Search results for: wireless performance analysis

Authors: Hyun-Woo Cho

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Detection of incipient abnormal events in production processes is important to improve safety and reliability of manufacturing operations and reduce losses caused by failures. The construction of calibration models for predicting faulty conditions is quite essential in making decisions on when to perform preventive maintenance. This paper presents a multivariate calibration monitoring approach based on the statistical analysis of process measurement data. The calibration model is used to predict faulty conditions from historical reference data. This approach utilizes variable selection techniques, and the predictive performance of several prediction methods are evaluated using real data. The results shows that the calibration model based on supervised probabilistic model yielded best performance in this work. By adopting a proper variable selection scheme in calibration models, the prediction performance can be improved by excluding non-informative variables from their model building steps.

Keywords: calibration model, monitoring, quality improvement, feature selection

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Authors: Bella Llego

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The purpose of this study was to explain and empirically test the influence of attitude towards work, job satisfaction and organizational commitment of SSRU employee’s evaluation and performance. Data used in this study was primary data which were collected through Organizational Commitment Questionnaire with 1-5 Likert Scale. The respondent of this study was 200 managerial and non-managerial staff of SSRU. The statistics to analyze the data provide the descriptive by the mean, standard deviation and test hypothesis by the use of multiple regression. The result of this study is showed that attitude towards work have positive but not significant effect to job satisfaction and employees evaluation and performance. Different with attitude towards work, the organizations commitment has positive and significant influence on job satisfaction and employee performance at SSRU. It means every improvement in organization’s commitment has a positive effect toward job satisfaction and employee evaluation and performance at SSRU.

Keywords: attitude towards work, employee’s evaluation and performance, jobs satisfaction, organization commitment

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Authors: Shilpee Jain, Sachin Latiyan, Kaushik Suneet

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Unlike traditional robots, medical microbots are not only smaller in size, but they also possess various unique properties, for example, biocompatibility, stability in the biological fluids, navigation opposite to the bloodstream, wireless control over locomotion, etc. The idea behind their usage in the medical field was to build a minimally invasive method for addressing the post-operative complications, including longer recovery time, infection eruption and pain. Herein, the present study demonstrates the fabrication of dual nature magneto-conducting Fe3O4 magnetic nanoparticles (MNPs) and SU8 derived carbon-based Janus microbots for the efficient intracellular delivery of biomolecules. The low aspect ratio with feature size 2-5 μm microbots were fabricated by using a photolithography technique. These microbots were pyrolyzed at 900°C, which converts SU8 into amorphous carbon. The pyrolyzed microbots have dual properties, i.e., the half part is magneto-conducting and another half is only conducting for sufficing the therapeutic payloads efficiently with the application of external electric/magnetic field stimulations. For the efficient intracellular delivery of the microbots, the size and aspect ratio plays a significant role. However, on a smaller scale, the proper control over movement is difficult to achieve. The dual nature of Janus microbots allowed to control its maneuverability in the complex fluids using external electric as well as the magnetic field. Interestingly, Janus microbots move faster with the application of an external electric field (44 µm/s) as compared to the magnetic field (18 µm/s) application. Furthermore, these Janus microbots exhibit auto-fluorescence behavior that will help to track their pathway during navigation. Typically, the use of MNPs in the microdevices enhances the tendency to agglomerate. However, the incorporation of Fe₃O₄ MNPs in the pyrolyzed carbon reduces the chances of agglomeration of the microbots. The biocompatibility of the medical microbots, which is the essential property of any biosystems, was determined in vitro using HeLa cells. The microbots were found to compatible with HeLa cells. Additionally, the intracellular uptake of microbots was higher in the presence of an external electric field as compared to without electric field stimulation. In summary, the cytocompatible Janus microbots were fabricated successfully. They are stable in the biological fluids, wireless controllable navigation with the help of a few Guess external magnetic fields, their movement can be tracked because of autofluorescence behavior, they are less susceptible to agglomeration and higher cellular uptake could be achieved with the application of the external electric field. Thus, these carriers could offer a versatile platform to suffice the therapeutic payloads under wireless actuation.

Keywords: amorphous carbon, electric/magnetic stimulations, Janus microbots, magnetic nanoparticles, minimally invasive procedures

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Authors: Umesh Kumar Singh, Abhishek Raghuvanshi, Suyash Kumar Singh

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As IoT networks gain popularity, they are more susceptible to security breaches. As a result, it is crucial to analyze the IoT platform as a whole from the standpoint of core security concepts. The Internet of Things relies heavily on wireless networks, which are well-known for being susceptible to a wide variety of attacks. This article provides an analysis of many techniques that may be used to identify vulnerabilities in the software and hardware associated with the Internet of Things (IoT). In the current investigation, an experimental setup is built with the assistance of server computers, client PCs, Internet of Things development boards, sensors, and cloud subscriptions. Through the use of network host scanning methods and vulnerability scanning tools, raw data relating to IoT-based applications and devices may be collected. Shodan is a tool that is used for scanning, and it is also used for effective vulnerability discovery in IoT devices as well as penetration testing. This article presents an efficient mitigation plan for encountering vulnerabilities in the Internet of Things.

