Search

Trichoderma harzianum EU2-77 was a mutant strain of the wild-type strain T. harzianum NP13a isolated in Singapore. A multi-mutagenesis one-screening (MMOS) method was developed to further improve strain EU2-77 and a new mutant EUA20 was obtained. It exhibited filter paper cellulase (FPase) activity up to 14.79 IU/mL within 6 days shake flask cultivation. Activities of FPase, endoglucanase, β-glucosidase, and xylanase, and protein content by EUA20 were respectively increased to 5.73, 4.35, 7.34, 1.80 and 2.70 folds. Using pretreated oil palm empty fruit bunch (OPEFB) and corncob powder as the substrates, strain EUA20 presented approximate 6.52 and 8.80 IU/ml FPase activity. Reducing sugar yield of 615.8 and 636.8 mg/g biomass were respectively obtained for OPEFB and corncob powder using cellulolytic enzymes of strain EUA20. Our results demonstrated that mutant strain EUA20 had great potential in on-site cellulase production for effective biomass bioconversion. [ABSTRACT FROM AUTHOR]

Plastic grocery bags are one of the most ubiquitous single-use packaging products. Recently, 'eco-friendly' options of plastic grocery bags have gained traction such as kraft paper, cotton, biodegradable, and reusable polypropylene non-woven bags. However, the impact of using various grocery bags in cities with dense population, well-developed infrastructure and thermal treatment as an end-of-life waste management option has been insufficiently documented. In this study, commonly found single-use (HDPE, biodegradable plastic, kraft paper) bags and reusable (cotton, polypropylene non-woven) bags were considered for the life cycle assessment (LCA). The usage characteristics (reusability, dimensions, carrying capacity) of bags, the production process (raw materials extraction, production processes), and emissions were determined as the significant factors contributing to the negative environmental impacts. In a model city with confined waste management, the assessment determined that the reusable polypropylene non-woven bag (PNB) caused the least overall negative environmental impacts when there are 50 instances of reuse, followed by single use HDPE plastic bag (HPB). The global warming potential (excluding biogenic carbon) was 14, 81, 17 and 16 times higher for HDPE plastic, kraft paper, cotton woven and biodegradable polymer bags, respectively, when compared to PNB. Moreover, kraft paper or cotton woven bags demonstrated the highest negative impacts for the impact categories including abiotic fossil depletion, freshwater-, marine- and terrestrial-ecotoxicities, human toxicity, acidification and eutrophication potentials. Further, sensitivity analysis indicated that the inflexion point for the PNB was minimum 4 reuses to avoid emission equivalent to the HPB. Singapore was adopted as the model city with confined waste management structure that imports most of the grocery bags, either as finished goods or as raw materials. Through comprehensive insights based on the new outlook of the integrated LCA model (cradle-to-grave) that included full-scale transportation component, the usage of the real case data from a city to develop the life cycle inventory, and consideration of the existing grocery bags options, the environmental assessment along with critical evaluation was conducted. • Case specific life cycle assessment of grocery bags in the context of Singapore. • Plastic bags presented lower environmental footprint than paper and cotton bags for Singapore. • Plastics are an environmental friendly option for waste management structures with end-of-life thermal treatment. • Multiple reuse of plastics is a means to minimize environmental footprint. [ABSTRACT FROM AUTHOR]

The Architecture, Engineering, Construction and Owner-operated (AECO) industry faces an array of productivity challenges, in part stemming from limited interoperability and suboptimal management of building information across project lifecycles. This paper investigates the application of rule-based systems from the manufacturing industry, especially as used in the semiconductor manufacturing sector, to improve productivity in the AECO industry. A comparative methodology is employed, examining processes in both the manufacturing and AECO industries. The results indicate that methodologies from semiconductor mask manufacturing can be effectively adapted for use in the AECO industry, particularly in design for buildability and standardized rule application. This paper includes the implementation of a Proof-of-Concept (POC) for Manufacturing Rule Check (MRC) in the AECO industry, focusing on Prefabricated Bathroom Units (PBU) production. The MRC developed for the POC could be integrated into the Model Checker platform of Singapore's CORENET X regulatory approval system, as well as deployed as a specialized application in the cloud that facilitates ease of collaboration among the design to fabrication players in the construction process. • Conducted a comparative analysis between semiconductor and AECO processes • Implemented Manufacturing Rule Check system focused on prefabricated bathrooms • Enhanced BIM and IDD interoperability with rule-based checking on regulatory platforms • Demonstrated the significance of adopting IDD to streamline AECO workflows [ABSTRACT FROM AUTHOR]

This paper developed a novel online optimization deep learning framework for accurate estimation and control of tunnel boring machine's (TBM) attitude and position. The proposed spatio-temporal deep learning model integrates graph convolutional network (GCN) and long short-term memorial (LSTM) neural network which can provide an accurate estimation of TBM's trajectory deviations. This model is later utilized as the meta-model and integrated with an online non-dominated sorting genetic algorithm II (NSGA-II) method to optimize and minimize the trajectory deviations in real-time. A tunnel project from Singapore is utilized as a case study for demonstration purposes. TBM's key operational parameters, articulation displacements, and TBM's trajectory deviations are processed and utilized for real-time prediction. The results indicate that (1) The developed deep learning models can predict TBM's trajectory deviations with high accuracy. (2) TBM's trajectory deviations can be effectively reduced by the proposed optimization method. (3) The proposed spatio-temporal deep learning methods outperform the state-of-the-art methods. (4) The proposed online optimization method is more practical and creates better overall improvement than the conventional multi-objective optimization (MOO) approach. The novelty of this paper includes (a) developing a hybrid framework for accurate trajectory deviation estimation and TBM operating optimization, and (b) investigating the influence of time and distance lag between the TBM operation and position control by considering an online optimization. • A novel online multi-objective optimization (MOO) method is proposed. • Deep learning model is established for reliable estimation on TBM's trajectory deviations. • The developed model is utilized as meta-models and hybrids with online NSGA-II method. • A tunnel project from Singapore is utilized as a case study • TBM's overall trajectory deviations can be reduced by 46.4% by the proposed method. [ABSTRACT FROM AUTHOR]

