Search results for: operational performance

Authors: H. W. Meerveld, R. H. A. Lindelauf

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In contemporary warfare, data science is crucial for the military in achieving information superiority. Yet, to the authors’ knowledge, no extensive literature survey on data science in military decision-making has been conducted so far. In this study, 156 peer-reviewed articles were analysed through an integrative, semi-systematic literature review to gain an overview of the topic. The study examined to what extent literature is focussed on the opportunities or risks of data science in military decision-making, differentiated per level of war (i.e. strategic, operational, and tactical level). A relatively large focus on the risks of data science was observed in social science literature, implying that political and military policymakers are disproportionally influenced by a pessimistic view on the application of data science in the military domain. The perceived risks of data science are, however, hardly addressed in formal science literature. This means that the concerns on the military application of data science are not addressed to the audience that can actually develop and enhance data science models and algorithms. Cross-disciplinary research on both the opportunities and risks of military data science can address the observed research gaps. Considering the levels of war, relatively low attention for the operational level compared to the other two levels was observed, suggesting a research gap with reference to military operational data science. Opportunities for military data science mostly arise at the tactical level. On the contrary, studies examining strategic issues mostly emphasise the risks of military data science. Consequently, domain-specific requirements for military strategic data science applications are hardly expressed. Lacking such applications may ultimately lead to a suboptimal strategic decision in today’s warfare.

Keywords: data science, decision-making, information superiority, literature review, military

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Authors: Rajeshkumar U. Sambhe

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Large scale Indian manufacturers started implementing Six Sigma to their supply core to fulfill the endless need of high quality products. As well, they initiated encouraging their suppliers to apply the well-ascertain SS management practice and kept no resource for supplier enterprises, generally small midsized enterprises to think for the admittance of Six Sigma as a quality promotion drive. There are many issues to study for requisite changes before the introduction of Six Sigma in auto SMEs. This paper converges on impeding factors while implementing SS drive and also pinpoints the gains achieved through successful implementation. The result of this study suggest some operational guidelines for effective implementation of Six Sigma from evidences acquired through research questionnaire and interviews with industrial professionals, apportioned to assort auto sector mid-sized enterprises (MSEs) in India.

Keywords: indian automotive SMEs, quality management practices, six sigma imperatives, problems faced in six sigma implementation, benefits, some guidelines for implementation

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Authors: Hamidoddin Yousife

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Drilling optimization requires a prediction of drilling rate of penetration (ROP) since it provides a significant reduction in drilling costs. There are several factors that can have an impact on the ROP, both controllable and uncontrollable. Numerous drilling penetration rate models have been considered based on drilling parameters. This papers considered the effect of proper drilling parameter selection such as bit, Mud Type, applied weight on bit (WOB), Revolution per minutes (RPM), and flow rate on drilling optimization and drilling cost reduction. A predicted analysis is used in real-time drilling performance to determine the optimal drilling operation. As a result of these modeling studies, the real data collected from three directional wells at Azadegan oil fields, Iran, was verified and adjusted to determine the drillability of a specific formation. Simulation results and actual drilling results show significant improvements in inaccuracy. Once simulations had been validated, optimum drilling parameters and equipment specifications were determined by varying weight on bit (WOB), rotary speed (RPM), hydraulics (hydraulic pressure), and bit specification for each well until the highest drilling rate was achieved. To evaluate the potential operational and economic benefits of optimizing results, a qualitative and quantitative analysis of the data was performed.

Keywords: drlling, cost, optimization, parameters

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Authors: Mohammed Nishat, Ahmad Ghazali

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This study empirically examines the corporate governance and firm performance, and tries to evaluate the governance, ownership and control related variables which are hypothesized to affect on firms performance. This study tries to evaluate the effectiveness of corporate governance mechanism to achieve high level performance among companies listed on the Karachi Stock Exchange (KSE) over the period from 2005 to 2008. To measure the firm performance level this research uses three measures of performance; Return on assets (ROA), Return on Equity (ROE) and Tobin’s Q. To link the performance of firms with the corporate governance three categories of corporate governance variables are tested which includes governance, ownership and control related variables. Fixed effect regression model is used to test the link between corporate governance and firm performance for 267 KSE listed Pakistani firms. The result shows that corporate governance variables such as percentage block holding by individuals have positive impact on firm performance. When CEO is also the chairperson of board then it is found that firm performance is adversely affected. Also negative relationship is found between share held by insiders and performance of firm. Leverage has negative impact on the performance of the firm and firm size is positively related with the firms performance.