Keywords: internet of things, security, privacy, vulnerability identification, mitigation plan

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Authors: A. O. Idris, J. Virgone, A. I. Ibrahim, D. David, E. Vergnault

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In hot countries, the major challenge is the air conditioning. The increase in energy consumption by air conditioning stems from the need to live in more comfortable buildings, which is understandable. But in Djibouti, one of the countries with the most expensive electricity in the world, this need is exacerbated by an architecture that is inappropriate and unsuitable for climatic conditions. This paper discusses the design of the roof which is the surface receiving the most solar radiation. The roof determines the general behavior of the building. The study presents Computational Fluid Dynamics (CFD) modeling and analysis of the energy performance of a double skin ventilated roof. The particularity of this study is that it considers the climate of Djibouti characterized by hot and humid conditions in winter and very hot and humid in summer. Roof simulations are carried out using the Ansys Fluent software to characterize the flow and the heat transfer induced in the ventilated roof in steady state. This modeling is carried out by comparing the influence of several parameters such as the internal emissivity of the upper surface, the thickness of the insulation of the roof and the thickness of the ventilated channel on heat gain through the roof. The energy saving potential compared to the current construction in Djibouti is also presented.

Keywords: building, double skin roof, CFD, thermo-fluid analysis, energy saving, forced convection, natural convection

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Authors: U. Ali Rahoma, Nabil Esawy, Fawzia Ibrahim Moursy, A. H. Hassan, Samy A. Khalil, Ashraf S. Khamees

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The design of any solar energy conversion system requires the knowledge of solar radiation data obtained over a long period. Satellite data has been widely used to estimate solar energy where no ground observation of solar radiation is available, yet there are limitations on the temporal coverage of satellite data. Reanalysis is a “retrospective analysis” of the atmosphere parameters generated by assimilating observation data from various sources, including ground observation, satellites, ships, and aircraft observation with the output of NWP (Numerical Weather Prediction) models, to develop an exhaustive record of weather and climate parameters. The evaluation of the performance of reanalysis datasets (ERA-5) for North Africa against high-quality surface measured data was performed using statistical analysis. The estimation of global solar radiation (GSR) distribution over six different selected locations in North Africa during ten years from the period time 2011 to 2020. The root means square error (RMSE), mean bias error (MBE) and mean absolute error (MAE) of reanalysis data of solar radiation range from 0.079 to 0.222, 0.0145 to 0.198, and 0.055 to 0.178, respectively. The seasonal statistical analysis was performed to study seasonal variation of performance of datasets, which reveals the significant variation of errors in different seasons—the performance of the dataset changes by changing the temporal resolution of the data used for comparison. The monthly mean values of data show better performance, but the accuracy of data is compromised. The solar radiation data of ERA-5 is used for preliminary solar resource assessment and power estimation. The correlation coefficient (R2) varies from 0.93 to 99% for the different selected sites in North Africa in the present research. The goal of this research is to give a good representation for global solar radiation to help in solar energy application in all fields, and this can be done by using gridded data from European Centre for Medium-Range Weather Forecasts ECMWF and producing a new model to give a good result.

Keywords: solar energy, solar radiation, ERA-5, potential energy

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Authors: Theresia Dwi Hastuti, Kristiana Haryanti, Agustine Eva Maria Soekesi

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Today's family business continues to grow in big cities and in rural areas throughout Indonesia in line with the development of the business world and global competition. This study aims to analyze the effect of company value, leadership, and ownership succession on the financial performance of the family business. The research method was carried out quantitatively with multiple regression. The respondent amounted to 63 entrepreneurs. This study found that company value, leadership succession, relationships, and communication affect the financial performance of the family business.

Keywords: company value, family business, financial performance, leadership succession, ownership succession

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Authors: Fidelia A. Orji, Julita Vassileva

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This research aims to develop machine learning models for students' academic performance and study strategy prediction, which could be generalized to all courses in higher education. Key learning attributes (intrinsic, extrinsic, autonomy, relatedness, competence, and self-esteem) used in building the models are chosen based on prior studies, which revealed that the attributes are essential in students’ learning process. Previous studies revealed the individual effects of each of these attributes on students’ learning progress. However, few studies have investigated the combined effect of the attributes in predicting student study strategy and academic performance to reduce the dropout rate. To bridge this gap, we used Scikit-learn in python to build five machine learning models (Decision Tree, K-Nearest Neighbour, Random Forest, Linear/Logistic Regression, and Support Vector Machine) for both regression and classification tasks to perform our analysis. The models were trained, evaluated, and tested for accuracy using 924 university dentistry students' data collected by Chilean authors through quantitative research design. A comparative analysis of the models revealed that the tree-based models such as the random forest (with prediction accuracy of 94.9%) and decision tree show the best results compared to the linear, support vector, and k-nearest neighbours. The models built in this research can be used in predicting student performance and study strategy so that appropriate interventions could be implemented to improve student learning progress. Thus, incorporating strategies that could improve diverse student learning attributes in the design of online educational systems may increase the likelihood of students continuing with their learning tasks as required. Moreover, the results show that the attributes could be modelled together and used to adapt/personalize the learning process.