This paper explores the influence of political leaders' populist communication styles on public adherence to government policies regarding COVID-19 containment. We adopt a mixed-methods approach that combines: theory building with a nested multicase study design for Study 1 and an empirical study in a natural setting for Study 2. Based on the results from Studies 1 and 2, we develop two propositions that we further explain theoretically: (P1) countries with political leaders associated with engaging or intimate populist communication styles (i.e., the UK, Canada, Australia, Singapore, and Ireland) exhibit better public adherence to their governments' COVID-19 movement restrictions than do countries with political leaders associated with communication styles that combine the champion of the people and engaging styles (i.e., the US); (P2) the country whose political leader is associated with a combination of engaging and intimate populist communication styles (i.e., Singapore) exhibits better public adherence to the government's COVID-19 movement restrictions than do countries whose political leaders adopted solely engaging or solely intimate styles, namely, the UK, Canada, Australia, and Ireland. This paper contributes to the research on political leadership in crises and populist political communication. [ABSTRACT FROM AUTHOR]

This research develops a hybrid approach that integrates light gradient boosting machine (LightGBM) and non-dominated sorting genetic algorithm II (NSGA-II) to optimize the tunnel boring machine (TBM) performance during excavation. The TBM operational data are first extracted and meta -models are established to estimate the key TBM performance, including the penetration rate, over/under excavation ratio, and energy consumption. An optimization process is proposed by adopting NSGA-II and the technique for order preference by similarity to an ideal solution (TOPSIS) analysis to determine ideal operational parameters. The developed approach acts as a useful tool that assists tunnel construction automation and improves TBM performance under different in-situ conditions. Real data from a tunnel project in Singapore is utilized as a case study to examine the applicability and efficiency of the proposed approach. The results indicate that (1) The proposed meta -model provides reliable estimation with an average RMSE and MAE of 2.604 m m / m i n and 3.402 m m / m i n for TBM's penetration rate(O 1), 0.0211 and 0.0324 for over/under excavation ratio (O 2), and 15.512 k w h and 23.088 k w h for energy consumption (O 3), respectively. The prediction accuracy is better than the state-of-the-art methods; (2) The TBM's performance can be optimized by the proposed approach with an average improvement of 33.14 %, 1.32 %, and 17.95 % for O 1 to O 3 , respectively, and an overall improvement of 39.60 %; (3) The overall reliability of TBM operation improved after optimization with a significant reduction in data variance by 91.16 %, 76.92 %, and 97.35 % for O 1 to O 3 , respectively. This paper contributes to proposing a novel method that integrates LightGBM with NSGA-II in resolving the complex TBM operation problem by considering the major performance indexes including excavation efficiency, safety, and energy consumption during TBM operation. [ABSTRACT FROM AUTHOR]

Faced with international climate obligations and domestic pressure, Singapore has recently raised its climate goals significantly. The government had affirmed its intention for carbon emissions to peak before 2030 and for Singapore to attain net zero greenhouse gas emissions by 2050. However, as Singapore transitions to green energy, there remains much uncertainty if this transformation, coupled with rapidly evolving geopolitics, would present vulnerabilities to energy security. Hence, this paper is an attempt to investigate Singapore's possible paths to achieve these goals while enhancing energy security in view of present and future energy plans. Key parameters of energy security in Singapore's context are identified to determine how different policy decisions would influence them. The effects of various current and potential policies can thus be evaluated using a systems thinking and system dynamics approach to propose new energy solutions to improve energy security. System dynamics modelling reveals that new energy supply solutions would have to be considered in Singapore's Energy 2050 Plan while furthering efforts in reducing energy demand. Findings reveal that Singapore should have a target of >80% renewable energy by 2050, pursue a central strategy towards sustainable diversification of its energy sources into hydrogen, electricity imports and solar energy and reduce energy consumption. Accordingly, Singapore's energy security can then be improved in terms of the economic, energy supply chain and environmental dimensions, and towards attaining net-zero emissions. [Display omitted] • Systems approach to Singapore Green Plan 2030 and simulation of policies towards energy security and net zero. • Systems thinking and system dynamics modeling to evaluate key assumptions and energy security parameters. • Model validation, both structural and behavioral, through base model simulations as well as behavioral tests. • Effect of government policies on hydrogen energy, low carbon electricity imports and energy saving on energy security. • Simulations suggest policies for higher renewable energy targets to attain net zero carbon emissions and energy security. [ABSTRACT FROM AUTHOR]

