Search results for: permanent magnet machines performance

Authors: Florin Leon, Silvia Curteanu

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Developing complete mechanistic models for polymerization reactors is not easy, because complex reactions occur simultaneously; there is a large number of kinetic parameters involved and sometimes the chemical and physical phenomena for mixtures involving polymers are poorly understood. To overcome these difficulties, empirical models based on sampled data can be used instead, namely regression methods typical of machine learning field. They have the ability to learn the trends of a process without any knowledge about its particular physical and chemical laws. Therefore, they are useful for modeling complex processes, such as the free radical polymerization of methyl methacrylate achieved in a batch bulk process. The goal is to generate accurate predictions of monomer conversion, numerical average molecular weight and gravimetrical average molecular weight. This process is associated with non-linear gel and glass effects. For this purpose, an adaptive sampling technique is presented, which can select more samples around the regions where the values have a higher variation. Several machine learning methods are used for the modeling and their performance is compared: support vector machines, k-nearest neighbor, k-nearest neighbor and random forest, as well as an original algorithm, large margin nearest neighbor regression. The suggested method provides very good results compared to the other well-known regression algorithms.

Keywords: batch bulk methyl methacrylate polymerization, adaptive sampling, machine learning, large margin nearest neighbor regression

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Authors: Ummu Salma Al Azizah, Herri Mulyono, Anisa Mauliata Suryana

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The significance of corporate governance regarding to the agency problem have been transparent. This study examine the impact of corporate governance on the performance of Islamic banking in Indonesia. By using fixed effect model and added some control variable, the current study try to explore the correlation between the theoretical framework on corporate governance, such as agency theory and risk management theory. The bank performance (Return on Asset and Return on Equity) which are operational performance and financial performance. And Corporate governance based on Board size, CEO duality, Audit committee and Shariah supervisory board. The limitation of this study only focus on the Islamic banks performance from year 2015 to 2020. The study fill the gap in the literature by addressing the issue of corporate governance on Islamic banks performance in Indonesia.

Keywords: corporate governance, financial performance, islamic banks, listed companies, Indonesia

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Authors: Marcin Zieliński, Marcin Dębowski, Mirosław Krzemieniewski

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This publication presents a device designed for mechanical fragmentation of plant substrate before methane fermentation. The device is equipped with a perforated rotary cylindrical drum coated with a thermal layer, connected to a substrate feeder and driven by a motoreducer. The drum contains ball- or cylinder-shaped weights of different diameters, while its interior is mounted with lateral permanent magnets with an attractive force ranging from 100 kg to 2 tonnes per m2 of the surface. Over the perforated rotary drum, an infrared radiation generator is mounted, producing 0.2 kW to 1 kW of infrared radiation per 1 m2 of the perforated drum surface. This design reduces the energy consumption required for the biomass destruction process by 10-30% in comparison to the conventional ball mill. The magnetic field generated by the permanent magnets situated within the perforated rotary drum promotes this process through generation of free radicals that act as powerful oxidants, accelerating the decomposition rate. Plant substrate shows increased susceptibility to biodegradation when subjected to magnetic conditioning, reducing the time required for biomethanation by 25%. Additionally, the electromagnetic radiation generated by the radiator improves substrate destruction by 10% and the efficiency of the process. The magnetic field and the infrared radiation contribute synergically to the increased efficiency of destruction and conversion of the substrate.

Keywords: biomass pretreatment, mechanical fragmentation, biomass, methane fermentation

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Authors: Kwong Yeung

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Theories about strategic purchasing and quality performance are underdeveloped. Understanding the evolving role of purchasing from reactive to proactive is a pressing strategic issue. Using survey responses from 176 manufacturing and electronics industry professionals, we study the relationships between strategic purchasing and supply chain partners’ quality performance to answer the following questions: Can transaction cost economics be used to elucidate the strategic purchasing-quality performance relationship? Is this strategic purchasing-quality performance relationship moderated by critical item analysis? The findings indicate that critical item analysis positively and significantly moderates the strategic purchasing-quality performance relationship.