Keywords: classification models, learning strategy, predictive modeling, regression models, student academic performance, student motivation, supervised machine learning

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Authors: Lilah Inzelberg, David Rand, Stanislav Steinberg, Moshe David Pur, Yael Hanein

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Human facial expressions carry important psychological and neurological information. Facial expressions involve the co-activation of diverse muscles. They depend strongly on personal affective interpretation and on social context and vary between spontaneous and voluntary activations. Smiling, as a special case, is among the most complex facial emotional expressions, involving no fewer than 7 different unilateral muscles. Despite their ubiquitous nature, smiles remain an elusive and debated topic. Smiles are associated with happiness and greeting on one hand and anger or disgust-masking on the other. Accordingly, while high-resolution recording of muscle activation patterns, in a non-interfering setting, offers exciting opportunities, it remains an unmet challenge, as contemporary surface facial electromyography (EMG) methodologies are cumbersome, restricted to the laboratory settings, and are limited in time and resolution. Here we present a wearable and non-invasive method for objective mapping of facial muscle activation and demonstrate its application in a natural setting. The technology is based on a recently developed dry and soft electrode array, specially designed for surface facial EMG technique. Eighteen healthy volunteers (31.58 ± 3.41 years, 13 females), participated in the study. Surface EMG arrays were adhered to participant left and right cheeks. Participants were instructed to imitate three facial expressions: closing the eyes, wrinkling the nose and smiling voluntary and to watch a funny video while their EMG signal is recorded. We focused on muscles associated with 'enjoyment', 'social' and 'masked' smiles; three categories with distinct social meanings. We developed a customized independent component analysis algorithm to construct the desired facial musculature mapping. First, identification of the Orbicularis oculi and the Levator labii superioris muscles was demonstrated from voluntary expressions. Second, recordings of voluntary and spontaneous smiles were used to locate the Zygomaticus major muscle activated in Duchenne and non-Duchenne smiles. Finally, recording with a wireless device in an unmodified natural work setting revealed expressions of neutral, positive and negative emotions in face-to-face interaction. The algorithm outlined here identifies the activation sources in a subject-specific manner, insensitive to electrode placement and anatomical diversity. Our high-resolution and cross-talk free mapping performances, along with excellent user convenience, open new opportunities for affective processing and objective evaluation of facial expressivity, objective psychological and neurological assessment as well as gaming, virtual reality, bio-feedback and brain-machine interface applications.

Keywords: affective expressions, affective processing, facial EMG, high-resolution electromyography, independent component analysis, wireless electrodes

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Authors: N. F. Hanna, A. M. Haridy

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One of the main drawbacks of the Modal Pushover Analysis (MPA) is the need to perform nonlinear time-history analysis, which complicates the analysis method and time. A simplified version of the MPA has been proposed based on the concept of the inelastic deformation ratio. Furthermore, the effect of the higher modes of vibration is considered by assuming linearly-elastic responses, which enables the use of standard elastic response spectrum analysis. In this thesis, the simplified MPA (SMPA) method is applied to determine the target global drift and the inter-story drifts of steel frame building. The effect of the higher vibration modes is considered within the framework of the SMPA. A comprehensive survey about the inelastic deformation ratio is presented. After that, a suitable expression from literature is selected for the inelastic deformation ratio and then implemented in the SMPA. The estimated seismic demands using the SMPA, such as target drift, base shear, and the inter-story drifts, are compared with the seismic responses determined by applying the standard MPA. The accuracy of the estimated seismic demands is validated by comparing with the results obtained by the nonlinear time-history analysis using real earthquake records.

Keywords: modal analysis, pushover analysis, seismic performance, target displacement

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Authors: Soheila Sadeghi

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Infrastructure projects often encounter contract variations that can significantly deviate from the original tender estimates, leading to cost overruns, schedule delays, and financial implications. This research aims to quantitatively assess the impact of changes in contract variations on project performance by conducting an in-depth analysis of a comprehensive dataset from the Regional Airport Car Park project. The dataset includes tender budget, contract quantities, rates, claims, and revenue data, providing a unique opportunity to investigate the effects of variations on project outcomes. The study focuses on 21 specific variations identified in the dataset, which represent changes or additions to the project scope. The research methodology involves establishing a baseline for the project's planned cost and scope by examining the tender budget and contract quantities. Each variation is then analyzed in detail, comparing the actual quantities and rates against the tender estimates to determine their impact on project cost and schedule. The claims data is utilized to track the progress of work and identify deviations from the planned schedule. The study employs statistical analysis using R to examine the dataset, including tender budget, contract quantities, rates, claims, and revenue data. Time series analysis is applied to the claims data to track progress and detect variations from the planned schedule. Regression analysis is utilized to investigate the relationship between variations and project performance indicators, such as cost overruns and schedule delays. The research findings highlight the significance of effective variation management in construction projects. The analysis reveals that variations can have a substantial impact on project cost, schedule, and financial outcomes. The study identifies specific variations that had the most significant influence on the Regional Airport Car Park project's performance, such as PV03 (additional fill, road base gravel, spray seal, and asphalt), PV06 (extension to the commercial car park), and PV07 (additional box out and general fill). These variations contributed to increased costs, schedule delays, and changes in the project's revenue profile. The study also examines the effectiveness of project management practices in managing variations and mitigating their impact. The research suggests that proactive risk management, thorough scope definition, and effective communication among project stakeholders can help minimize the negative consequences of variations. The findings emphasize the importance of establishing clear procedures for identifying, assessing, and managing variations throughout the project lifecycle. The outcomes of this research contribute to the body of knowledge in construction project management by demonstrating the value of analyzing tender, contract, claims, and revenue data in variation impact assessment. However, the research acknowledges the limitations imposed by the dataset, particularly the absence of detailed contract and tender documents. This constraint restricts the depth of analysis possible in investigating the root causes and full extent of variations' impact on the project. Future research could build upon this study by incorporating more comprehensive data sources to further explore the dynamics of variations in construction projects.