This paper establishes a digital twin (DT) enabled model that aims to achieve real-time monitoring and control to enhance the overall performance of tunnel boring machines (TBM) during excavation. Through the Internet of Things (IoT) sensors that are installed on TBM, the actual operating status is transferred from the physical object to the digital model. Deep learning models that integrated graph convolutional network (GCN) and long short-term memory (LSTM) networks are employed for reliable TBM performance estimation. An online multi-objective optimization (MOO) approach is then proposed to determine the optimal operating parameters for advanced control. Real data from Singapore's Circle Line 6 C885 project is utilized as a case study to examine the applicability of the developed digital twin model. TBM's penetration rate, over-excavation ratio, energy consumption, and tool wear are selected as the objectives (O 1 to O 4) for optimization. The results indicate that (1) The digital twin model can provide a reliable estimation of TBM's performance indicators with a high coefficient of determination (R 2) values. (2) TBM's overall performance can be effectively improved through the proposed online optimization method, with an overall improvement of 21.12%. (3) The proposed online optimization method is more practical and creates better improvement than the conventional MOO approach. This study addresses the existing research gaps of lacking a reliable method to guide TBM operation with enhanced performances for the major objectives. It also contributes to proposing a novel intelligent approach that integrates DT, deep learning, and an online-NSGA-II method for TBM operation optimization during tunnel excavation. • A digital twin enabled approach is proposed for real-time intelligent control for TBM operation. • An MOO approach that integrates deep-learning and online optimization is established. • Data from a realistic tunnel project in Singapore is used to demonstrate as a case study. • TBM's efficiency, safety, energy consumption and tool wear are considered as objectives. • An overall improvement of 21.12% is achieved by implementing the proposed method. [ABSTRACT FROM AUTHOR]

Energy trilemma is one of the most pressing concerns on agendas of many governments and international organizations. In this paper, the authors propose a novel quantitative tool to aid designing policies for energy systems planning and creating research and developments programs aimed at achieving specific policy goals. The proposed modified Markowitz theory can be used to build the efficient plane considering sustainability, security and affordability of the energy system composed of a portfolio of competing technologies. The novel and original contribution of this paper is the extension of the Markowitz theory to include the measure of portfolio’s sustainability and proposing a new tool to tackle the energy trilemma. The proposed tool was used to compare policy packages to support possible steady green growth of Singapore economy – a densely populated city state with no natural resources, dynamic economy requiring secured supply of energy, and ambitions of being a leader in sustainable development. It was found that efforts aimed at simultaneous improving performance and lowering costs of novel technologies is more desirable, contrary to policy focusing on either alone. Fuel cells and solar photovoltaic panels were found to be important pieces of an efficient power generation portfolio. [ABSTRACT FROM AUTHOR]

• There was a substantial shift in the population at risk of COVID-19 in Singapore over time. • Successful control in the community protected an at-risk aging population. • There were large outbreaks in the younger migrant worker population, with less severe disease. • This resulted in one of the lowest case fatality rates globally. The vast majority of COVID-19 cases in Singapore have occurred amongst migrant workers. This paper examined trends in the hospitalised cases and tested the assumption that the low severity of disease was related to the relatively young affected population. All patients with PCR-positive SARS-CoV-2 admitted from February to April 2020 were divided into: (i) imported cases, (ii) locally-transmitted cases outside migrant worker dormitories and (iii) migrant worker dormitory cases. They were examined for underlying comorbidities, clinical progress and outcomes. Imported cases (n = 29) peaked in mid-March 2020, followed by local cases (n = 100) in mid-April 2020; migrant worker cases (n = 425) continued to increase in late April 2020. Migrant worker cases were younger, had few medical comorbidities and less severe disease. As the migrant worker cases increased, the proportion of patients with pneumonia decreased, whilst patients presenting earlier in their illness and asymptomatic disease became more common. Singapore experienced a substantial shift in the population at risk of severe COVID-19. Successful control in the community protected an aging population. Large migrant worker dormitory outbreaks occurred, but the disease incurred was less severe, resulting in Singapore having one of the lowest case fatality rates in the world. [ABSTRACT FROM AUTHOR]

• A real-time operational optimization for district cooling system operations. • Established a holistic optimization comprising of every component of the system. • Implemented the proposed optimization in a live district cooling plant in Singapore. • Achieved 10% efficiency improvement and 2.9 million kWh of electric energy saving. • A complete holistic district cooling system optimization at least in South East Asia region. This paper is proposing a real-time optimization system for the district cooling systems which comprises of three different modules being the cooling demand prediction and guidance, chiller system optimization, and cooling tower system optimization modules. First and foremost, the cooling demand for a district cooling system (DCS) is predicted by engaging the artificial Neural Network technique. The Mixed Integer Linear Programming technique then does its job to help in defining the optimal chiller dispatch schedule and allocation of cooling loads among chillers in the district cooling plant. Afterwards, the previously predicted demand is introduced into the chiller system and cooling tower system optimization modules to define an optimal operation in real-time. The regression technique and historical operation data are employed to capture the characteristics and operating performance of each component present in the DCS plant. An objective function, i.e., minimization of energy consumption, is established for the carrying out of the optimization by applying the Sequential Quadratic Programming. The proposed optimization is then deployed to a commercial DCS plant in Singapore. Subsequently, two years' worth of operating data are collected and compared. Three important contributions are presented. The first contribution is that the proposed intelligent operation strategy offers approximately 10% energy efficiency improvement. The second contribution is creating detailed mathematical models and defining the important interrelations of different DCS components. The last contribution is a holistic DCS optimization coupling with demand prediction. The latter two contributions allow to avoid suboptimal solution and grasp an optimal operation from different performance combination of DCS components. A practical implementation in a commercial DCS plant is done and offers 2.4 million kWh of annual electric energy saving. [ABSTRACT FROM AUTHOR]

