Management competencies for preventing and reducing stress at construction site

Construction industry involved very complicated process and extensive linkages to more than hundred of upstream and downstream industries. Therefore, an effective leadership of managerial level of construction organization is needed to well manage and control their subordinates in order to make sure the efficiency and productivity of the construction work. However, both managerial level of the construction organization and their subordinates also would experience stress due to increase of workload and work pressure. Hence, management competency has become significant in human resource practice in order to increase individual and organizational effectiveness. Consequently, a study on management competency of the managerial level is conducted for preventing and reducing stress at construction site in Johor. A total of 78 sets of questionnaires have been collected from several professions within 20 organizations. Among the 78 number of respondents, 21 persons were from managerial level and 57 persons were from subordinates’ level. From the survey, managerial levels have the highest percentage score of sub-competency in managing conflict meanwhile the subordinates level assess their managerial level as the participative/empowering is having the highest percentage score among all the listed sub-competency for preventing and reducing stress at construction site. Generally, the managerial level and subordinates level have the same perception that the managerial level is having the highest percentages score in competency of managing and communicating existing and future work among all of the competency. The managerial level behaviour is an important determinant of theirs subordinate stress levels. Thus, throughout the study, the managerial level of the construction organization can have better understanding on stress as well as the skills, abilities and behaviours needed to implement the management standard and manage their subordinates in a way that minimizes work-related stress in construction works

COVID-19: Notes from the Frontline, Singapore’s Primary Healthcare Perspective

The authors share their experience with the implementation of COVID-19 containment measures from a network of 50 private general practitioner clinics in Singapore.Coronavirus disease 2019 (COVID-19) is a rapidly progressing global pandemic as nations struggle for containment. Singapore is known to have promptly instituted aggressive public health and containment measures. A key pillar sustaining this is the response of its primary healthcare network. It is important for healthcare systems worldwide to recognize the value of a strong coordinated response to this crisis from a primary health perspective. There are best practices for early isolation and containment of suspect cases while protecting healthcare workers and limiting cross infections that are transferable across nations. We describe our framework for how our primary care clinics respond to this pandemic in the hope others may find solutions to their unique needs. Moving forward, there is a pressing necessity for more studies to enhance our understanding of the response of primary care during these public health crises.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154576/1/LimAFM-152-20-ms.pdfDescription of LimAFM-152-20-ms.pdf : Final pdf for Annals of Family Medicine COVID-19 Collectio

A Comparative Study of Deep Learning Model and Simple Prediction Charts in Construction Noise Prediction

Construction noise monitoring is crucial to assess the impacts of construction noise on the workers and surroundings. However, the existing noise prediction methods are time-consuming in which required laborious work for the computation of noise levels. This study aims to assess the accuracy and reliability of deep learning model (DL) that adopted stochastic modelling and artificial neural network (ANN) in construction noise prediction. The artificial neural network was trained with the output of stochastic modelling. The outcome of noise level prediction using simple prediction chart (SPC) and DL model was discussed and compared to 3 case studies. The case studies were conducted at construction sites located in Semenyih, Selangor, Malaysia. The results of DL model showed high accuracy of predicted noise levels along with an absolute difference of less than 2.3 dBA. Besides, the predicted noise levels are reliable as the R-squared value is higher than 0.992. On that account, DL model is proved to be reliable and accurate in noise level prediction and it has the potential to be utilized as a managerial tool to monitor construction noise more effectively

Effect of Ceramic Dust as Partial Replacement of Cement on Lightweight Foamed Concrete

Disposal of waste into the landfill causes a severe impact on the environment. One of the waste products is ceramic waste. Ceramic waste has some excellent properties in its durability, hardness, and highly resistant to biological, chemical, and physical degradation forces. These excellent properties of the ceramic waste may make it suitable to be used in concrete. This study investigates the effect on the compressive strength of lightweight foamed concrete with different percentage of ceramic dust replacement level towards the cement and three different levels of water-cement ratio. 0%, 5%, 15%, and 25% of replacement level with 0.52, 0.56, and 0.60 water-cement ratios respectively for each replacement level was used as the parameter to investigate the fresh properties, and strength performance of lightweight foamed concrete. The stability and consistency of every mix are studied as well. From this study, it was observed that the incorporation of ceramic waste dust partially replaced the cement did not affect on the fresh properties of the foamed concrete. However, the compressive strength of foamed concrete affected by ceramic waste dust partially replaced the cement

EDI in Singapore: emerging issues with sexual and gender minorities and people living with HIV