Keywords: contract variation impact, quantitative analysis, project performance, claims analysis

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Authors: Mohammad Q. M. Momani

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The objective of this study is to examine whether the value relevance of ownership structure changed as the Amman Stock Exchange market conditions changed. Using data from 2005 to 2014, the study finds that the performance of portfolios that contain firms with concentrated ownership structure declines significantly during the post-crisis period. These portfolios exhibit poor performance relative to portfolios that contain firms with dispersed ownership structure during the post-crisis period. The results argue that uninspired performance of the Amman Stock Exchange during the post-crisis period, increased the incentives for controlling shareholders to expropriate. Investors recognized these incentives and discounted firms that were more likely to expropriate.

Keywords: value relevance, ownership structure, portfolio performance, Jordan, ASE

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Authors: Munirajulu M, Srikanth Modem

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A large cricket stadium with the capacity to accommodate several thousands of spectators has the seating arena consisting of a two-tier arrangement with an upper and a lower bowl and an intermediate concourse podium level for pedestrian movement to access the bowls. The uniqueness of the stadium is that spectators can have an unobstructed view from all around the podium towards the field of play. Upper and lower bowls are connected by stairs. The stairs landing is a precast slab supported by cantilevered steel beams. These steel beams are fixed to precast columns supporting the stadium structure. The stair slabs are precast concrete supported on a landing slab and cantilevered steel beams. During an event of a fire at podium level between two staircases, fire resistance of steel beams is very critical to life safety. If the steel beam loses its strength due to lack of fire resistance, it will be weak in supporting stair slabs and may lead to a hazard in evacuating occupants from the upper bowl to the lower bowl. In this study, to ascertain fire rating and life safety, a performance-based design using CFD analysis is used to evaluate the steel beams' fire resistance. A fire size of 3.5 MW (convective heat output of fire) with a wind speed of 2.57 m/s is considered for fire and smoke simulation. CFD results show that the smoke temperature near the staircase/ around the staircase does not exceed 1500 C for the fire duration considered. The surface temperature of cantilevered steel beams is found to be less than or equal to 1500 C. Since this temperature is much less than the critical failure temperature of steel (5200 C), it is concluded that the design of structural steel supports on the staircase is adequate and does not need additional fire protection such as fire-resistant coating. CFD analysis provided an engineering basis for the performance-based design of steel structural elements and an opportunity to optimize fire protection requirements. Thus, performance-based design using CFD modeling and simulation of fire and smoke is an innovative way to evaluate fire rating requirements, ascertain life safety and optimize the design with regard to fire protection on structural steel elements.

Keywords: fire resistance, life safety, performance-based design, CFD analysis

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Authors: D. Habibinia, M. R. Feyzi

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Nowadays, specialized software is vastly used to verify the performance of an electric machine prototype by evaluating a model of the system. These models mainly consist of electrical parameters such as inductances and resistances. However, when the operating frequency of the device is above one kHz, the effect of parasitic capacitances grows significantly. In this paper, a software-based procedure is introduced to model these capacitances within the electromagnetic simulation of the device. The case study is a high-frequency high-voltage pulse transformer. The Finite Element Analysis (FEA) software with coupled field analysis is used in this method.

Keywords: finite element analysis, parasitic capacitance, pulse transformer, high frequency

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Authors: Firooz Bakhtiari-Nejad, Hamidreza Rostami, Meysam Mirzaee, Mona Zandbaf

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Dynamic tests are an important step of the design of engineering structures, because the accuracy of predictions of theoretical–numerical procedures can be assessed. In experimental test of moving loads that is one of the major research topics, the load is modeled as a simple moving mass or a small vehicle. This paper deals with the applicability of Non-Contact Moving Load (NML) for vibration analysis. For this purpose, an experimental set-up is designed to generate the different types of NML including constant and harmonic. The proposed method relies on pressurized air which is useful, especially when dealing with fragile or sensitive structures. To demonstrate the performance of this system, the set-up is employed for a modal analysis of a beam and detecting crack of the beam. The obtained results indicate that the experimental set-up for NML can be an attractive alternative to the moving load problems.