Keywords: corporate governance, performance, agency cost, Karachi stock market

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Authors: Daniel Martinez, Tim de Leeuw, Stefan Haefliger

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The challenges of managing a large and geographically dispersed R&D organization have been further increasing during the past years, concentrating on the leverage of a geo-graphically dispersed body of knowledge in an efficient and effective manner. In order to reduce complexity and improve performance, firms introduce product modularity as one key element for global R&D network teams to develop their products and projects in collaboration. However, empirical studies on the effects of product modularity on innovation performance are really scant. Furthermore, some researchers have suggested that product modularity promotes innovation performance, while others argue that it inhibits innovation performance. This research fills this gap by investigating the impact of product modularity on various dimensions of innovation performance, i.e. effectiveness and efficiency. By constructing the theoretical framework, this study suggests that that there is an inverted U-shaped relationship between product modularity and innovation performance. Moreover, this research work suggests that the optimum of innovation performance efficiency will be at a higher level than innovation performance effectiveness at a given product modularity level.

Keywords: modularity, innovation performance, networks, R&D, collaboration

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Authors: Jaroslav Masek, Juraj Camaj, Eva Nedeliakova

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The paper is focused on the operational model for transport the single wagon consignments on railway network by using two different models of train formation. The paper gives an overview of possibilities of improving the quality of transport services. Paper deals with two models used in problematic of train formatting - time continuously and time discrete. By applying these models in practice, the transport company can guarantee a higher quality of service and expect increasing of transport performance. The models are also applicable into others transport networks. The models supplement a theoretical problem of train formation by new ways of looking to affecting the organization of wagon flows.

Keywords: train formation, wagon flows, marshalling yard, railway technology

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Authors: Z. Q. Zhang, Y. Zhang, D. L. Li

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To overcome the some shortcomings associated with traditional flotation machines and columns in collophanite flotation, a flotation device was designed and fabricated in the laboratory. A multi-impeller pump with same function as a mechanical cell was used instead of the injection sparger and circulation pump in column flotation unit. The influence of main operational parameters of the device like feed flow rate, air flow rate and impellers’ speed on collophanite flotation was analyzed. Experiment results indicate that the influence of the operational parameters were significant on flotation recovery and grade of phosphate concentrate. The best operating conditions of the device were: feed flow rate 0.62 L/min, air flow rate 6.67 L/min and impellers speed 900 rpm. At these conditions, a phosphate concentrate assaying about 30.5% P₂O₅ and 1% MgO with a P₂O₅ recovery of about 81% was obtained from a Yuan'an phosphate ore sample containing about 22.30% P₂O₅ and 3.2% MgO.

Keywords: collophanite flotation, flotation columns, flotation machines, multi-impeller pump

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Authors: Maier Dorin, Maier Andreea

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Today, any organization - regardless of the specific activity - must be prepared to face continuous radical changes, innovation thus becoming a condition of survival in a globalized market. Not all managers have an overall view on the real size of necessary innovation potential. Unfortunately there is still no common (and correct) understanding of the term of innovation among managers. Moreover, not all managers are aware of the need for innovation. This article highlights and analyzes a series of models of innovation processes and their evolution. The models analyzed encompass both the strategic level and the operational one within an organization, indicating performance innovation on each landing. As the literature review shows, there are no easy answers to the innovation process as there are no shortcuts to great results. Successful companies do not have a silver innovative bullet - they do not get results by making one or few things better than others, they make everything better.

Keywords: innovation, innovation process, business success, models of innovation

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Authors: Rıza Gürhan Korkut, Metin Çelik, Süleyman Özkaynak

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The early-stage design and development projects for the freight village initiatives require a comprehensive analysis of both qualitative and quantitative data. Considering the literature review on structural and operational management requirements, this study proposed an original taxonomy on criterion structure to assess freight village conceptualization. The potential challenges and uncertainties of the developed taxonomy are extended. Besides requirement analysis, this study is also expected to contribute to forthcoming research on benchmarking of freight villages in different regions. The methodology used in this research is a systematic review on several articles as per their modelling approaches, sustainability, entities and decisions made together with the uncertainties and features of their models taken into consideration. The major findings of the study that are the categories for assessing the projects attributes on their environmental, socio-economical, accessibility and location aspects.