Keywords: critical item analysis, moderation, quality performance, strategic purchasing, transaction cost economics

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Authors: Kari M. Solomon

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Companies with a culture accepting of change management and performance excellence are better suited to determine their sustainability performance and impacts. A mature corporate culture supportive of performance excellence is better positioned to integrate sustainability management tools into their standard business strategy. Companies use various sustainability management tools and reporting standards to communicate levels of sustainability performance to their stakeholders, more often focusing on shareholders and investors. A research gap remains in understanding how companies adapt business excellence models to define corporate sustainability performance. A content analysis of medium-sized enterprises using corporate sustainability reports and business excellence models reveals the challenges and opportunities of reporting sustainability performance in the context of organizational excellence. The outcomes of this content analysis contribute knowledge on the resources needed for companies to build sustainability performance management systems integral to existing management systems. The findings of this research inform academic research areas of corporate sustainability performance, the business community contributing to sustainable development initiatives, and integrating sustainable development issues into business excellence models. There are potential research links between sustainability performance management and the alignment of the United Nations Sustainable Development Goals (UN SDGs) when organizations promote a culture of performance or business excellence.

Keywords: business excellence, corporate sustainability, performance excellence, sustainability performance

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Authors: Dixit Garg, S. Luthra, A. Haleem

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During recent years, the natural environment has become a challenging topic that business organizations must consider due to the economic and ecological impacts and increasing awareness of environment protection among society. Organizations are trying to achieve the goals of improvement in environment, low cost, high quality, flexibility and more customer satisfaction. Performance measurement frameworks are very useful to monitor the performance of any organization. The basic goal of this paper is to identify performance measures and ranking of these performance measures of GSCM performance measurement towards sustainability framework. Five perspectives (Environment, Economic, Social, Operational and Cost performances) and nineteen performance measures of GSCM performance towards sustainability have been have been identified from extensive literature review. Analytical Hierarchy Process (AHP) technique has been utilized for ranking of these performance perspectives and measures. All pair comparisons in AHP have been made on the basis on the experts’ opinions (selected from academia and industry). Ranking of these performance perspectives and measures will help to understand the importance of environmental, economic, social, operational performances, and cost performances in the supply chain.

Keywords: analytical hierarchy process, green supply chain management, performance measures, sustainability

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Authors: Ayan Giri, Lukaranjan Phukan, Shantanu Karmakar

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Structure and tectonics play a vital role in ore genesis and deposition. The existence of a swelling structure below the current level of a mine leads to the discovery of ores below some permeant developments of the mine. The discovery and the extraction of the ore body are very critical to sustain the business requirement of the mine. The challenge was to extract the ore without hampering the global stability of the mine. In order to do so, different mining options were considered and analysed by numerical modelling in FLAC3d software. The constitutive model prepared for this simulation is the improved unified constitutive model, which can better and more accurately predict the stress-strain relationships in a continuum model. The IUCM employs the Hoek-Brown criterion to determine the instantaneous Mohr-Coulomb parameters cohesion (c) and friction (ɸ) at each level of confining stress. The extra swelled part can be dimensioned as north-south strike width 50m, east-west strike width 50m. On the north side, already a stope (P1) is excavated of the dimension of 25m NS width. The different options considered were (a) Open stoping of extraction of southern part (P0) of 50m to the full extent, (b) Extraction of the southern part of 25m, then filling of both the primaries and extraction of secondary (S0) 25m in between. (c) Extraction of the southern part (P0) completely, preceded by backfill and modify the design of the secondary (S0) for the overall stability of the permanent excavation above the stoping.

Keywords: extraction, IUCM, FLAC 3D, stoping, tectonics

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Authors: S. Ghoudelbourk, A. Omeiri, D. Dib, H. Cheghib

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This paper shows that we can improve the performance of the auto-adjustable electric machines if a fractional dynamic is considered in the algorithm of the controlling order. This structure is particularly interested in the separate control of active and reactive power of the double-fed induction generator (DFIG) of wind power conversion chain. Fractional regulators are used in the regulation of chain of powers. Knowing that, usually, the source of DFIG is provided by converters through controlled rectifiers, all this system makes the currents of lines strongly polluted that can have a harmful effect for the connected loads and sensitive equipment nearby. The solution to overcome these problems is to replace the power of the rotor DFIG by multilevel inverters supplied by PV which improve the THD. The structure of the adopted adjustment is tested using Matlab/Simulink and the results are presented and analyzed for a variable wind.