Keywords: experimental analysis, moving load, non-contact excitation, materials engineering

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Authors: Gloria Toledo, Andrea Lizasoain, Leonardo Mena

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Immigration has largely increased in Chile in the last 20 years. About 6.6% of our population is foreign, from which 14.3% is Haitian. Haitians are between 15 and 29 years old and have come to Chile escaping from a social crisis. They believe that education and work will help them do better in life. Therefore, rates of Haitian students in the Chilean school system have also increased: there were 3,121 Haitian students enrolled in 2017. This is a challenge for the public school, which takes in young people who must face schooling, social immersion and learning of a second language simultaneously. The linguistic barrier affects both students’ and teachers’ adaptation process, which has an impact on the students’ academic performance and consequent acquisition of Spanish. In order to explore students’ academic performance and interlanguage development, we examined how L1 teachers assess Haitian high school students’ written production in Spanish. With this purpose, teachers were asked to use a specially designed grid to assess correction, accommodation, lexical and analytical complexity, organization and fluency of both Haitian and Chilean students. Parallelly, texts were approached from an error analysis perspective. Results from grids and error analysis were then compared. On the one hand, it has been found that teachers give very little feedback to students apart from scores and grades, which does not contribute to the development of the second language. On the other hand, error analysis has yielded that Haitian students are in a dynamic process of the acquisition of Spanish, which could be enhanced if L1 teacher were aware of the process of interlanguage developmen.

Keywords: assessment, error analysis, grid, immigration, Spanish aquisition, writing

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Authors: Santi Gopal Maji, R. A. J. Syngkon

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The changing attitude of the corporate enterprises from maximizing economic benefit to corporate sustainability after the publication of Brundtland Report has attracted the interest of researchers to investigate the sustainability practices of firms and its impact on financial performance. To enrich the empirical literature in Asian context, this study examines the disclosure pattern of corporate sustainability and the influence of sustainability reporting on financial performance of firms from four Asian countries (Japan, South Korea, India and Indonesia) that are publishing sustainability report continuously from 2009 to 2016. The study has used content analysis technique based on Global Reporting Framework (3 and 3.1) reporting framework to compute the disclosure score of corporate sustainability and its components. While dichotomous coding system has been employed to compute overall quantitative disclosure score, a four-point scale has been used to access the quality of the disclosure. For analysing the disclosure pattern of corporate sustainability, box plot has been used. Further, Pearson chi-square test has been used to examine whether there is any difference in the proportion of disclosure between the countries. Finally, quantile regression model has been employed to examine the influence of corporate sustainability reporting on the difference locations of the conditional distribution of firm performance. The findings of the study indicate that Japan has occupied first position in terms of disclosure of sustainability information followed by South Korea and India. In case of Indonesia, the quality of disclosure score is considerably less as compared to other three countries. Further, the gap between the quality and quantity of disclosure score is comparatively less in Japan and South Korea as compared to India and Indonesia. The same is evident in respect of the components of sustainability. The results of quantile regression indicate that a positive impact of corporate sustainability becomes stronger at upper quantiles in case of Japan and South Korea. But the study fails to extricate any definite pattern on the impact of corporate sustainability disclosure on the financial performance of firms from Indonesia and India.

Keywords: corporate sustainability, quality and quantity of disclosure, content analysis, quantile regression, Asian countries

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Authors: Ambuj Srivastava, Narender Singh

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This paper presents the effect of installation of cylindrical external store on the performance, stability, control and handling qualities of light transport category aircraft. A pair of long cylindrical store was installed symmetrically on either side of the fuselage (port and starboard) ahead of the wing and below the fuselage bottom surface running below pilot and co-pilot window. The cylindrical store was installed as hanging from aircraft surface through specially designed brackets. The adjoining structure was sufficiently reinforced for bearing aerodynamic loads. The length to diameter ratio of long cylindrical store was ~20. Based on academic studies and flow simulation analysis, a considerable detrimental effect on single engine second segment climb performance was found which was later validated through extensive flight testing exercise. The methodology of progressive flight envelope opening was adopted. The certification was sought from Regional airworthiness authorities and for according approval.

Keywords: second segment climb, maximum operating speed, cruise performance (single engine and twin engine), minimum control speed, and additional trim required

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Authors: Taiwo, Richard Oluseyi, Morakinyo, Kolawole O., Oyeniran, Demilade O.

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This study examines the effects of digitalization and sustainability on professionals' performance within the built environment. By examining the interplay between these two transformative forces, the study seeks to unravel the complexities and opportunities presented by digital technologies in fostering sustainable practices across various professional disciplines. Through an extensive analysis of literature and expert interviews, this research explores how digitalization can enhance professionals' abilities to incorporate sustainability principles, optimize resource utilization, and promote resilient and inclusive built environments. Furthermore, it examines the challenges and barriers professionals face in adapting to and harnessing the potential of digital tools and processes. The findings will contribute to a greater comprehension of the beneficial interactions between digitalization and sustainable development and provide valuable insights for policymakers, practitioners, and educators in fostering an ecosystem that supports professionals' capacity building, collaboration, and innovation toward achieving sustainable goals in the built environment.

