Leading sustainable schools in the era of Education 4.0: Identifying school leadership competencies in Malaysian secondary schools

The purpose of the study was to develop an empirical School Leadership Competency Model for the era of Education 4.0 (SLCMEduc4.0) to identify school leadership competencies that facilitate and maximize effectiveness in leading sustainable schools in Malaysia. Exploratory Factor Analysis (EFA) was employed to identify the underlying factors whereas Confirmatory Factor Analysis (CFA) was applied to test the measurement models using Structural Equation Modelling. A total of 444 and 931 respondents completed the survey with usable data for EFA and CFA respectively. The results suggested that the SLCMEdu4.0 can be explained by eight factors namely; Leading for Learning, Emotional Intelligence, Critical Thinking, Communication and Ethics, Collaboration, Decision Making and Problem Solving, Digital Dexterity and Entrepreneurial with good fit statistics; normed x2=2.628, TLI=.950, CFI=.954 and RMSEA=.042. With a total of 40 items, the model also features good convergent and discriminant validity and construct reliability. The SLCMEduc4.0 is a coherent premier model that provides useful feedback for practitioners in planning, designing and evaluating future professional development programmes for school leaders. The study encourages a fresh look at educational leadership development locally and globally specifically in enhancing the leadership development of Malaysian school leaders towards productive change in the era of Education 4.0

TRA-953: AUTOMATION IN DRIVING FOR ENHANCING RESILIENCY IN TRANSPORTATION SYSTEM

The ability of the transportation system to continue to serve traffic under disruptive conditions is a resilience characteristic of infrastructure and traffic management. In the context of this research, resilience is defined as the ability to resist the loss of traffic-serving capability by using traffic (including geometric) and control system design advances (i.e. the inherent resilience) and by activating capacity-enhancing measures (i.e. the dynamic resilience). Vulnerabilities in road traffic networks cause the loss of capability to serve demand overloads. On the other hand, intelligent technology and associated methodology can potentially prevent or reduce this loss of capability. An outstanding research question is the role of automation in driving for enhancing the resilience of urban road traffic network. This paper reports research in-progress on improving resilience of adaptive capacity in traffic networks with intelligent systems and advanced methods. An introduction is provided to vulnerabilities in traffic network, and available information is used as empirical evidence of vulnerabilities. Inherent and dynamic resilience measures of the traffic system are defined at the scales of corridors and networks that can potentially overcome vulnerabilities. Features of autonomous driving are presented as resilience-enhancing measures. Finally, conclusions are presented on the potential of automation in driving to enhance the resilience of urban traffic network so that it can withstand high predictive imbalances of demand vs. capacity as well as stochastic traffic overloads and recover functionality at a tolerable level of performance within an acceptable time period

TRA-952: ENHANCING RESILIENCE OF TRAFFIC NETWORKS WITH CONNECTED VEHICLES

Improving resilience of transportation infrastructure is a multifaceted subject. One of these addresses the traffic serving capability of the transportation system. As the profession progresses in finding ways to improve infrastructure resilience in physical terms, an associated thought process is underway to enhance the adaptive capacity in traffic networks with intelligent systems and advanced related methods in order to cope with shocks in the traffic environment caused by nature-induced or other events. This paper reports research in-progress on measures for enhancing the resilience of road traffic networks with applications of connected vehicles. The need for resilient road traffic networks is defined in order to reduce the risk of severe loss of capability to serve demand. Resilience is the ability to resist the loss of traffic-serving capability by using traffic (geometric) and control system design advances (i.e. the inherent resilience) and by dynamically activating capacity-enhancing measures (i.e. the dynamic resilience). There is a need to go beyond the adaptive traffic control of intersections by enhancing inherent plus dynamic resilience of the traffic system at a broader spatial scale of a corridor or a wide-area road network. Connected vehicle technology and associated methods that yield resiliency measures (i.e. adaptive capacity attributes) are described. Ideas are advanced on how to apply these resiliency measures in practice in order to address efficiency and other issues in urban transportation. Finally, concluding remarks are presented on the technical feasibility of implementing the research ideas presented in this paper

The effectiveness of robot-enacted messages to reduce the consumption of high-sugar energy drinks

This exploratory study examines the effectiveness of social robots' ability to deliver advertising messages using different "appeals" in a business environment. Specifically, it explores the use of three types of message appeals in a human-robot interaction scenario: guilt, humour and non-emotional. The study extends past research in advertising by exploring whether messages communicated by social robots can impact consumers' behaviour. Using an experimental research design, the emotional-themed messages focus on the health-related properties of two fictitious energy drink brands. The findings show mixed results for humour and guilt messages. When the robot delivered a promotion message using humour, participants perceived it as being less manipulative. Participants who were exposed to humourous messages also demonstrated a significantly greater intent for future purchase decisions. However, guilt messages were more likely to persuade consumers to change their brand selection. This study contributes to the literature as it provides empirical evidence on the social robots' ability to deliver different advertising messages. It has practical implications for businesses as a growing number seek to employ humanoids to promote their services

Trends in hospital-based management of acute asthma from a teaching hospital in South Asia.

The aim of this study is to evaluate the hospital-based management of acute asthma in south Asia and to compare practices over a 10-year period. Adult patients (n = 102) admitted at a teaching hospital with acute asthma were studied. Documentation of precipitating factors, family history and physical signs were inadequate in more than half of patients. Pulse oximetry was documented in 95 (93%) patients, but peak flow monitoring was performed only in 50 (49%) patients. Ten-year trend showed deterioration in history and physical examination skills, under use of peak flow readings, and poor pre-discharge instructions. Some aspects of improved care included frequent use of pulse oximeter, preference of inhaled over systemic bronchodilators and increased use of systemic steroids. Significant deficiencies were identified in hospital-based management of acute asthma. Most aspects of asthma care continued to fall short of asthma guidelines

A preliminary evaluation of mobile phone apps to curb alcohol consumption

Mobile apps have become increasingly prevalent in modern society, and persuasive technology has a broader market than ever. Mobile-based alcohol cessation apps can promote positive behaviour change in users and improve the overall health of our society. This research aimed to understand the various features users respond to and make design recommendations for alcohol cessation apps. This paper reports on three sources of feedback (user ratings, user reviews, MARS App Quality score) provided on 20 alcohol cessation apps in the Google Play Store. Our findings suggest that self-control type apps received much greater positive user reviews than motivational apps. In addition, this trend was not observed through numeric user ratings. We also speculate on design recommendations for apps that are meant to inhibit alcohol intake

Evaluation of efficient vehicular ad hoc networks based on a maximum distance routing algorithm

Traffic management at road intersections is a complex requirement that has been an important topic of research and discussion. Solutions have been primarily focused on using vehicular ad hoc networks (VANETs). Key issues in VANETs are high mobility, restriction of road setup, frequent topology variations, failed network links, and timely communication of data, which make the routing of packets to a particular destination problematic. To address these issues, a new dependable routing algorithm is proposed, which utilizes a wireless communication system between vehicles in urban vehicular networks. This routing is position-based, known as the maximum distance on-demand routing algorithm (MDORA). It aims to find an optimal route on a hop-by-hop basis based on the maximum distance toward the destination from the sender and sufficient communication lifetime, which guarantee the completion of the data transmission process. Moreover, communication overhead is minimized by finding the next hop and forwarding the packet directly to it without the need to discover the whole route first. A comparison is performed between MDORA and ad hoc on-demand distance vector (AODV) protocol in terms of throughput, packet delivery ratio, delay, and communication overhead. The outcome of the proposed algorithm is better than that of AODV