For automatic geology perception, this paper develops a DTW-Kmedoids-enabled time series clustering framework to gain a clear insight into the geological condition ahead of the tunnel boring machine (TBM) head. The core idea of DTW-Kmedoids is to incorporate dynamic time warping (DTW) as a distance metric into a popular clustering algorithm Kmedoids, aiming to aggregate time series data reflecting similar conditions of surrounding geology into the same cluster. It has been verified in a sequence dataset recording 377 operational rings from a TBM tunneling project in Singapore. Results indicate that the proposed DTW-Kmedoids algorithm outperforms Kmedoids and softDTW-Kmedoids in partitioning the whole dataset into four meaningful clusters on behalf of four geological conditions. Moreover, it shows merits in great robustness to handle varying-length temporal sequences and even fragmentary data instead of the full observations. Furthermore, an online clustering mechanism is well designed to adaptively update the cluster center, which can accomplish the dynamic recognition of the forward geological circumstances ring by ring. In short, the practical value behind the hybrid time series clustering is to automatically and quickly perceive lithology categories along the designed tunnel trail with no requirement of data labeling, possibly allowing for further inference of geological risk and guidance in safe excavation. • A hybrid unsupervised algorithm for time series clustering named DTW-Kmedoids is developed. • It aims to automatically perceive the geological condition ahead of TBM head during tunneling. • It is verified in a TBM project to divide data into four clusters representing geological conditions. • The proposed algorithm can well deal with varying-length and incomplete temporal sequences. • The online clustering mechanism is proposed to carry out the dynamic recognition ring by ring. [ABSTRACT FROM AUTHOR]

• General decoupled method for reliability-based geotechnical design. • The method is robust to model complexity and parameter dimension. • Non-parametric and global estimation of failure probability functions. • Case study on the design optimization of deep excavation in Singapore marine clay. • Effects of statistical characteristics of soil properties on design is investigated. This paper presents a general decoupled method for reliability-based geotechnical design that takes into account the spatial variability of soil properties. In this method, reliability analyses that require a lot of computational resources are decoupled from the optimization procedure by approximating the failure probability function globally. Failure samples are iteratively generated over the entire design space so that their global distribution information can be extracted to construct the failure probability function. The method is computationally efficient, is flexible to implement, and is well suited for geotechnical problems that may involve sophisticated models. A design example of two-dimensional deep excavation against basal heave is discussed for Singapore marine clay where the density and normalized undrained shear strength of soil mass are modeled as random fields. Results demonstrate that the proposed method works well in practice and is advantageous over the coupled or locally decoupled reliability-based geotechnical design methods. [ABSTRACT FROM AUTHOR]

VELOX-CI was launched on December 16, 2015 into the near-equatorial orbit. It is the second micro-satellite of Satellite Research Center (SaRC) in Nanyang Technological University in Singapore. VELOX-CI is designed to explore the potential of using the commercial-off-the-shelf (COTS) GPS receivers for RO mission for the first time. Three GPS antennas are located at the zenith, forward-velocity, and after-velocity directions. In total, VELOX-CI collected 240 radio occultation (RO) missions (570 h) from 2015 to 2018 with mission durations ranging from 0.5 to 16.7 h. The lowest penetration altitude from the COTS receivers reaches 6 km. In this paper, the RO performance of the VELOX-CI is evaluated and validated with both ground-based and space-based measurements. Tropospheric and ionospheric profiles obtained from VELOX-CI are also compared with assimilative atmospheric models and empirical ionospheric models, respectively. Results show that with proper sampling frequencies (5–20 Hz), the refractivity error estimated by VELOX-CI RO is below 5% at altitudes below 25 km compared to reanalysis model estimations and radiosonde measurements. The observed ionospheric peak density and height show reasonable ranges for both daytime and nighttime. This study demonstrates the capability of COTS receiver in observing atmospheric and ionospheric parameters. In the future, utilizing COTS receivers with lower-cost low Earth orbit (LEO) satellite missions can largely increase the data volume of RO and enhance our capability in monitoring the Earth's atmosphere. [ABSTRACT FROM AUTHOR]

This paper investigates bike allocation strategy in a competitive dockless bike sharing market from both market leader and market follower's perspective. Market leader aims to grasp the market using the shortest time, while market follower wants to get the market share from market leader. The initial bike allocation position, coverage area and allocation method are investigated based on community structure method. An approximate optimal allocation model is proposed to maximise the recourses. Numerical examples are tested in a simplified Sioux Falls network and a real bike sharing network in Singapore to illustrate the effectiveness and practicability. Results show that the proposed method could identify the reasonable and efficient allocation position quickly. Market follower should apply the same allocation strategy as market leader, while use lower ticket, more bikes, and large batches allocation to strive for market share. [ABSTRACT FROM AUTHOR]

Time series forecasting is an important area of forecasting which has gained many attentions from various research areas. In line with its popularity, various models have been introduced for the purpose of producing accurate time series forecasts. Nevertheless, it is difficult to find an ideal model as there is no model that can perform best for all types of data. Recently, combination of forecasts has gained immense popularity in the time series forecasting area. Among the well-known combination technique is the weighted-based approach, where appropriate weights are given based on the performance of each individual model. In this paper, a robust methodology for accurate time series forecasting based on Artificial Bee Colony (ABC) algorithm and four Group Method of Data Handling (GMDH) models, namely GMDH-Polynomial, GMDH-Radial Basis Function, GMDH-Sigmoid and GMDH-Tangent are proposed. In this methodology, the first step was to develop forecasts using individual GMDH models. In the second step, weights for each individual GMDH were calculated heuristically using ABC algorithm. In the final step, the results were aggregated to form a new forecast. For the purpose of evaluating the performance of the proposed model, the model was applied to a real time series data which is the monthly tourist arrivals from Singapore to Malaysia from year 2000 to 2017. Based on the empirical results, the application of nonlinear transfer function such as Tangent function has the potential to improve the performance of GMDH model, while the other functions such as Sigmoid function produced a forecast which is worse than the conventional GMDH-Polynomial. However, the combination of GMDH models using ABC managed to outperform all the individual models. The empirical finding demonstrated the efficiency of Combined GMDH model in time series forecasting, as well as the applicability of implementing optimization algorithm to find appropriate weights for the individual models. [ABSTRACT FROM AUTHOR]