Keywords: digitisation, sustainability, professional performance, built environment

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Authors: Saumyaranjan Sahoo, Sudhir Yadav

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Indian manufacturing firms operating in rapidly changing and highly competitive market, over the last few decades, have embraced organization-wide transformation to achieve cultural and operational excellence. In recent years, numerous approaches have been proposed to improve business and manufacturing performance. Lean practices in particular, Total Productive Management (TPM) and Total Quality Management (TQM) have received considerable attention, as they being adopted and adapted for raising the performance standard of Indian manufacturing firms to world class levels. The complementary nature of TPM and TQM is being practiced in many companies to achieve synergy. Specifically, this research investigates whether joint TPM-TQM implementation contribute to higher business performance when compared to individual implementation. Data from 160 manufacturing firms were analyzed that demonstrate synergetic implementation of both TPM-TQM practices over a reasonable period of time, contributed in delivering better business performance as compared to individual implementation strategy.

Keywords: total productive management, total quality management, Indian manufacturing firms, business performance

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Authors: Catrin Morgan, Atholl Johnston

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Creatine supplementation should theoretically increase total muscle creatine and so enhance the generation of intramuscular phosphocreatine and subsequent ATP formation. The use of creatine as a potential ergogenic aid in sport has been an area of significant scientific research for a number of years. However the effect of creatine supplementation and swimming performance is a relatively new area of research and is the subject of this review. In swimming creatine supplementation could help maintain maximal power output, aid recovery and increase lean body mass. After investigating the underlying theory and science behind creatine supplementation, a literature review was conducted to identify the best evidence looking at the effect of creatine supplementation on swimming performance. The search identified 27 potential studies, and of these 17 were selected for review. The studies were then categorised into single sprint performance, which involves swimming a short distance race, or repeated interval performance, which involves swimming a series of sprints with intervals of rest between them. None of the studies on the effect of creatine controlled for the multiple confounding factors associated with measurement of swimming performance. The sample size in the studies was limited and this reduced the reliability of the studies and introduced the possibility of bias. The studies reviewed provided insufficient evidence to determine if creatine supplementation is beneficial to swimming performance. However, what data there was supported the use of creatine supplementation in repeated interval swimming rather than in single sprint swimming. From a review of the studies, it was calculated on average, there was a 1.37% increase in swimming performance with the use of creatine for repeated intervals and a 0.86% increase in performance for single sprint. While this may seem minor, it should be remembered that swimming races are often won by much smaller margins. In the 2012 London Olympics the Men’s 100 metres freestyle race was won by a margin of only 0.01 of a second. Therefore any potential benefit could make a dramatic difference to the final outcome of the race. Overall more research is warranted before the benefits of creatine supplementation in swimming performance can be further clarified.

Keywords: creatine supplementation, repeated interval, single sprint, swimming performance

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Authors: Irina Canco, Amela Malaj

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It is evident that there exists a relationship between supply chain management and business performance. Surveys have showed that in many cases the manager's beliefs and expectations on supply chain management do not match the reality of the business. In this context, the study of supply chain issues is of particular importance and interest considering specifically the current period. The economic problems of this period, are present in Albania as well. The complexity of the supply chain focuses on order fulfilment. Therefore, in this paper, attention will be paid to the impact of supply chain management on business performance. The objective of the paper is to find a relationship between the good supply chain management and business performance. This research is based on the results of surveys referring to the experience of successful businesses on issues related to sustainable supply chain management and its synchronization with the provision of products and services required by the final customers. This study clearly evidenced the impact of the speed of meeting customer requirements on AMAZONA performance. This was also confirmed mathematically through one of the decision criteria in conditions of uncertainty—Laplace criterion.

Keywords: supply chain management, AMAZONA, business performance, Laplace criteria

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Authors: B. Chandra

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In Association Rule Mining, much attention has been paid for developing algorithms for large (frequent/closed/maximal) itemsets but very little attention has been paid to improve the performance of rule generation algorithms. Rule generation is an important part of Association Rule Mining. In this paper, a novel approach named NARG (Association Rule using Antecedent Support) has been proposed for rule generation that uses memory resident data structure named FCET (Frequent Closed Enumeration Tree) to find frequent/closed itemsets. In addition, the computational speed of NARG is enhanced by giving importance to the rules that have lower antecedent support. Comparative performance evaluation of NARG with fast association rule mining algorithm for rule generation has been done on synthetic datasets and real life datasets (taken from UCI Machine Learning Repository). Performance analysis shows that NARG is computationally faster in comparison to the existing algorithms for rule generation.