Keywords: DFIG, fractional regulator, multilevel inverters, PV

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Authors: Chirawat Wattanapanich, Hong Wei

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This study presents new gait representations for improving gait recognition accuracy on cross gait appearances, such as normal walking, wearing a coat and carrying a bag. Based on the Gait Energy Image (GEI), two ideas are implemented to generate new gait representations. One is to append lower knee regions to the original GEI, and the other is to apply convolutional operations to the GEI and its variants. A set of new gait representations are created and used for training multi-class Support Vector Machines (SVMs). Tests are conducted on the CASIA dataset B. Various combinations of the gait representations with different convolutional kernel size and different numbers of kernels used in the convolutional processes are examined. Both the entire images as features and reduced dimensional features by Principal Component Analysis (PCA) are tested in gait recognition. Interestingly, both new techniques, appending the lower knee regions to the original GEI and convolutional GEI, can significantly contribute to the performance improvement in the gait recognition. The experimental results have shown that the average recognition rate can be improved from 75.65% to 87.50%.

Keywords: convolutional image, lower knee, gait

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Authors: Yang-Kuei Lin, Yun-Xi Zhang

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This research focuses on the bicriteria correlated parallel machine scheduling problem. The two objective functions considered in this problem are to minimize maximum lateness and total weighted completion time. We first present a mixed integer programming (MIP) model that can find the entire efficient frontier for the studied problem. Next, we have proposed a bicriteria heuristic that can find non-dominated solutions for the studied problem. The performance of the proposed bicriteria heuristic is compared with the efficient frontier generated by solving the MIP model. Computational results indicate that the proposed bicriteria heuristic can solve the problem efficiently and find a set of diverse solutions that are uniformly distributed along the efficient frontier.

Keywords: bicriteria, correlated parallel machines, heuristic, scheduling

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Authors: Kevin Fernagut, Olivier Flauzac, Erick M. G. Robledo, Florent Nolot

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The adoption of modern lightweight virtualization often comes with new threats and network vulnerabilities. This paper seeks to assess this with a different approach studying the behavior of a testbed built with tools such as Kernel-Based Virtual Machine (KVM), Linux Containers (LXC) and Docker, by performing stress tests within a platform where students experiment simultaneously with cyber-attacks, and thus observe the impact on the campus network and also find the best solution for cyber-security learning. Interesting outcomes can be found in the literature comparing these technologies. It is, however, difficult to find results of the effects on the global network where experiments are carried out. Our work shows that other physical hosts and the faculty network were impacted while performing these trials. The problems found are discussed, as well as security solutions and the adoption of new network policies.

Keywords: containerization, containers, cybersecurity, cyberattacks, isolation, performance, virtualization, virtual machines

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Authors: Amlan Kumar Das, Avinash Marwal, Vikram Pareek

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Liposome plays an important role in medical and pharmaceutical science as e.g. nano scale drug carriers. Liposomes are vesicles of varying size consisting of a spherical lipid bilayer and an aqueous inner compartment. Magnet-driven liposome used for the targeted delivery of drugs to organs and tissues1. These liposome preparations contain encapsulated drug components and finely dispersed magnetic particles. Liposomes are vesicles of varying size consisting of a spherical lipid bilayer and an aqueous inner compartment that are generated in vitro. These are useful in terms of biocompatibility, biodegradability, and low toxicity, and can control biodistribution by changing the size, lipid composition, and physical characteristics2. Furthermore, liposomes can entrap both hydrophobic and hydrophilic drugs and are able to continuously release the entrapped substrate, thus being useful drug carriers. Magnetic liposomes (MLs) are phospholipid vesicles that encapsulate magneticor paramagnetic nanoparticles. They are applied as contrast agents for magnetic resonance imaging (MRI)3. The biological synthesis of nanoparticles using plant extracts plays an important role in the field of nanotechnology4. Green-synthesized magnetite nanoparticles-protein hybrid has been produced by treating Iron (III)/Iron(II) chloride with the leaf extract of Dhatura Inoxia. The phytochemicals present in the leaf extracts act as a reducing as well stabilizing agents preventing agglomeration, which include flavonoids, phenolic compounds, cardiac glycosides, proteins and sugars. The magnetite nanoparticles-protein hybrid has been trapped inside the aqueous core of the liposome prepared by reversed phase evaporation (REV) method using oleic and linoleic acid which has been shown to be driven under magnetic field confirming the formation magnetic liposome (ML). Chemical characterization of stealth magnetic liposome has been performed by breaking the liposome and release of magnetic nanoparticles. The presence iron has been confirmed by colour complex formation with KSCN and UV-Vis study using spectrophotometer Cary 60, Agilent. This magnet driven liposome using nanoparticles-protein hybrid can be a smart vesicles for the targeted drug delivery.

