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Many industries operate or run 24 h and seven days a week with downtime only for maintenance and repair in manufacturing facilities. This continuous operating trend allows for a higher production volume since the industry has relentless pressures on cost containment to maintain profit margins. However, the practice poses high risks of occupational injuries or major accidents. Shift working hours could lead to various safety and health and significantly impact the workers' well-being. Based on this fact, this paper presents a correlation analysis of shift works with sleep patterns, fatigue, and work injuries in food manufacturing plants, specifically in Malaysia. A survey using a set of questionnaires was conducted on two food manufacturing industries in Selangor, Malaysia. The industry operates continuously with a pre-planned downtime due to market globalization, industrialization transformation, and the rising demand for food. The companies in the food manufacturing industry held frequent internal and external audits to ensure the food quality was not being compromised and adhered to the local acts and regulations. To ensure the company runs continuously, the companies practice slow rotation schedules of shift work systems, where workers change to a new shift every three months. The companies have three working shifts per day, namely the morning shift (7.00 am to 3.00 pm), the afternoon shift (3.00–11.00 pm) and the night shift (11.00 pm to 7.00 am). Based on the statistical analysis, many workers prefer the day shift over the afternoon and night shifts. Sleep patterns and fatigue are significantly correlated with work-related injuries. Due to shift work, the workers tend to have fewer sleep hours, resulting in poor sleep patterns, which could increase the possibility of work injuries. In conclusion, workers' physical, mental and social well-being in any industry should be promoted and maintained to the highest degree. [ABSTRACT FROM AUTHOR]

• Pilot study of solar/hybrid/storage system for vertical farming under tropical climate condition with a case study at Malaysia. • Energy utilization and management via optimized building geometry modeling integrated with energy yield estimation tool to evaluate the potential of integrating green energy into urban agriculture. • Comprehensive analysis and assessments including technological, economic and environmental aspects of the proposed work. • The proposed work is evaluated under different design configuration (grid connected, stand alone, hybrid, storage etc) considering various optimization and design requirements and real-life constraints. • Comparative studies with hypothetical model and verification with additional energy modeling tool. Human population is projected to reach 9.7 billion in 2050 and strike 11.2 billion by 2100. Residence shift from countryside to cities will occur and the human population resides in the cities is envisaged to rise from 55% to 68%. Vertical farming was proposed to address food insecurity caused by overcrowded population and farmland shortages. The compound annual growth rate (CAGR) of vertical farming in the Asia Pacific is forecasted to grow at 22.1% with a market size reaching USD 2,101.0 million by 2024. Malaysian government encourages the implementation of vertical farming as the production of major agricultural commodities has contracted by 3.4% from 2015 to 2017. However, high energy consumption is one of the shortcomings of a vertical farm as the estimated annual energy consumption for each square meter of growing area is 3500 kW h. Thus, this paper proposes an optimized building geometry modeling integrated with energy yield estimation tool to evaluate the potential of integrating green energy into urban agriculture. This research examines the load demand in the vertical farming systems and develops solar/hybrid/storage for vertical farming system with energy yield, performance ratio, economics and environmental assessments. Preliminary resources assessment by analyzing the solar radiation of the sites was carried out at stage 1. At stage 2, load consumption was calculated, and specifications of the system were justified. Stage 3 included the development of solar PV system for the vertical farms, the economic evaluation in the context of net present cost (NPC), levelized cost of energy (LCOE) and investigation of the environmental impact. Grid-connected and standalone solar PV systems were developed for comparative studies. The estimated daily energy consumption for vertical farms in Selangor and Kuching was 430.116 kW h and 1002.024 kW h. Energy generated by grid-connected solar PV systems supported 11.6% and 8.35% of the load consumption in Selangor and Sarawak. The performance ratios of grid-connected solar PV systems in both selected sites were 82.22% and 82.56%. The finding proved that proposed work has significantly reduced the dependency of the utility grid. Additionally, the LCOE with solar PV integration vertical farming system appeared to be lower than the LCOE of the grid and lower CO 2 emission. This paper serves as a reference guide to the vertical farming stakeholders, national policy-decision makers and non-profit organizations who planned for similar initiatives especially those within the tropical climate regions. [ABSTRACT FROM AUTHOR]

Abstract: Building integrated photovoltaic (BIPV) systems are likely to become a dominant type of small-scale embedded generator (SSEG) on public low voltage (LV) distribution network in Malaysia due to the enormous amount of initiatives and efforts taken by the government to promote the use of BIPV. The growth of BIPV systems on LV distribution networks has the potential to alter the direction of power flow across the distribution networks, hence imposing several serious technical issues relating to power quality, distribution system efficiency and possible equipment overloading. Therefore, the utility companies need to study the following technical issues: (i) voltage regulation, (ii) voltage rise, (iii) voltage unbalance, (iv) network power losses, and (v) cable and transformer thermal limits. This paper describes research carried out to investigate and quantify the impacts of BIPV on LV networks with particular reference to developing countries striving to increase the utilisation of renewable energy. This paper presents and discusses the impacts of BIPV systems on two types of LV distribution network: a commercial LV distribution network and a residential LV distribution network in the state of Selangor, Malaysia. The results of these studies are compared with those from European networks to identify how the differences in the electrical network characteristics influence the allowable penetration of small-scale embedded generators. [Copyright &y& Elsevier]

