the controllers presented, two different desired trajectories are followed by using the computed force control method and a switching control method. The switching control method is combined with the computed force control method and genetic algorithm. In the switching control method, the genetic algorithm is only used for fine tuning in the compensation of the trajectory tracking errors.

Keywords: computed force method, genetic algorithm, hybrid manipulator, inverse kinematics of redundant manipulators, variable geometry truss

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Authors: Bit-Na Kwon, Hyun-Jee Yang, Dong-Hyun Ha, Hyoung-Kyu Song

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In this paper, an adaptive cooperative scheme in the cell edge is proposed. The proposed scheme considers the location of a user and applies the suitable cooperative scheme. In cellular systems, the performance of communication is degraded if the user is located in the cell edge. In conventional scheme, two base stations are used in order to obtain diversity gain. However, the performance of communication is not sufficiently improved since the distance between each base station and a user is still distant. Therefore, we propose a scheme that the relays are used and the cooperative scheme is adaptively applied according to the user location. Through simulation results, it is confirmed that the proposed scheme has better performance than the conventional scheme.

Keywords: adaptive transmission, cooperative communication, diversity gain, OFDM

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Authors: Daneal Rorke, Gueguim Kana

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The shift towards renewable energy sources for biofuel production has received increasing attention. However, the use and pre-treatment of lignocellulosic material are inundated with the generation of fermentation inhibitors which severely impact the feasibility of bioprocesses. This study reports the profiling of all volatile compounds generated during microwave assisted chemical pre-treatment of sorghum leaves. Furthermore, the optimization of reducing sugar (RS) from microwave assisted acid pre-treatment of sorghum leaves was assessed and gave a coefficient of determination (R2) of 0.76, producing an optimal RS yield of 2.74 g FS/g substrate. The development of an intelligent model to predict volatile compound fractions gave R2 values of up to 0.93 for 21 volatile compounds. Sensitivity analysis revealed that furfural and phenol exhibited high sensitivity to acid concentration, alkali concentration and S:L ratio, while phenol showed high sensitivity to microwave duration and intensity as well. These findings illustrate the potential of using an intelligent model to predict the volatile compound fraction profile of compounds generated during pre-treatment of sorghum leaves in order to establish a more robust and efficient pre-treatment regime for biofuel production.

Keywords: artificial neural networks, fermentation inhibitors, lignocellulosic pre-treatment, sorghum leaves

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Authors: Pulkeria Pascoe, Hawa P. Tundui, Marcia Dutra de Barcellos, Hans de Steur, Xavier Gellynck

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A majority of Micro and Small Enterprises (MSEs) experience low or no growth. Understanding their performance remains unfinished and disjointed as there is no consensus on the factors influencing it, especially in developing countries. Using a Resource-Based View (RBV) as the theoretical background, this cross-sectional study employed four regression models to examine the influence of firm-level factors (firm-specific characteristics, firm resources, manager socio-demographic characteristics, and selected management practices) on the overall performance variations among 442 Tanzanian micro and small agri-food processing firms. Study results confirmed the RBV argument that intangible resources make a larger contribution to overall performance variations among firms than that tangible resources. Firms' tangible and intangible resources explained 34.5% of overall performance variations (intangible resources explained the overall performance variability by 19.4% compared to tangible resources, which accounted for 15.1%), ranking first in explaining the overall performance variance. Firm-specific characteristics ranked second by influencing variations in overall performance by 29.0%. Selected management practices ranked third (6.3%), while the manager's socio-demographic factors were last on the list, as they influenced the overall performance variability among firms by only 5.1%. The study also found that firms that focus on proper utilization of tangible resources (financial and physical), set targets, and undertake better working capital management practices performed higher than their counterparts (low and average performers). Furthermore, accumulation and proper utilization of intangible resources (relational, organizational, and reputational), undertaking performance monitoring practices, age of the manager, and the choice of the firm location and activity were the dominant significant factors influencing the variations among average and high performers, relative to low performers. The entrepreneurial background was a significant factor influencing variations in average and low-performing firms, indicating that entrepreneurial skills are crucial to achieving average levels of performance. Firm age, size, legal status, source of start-up capital, gender, education level, and total business experience of the manager were not statistically significant variables influencing the overall performance variations among the agri-food processors under the study. The study has identified both significant and non-significant factors influencing performance variations among low, average, and high-performing micro and small agri-food processing firms in Tanzania. Therefore, results from this study will help managers, policymakers and researchers to identify areas where more attention should be placed in order to improve overall performance of MSEs in agri-food industry.