Keywords: nanoparticles-protein hybrid, magnetic liposome, medical, pharmaceutical science

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Authors: Sheng-Ching Wu

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This paper examines the interaction between mutual fund performance and portfolio turnover. Active trading could affect fund performance, but underperforming funds could also be traded actively at the same time to perform well. Therefore, we used two-stage least squares to address with simultaneity. The results indicate that funds with higher portfolio turnovers exhibit inferior performance compared with funds having lower turnovers. Moreover, funds with poor performance exhibit higher portfolio turnover. The findings support the assumptions that active trading erodes performance, and that fund managers with poor performance attempt to trade actively to retain employment.

Keywords: mutual funds, portfolio turnover, simultaneity, two-stage least squares

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Authors: Suleiman Ahmed Badayi

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Corporate governance literature is very wide and involves several empirical studies conducted on the relationship between board structure, composition and firm performance. The separation of ownership and control in organizations were aimed at reducing the losses suffered by the investors in the event of financial scandals. This paper reviewed the theoretical and empirical literature on the relationship between board composition and its impact on firm performance. The findings from the studies provide different results while some are of the view that board structure is related to firm performance, many empirical studies indicates no relationship. However, others found a U-shape relationship between firm performance and board structure. Therefore, this study argued that board structure is not much significant to determine the financial performance of a firm.

Keywords: board structure, composition, firm performance, corporate governance

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Authors: Juang R. Matangaran, Erianto I. Putra, Iis Diatin, Muhammad Mujahid, Qi Adlan

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Industrial plantation forest is the producer of logs in Indonesia. Several companies of industrial plantation forest have been successfully planted with fast-growing species, and it entered their annual harvesting period. Heavy machines such as forwarders are used in timber harvesting to extract logs from stump to landing site. The negative impact of using such machines are loss of topsoil and soil compaction. Compacted soil is considered unfavorable for plant growth. The research objectives were to analyze the soil bulk density, rut, and cone index of the soil caused by a forwarder passes, to analyze the relation between several times of forwarder passes to the increase of soil bulk density. A Valmet forwarder was used in this research. Soil bulk density at soil surface and cone index from the soil surface to the 50 cm depth of soil were measured at the harvested area. The result showed that soil bulk density increase with the increase of the Valmet forwarder passes. Maximum soil bulk density occurred after 5 times forwarder Valmet passed. The cone index tended to increase from the surface until 50 cm depth of soil. Rut formed and high soil bulk density indicated the soil compaction occurred by the forwarder operation.