Keywords: logistics centers, freight village, operational management, taxonomy

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Authors: Justin Woulfe

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Siloed logistics and supply chain management systems throughout the Department of Defense (DOD) has led to disparate approaches to modeling and simulation (M&S), a lack of understanding of how one system impacts the whole, and issues with “optimal” solutions that are good for one organization but have dramatic negative impacts on another. Many different systems have evolved to try to understand and account for uncertainty and try to reduce the consequences of the unknown. As the DoD undertakes expansive digital transformation initiatives, there is an opportunity to fuse and leverage traditionally disparate data into a centrally hosted source of truth. With a streamlined process incorporating machine learning (ML) and artificial intelligence (AI), advanced M&S will enable informed decisions guiding program success via optimized operational readiness and improved mission success. One of the current challenges is to leverage the terabytes of data generated by monitored systems to provide actionable information for all levels of users. The implementation of a cloud-based application analyzing data transactions, learning and predicting future states from current and past states in real-time, and communicating those anticipated states is an appropriate solution for the purposes of reduced latency and improved confidence in decisions. Decisions made from an ML and AI application combined with advanced optimization algorithms will improve the mission success and performance of systems, which will improve the overall cost and effectiveness of any program. The Systecon team constructs and employs model-based simulations, cutting across traditional silos of data, aggregating maintenance, and supply data, incorporating sensor information, and applying optimization and simulation methods to an as-maintained digital twin with the ability to aggregate results across a system’s lifecycle and across logical and operational groupings of systems. This coupling of data throughout the enterprise enables tactical, operational, and strategic decision support, detachable and deployable logistics services, and configuration-based automated distribution of digital technical and product data to enhance supply and logistics operations. As a complete solution, this approach significantly reduces program risk by allowing flexible configuration of data, data relationships, business process workflows, and early test and evaluation, especially budget trade-off analyses. A true capability to tie resources (dollars) to weapon system readiness in alignment with the real-world scenarios a warfighter may experience has been an objective yet to be realized to date. By developing and solidifying an organic capability to directly relate dollars to readiness and to inform the digital twin, the decision-maker is now empowered through valuable insight and traceability. This type of educated decision-making provides an advantage over the adversaries who struggle with maintaining system readiness at an affordable cost. The M&S capability developed allows program managers to independently evaluate system design and support decisions by quantifying their impact on operational availability and operations and support cost resulting in the ability to simultaneously optimize readiness and cost. This will allow the stakeholders to make data-driven decisions when trading cost and readiness throughout the life of the program. Finally, sponsors are available to validate product deliverables with efficiency and much higher accuracy than in previous years.

Keywords: artificial intelligence, digital transformation, machine learning, predictive analytics

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Authors: Seungchul Lee, Minjeong Kim, Iman Janghorban Esfahani, Jeong Tai Kim, ChangKyoo Yoo

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It is hard to maintain the effluent quality of the wastewater treatment plants (WWTPs) under with fixed types of operational control because of continuously changed influent flow rate and pollutant load. The aims of this study is development of multi-loop multi-objective control (ML-MOC) strategy in plant-wide scope targeting four objectives: 1) maximization of nutrient removal efficiency, 2) minimization of operational cost, 3) maximization of CH4 production in anaerobic digestion (AD) for CH4 reuse as a heat source and energy source, and 4) minimization of N2O gas emission to cope with global warming. First, benchmark simulation mode is modified to describe N2O dynamic in biological process, namely benchmark simulation model for greenhouse gases (BSM2G). Then, three types of single-loop proportional-integral (PI) controllers for DO controller, NO3 controller, and CH4 controller are implemented. Their optimal set-points of the controllers are found by using multi-objective genetic algorithm (MOGA). Finally, multi loop-MOC in BSM2G is implemented and evaluated in BSM2G. Compared with the reference case, the ML-MOC with the optimal set-points showed best control performances than references with improved performances of 34%, 5% and 79% of effluent quality, CH4 productivity, and N2O emission respectively, with the decrease of 65% in operational cost.

Keywords: Benchmark simulation model for greenhouse gas, multi-loop multi-objective controller, multi-objective genetic algorithm, wastewater treatment plant

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Authors: Junhai Liao, Yansong Shen, Aibing Yu

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A 3D numerical model is developed to simulate the complicated in-furnace combustion phenomena in the lower part of an ironmaking blast furnace (BF) while using pulverized coal injection (PCI) technology to reduce the consumption of relatively expensive coke. The computational domain covers blowpipe-tuyere-raceway-coke bed in the BF. The model is validated against experimental data in terms of gaseous compositions and coal burnout. Parameters, such as coal properties and some key operational variables, play an important role on the performance of coal combustion. Their diverse effects on different combustion characteristics are examined in the domain, in terms of gas compositions, temperature, and burnout. The heat generated by the combustion of upgraded Victorian brown coal is able to meet the heating requirement of a BF, hence making upgraded brown coal injected into BF possible. It is evidenced that the model is suitable to investigate the mechanism of the PCI operation in a BF. Prediction results provide scientific insights to optimize and control of the PCI operation. This model cuts the cost to investigate and understand the comprehensive combustion phenomena of upgraded Victorian brown coal in a full-scale BF.