Diversity management had always been at the forefront of Singapore's social and economic policies. Over the last half a century, a slew of legislation, social and economic policies aimed at maintaining harmony and ensuring economic progress have successfully put Singapore on the world map as a global trading hub. Owing to Singapore's heritage as a migrant nation, much of the diversity management efforts in the past had focused on bases of diversity such as age, race, gender, religion. However, in recent years, there was much public discourse on the inclusion of gender and sexual minorities and people living with HIV, pushing for a greater need to address issues that have long been considered sensitive. This chapter spotlights the two issues against a backdrop of how diversity is managed in the Singapore context, and discusses two frameworks that may help shed more light on Singapore's approach to diversity management.acceptedVersio

The Impact of Online Learning on Student\u27s Academic Performance

The spread of online learning has grown exponentially at every academic level and in many countries in our COVID-19 world. Due to the relatively new nature of such widespread use of online learning, little analysis or studies have been conducted on whether student performance takes a toll through this different medium. This paper aims to propose a research project targeted to study the impact of online learning on the academic performance of Embry-Riddle Aeronautical University (ERAU) students, as compared to an in-person medium. The research will be conducted over a period of 2 years for 3 modules that are common for students across all courses. Data utilized in the study will be obtained through a survey, as well as academic performance data sourced from ERAU. The analysis will be conducted using T-test and Regression techniques to identify statistically significant impacts of student performance in online versus in-person classes. The results obtained can be an estimated general trend of student performance in various other universities which conduct a mix of in-class and online learning in this COVID-19 era. The results obtained will also serve as a framework, and as possible preliminary results for future academic research with regards to the proposed topic. The observed trend will benefit institutions in identifying the method of instruction in which they would need to refine, to raise the standards of different instructional methods to a parity

Feasibility Analysis of Implementing Hybrid Powered Electric Vehicle Charging Stations in Sarawak

— The transportation sector in Sarawak completely depends on fossil fuel which produces a high quantity of greenhouse gases. A suitable design of charging stations for electric vehicles (EVs) equipped with grid-integrated renewable energy resources (RERs) can help in addressing this issue. This paper proposes to enhance the execution requirements of the hybridpowered electric vehicle charging stations (EVCSs) in Sarawak. A generalized approach for modelling a renewable energy-based hybrid microgrid equipped with EVCS is presented in detail. Four types of microgrid configurations with biomass and solar photovoltaic (PV) systems have been studied to find the optimal size of each component feasible for EVCS. Each design of the hybridpowered EVCS has been analyzed in terms of economic and environmental viability using the climate data with associated monetary data. The analysis shows that the cost of lowering emission to zero is directly proportional to the total net present cost (RM 259,088) when using PV microgrid-powered EVCS. The outcome of this paper provides insight for policymakers on the technical and financial benefits of EVCS deployment. It also promotes the industry of Plug-in Electric Vehicles (PEVs) in Malaysia

Multi-Objective Optimization and Network Routing with Near-Term Quantum Computers

Multi-objective optimization is a ubiquitous problem that arises naturally in many scientific and industrial areas. Network routing optimization with multi-objective performance demands falls into this problem class, and finding good quality solutions at large scales is generally challenging. In this work, we develop a scheme with which near-term quantum computers can be applied to solve multi-objective combinatorial optimization problems. We study the application of this scheme to the network routing problem in detail, by first mapping it to the multi-objective shortest path problem. Focusing on an implementation based on the quantum approximate optimization algorithm (QAOA) -- the go-to approach for tackling optimization problems on near-term quantum computers -- we examine the Pareto plot that results from the scheme, and qualitatively analyze its ability to produce Pareto-optimal solutions. We further provide theoretical and numerical scaling analyses of the resource requirements and performance of QAOA, and identify key challenges associated with this approach. Finally, through Amazon Braket we execute small-scale implementations of our scheme on the IonQ Harmony 11-qubit quantum computer

Pr0.67Ba0.33MnO3 in bulk and thin film ceramic

Bulk polycrystalline of Pr0.67Ba0.33MnO3 (PBMO) ceramic prepared via solid‐state reaction and converted into thin films on corning glass, fused silica and MgO (100) by pulsed laser deposition (PLD) technique. As compared to bulk PBMO, the unit cell in thin film PBMO experienced positive misfit due to lattice strain induced by substrate used resulting MnO6 to deform (change in Mn‐O‐Mn bond angle and Mn‐O bond length). Bulk PBMO had large grains (∼1.5μm) as compared to thin film which are nano‐sized (<100 nm). Two metal‐insulator transition temperatures, TP (156 K and 190 K) were observed in bulk due to core‐shell effect as proposed by Zhang et al.. In summary, variation of electrical behaviour was observed between bulk and thin film samples which believed to be due to the difference of ordering in core (body) and grain surface