Keywords: bulk density, forwarder Valmet, plantation forest, soil compaction, timber harvesting

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Authors: Sultan Mahmud, Qamar Zaman, Travis Esau, Young Chang

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Strawberry powdery mildew (PM) is a serious disease that has a significant impact on strawberry production. Field scouting is still a major way to find PM disease, which is not only labor intensive but also almost impossible to monitor disease severity. To reduce the loss caused by PM disease and achieve faster automatic detection of the disease, this paper proposes an approach for detection of the disease, based on image texture and classified with support vector machines (SVMs) and k-nearest neighbors (kNNs). The methodology of the proposed study is based on image processing which is composed of five main steps including image acquisition, pre-processing, segmentation, features extraction and classification. Two strawberry fields were used in this study. Images of healthy leaves and leaves infected with PM (Sphaerotheca macularis) disease under artificial cloud lighting condition. Colour thresholding was utilized to segment all images before textural analysis. Colour co-occurrence matrix (CCM) was introduced for extraction of textural features. Forty textural features, related to a physiological parameter of leaves were extracted from CCM of National television system committee (NTSC) luminance, hue, saturation and intensity (HSI) images. The normalized feature data were utilized for training and validation, respectively, using developed classifiers. The classifiers have experimented with internal, external and cross-validations. The best classifier was selected based on their performance and accuracy. Experimental results suggested that SVMs classifier showed 98.33%, 85.33%, 87.33%, 93.33% and 95.0% of accuracy on internal, external-I, external-II, 4-fold cross and 5-fold cross-validation, respectively. Whereas, kNNs results represented 90.0%, 72.00%, 74.66%, 89.33% and 90.3% of classification accuracy, respectively. The outcome of this study demonstrated that SVMs classified PM disease with a highest overall accuracy of 91.86% and 1.1211 seconds of processing time. Therefore, overall results concluded that the proposed study can significantly support an accurate and automatic identification and recognition of strawberry PM disease with SVMs classifier.

Keywords: powdery mildew, image processing, textural analysis, color co-occurrence matrix, support vector machines, k-nearest neighbors

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Authors: Sara Najiazarpour, Mahsa Najiazarpour

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There are many problems in contracting projects and their performance. At each project stage and due to different reasons, these problems affect cost, time and overall project quality. Hence, in order to increase the efficiency and performance in all levels of the chain and with supply chain management approach, there will be a coordination from the beginning of a project (contractor selection) to the end of project (handover of project). Contractor selection is the foremost part of construction projects which in this multi-criteria decision-making, the best contractor is determined by expert judgment, different variables and their priorities. In this paper for selecting the best contractor, numerous criteria were collected by asking from adept experts and then among them, 16 criteria with highest frequency were considered for questionnaire. This questionnaire was distributed between experts. Cronbach's alpha coefficient was obtained as 72%. Then based on Borda's function 12 important criteria was selected which was categorized in four main criteria and related sub-criteria as follow: Environmental factors and physical equipment: procurement and materials (supplier), company's machines, contractor’s proposed cost estimate - financial capacity: bank turnover and company's assets, the income of tax declaration in last year, Ability to compensate for losses or delays - past performance- records and technical expertise: experts and key personnel, the past technical backgrounds and experiences, employer satisfaction of previous contracts, the number of similar projects was done - standards: rank and field of expertise which company is qualified for and its validity, availability and number of permitted projects done. Then with PROMTHEE method, the criteria were normalized and monitored, finally the best alternative was selected. In this research, qualitative criteria of each company is became a quantitative criteria. Finally, information of some companies was evaluated and the best contractor was selected based on all criteria and their priorities.

Keywords: contractor evaluation and selection, project development, supply chain management, PROMTHEE method

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Authors: Chandan Jha, Amit Sachan, Arnab Adhikari, Sayantan Kundu

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The purpose of this study is to evaluate the performance of Higher Education Institutions (HEIs) of India and examine the impact of urbanization on the performance of HEIs. In this study, the Data Envelopment Analysis (DEA) has been used, and the authors have collected the required data related to performance measures from the National Institutional Ranking Framework web portal. In this study, the authors have evaluated the performance of HEIs by using two different DEA models. In the first model, geographic locations of the institutes have been categorized into two categories, i.e., Urban Vs. Non-Urban. However, in the second model, these geographic locations have been classified into three categories, i.e., Urban, Semi-Urban, Non-Urban. The findings of this study provide several insights related to the degree of urbanization and the performance of HEIs.