Keywords: blast furnace, numerical study, pulverized coal injection, Victorian brown coal

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Authors: Jing Jiang, Yuguang Gao, Yang Yu

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Facing increasingly challenging insurance payment pressures, the Chinese healthcare system is undergoing significant transformations, akin to the implementation of DRG payment models by the United States' Medicare. Consequently, there is a pressing need for Chinese hospitals to establish optimizations in departmental operations tailored to the ongoing healthcare payment reforms. This abstract delineates the meticulous construction of a scientifically rigorous and comprehensive index system at the departmental level in China strategically aligned with the evolving landscape of healthcare payment reforms. Methodologically, it integrates key process areas and maturity assessment theories, synthesizing relevant literature and industry standards to construct a robust framework and indicator pool. Employing the Delphi method, consultations with 21 experts were conducted, revealing a collective demonstration of high enthusiasm, authority, and coordination in designing the index system. The resulting model comprises four primary indicators -technical capabilities, cost-effectiveness, operational efficiency, and disciplinary potential- supported by 14 secondary indicators and 23 tertiary indicators with varied coefficient adjustment for department types (platform or surgical). The application of this evaluation system in a Chinese hospital within the northeastern region yielded results aligning seamlessly with the actual operational scenario. In conclusion, the index system comprehensively considers the integrity and effectiveness of structural, process, and outcome indicators and stands as a comprehensive reflection of the collective expertise of the engaged experts, manifesting in a model designed to elevate the operational management of hospital departments. Its strategic alignment with healthcare payment reforms holds practical significance in guiding departmental development positioning, brand cultivation, and talent development.

Keywords: Chinese healthcare system, Delphi method, departmental management, evaluation indicators, hospital operations, weight coefficients

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Authors: Utsav Bhardwaj, Shyama Prasad Das

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To meet the extensive requirements of thermal management of the circuit card assemblies (CCAs), satellites, PCBs, microprocessors, any other electronic circuitry, pulsating heat pipes (PHPs) have emerged in the recent past as one of the best solutions technically. But industrial application of PHPs is still unexplored up to a large extent due to their poor reliability. There are several systems as well as operational parameters which not only affect the performance of an operating PHP, but also decide whether the PHP can operate sustainably or not. Functioning may completely be halted for some particular combinations of the values of system and operational parameters. Among the system parameters, adiabatic length is one of the important ones. In the present work, a simplest single branch PHP system with an adiabatic section has been considered. It is assumed to have only one vapour bubble and one liquid plug. First, the system has been mathematically modeled using film evaporation/condensation model, followed by the steps of recognition of equilibrium zone, non-dimensionalization and linearization. Then proceeding with a periodical solution of the linearized and reduced differential equations, stability analysis has been performed. Slow and fast variables have been identified, and averaging approach has been used for the slow ones. Ultimately, temporal evolution of the PHP is predicted by numerically solving the averaged equations, to know whether the oscillations are likely to sustain/decay temporally. Stability threshold has also been determined in terms of some non-dimensional numbers formed by different groupings of system and operational parameters. A combined analytical and numerical approach has been used, and it has been found that for each combination of all other parameters, there exists a maximum length of the adiabatic section beyond which the PHP cannot function at all. This length has been called as “Critical Adiabatic Length (L_ac)”. For adiabatic lengths greater than “L_ac”, oscillations are found to be always decaying sooner or later. Dependence of “L_ac” on some other parameters has also been checked and correlated at certain evaporator & condenser section temperatures. “L_ac” has been found to be linearly increasing with increase in evaporator section length (L_e), whereas the condenser section length (L_c) has been found to have almost no effect on it upto a certain limit. But at considerably large condenser section lengths, “L_ac” is expected to decrease with increase in “L_c” due to increased wall friction. Rise in static pressure (p_r) exerted by the working fluid reservoir makes “L_ac” rise exponentially whereas it increases cubically with increase in the inner diameter (d) of PHP. Physics of all such variations has been given a good insight too. Thus, a methodology for quantification of the critical adiabatic length for any possible set of all other parameters of PHP has been established.