Keywords: firm-level factors, micro and small enterprises, performance, regression analysis, resource-based-view

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Authors: Juniarti, Agus Arianto Toly

Abstract:

This study aims to examine the effect of capital expenditure on the investors’ responses. The respondents were companies with the best stock performance in each sector in 2017. The observation period is 2017 to 2019. Top 10 companies in each sector with the best stock performance in companies listed on the Indonesia Stock Exchange were selected. The main variables are a growth signal which is proxied by growth in capital spending and capital expenditure, and risk and investor response, which is proxied by CAR. Financial performance as measured by ROA is a control variable in this study. The results showed that the signal of growth as measured by capital expenditures responded positively by the market, the risk moderates this influence, companies with high risk will be responded negatively by investors and vice versa. This finding corrects previous findings that only looked at the signal aspect of growth, without linking it to risk. In addition, these findings reinforce the argument that investors buy the future of the company, not a momentary financial performance. This can be seen from the absence of ROA influence on investor response. This study found that companies need to manage risk appropriately, because the risk aspect of the company is a crucial factor for investors. High risks will eliminate the benefits of strategic decisions in this case in the form of capital expenditures.

Keywords: capital expenditure, growth signals, investor response, risk

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Authors: Abderrahmane El Kachani, El Mahjoub Chakir, Anass Ait Laachir, Abdelhamid Niaaniaa, Jamal Zerouaoui, Tarik Jarou

Abstract:

This paper presents a wind turbine based on the doubly fed induction generator (DFIG) connected to the utility grid through a shunt active power filter (SAPF). The whole system is controlled by a double nonlinear predictive controller (DNPC). A Taylor series expansion is used to predict the outputs of the system. The control law is calculated by optimization of the cost function. The first nonlinear predictive controller (NPC) is designed to ensure the high performance tracking of the rotor speed and regulate the rotor current of the DFIG, while the second one is designed to control the SAPF in order to compensate the harmonic produces by the three-phase diode bridge supplied by a passive circuit (rd, Ld). As a result, we obtain sinusoidal waveforms of the stator voltage and stator current. The proposed nonlinear predictive controllers (NPCs) are validated via simulation on a 1.5 MW DFIG-based wind turbine connected to an SAPF. The results obtained appear to be satisfactory and promising.

Keywords: wind power, doubly fed induction generator, shunt active power filter, double nonlinear predictive controller

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Authors: N. Alias, W. Z. W. Muhammad, M. N. M. Ibrahim, M. Mohamed, H. F. S. Saipol, U. N. Z. Ariffin, N. A. Zakaria, M. S. Z. Suardi

Abstract:

This paper presents the performance comparison of some computation software for solving the boundary element method (BEM). BEM formulation is the numerical technique and high potential for solving the advance mathematical modeling to predict the production of oil well in arbitrarily shaped based on multiple leases reservoir. The limitation of data validation for ensuring that a program meets the accuracy of the mathematical modeling is considered as the research motivation of this paper. Thus, based on this limitation, there are three steps involved to validate the accuracy of the oil production simulation process. In the first step, identify the mathematical modeling based on partial differential equation (PDE) with Poisson-elliptic type to perform the BEM discretization. In the second step, implement the simulation of the 2D BEM discretization using COMSOL Multiphysic and MATLAB programming languages. In the last step, analyze the numerical performance indicators for both programming languages by using the validation of Fortran programming. The performance comparisons of numerical analysis are investigated in terms of percentage error, comparison graph and 2D visualization of pressure on oil production of multiple leases reservoir. According to the performance comparison, the structured programming in Fortran programming is the alternative software for implementing the accurate numerical simulation of BEM. As a conclusion, high-level language for numerical computation and numerical performance evaluation are satisfied to prove that Fortran is well suited for capturing the visualization of the production of oil well in arbitrarily shaped.

Keywords: performance comparison, 2D visualization, COMSOL multiphysic, MATLAB, Fortran, modelling and simulation, boundary element method, reservoir pressure

Procedia PDF Downloads 477