Abstract: Landslide-susceptibility mapping is one of the most critical issues in Malaysia. These landslides can be systematically assessed and mapped through a traditional mapping framework that uses geoinformation technologies (GIT). The main purpose of this paper is to investigate the possible application of an artificial neural network model and its cross-application of weights at three study areas in Malaysia, Penang Island, Cameron Highland and Selangor. Landslide locations were identified in the study areas from the interpretation of aerial photographs, field surveys and inventory reports. A landslide-related spatial database was constructed from topographic, soil, geology, and land-cover maps. For the calculation of the relative weight and importance of each factor to a particular landslide occurrence, an artificial neural network (ANN) method was applied. Landslide susceptibility was analyzed using the landslide occurrence factors provided by the artificial neural network model. Then, the landslide-susceptibility analysis results were validated and cross-validated using the landslide locations as study areas. Different training sites were randomly selected to train the neural network, and nine sets of landslide-susceptibility maps were prepared. The paper then illustrates the verification of those maps using an “area under the curve” (AUC) method. The verification results show that the case of the weight using the same test area showed slightly higher accuracy than the weight used for the cross-applied area. Among the three studied areas, the verification results showed similar accuracy trends while using the weight for the study area itself. Cameron showed the best accuracy and Penang showed the worst accuracy. Generally, the verification results showed satisfactory agreement between the susceptibility map and the existing data on the landslide location. [Copyright &y& Elsevier]

Abstract: This paper presents a method of calculating long-term settlement of a loaded pad on soft clay at Klang, Selangor, Malaysia where the soil model is treated as an anelastic material of viscoelastic property. Initially, an elastic shear modulus (G) value from shear wave velocity profiles of the seismic tests from spectral analysis of surface wave (SASW) and continuous surface wave (CSW) tests was obtained. A value of damping (D) at an equivalent elastic strain is then calculated from the hysteresis of the plate load tests corrected to equivalent strain using the Damping–Strain formula. The calculated elastic settlement and its equivalent damping are then used to calculate the long-term settlement by applying the generalised viscoelastic formula. Comparisons to traditional methods of settlement predictions were made and the viscoelastic formula has shown better agreement to the observed settlement. Further modification of the settlement formula is introduced to improve the settlement accuracy to 10%. [Copyright &y& Elsevier]

Abstract: This paper presents the results of the cross-validation of a multivariate logistic regression model using remote sensing data and GIS for landslide hazard analysis on the Penang, Cameron, and Selangor areas in Malaysia. Landslide locations in the study areas were identified by interpreting aerial photographs and satellite images, supported by field surveys. SPOT 5 and Landsat TM satellite imagery were used to map landcover and vegetation index, respectively. Maps of topography, soil type, lineaments and land cover were constructed from the spatial datasets. Ten factors which influence landslide occurrence, i.e., slope, aspect, curvature, distance from drainage, lithology, distance from lineaments, soil type, landcover, rainfall precipitation, and normalized difference vegetation index (ndvi), were extracted from the spatial database and the logistic regression coefficient of each factor was computed. Then the landslide hazard was analysed using the multivariate logistic regression coefficients derived not only from the data for the respective area but also using the logistic regression coefficients calculated from each of the other two areas (nine hazard maps in all) as a cross-validation of the model. For verification of the model, the results of the analyses were then compared with the field-verified landslide locations. Among the three cases of the application of logistic regression coefficient in the same study area, the case of Selangor based on the Selangor logistic regression coefficients showed the highest accuracy (94%), where as Penang based on the Penang coefficients showed the lowest accuracy (86%). Similarly, among the six cases from the cross application of logistic regression coefficient in other two areas, the case of Selangor based on logistic coefficient of Cameron showed highest (90%) prediction accuracy where as the case of Penang based on the Selangor logistic regression coefficients showed the lowest accuracy (79%). Qualitatively, the cross application model yields reasonable results which can be used for preliminary landslide hazard mapping. [Copyright &y& Elsevier]

The perception that better information on environment and development is the determinant of effective rational decision- and policy-making processes provide the impetus for global interest in the use of sustainable development indicators (SDIs). Accordingly, proposals for SDIs are framed either on organisational goals or on disciplinary and multidisciplinary theories—aiming to reduce uncertainties in choosing the best alternative among a set of options concerning sustainability. Despite the fact that many SDI initiatives are explicitly aimed at improving policy-making, it is not apparent that political settings and organisational realities are taken into consideration in designing the framework for sustainability assessment. Ignoring the realities of policy-making dynamics can result in poor institutionalisation of the SDI development process, and therefore reduced impact of indicators. Linkage of SDIs to policy processes must also take into account the complex role of information in policy processes. The importance of societal values, cultural contexts and behaviour of bureaucracies must be understood and used to assist the assessment of progress towards sustainability using SDIs. Essentially, objective knowledge must be tampered with pragmatism in governance. This paper highlights the case of SDI development in the state of Selangor where the notion of instrumental rationality is balanced with the ‘incrementalism’ of the policy process that provided the foundation for institutionalising the reporting and use of SDIs. The ideals and paradoxes of participatory decision-making, the principles of the rational model and decision-making processes within a state government are critically examined. [Copyright &y& Elsevier]