Keywords: critical adiabatic length, evaporation/condensation, pulsating heat pipe (PHP), thermal management

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Authors: Nur Sahver Uslu, Ali̇ Hakan Büyüklü

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Maintenance, Repair, and Overhaul (MRO) costs are significant in the aviation industry. On the other hand, companies that provide MRO services to the aviation industry but are not dominant in the sector, need to determine the right strategies for sustainable profitability in a competitive environment. This study examined the operational real data of a small medium enterprise (SME) MRO company where analytical methods are not widely applied. The company's customers were divided into two categories: airline companies and non-airline companies, and the variables that best explained profitability were analyzed with Logistic Regression for each category and the results were compared. First, data reduction was applied to the transformed variables that went through the data cleaning and preparation stages, and the variables to be included in the model were decided. The misclassification rates for the logistic regression results concerning both customer categories are similar, indicating consistent model performance across different segments. Less profit margin is obtained from airline customers, which can be explained by the variables part description, time to quotation (TTQ), turnaround time (TAT), manager, part cost, and labour cost. The higher profit margin obtained from non-airline customers is explained only by the variables part description, part cost, and labour cost. Based on the two models, it can be stated that it is significantly more challenging for the MRO company, which is the subject of our study, to achieve profitability from Airline customers. While operational processes and organizational structure also affect the profit from airline customers, only the type of parts and costs determine the profit for non-airlines.

Keywords: aircraft, aircraft components, aviation, data analytics, data science, gini index, maintenance, repair, and overhaul, MRO, logistic regression, profit, variable clustering, variable reduction

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Authors: Abiodun Oluwaseun Ibude

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Every now and then we hear of companies closing down their operations due to unethical practices like an overstatement of company’s balance sheet, concealing company’s debt, embezzlement of company’s fund, declaring false profit and so on. This has led to the liquidation of companies and the loss of investments of shareholders as well as the interest of other stakeholders. As a result of these ugly trends, there is need to put in place a formidable mechanism that will ensure that business activities are conducted in a healthy manner. It should also promote good ethics as well as ensure that the interest of stakeholders and the objectives of any organization is achieved within the confines of the law; wherein law exists to provide criminal penalties for falsification of documents and for conducting other irregularities. Based on the foregoing, it becomes imperative to ensure that steps are taken to stop this menace and face the challenges ahead. This calls for the practice of good governance. The purpose of this study is to identify various components of corporate governance and determine the impact of it on the performance of established organizations. A survey method with the use of questionnaire was applied in collecting data useful for this study which were later analyzed using correlation co-efficiency statistical tools in generating finding, making a conclusion, and necessary recommendation. From the research conducted, it was discovered that there are systems within organizations apart from regulatory agencies that ensure effective control of activities, promote accountability, and operational efficiency. However, some members of organizations fail to explore the usage of corporate governance and impact negatively of an organization’s performance. In conclusion, good corporate governance will not be achieved unless there is openness, honesty, transparency, accountability, and fairness.

Keywords: corporate governance, formidable mechanism, company’s balance sheet, stakeholders

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Authors: Eldah Ephraim Buba

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The study is aimed at assessing the effect of maintenance practices on tourist patronage. Yankari resort and Safari had a patronage of twenty thousand, three hundred and two international and national tourists in two thousand and ten, fourteen thousand nine hundred and sixty two, in two thousand and eleven and ten thousand six hundred and one, in two thousand and twelve. The number of tourists keeps falling as the resort has been witnessing low patronage. Personal observation has shown that the state of facilities in the resort is bad. This study aims to appraise maintenance practices in the resort and how it affects tourist patronage. Standard checklist was used for the appraisal of facilities, while questionnaires were administered to tourists to examine whether maintenance practices in the resort do affect their patronage. Findings show that Operational maintenance was poorly carried out while repairs maintenance was fairly done. The study also discovered that there is significant relationship between maintenance practices and tourist patronage. It is recommended that adequate repairs and operational maintenance practices should be carried out in the resort to encourage tourist patronage.