Keywords: DEA, higher education, performance evaluation, urbanization

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Authors: Ambra Giovannelli, Erika Maria Archilei

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The electrical power consumption related to refrigeration systems is evaluated to be in the order of 15% of the total electricity consumption worldwide. For this reason, in the last years several energy saving techniques have been suggested to reduce the power demand of refrigeration and air conditioning plants. The research work deals with the development of an innovative internal power recovery system for industrial cryogenic cooling plants. Such system is based on a Compressor-Expander Group (CEG). Both the expander and the compressor have been designed starting from automotive turbocharging components, strongly modified to take refrigerant fluid properties and specific system requirements into consideration. A preliminary choice of the machines (radial compressors and expanders) among existing components available on the market was realised according to the rules of the similarity theory. Once the expander was selected, it was strongly modified and performance verified by means of steady-state 3D CFD simulations. This paper focuses the attention on the development of the second CEG main component: the compressor. Once the preliminary selection has been done, the compressor geometry has been modified to take the new boundary conditions into account. In particular, the impeller has been machined to address the required total enthalpy increase. Such evaluation has been carried out by means of a simplified 1D model. Moreover, a vaneless diffuser has been added, modifying the shape of casing rear and front disks. To verify the performance of the modified compressor geometry and suggest improvements, a numerical fluid dynamic model has been set up and the commercial Ansys-CFX software has been used to perform steady-state 3D simulations. In this work, all the numerical results will be shown, highlighting critical aspects and suggesting further developments to increase compressor performance and flexibility.

Keywords: vapour compression systems, energy saving, refrigeration plant, organic fluids, centrifugal compressor

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Authors: Ka C. Lam, Oluwafunmibi S. Idowu

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Uncertainty in cost is a major factor affecting performance of construction projects. To our knowledge, several conceptual cost models have been developed with varying degrees of accuracy. Incorporating conceptual quantities into conceptual cost models could improve the accuracy of early predesign cost estimates. Hence, the development of quantity models for estimating conceptual quantities of framed reinforced concrete structures using supervised machine learning is the aim of the current research. Using measured quantities of structural elements and design variables such as live loads and soil bearing pressures, response and predictor variables were defined and used for constructing conceptual quantities models. Twenty-four models were developed for comparison using a combination of non-parametric support vector regression, linear regression, and bootstrap resampling techniques. R programming language was used for data analysis and model implementation. Gross soil bearing pressure and gross floor loading were discovered to have a major influence on the quantities of concrete and reinforcement used for foundations. Building footprint and gross floor loading had a similar influence on beams and slabs. Future research could explore the modelling of other conceptual quantities for walls, finishes, and services using machine learning techniques. Estimation of conceptual quantities would assist construction planners in early resource planning and enable detailed performance evaluation of early cost predictions.

Keywords: bootstrapping, conceptual quantities, modelling, reinforced concrete, support vector regression

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Authors: Ljubica Milanović Glavan, Vesna Bosilj Vukšić, Dalia Suša

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In order to gain a competitive advantage, many companies are focusing on reorganization of their business processes and implementing process-based management. In this context, assessing process performance is essential because it enables individuals and groups to assess where they stand in comparison to their competitors. In this paper, it is argued that process performance measurement is a necessity for a modern process-oriented company and it should be supported by a holistic process performance measurement system. It seems very unlikely that a universal set of performance indicators can be applied successfully to all business processes. Thus, performance indicators must be process-specific and have to be derived from both the strategic enterprise-wide goals and the process goals. Based on the extensive literature review and interviews conducted in Croatian company a conceptual framework for process performance measurement system was developed. The main objective of such system is to help process managers by providing comprehensive and timely information on the performance of business processes. This information can be used to communicate goals and current performance of a business process directly to the process team, to improve resource allocation and process output regarding quantity and quality, to give early warning signals, to make a diagnosis of the weaknesses of a business process, to decide whether corrective actions are needed and to assess the impact of actions taken.