How to scientifically measure corruption has become a key issue for both the anti-corruption research and practice. By introducing the search popularity of corruption-related topics in Google Trends, this paper proposes a comprehensive corruption index called Corruption Search Index (CSI). A novel search strategy is designed, aiming to adjust the search popularity data for the comparison among different countries. The empirical analysis of 63 countries along the Belt and Road shows that Singapore remains the cleanest status among these countries while Afghanistan is facing a serious corruption situation. [ABSTRACT FROM AUTHOR]

• A brief overview of small modular NPPs and its feasibility for Singapore. • MINLP model for optimal site selection of modular NPPs in a region. • A case study on JPark Simulator, a virtual environment for the EIP in Jurong island, Singapore. • The model can serve as a preliminary feasibility analysis tool for SMR site selection. Small Modular Reactor (SMR) is a small, compact version of a conventional Nuclear Power Plant (NPP) and holds much promise for the future. Installing SMRs in a region requires a series of carefully planned steps out of which site selection is a critical one. This paper proposes a novel mathematical model for evaluating potential land sites for their suitability of hosting a modular NPP. Most existing decision making tools for NPP site selection rely on qualitative information from the experts. These tools require significant resources and therefore can only be applied to a limited number of selected sites. The proposed model is a Mixed Integer Non-linear Programming (MINLP) formulation which considers a variety of factors like cost, cooling water availability, earthquake risk, etc. to identify best locations for the SMRs in a distributed power system. A case study based on a virtual EIP simulator is conducted to demonstrate the capabilities of the model by finding the optimal locations of modular NPPs. The model offers a preliminary platform for carrying out further extensive studies. [ABSTRACT FROM AUTHOR]

Gravity waves are recognized as an integral part of earth's atmosphere which are mainly responsible for energy and momentum distribution among different layers and regions in the atmosphere. Various sources present in land, ocean, and atmosphere such as mountains, convection, jets and fronts etc. are responsible for gravity waves generation. Thunderstorms (deep convection) are one of the major sources of gravity waves in the tropical region, capable of generating waves with a wide range of frequencies and scales and significantly affecting the existing waves. Previous numerical studies have characterised the wave properties that are generated from thunderstorms, but there are no statistically quantified studies. In this paper, we have modelled the relationship between the latent heat generated inside a thunderstorm and the gravity wave properties at the geo-collocated points. Gravity waves are identified over Singapore radiosonde station (with data available until 30 km altitude with 12 h temporal resolution) in the stratosphere using wavelet studies. Based on the GROGRAT ray tracing methods to identify the thunderstorm locations, and RAMS cloud-resolving models simulations to obtain the latent heating of the thunderstorm, a regression analysis is performed using 200 cases of gravity waves. Furthermore, cloud-top momentum flux analysis is performed for various cases latent heat. This study is expected to provide more quantified and concrete information on the coupling between the thunderstorm and gravity wave which includes the variance in these relationships due to wave frequency spectrum and generation mechanisms. [ABSTRACT FROM AUTHOR]

Accurate power load prediction plays a key role in reducing resource waste and ensuring stable and safe operations of power systems. To address the problems of poor stability and unsatisfactory prediction accuracy of existing prediction methods, in this paper, we propose a novel approach for short-term power load prediction by improving the sequence to sequence (Seq2Seq) model based on bidirectional long-short term memory (Bi-LSTM) network. Different from existing prediction models, we apply convolutional neural network, attention mechanism, and Bayesian optimization for the improvement of the Seq2Seq model. Moreover, in the data processing stage, we use the random forest algorithm for feature selection, and also adopt the weighted grey relational projection algorithm for holiday load processing to process the data and thereby overcome the difficulty of holiday load prediction. To validate our model, we choose the power load dataset in Singapore and Switzerland as experimental data and compare our prediction results with those by other models to show that our method can generate a higher prediction accuracy. • Develop a novel power load forecasting approach by improving the Seq2Seq model with various advanced algorithms. • Use the Bi-LSTM in the encoder and decoder of Seq2Seq model to enhance information utilization. • Introduce the Attention mechanism in the Seq2Seq model to help the decoder focus on key sequence information. • CNN and BO algorithm are combined with Seq2Seq model to improve effectively model prediction accuracy. • Random forest and WGRP are used for data processing respectively to improve the effectiveness of data processing. [ABSTRACT FROM AUTHOR]

This paper adopts the Circuit of Culture (COC) – an interpretive approach to international public relations practice based on its five moments (i.e., regulations, production, representations, consumption and identity) – as a guiding framework to analyze corporate social responsibility discourses of Wilmar, a multinational corporation based in Singapore. Sustainability reports from 2009 to 2019 were first accessed to examine the negotiation dynamics that occur in textual discourse when the company dealt with the talk-action relationship through the Communication as Constitutive of Organization (CCO) approach. These were integrated with the contextual propositions nurtured in the five moments of COC to identify the negotiating mechanisms that Wilmar constructed to make sense of, explain, and justify tensional situations between set commitments and actual performance. This study aims to demonstrate how CCO can complement COC to offer a holistic interpretive approach to understand the situated communication dynamics and discursive construction process of talk-action relationship in an international public relations context. • Provided empirical discourse to illustrate the negotiation dynamics of handling talk-action relationship. • Identified the tension mechanisms to exemplify and interpret interactions between the five moments. • Offered a holistic interpretative CSR framework to suggest how CCO can complement COC. [ABSTRACT FROM AUTHOR]