Keywords: knowledge discovery, association rule mining, antecedent support, rule generation

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Authors: Yusuf A. Bako, Olubunmi O. Kolawole

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This study sought to establish the effect of recruitment and selection on the employee performance in hospitality industries. The success of any organization in this modern business environment depends on the caliber of the manpower that steer the affairs of the organization. History has shown that recruitment and selection as a function of human resources management practices have a pivotal role in determining the level of employee performance in an organization. The hospitality industries have been faced with challenges of performance due to unconventional selection and placement practices in terms of poor policy in selecting candidate, inconsistency in selection process, sidetracking employment test and interview, godfatherism and regional selection process etc. The overall objective of the study was to determine how recruitment and selection affect employee performance in hospitality industry in Ogun State, Nigeria. This study adopts descriptive and inferential research design while population was drawn from leading hotels in Ogun State, Nigeria. The samples size was 100 employees and questionnaire was used to collect data while Cronbach alpha was used to test the instrument. The result of the study reveals that correlation between employee performance and recruitment and selection were highly significant.

Keywords: employee performance, human resources management, practices, recruitment, selection

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Authors: Francesca di Donato, Sara Trucco

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Green accounting is a growing topic of interest. Indeed, nowadays, most firms affect the environment; therefore, companies are seeking the best way to disclose environmental information. Furthermore, companies are increasingly committed to improving the environment, and the topic is gaining more importance to the public, governments, and policymakers. Green accounting is a type of accounting that considers environmental costs and their impact on the financial performance of firms. Thus, the motivation of the current research is to investigate the state-of-the-art literature on the relationship between green accounting and firm performance since the birth of the topic of green accounting and to investigate gaps in the literature that represent fruitful terrain for future research. In doing so, this study provides a bibliometric literature review of existing evidence related to the link between green accounting and firm performance since 2000. The search, based on the most relevant databases for scientific journals (which are Scopus, Emerald, Web of Science, Google Scholar, and Econlit), returned 1917 scientific articles. The articles were manually reviewed in order to identify only the relevant studies in the field by excluding articles with titles and abstracts out of scope. The final sample was composed of 107 articles. A content analysis was carried out on the final sample of articles; in doing so, a classification system has been proposed. Findings show the most relevant environmental costs and issues considered in previous studies and how green accounting may be linked to the financial and non-financial performance of a firm. The study also offers suggestions for future research in this domain. This study has several practical implications. Indeed, the topic of green accounting may be applied to different sectors and different types of companies. Therefore, this study may help managers to better understand the most relevant environmental information to disclose and how environmental issues may be managed to improve the performance of the firms. Moreover, the bibliometric literature review may be of interest to those stakeholders who are interested in the historical evolution of the topic.

Keywords: bibliometric literature review, firm performance, green accounting, literature review

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Authors: Tukundane Hillary

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This research paper analytically evaluates the project control practice levels used by the building construction companies within Kampala, Uganda. The research also assesses the outcome of project control practices on the productivity of the companies. The research was performed to ascertain the current control practices among 160 respondents from various construction companies registered with the Uganda Registration Services Bureau. This research used amalgamation from multiple literature to obtain the variables. The research adopts 34 standard control practices from four vital project control duties: planning, monitoring, analyzing, and reporting. These project control tasks were organized using mean response ratings grounded on their relevance to the construction companies. Results showed that evaluating performance with the use of curves (4.32), timely access to information and encouragement (4.55), report representation using quantitative tools 4.75, and cost value comparison application during analysis (4.76) were rated least among the control practices. On the other hand, the top project control practices included formulation of the project schedule (8.88), Project feasibility validation (8.86), Budgeting for each activity (8.84), Key project route definition (8.81), Team awareness of the budget (8.77), Setting realistic targets for projects (8.50) and Consultation from subcontractors (8.74). From the results obtained by the sample respondents specified, it can be concluded that planning is the most vital project control task practiced in the building construction industry in Uganda. In addition, this research ascertained a substantial relationship between project control practices and the performance of building construction companies. Accordingly, this research recommends that project control practices be effectively observed by both contracting and consulting companies to enhance their overall performance and governance.

Keywords: cost value, project control, cost control, time control, project performance, control practices

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Authors: Javad Izadi, Sahar Majioud

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This study presents an approach of assessing the choice of performance measures of companies in the United Kingdom after the application of IFRS in 2005. The aim of this study is to investigate the effects of IFRS on the choice of performance evaluation methods for UK companies. We analyse through an econometric model the relationship of the dependent variable, the firm’s performance, which is a nominal variable with the independent ones. Independent variables are split into two main groups: the first one is the group of accounting-based measures: Earning per share, return on assets and return on equities. The second one is the group of market-based measures: market value of property plant and equipment, research and development, sales growth, market to book value, leverage, segment and size of companies. Concerning the regression used, it is a multinomial logistic regression performed on a sample of 130 UK listed companies. Our finding shows after IFRS adoption, and companies give more importance to some variables such as return on equities and sales growth to assess their performance, whereas the return on assets and market to book value ratio does not have as much importance as before IFRS in evaluating the performance of companies. Also, there are some variables that have no impact on the performance measures anymore, such as earning per share. This article finding is empirically important for business in subjects related to IFRS and companies’ performance measurement.