Keywords: Croatia, key performance indicators, performance measurement, process performance

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Authors: Naci Büyükkaraciğan, Yildirim Akyol

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Large plants that covering the back and accumulate water of a river valley for energy production, drinking, irrigation water supply, economic benefits that serve many purposes, such as regulation of flood protection, are called dams. Place, in which unites in order to achieve an optimum balance between manpower for Lowest cost and economic as belonging to that structure to create machines, materials and construction of the project, is called as the site. Dam construction sites are combined sites in together in many businesses. Therefore, there can be found in the many workers and machines are many accidents in this type of construction sites. The necessity of systematic and scientific studies due to various reasons arises in order to be protected from conditions that could damage the health, During the execution of the work on construction sites. Occupational health and safety of the study, called the case, also in the European Union has begun to be addressed by weight since the 1980s. In particular, issued in 1989 89/391/EEC on occupational health and safety directive, occupational health and adopted the Directive within the framework of the security field, and then exposed to a large number of individual directive within this framework on the basis of the directive. Turkey's Law No. 6331 entered into force in June 2012 on the subject. In this study, measures related to the construction site of the dam should be taken with occupational safety and health have been examined and tried to put forward recommendations on the subject.

Keywords: civil engineering, dam, occupational safety and health, site organizations

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Authors: Duc V. Nguyen

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Induction motors are widely used in different industry areas and can experience various kinds of faults in stators and rotors. In general, fault detection and diagnosis techniques for induction motors can be supervised by measuring quantities such as noise, vibration, and temperature. The installation of mechanical sensors in order to assess the health conditions of a machine is typically only done for expensive or load-critical machines, where the high cost of a continuous monitoring system can be Justified. Nevertheless, induced current monitoring can be implemented inexpensively on machines with arbitrary sizes by using current transformers. In this regard, effective and low-cost fault detection techniques can be implemented, hence reducing the maintenance and downtime costs of motors. This work proposes a method for fault detection and diagnosis of induction motors, which combines classical fast Fourier transform and modern/advanced machine learning techniques. The proposed method is validated on real-world data and achieves a precision of 99.7% for fault detection and 100% for fault classification with minimal expert knowledge requirement. In addition, this approach allows users to be able to optimize/balance risks and maintenance costs to achieve the highest benet based on their requirements. These are the key requirements of a robust prognostics and health management system.

Keywords: fault detection, FFT, induction motor, predictive maintenance

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Authors: Nooralhuda Aljlas

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In the ever-growing field of non-governmental organizations, the enhancement of performance management and measurement systems has been increasingly acknowledged by political, economic, social, legal, technological and environmental factors. Within Bahrain Athletics Association, such enhancement results from the key factors leading performance management including collaboration, feedback, human resource management, leadership and participative management. The exploratory, qualitative research conducted reviewed performance management theory. As reviewed, the key factors leading performance management were identified. Drawing on a non-governmental organization case study, the key factors leading Bahrain Athletics Association’s performance management were explored. By exploring the key factors leading Bahrain Athletics Association’s performance management, the research study proposed a theoretical framework of the key factors leading performance management in non-governmental organizations in general. The research study recommended further investigation of the role of the two key factors of command and control and leadership, combining military and civilian approaches to enhancing non-governmental organizations’ performance management.

Keywords: Bahrain athletics association, exploratory, key factor, performance management

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Authors: Hideki Igawa, Yoshinori Kitsutaka, Takashi Yokomuro, Hideo Eguchi

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In this study, the crack self-healing performance of the heavyweight concrete used in the walls of containers and structures designed to shield radioactive materials was investigated. A steam curing temperature that preserves self-healing properties and demolding strength was identified. The presented simultaneously mixing method using the expanding material and the fly ash in the process of admixture can maximize the self-curing performance. Also adding synthetic fibers in the heavyweight concrete improved the self-healing performance.

Keywords: expanding material, heavyweight concrete, self-healing performance, synthetic fiber

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Authors: Nyeng P. Gyang

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Even though past, current and future trends suggest that multicore and cloud computing systems are increasingly prevalent/ubiquitous, this class of parallel systems is nonetheless underutilized, in general, and barely used for research on employing parallel Delaunay triangulation for parallel surface modeling and generation, in particular. The performances, of actual/physical and virtual/cloud multicore systems/machines, at executing various algorithms, which implement various parallelization strategies of the incremental insertion technique of the Delaunay triangulation algorithm, were evaluated. T-tests were run on the data collected, in order to determine whether various performance metrics differences (including execution time, speedup and efficiency) were statistically significant. Results show that the actual machine is approximately twice faster than the virtual machine at executing the same programs for the various parallelization strategies. Results, which furnish the scalability behaviors of the various parallelization strategies, also show that some of the differences between the performances of these systems, during different runs of the algorithms on the systems, were statistically significant. A few pseudo superlinear speedup results, which were computed from the raw data collected, are not true superlinear speedup values. These pseudo superlinear speedup values, which arise as a result of one way of computing speedups, disappear and give way to asymmetric speedups, which are the accurate kind of speedups that occur in the experiments performed.