Keywords: maintenance, practices, tourist, patronage

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Authors: Faisel Elramalli, Ibrahim Althomali Amjad Sabbagh, Dhananjay Tambe

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SPEC CPU benchmarks are used to evaluate the performance of CPUs on computer systems. In our project we are going to use SPEC CPU suite that contains several benchmarks running on two different compilers gcc and icc in different optimizations levels to evaluate the performance of a CPU. The motivation of this project is to find out which compiler and in which optimization level makes the CPU reaches the best performance. The results of that evaluation will help users of these compilers to choose the best compiler and optimization level that perform efficiently for their work. In other words, it will give users the best performance of the CPU while doing their works. This project is interesting since it will provide the method used to measure the performance of CPU and how different optimization levels of compilers can help achieve a higher performance. Moreover, it will give a good understanding of how benchmarks are used to evaluate a CPU performance. For the reader, in reality SPEC CPU benchmarks are used to measure the performance of new released CPUs to be compared to other CPUs.

Keywords: SPEC, CPU, GCC, ICC, copilers

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Authors: Arun Prasad Jaganathan

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In today's dynamic industrial world, traditional task allocation methods often fall short in adapting to evolving operational conditions. This paper introduces an AI-enabled task assistance and management system designed to overcome the limitations of conventional approaches. By using artificial intelligence (AI) and machine learning (ML), the system intelligently interprets user instructions, analyzes tasks, and allocates resources based on real-time data and environmental factors. Additionally, geolocation tracking enables proactive identification of potential delays, ensuring timely interventions. With its transparent reporting mechanisms, the system provides stakeholders with clear insights into task progress, fostering accountability and informed decision-making. The paper presents a comprehensive overview of the system architecture, algorithm, and implementation, highlighting its potential to revolutionize task management across diverse industries.

Keywords: artificial intelligence, machine learning, task allocation, operational efficiency, resource optimization

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Authors: Haniye Dehestani, Yadollah Ordokhani

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In this work, we present an efficient approach for solving variable-order time-fractional partial differential equations, which are based on Legendre and Laguerre polynomials. First, we introduced the pseudo-operational matrices of integer and variable fractional order of integration by use of some properties of Riemann-Liouville fractional integral. Then, applied together with collocation method and Legendre-Laguerre functions for solving variable-order time-fractional partial differential equations. Also, an estimation of the error is presented. At last, we investigate numerical examples which arise in physics to demonstrate the accuracy of the present method. In comparison results obtained by the present method with the exact solution and the other methods reveals that the method is very effective.

Keywords: collocation method, fractional partial differential equations, legendre-laguerre functions, pseudo-operational matrix of integration

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Authors: Shubham Jaiswal

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During modeling of transport phenomena in porous media, many nonlinear partial differential equations (NPDEs) encountered which greatly described the convection, diffusion and reaction process. To solve such types of nonlinear problems, a reliable and efficient technique is needed. In this article, the numerical solution of NPDEs encountered in porous media is derived. Here Jacobi collocation method is used to solve the considered problems which convert the NPDEs in systems of nonlinear algebraic equations that can be solved using Newton-Raphson method. The numerical results of some illustrative examples are reported to show the efficiency and high accuracy of the proposed approach. The comparison of the numerical results with the existing analytical results already reported in the literature and the error analysis for each example exhibited through graphs and tables confirms the exponential convergence rate of the proposed method.

Keywords: nonlinear porous media equation, shifted Jacobi polynomials, operational matrix, spectral collocation method

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Authors: Kamalendu Pal

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Supply chains are the spinal cord of trade and commerce. Their logistics use different transport corridors on regular basis for operational purpose. The international supply chain transport corridors include different infrastructure elements (e.g. weighbridge, package handling equipment, border clearance authorities, and so on) in supply chains. This paper presents the use of multi-agent systems (MAS) to model and simulate some aspects of transportation corridors, and in particular the area of weighbridge resource optimization for operational profit generation purpose. An underlying multi-agent model provides a means of modeling the relationships among stakeholders in order to enable coordination in a transport corridor environment. Simulations of the costs of container unloading, reloading, and waiting time for queuing up tracks have been carried out using data sets. Results of the simulation provide the potential guidance in making decisions about optimal service resource allocation in a trade corridor.

Keywords: multi-agent systems, simulation, supply chain, transport corridor, weighbridge

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Authors: Liang Zhao, Jili Zhang, Chongquan Zhong

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Energy consumption data, in particular those involving public buildings, are impacted by many factors: the building structure, climate/environmental parameters, construction, system operating condition, and user behavior patterns. Traditional methods for data analysis are insufficient. This paper delves into the data mining technology to determine its application in the analysis of building energy consumption data including energy consumption prediction, fault diagnosis, and optimal operation. Recent literature are reviewed and summarized, the problems faced by data mining technology in the area of energy consumption data analysis are enumerated, and research points for future studies are given.