Keywords: performance’s Measure, nominal variable, econometric model, evaluation methods

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Authors: Rakelane A. Mendes, Sandro T. M. Goncalves, Raphaella L. R. Silva

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The concepts of energy harvesting and wireless energy transfer have been widely discussed in recent times. There are some ways to create autonomous systems for collecting ambient energy, such as solar, vibratory, thermal, electromagnetic, radiofrequency (RF), among others. In the case of the RF it is possible to collect up to 100 μW / cm². To collect and/or transfer energy in RF systems, a device called rectenna is used, which is defined by the junction of an antenna and a rectifier circuit. The rectenna presented in this work is resonant at the frequencies of 1.8 GHz and 2.45 GHz. Frequencies at 1.8 GHz band are e part of the GSM / LTE band. The GSM (Global System for Mobile Communication) is a frequency band of mobile telephony, it is also called second generation mobile networks (2G), it came to standardize mobile telephony in the world and was originally developed for voice traffic. LTE (Long Term Evolution) or fourth generation (4G) has emerged to meet the demand for wireless access to services such as Internet access, online games, VoIP and video conferencing. The 2.45 GHz frequency is part of the ISM (Instrumentation, Scientific and Medical) frequency band, this band is internationally reserved for industrial, scientific and medical development with no need for licensing, and its only restrictions are related to maximum power transfer and bandwidth, which must be kept within certain limits (in Brazil the bandwidth is 2.4 - 2.4835 GHz). The rectenna presented in this work was designed to present efficiency above 50% for an input power of -15 dBm. It is known that for wireless energy capture systems the signal power is very low and varies greatly, for this reason this ultra-low input power was chosen. The Rectenna was built using the low cost FR4 (Flame Resistant) substrate, the antenna selected is a microfita antenna, consisting of a Meandered dipole, and this one was optimized using the software CST Studio. This antenna has high efficiency, high gain and high directivity. Gain is the quality of an antenna in capturing more or less efficiently the signals transmitted by another antenna and/or station. Directivity is the quality that an antenna has to better capture energy in a certain direction. The rectifier circuit used has series topology and was optimized using Keysight's ADS software. The rectifier circuit is the most complex part of the rectenna, since it includes the diode, which is a non-linear component. The chosen diode is the Schottky diode SMS 7630, this presents low barrier voltage (between 135-240 mV) and a wider band compared to other types of diodes, and these attributes make it perfect for this type of application. In the rectifier circuit are also used inductor and capacitor, these are part of the input and output filters of the rectifier circuit. The inductor has the function of decreasing the dispersion effect on the efficiency of the rectifier circuit. The capacitor has the function of eliminating the AC component of the rectifier circuit and making the signal undulating.

Keywords: dipole antenna, double-band, high efficiency, rectenna

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Authors: Neha Singh, Shristi Singh

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Accidents involving motor vehicles are more likely to cause serious injuries and fatalities. It also has a host of other perpetual issues, such as the regular loss of life and goods in accidents. To solve these issues, appropriate measures must be implemented, such as establishing an autonomous incident detection system that makes use of machine learning and artificial intelligence. In order to reduce traffic accidents, this article examines the overview of artificial intelligence and machine learning in autonomous event detection systems. The paper explores the major issues, prospective solutions, and use of artificial intelligence and machine learning in road transportation systems for minimising traffic accidents. There is a lot of discussion on additional, fresh, and developing approaches that less frequent accidents in the transportation industry. The study structured the following subtopics specifically: traffic management using machine learning and artificial intelligence and an incident detector with these two technologies. The internet of vehicles and vehicle ad hoc networks, as well as the use of wireless communication technologies like 5G wireless networks and the use of machine learning and artificial intelligence for the planning of road transportation systems, are elaborated. In addition, safety is the primary concern of road transportation. Route optimization, cargo volume forecasting, predictive fleet maintenance, real-time vehicle tracking, and traffic management, according to the review's key conclusions, are essential for ensuring the safety of road transportation networks. In addition to highlighting research trends, unanswered problems, and key research conclusions, the study also discusses the difficulties in applying artificial intelligence to road transport systems. Planning and managing the road transportation system might use the work as a resource.

Keywords: artificial intelligence, machine learning, incident detector, road transport systems, traffic management, automatic incident detection, deep learning

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Authors: Mustafa Elfituri, Jonathan Cook

Abstract:

Recently, graph-based computations have become more important in large-scale scientific computing as they can provide a methodology to model many types of relations between independent objects. They are being actively used in fields as varied as biology, social networks, cybersecurity, and computer networks. At the same time, graph problems have some properties such as irregularity and poor locality that make their performance different than regular applications performance. Therefore, parallelizing graph algorithms is a hard and challenging task. Initial evidence is that standard computer architectures do not perform very well on graph algorithms. Little is known exactly what causes this. The Graph500 benchmark is a representative application for parallel graph-based computations, which have highly irregular data access and are driven more by traversing connected data than by computation. In this paper, we present results from analyzing the performance of various example implementations of Graph500, including a shared memory (OpenMP) version, a distributed (MPI) version, and a hybrid version. We measured and analyzed all the factors that affect its performance in order to identify possible changes that would improve its performance. Results are discussed in relation to what factors contribute to performance degradation.

Keywords: graph computation, graph500 benchmark, parallel architectures, parallel programming, workload characterization.

Procedia PDF Downloads 149