Keywords: cloud computing systems, multicore systems, parallel Delaunay triangulation, parallel surface modeling and generation

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Authors: Joseph Akyeh, Abdul Samed Muntaka, Emmanuel Anin, Dorcas Nuertey

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Purpose: This study develops and tests arguments that the relationship between technology alignment and supply chain performance is conditional upon levels of technology championing. Methodology: The proposed relationships are tested on a sample of 217 hospitals in a major sub-Saharan African economy. Findings: Findings from the study indicate that technology alignment has a positive and significant effect on supply chain performance. The study further finds that while technology championing strengthens the direct effects of technology alignment on supply chain performance. Theoretical Contributions: A theoretical contribution from this study is the finding that when technology alignment drives supply chain performance is more complex than previously thought it depends on whether or not technology alignment is first championed by top management. Originality: Though some studies have been conducted on technology alignment and health supply chain performance, to the best of the researcher’s knowledge, no previous study has examined the moderating role of technology championing the link between technology alignment and supply chain performance.

Keywords: technology alignment, supply chain performance, technology championing, structural equation modelling

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Authors: Marion Francisco

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The study sought to investigate the psychological capital and work engagement of employees as predictors of employee performance in the technology industry in Makati City. It made used of a descriptive correlational method of research and utilized standardized tests, such as Psychological Capital Scale, Utrech Work Engagement Scale, and Employee Performance Scale. A convenience sampling technique was used to gather data samples from 100 populations with the help of Roscoe concept approach. The study revealed that both psychological capital and work engagement have a significant relationship with employee performance. Psychological capital and work engagement can predict employee performance of the respondents. With the results given, the study suggests: (1) to focus on maintaining a high level of psychological capital and work engagement, on achieving a very high level of psychological capital and work engagement, and on improving the low level of psychological capital or work engagement mostly during this COVID-19 pandemic using the proposed employee performance management plan and (2) to create a proposed employee performance management plan as necessary to tailor fit on employees needs to enhance their performance that will help meet company and client’s needs.

Keywords: employee performance, performance management, psychological capital, technology industry, work engagement

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Authors: Yoon Suh Song

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Though music education can broaden one’s capacity for mathematical performance, many countries lag behind in music education. Little empirical evidence is found to identify the connection between math and music. Therefore, this research was set out to explore what music-related variables are associated with mathematical performance. The result of our analysis is as follows: A Pearson's Correlation analysis revealed that PISA math score is strongly correlated with students' Intelligence Quotient (IQ). This lays the foundation for further research as to what factors in students’ IQ lead to a better performance in math.

Keywords: music education, mathematical performance, education, IQ

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Authors: Nikhil Byanna, Abdolghani Ebrahimi, Diego Klabjan

Abstract:

How does one objectively measure the performance of an individual offensive lineman in the NFL? The existing literature proposes various measures that rely on subjective assessments of game film, but has yet to develop an objective methodology to evaluate performance. Using a variety of statistics related to an offensive lineman’s performance, we develop a framework to objectively analyze the overall performance of an individual offensive lineman and determine specific linemen who are overvalued or undervalued relative to their salary. We identify eight players across the 2013-2014 and 2014-2015 NFL seasons that are considered to be overvalued or undervalued and corroborate the results with existing metrics that are based on subjective evaluation. To the best of our knowledge, the techniques set forth in this work have not been utilized in previous works to evaluate the performance of NFL players at any position, including offensive linemen.

Keywords: offensive lineman, player performance, NFL, machine learning

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