The topic of this paper evolves on the discourse of digital modeling in landscape design. Current design methods stagger to address physical forms and dynamics present in the environment. This status quo limits possibilities to integrate scientific evidence when developing spatial and aesthetic configurations in urban landscapes. Remote sensing technology such as laser scanning measures physical forms to reproduce them as geo-specific digital 3D models, while dynamic simulation is widely used to predict how scenarios will perform under given conditions. However, there is still a need for a holistic design process that is capable of integrating both the measured physical forms and physical dynamics. This paper presents a novel framework using point cloud modeling to shape design scenarios that are iteratively evaluated for their performance. The proposed framework is demonstrated through a case study in Singapore. New spatial configurations are tested for the site through an iterative and comparative analysis of the design performance. The case study exposes (1) a site-specific design approach by iteratively modeling a laser-scanned point cloud model, (2) a workflow to convert the geometric data from the point cloud models into voxels and meshes, (3) an integration of computational fluid dynamics (CFD) simulation during design development as per-point attributes, and (4) a comparison of the configurations to identify best performing scenarios. This design framework can support city managers, planners, urban and landscape designers to better inform their decision-making process by relying on accurate scientific feedback. By guiding the design process with the consideration of the built environment as a complex adaptive system, it will be possible to improve how open spaces and ecosystem services perform in cities, and to design landscapes that can mitigate dynamic events such as urban heat islands. • Evidence-based approach for urban landscape design using point cloud modeling • Iterative process integrating digital modeling and assessment of design performance • Feedback loop with scenario comparison [ABSTRACT FROM AUTHOR]

Urban air mobility (UAM) has attracted the attention of aircraft manufacturers, air navigation service providers and governments in recent years. Preventing the conflict among urban aircraft is crucial to UAM traffic safety, which is a key in enabling large scale UAM operation. Pre-flight conflict-free path planning can provide a strategic layer in the maintenance of safety performance, thus becomes an important element in UAM. This paper aims at tackling conflict-free path planning problem for UAM operation with a consideration of four-dimensional airspace management. In the paper, we first introduce AirMatrix, previously developed by the team, and extend it as a four-dimensional airspace management concept. On the basis of AirMatrix, we formulate the shortest flight time path planning problem considering resolution of conflicts with both static and dynamic obstacles. A Conflict-Free A* (CFA*) algorithm is developed for planning four-dimensional paths based on first-come-first-served scheme. The algorithm contains a novel design of heuristic function as well as a conflict detection and resolution strategy. Numerical simulation was carried out using the building information in a typical urban area in Singapore. The results show that the algorithm can generate paths resolving a significant number of potential conflicts in airspace utilization, with acceptable computational time and flight delay. The findings of this study will provide references for stakeholders to support the development of UAM. [ABSTRACT FROM AUTHOR]

Abstract: Singapore has a steady rise in its electricity demand. The Singaporean electricity supply system relies so far heavily on fossil fuels, especially gas and oil, which are both mainly imported from Malaysia and Indonesia. This makes the electricity system in Singapore rather vulnerable to price variations and possible political conflicts with neighbouring countries. A short term solution is the construction of a LNG (liquefied natural gas) terminal which opens supply options to many sources in the world. In the long term, renewable energies such as photovoltaics will certainly be introduced into the Singapore''s energy system in a more significant way. This paper discusses the possibility to produce substantial amounts of electricity by solar photovoltaics (PV). In addition, the integration of electromobility in Singapore is analysed. Using PV and electric vehicles (EV), the future primary energy demand and CO2 emissions in Singapore could be reduced significantly. The paper will describe the TIMES (The Integrated MARKAL (Market Allocation) EFOM (Energy Flow Optimisation Model) System) model for Singapore which is developed within the project TUM CREATE (Technische Universität München Campus for Research Excellence and Technological Enterprise). TUM CREATE is a research programme sponsored by the Singapore National Research Foundation (NRF). One research goal of a sub-project in TUM CREATE is to develop scenarios of the future energy demand and energy supply in Singapore under various boundary conditions, especially oil and gas prices or policies to reduce import dependencies etc. All upstream and downstream sectors of the energy system, including traffic and heavy industry like refineries, will be part of the developed model. First results about the impact of PV and electromobility on Singapore''s primary energy demand and CO2 emissions are presented here. [Copyright &y& Elsevier]

• Advanced LCOS method to compare electricity and thermal energy storage. • Parametric storage sizing to analyse self-sufficiency and LCOS. • Evaluation of an office, a hotel and a warehouse scenario in Singapore. • Thermal energy storage offers lower LCOS, but achieves low self-sufficiency. • Battery storage needs to be well-sized. In this paper, we propose an advanced Levelised Cost of Storage (LCOS) model to compare electricity and thermal energy storage for cooling applications. The proposed model is applied to evaluate the LCOS for Lithium-Ion (Li-Ion) battery, chilled water and ice storage for Photovoltaic (PV) powered cooling for an office, a hotel, and a refrigerated warehouse scenario in Singapore. Parametric energy simulations varying the storage size were carried out to analyse the optimal storage size for different applications and technologies. The thermal energy storages were found to cause a lower chiller plant Coefficient of Performance (COP), which leads to an increased energy consumption. As a result, the battery can achieve a better performance in terms of self-sufficiency. The LCOS for the thermal energy storages are generally lower than that of the battery, at 23–47 USD ct / kWh el for all the analysed storage sizes. However, a well-sized battery can only achieve LCOS of 55 USD ct / kWh el for the office scenario, 71 USD ct / kWh el for the hotel scenario, and 55 USD ct / kWh el for the refrigerated warehouse, due to high investment cost. This work also highlights that thermal energy storage has a better potential for applications that require a larger shift of energy, such as in the investigated hotel and refrigerated warehouse scenario. [ABSTRACT FROM AUTHOR]