Keywords: data mining, data analysis, prediction, optimization, building operational performance

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Authors: Kgabo H. Badimo, Sheryl Buckley

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Knowledge is increasingly recognised in this, the knowledge era, as a strategic resource, by public sector organisations, in view of the public sector reform initiatives. People and knowledge play a vital role in attaining improved organisational performance and high service quality. Many government departments in the public sector have started to realise the importance of knowledge management in streamlining their operations and processes. This study focused on knowledge management in the public healthcare service organisations, where the concept of service provider competitiveness pales to insignificance, considering the huge challenges emanating from the healthcare and public sector reforms. Many government departments are faced with challenges of improving organisational performance and service delivery, improving accountability, making informed decisions, capturing the knowledge of the aging workforce, and enhancing partnerships with stakeholders. The purpose of this paper is to examine the knowledge management practices of the Gauteng Department of Health in South Africa, in order to understand how knowledge management practices influence improvement in organisational performance and healthcare service delivery. This issue is explored through a review of literature on dominant views on knowledge management and healthcare service delivery, as well as results of interviews with, and questionnaire responses from, the general staff of the Gauteng Department of Health. Web-based questionnaires, face-to-face interviews and organisational documents were used to collect data. The data were analysed using both the quantitative and qualitative methods. The central question investigated was: To what extent can the conditions required for successful knowledge management be observed, in order to improve organisational performance and healthcare service delivery in the Gauteng Department of Health. The findings showed that the elements of knowledge management capabilities investigated in this study, namely knowledge creation, knowledge sharing and knowledge application, have a positive, significant relationship with all measures of organisational performance and healthcare service delivery. These findings thus indicate that by employing knowledge management principles, the Gauteng Department of Health could improve its ability to achieve its operational goals and objectives, and solve organisational and healthcare challenges, thereby improving organisational.

Keywords: knowledge management, Healthcare Service Delivery, public healthcare, public sector

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Authors: Ali Asheibi

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The rapid increase in the size of databases required to store power quality monitoring data has demanded new techniques for analysing and understanding the data. One suggested technique to assist in analysis is data mining. Preparing raw data to be ready for data mining exploration take up most of the effort and time spent in the whole data mining process. Clustering is an important technique in data mining and machine learning in which underlying and meaningful groups of data are discovered. Large amounts of harmonic data have been collected from an actual harmonic monitoring system in a distribution system in Australia for three years. This amount of acquired data makes it difficult to identify operational events that significantly impact the harmonics generated on the system. In this paper, harmonic data preparation processes to better understanding of the data have been presented. Underlying classes in this data has then been identified using clustering technique based on the Minimum Message Length (MML) method. The underlying operational information contained within the clusters can be rapidly visualised by the engineers. The C5.0 algorithm was used for classification and interpretation of the generated clusters.

Keywords: data mining, harmonic data, clustering, classification

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Authors: Mehmet Savsar

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This paper presents a practical case application of simulation modeling and analysis in a specific industrial setting. Various maintenance related parameters of the equipment in the system under consideration are determined and a simulation model is developed to study system behavior. System performance is determined based on established parameters and operational policies, which included system operation with and without preventive maintenance implementation. The results show that preventive maintenance practice has significant effects on improving system productivity. The simulation procedures outlined in this paper can be used by operation managers to perform production line analysis under different maintenance policies in various industrial settings.

Keywords: simulation, production line, machine failures, maintenance, industrial bakery

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Authors: Sahani Rathnasiri, Pritee Ray, Sardar M. N. Isalm, Carlos A. Vega-Mejia

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This study develops a cooperative game theory-based cost-sharing contract model for a business to consumer (B2C) e-commerce supply chain to minimize the overall supply chain costs and the individual costs within an information asymmetry scenario. The objective of this study is to address the issues of strategic interactions among the key players of the e-commerce supply chain operation, which impedes the optimal operational outcomes. Game theory has been included in the field of supply chain management to resolve strategic decision-making issues; however, most of the studies are limited only to two-echelons of the supply chains. Multi-echelon supply chain optimizations based on game-theoretic models are less explored in the previous literature. This study adopts a cooperative game model to focus on the common payoff of operations and addresses the issues of information asymmetry and coordination of a three-echelon e-commerce supply chain. The cost-sharing contract model integrates operational features such as production, inventory management and distribution with the contract related constraints. The outcomes of the model highlight the importance of maintaining lower operational costs by all players to obtain benefits from the cost-sharing contract. Further, the cost-sharing contract ensures true cost revelation, and hence eliminates the information asymmetry issues among the players. Comparing the results of the contract model with the de-centralized e-commerce supply chain operation further emphasizes that the cost-sharing contract derives Pareto-improved outcomes and minimizes the costs of overall e-commerce supply chain operation.