• Simulated effects of building typology on solar potential and energy use intensity. • Identified impacts of design factors on solar potential and energy performance. • Hybrid and courtyard typologies have twice the rooftop solar potential from others. • Reduction in CO 2 emissions was twice higher for hybrid and courtyard typologies. • Roof PV for courtyard typology reduced building energy use intensity by up to 25%. This paper presents the results of an investigation on the relationship between urban block typology, solar energy harvesting potential and building energy use efficiency in the context of the tropical high-density city Singapore. Thirty generic urban block cases in six typologies that represent a diverse range of urban forms were examined through simulation-based studies under the same planning conditions and simulation assumptions so as to rule out the impact of non-design related factors. Several key planning and geometric parameters which capture the formal characteristics of the urban blocks were examined as independent variables, and the dependent variables include the performance indicators on solar energy harvesting potential and building net energy use intensity that capture the dual benefits of photovoltaic (PV) systems in reducing building cooling loads and offsetting local plug loads with electricity generated on site. The results indicate that, under the same planning conditions and design premises, differences in urban block typology could lead to up to 200% increase in solar energy harvesting potential and electricity generated from rooftop PV, twelve times higher rate of reduction in building cooling loads, tow times higher rate of reduction in net purchased electricity, and 25% lower building net energy use intensity. The courtyard and hybrid urban block typologies consistently outperform the other typologies, especially the commonly implemented tower and slab blocks, and they benefit the most from PV deployment in the tropics. The comparison between an existing residential precinct and a hypothetical alternative hybrid urban block further demonstrated the significant impact of urban design on efficiency of PV electricity generation and building energy use efficiency. In addition to the significant economic benefit in reduction in utility cost and environmental implication in terms of equivalent reduction in CO 2 emissions on urban scale, this study highlights the crucial role that urban design plays in terms of maximising on-site renewable energy production such as solar energy. The significant planning and geometric parameters in relation to the performance indicators provide insight as reference for establishing solar energy friendly urban planning and architectural design guidelines. The methodology and technical workflow as developed can support reliable and efficient feasibility studies, especially in the early stage of urban planning and architectural design. Integrated with other performance evaluations, they can facilitate decision-making on implementation of renewable energy integrated green building technologies and passive design strategies. [ABSTRACT FROM AUTHOR]

Highlights • A scalable and smart HVAC control approach. • An IoT architecture and prototype for implementing the control. • Deployment results in a test-bed. • Implementation aspects with IoT and legacy BMS. Abstract Scalability of control algorithms used for savings energy in commercial building Heating, Ventilation and Air-Conditioning (HVAC) system and their implementation on low cost resource constrained hardware is a challenging problem. This paper presents the Internet of Things (IoT) prototype which implements a smart and scalable control approach called the Smart-Token Based Scheduling Algorithm (Smart-TBSA) to minimize energy in commercial building HVAC systems. The IoT prototype is formalized with an architecture that encapsulates the different components (hardware, software, networking, and their integration) along with their interactions. A detailed description of the different components, hardware design, deployment issues, and their integration with legacy systems as well as cloud-connectivity is presented. In addition, simple modifications required for transforming the optimization models to an active control technique is also presented. While scalability is provided by the decentralized control, recursive zone thermal model identification, prediction occupant's thermal sensation, and embedding them within the optimization models enhances the smartness. Consequently, due to the implementation of Smart-TBSA using IoT devices, an otherwise centralized control architecture of the legacy building automation system is transformed to a more scalable and smart decentralized one. The proposed Smart-TBSA and IoT prototype are illustrated on a pilot building in Nanyang Technological University, Singapore having 85 zones. Our results shows that by combining IoT with decentralized control, energy savings up to 20% can be derived. Moreover, we show that legacy building automation system can be transformed into a more smart, adaptable, scalable, and decentralized control by deploying IoT devices without incurring significant costs. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents an interesting approach to develop a quantitative risk assessment (QRA) software tool for road tunnels. It first introduces a QRA model for road tunnels, consisting of event trees, fault trees and consequence estimation models. The model is developed by taking into account the unique characteristics of Singapore road tunnels. The paper proceeds to describe design of the QRA software tool based on the QRA model by means of the object oriented design (OOD) method and eXtensible Markup Language (XML) technique. The XML files are used to store the numerous tree structures in the proposed model thus making the programming much more efficiently and effectively. The QRA software tool is robust and flexible such that users can easily add or modify the event trees, fault trees and the consequence estimation models. An application to Singapore road tunnels has been carried out to assess the robustness and effectiveness of the QRA software tool. [Copyright &y& Elsevier]