Keywords: cooperative game theory, cost-sharing contract, e-commerce supply chain, information asymmetry

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Authors: Vishal Kumar Singh

Abstract:

Bioprocess development is a time-constrained activity aimed at harnessing the full potential of culture performance in an ambience that is not natural to cells. Even with the use of chemically defined media and feeds, a significant amount of time is devoted in identifying the apt operating parameters. In addition, the scale-up of these processes is often accompanied by loss of antibody titer and product quality, which further delays the commercialization of the drug product. In such a scenario, the investigation of this disparity of culture performance is done by further experimentation at a smaller scale that is representative of at-scale production bioreactors. These scale-down model developments are also time-intensive. In this study, a computation fluid dynamics-based multi-objective scaling approach has been illustrated to speed up the process transfer. For the implementation of this approach, a transient multiphase water-air system has been studied in Ansys CFX to visualize the air bubble distribution and volumetric mass transfer coefficient (kLa) profiles, followed by the design of experiment based parametric optimization approach to define the operational space. The proposed approach is completely in silico and requires minimum experimentation, thereby rendering a high throughput to the overall process development.

Keywords: bioprocess development, scale up, scale down, computation fluid dynamics, multi-objective, Ansys CFX, design of experiment

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Authors: Shobhit Mittal

Abstract:

Headcount budgeting stands as a pivotal element in organizational financial management, extending beyond traditional budgeting to encompass strategic resource allocation for workforce-related expenses. This process is integral to maintaining financial stability and fostering a productive workforce, requiring a comprehensive analysis of factors such as market trends, business growth projections, and evolving workforce skill requirements. It demands a collaborative approach, primarily involving Human Resources (HR) and finance departments, to align workforce planning with an organization's financial capabilities and strategic objectives. The dynamic nature of headcount budgeting necessitates continuous monitoring and adjustment in response to economic fluctuations, business strategy shifts, technological advancements, and market dynamics. Its significance in talent management is also highlighted, aligning financial planning with talent acquisition and retention strategies to ensure a competitive edge in the market. The consequences of incorrect headcount budgeting are explored, showing how it can lead to financial strain, operational inefficiencies, and hindered strategic objectives. Examining case studies like IBM's strategic workforce rebalancing and Microsoft's shift for long-term success, the importance of aligning headcount budgeting with organizational goals is underscored. These examples illustrate that effective headcount budgeting transcends its role as a financial tool, emerging as a strategic element crucial for an organization's success. This necessitates continuous refinement and adaptation to align with evolving business goals and market conditions, highlighting its role as a key driver in organizational success and sustainability.

Keywords: strategic planning, fiscal budget, headcount planning, resource allocation, financial management, decision-making, operational efficiency, risk management, headcount budget

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Authors: Chuan Yang, Jing Bie, Yueh-Lung Lin, Zhong Wang

Abstract:

Transportation planning is an academic integration discipline combining research and practice with the aim of mobility and accessibility improvements at both strategic-level policy-making and operational dimensions of practical planning. Transportation planning could build the linkage between traffic and social development goals, for instance, economic benefits and environmental sustainability. The transportation planning analysis and evaluation tend to apply empirical quantitative approaches with the guidance of the fundamental principles, such as efficiency, equity, safety, and sustainability. Space syntax theory has been applied in the spatial distribution of pedestrian movement or vehicle flow analysis, however rare has been written about its application in transportation planning. The correlated relationship between the variables of space syntax analysis and authentic observations have declared that the urban configurations have a significant effect on urban dynamics, for instance, land value, building density, traffic, crime. This research aims to explore the potentials of applying Space Syntax methodology to evaluate urban transportation planning through studying the effects of urban configuration on cities transportation performance. By literature review, this paper aims to discuss the effects that urban configuration with different degrees of integration and accessibility have on three elementary components of transportation planning - transportation efficiency, transportation safety, and economic agglomeration development - via intensifying and stabilising the nature movements generated by the street network. And then the potential and limits of Space Syntax theory to study the performance of urban transportation and transportation planning would be discussed in the paper. In practical terms, this research will help future research explore the effects of urban design on transportation performance, and identify which patterns of urban street networks would allow for most efficient and safe transportation performance with higher economic benefits.

Keywords: transportation planning, space syntax, economic agglomeration, transportation efficiency, transportation safety

Procedia PDF Downloads 189