Graphical abstract Highlights • An energy demand model for electric buses based on real-world data sets is proposed. • The approach can be easily applied on large-scale bus networks. • The model is demonstrated on the whole bus network of Singapore. • Real conditions of operation lead to high heterogeneity of energy demand. • 50% of the bus lines require less than 40 kWh for one terminus to terminus journey. Abstract An increasing number of cities are transitioning from fossil fuel-powered buses for public transport to battery electric buses. Evaluating the energy demand of buses has become an important prerequisite for the planning and deployment of large electric bus fleets and the required charging infrastructure. A number of state-of-the-art approaches to determining the energy requirements of electric buses use individual specific energy demand values or rely on standard driving cycles, though these do not consider local bus route characteristics. Others require high-resolution measurements of the vehicles' driving profiles, which is impractical for large bus fleets. This paper presents a longitudinal dynamics model to calculate the energy demand for electric buses. The model is designed to be easily applied to large bus networks using real data sources that are commonly available to bus transit operators. This data can be derived from low-resolution data collected from day-to-day operations, where only the arrival and departure time of the buses at each bus stop are available. This approach offers a practical alternative to state-of-the-art methods and requires no high-resolution velocity profiles, which are difficult to obtain, while still taking into account the details of the operational characteristics of the transportation network under consideration. The application of the model is demonstrated in a case study to electrify the complete public bus network in Singapore. The results showed that the heterogeneity of driving conditions observed in a large network leads to a high variance in energy requirements between different bus lines and at different times of day. This confirms the need to take the characteristics of each individual bus route into account. In the case-study, a fully electric public bus fleet would require about 1.4 GWh per day for revenue service, which is about one per cent of Singapore's daily electricity demand. Another finding is that 50% of the bus lines require less than 40 kWh per terminus-to-terminus journey, which indicates a good potential for fast opportunity charging during layover time. The results of the model should serve as the basis for further studies into battery sizes, charging strategies and charging infrastructure requirements. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a study on energy performance of Singapore''s hotel buildings. Energy consumption data and other pertinent information were collected from 29 quality hotels through a national survey. Building features and operational characteristics contributing to the variations in hotel energy performance were discussed. The annual average total energy use intensity (EUI) in these hotels is 427kWh/m2. Electricity and gas are used in all sampled hotels, and some hotels also use diesel to power standby generator or hot water boiler. We also investigated relationships between electricity consumption and number of occupied rooms in individual hotels; the weak correlations found indicate it is necessary to improve energy management when occupancy rate is low. Besides, Pearson correlations between hotel energy use intensity and possible explanatory indicators revealed that three-star hotels differ from high class establishments in energy use. Worker density and years after the last major energy retrofit were also found to be highly correlated to hotel building energy use intensity. Also discussed in this paper is the effect of weather conditions on electricity consumption of the hotels. [Copyright &y& Elsevier]

Abstract: A key characteristic of public relations excellence in organizations is ensuring that the senior public relations practitioner – the head of the communication function – has the competencies to enact the strategic role of a manager. It is only when the top communicator possesses strategic management knowledge and engages in managerial work with support from colleagues who are technically skilled in traditional craft work can public relations work be considered to be value-generating. This paper presents the findings of the examination of the role of senior public relations practitioners in organizations in Singapore. It also explores the importance of core communication activities to the role of top in-house communicators, examines the time they allocate to managerial and technical work, and assesses if the managerial role which the practitioners play adds value to organizations. Data collected from both in-depth interviews and self-reported log of daily activities showed that although top communicators in Singapore enjoy strategic reporting and unhindered access to senior management, it also revealed, paradoxically, senior management''s mixed worldviews of public relations; and that Singapore''s top in-house practitioners lack the strategic knowledge to enact the managerial role as they are too focused on technical work. The paper concludes with recommendations on how the level of public relations professionalism can be raised in Singapore, starting with the practitioners themselves having to be fully equipped with the relevant academic knowledge of what makes communication excellent. [Copyright &y& Elsevier]

Teenage marriage within the Malay community of Singapore was thrust under the national spotlight by the government in recent years. Though identified as one of the major social challenges confronting the Malay community, there is still at present, a gross lack of research necessary for an objective understanding of the phenomenon. The adverse implications of the lacunae are reinforced by instant solutions and prescriptions aimed at eradicating the problem. Utilising data obtained from interviews and responses to a survey administered to Malay teenage married couples, this paper examines dominant perceptions of teenage marriage in Singapore and their ramifications on policies and programmes. It is hoped that this paper can contribute towards a more objective understanding of the problem so vital for effective policy making. [ABSTRACT FROM AUTHOR]

In this paper, I develop a detailed consideration of ways in which Chinese religious practitioners, including Daoists, Christians, and spirit mediums, deploy syncretism in complex fields of practice. Rather than focusing on doctrinal blending, this study emphasises the ways in which these practitioners combine elements from diverse religious traditions through the media of ritual performance, visual representation, story, and landscape. After considering the diverse ways in which syncretic processes may be deployed in a field of practice, the paper investigates three ethnographic cases, exploring ritual co-celebration at Wudang Mountain in South-central China, charismatic Christian practices in Singapore, and the recent development of Holy Mount Zion as a Christian pilgrimage site in Taiwan. [ABSTRACT FROM AUTHOR]

This paper studied the work stressors and coping strategies of lawyers in Singapore. Data collection involved the use of both quantitative and qualitative research methods — a survey of 450 lawyers and in-depth interviews with 27 lawyers. This study found that while time pressure and work overload were the most stressful aspects of lawyering work, social interactions and interpersonal relationships at work proved to be a salient work stressor, when lawyers were dealing with clients, fellow lawyers and judges — that is, interpersonal stress. This study explains how lawyers constantly monitor and adjust their actions to negotiate for control or 'power' over others in their attempts to cope with work stress. In examining the correlation between lawyers' perceptions of work stress and their coping behaviours, this paper reveals that while lawyers tended to report more problem-focused than emotion-focused coping ways, the correlation analysis informed that emotion-focused and help-seeking coping ways were significantly correlated with interpersonal stress, such as in dealing with clients and colleagues. This study further shows that lawyers invoke social and psychological coping resources to position themselves strategically within prevailing power relations to cope with their interpersonal stress at work. [ABSTRACT FROM AUTHOR]

The paper presents evaluation of the newly proposed hypoplastic model for soft clays by modelling of the well-documented geotechnical failure of a deep excavation of Nicoll Highway, Singapore, in 2004. The marine clays present at the site are typical normally consolidated soft clays, exhibiting large deformability and stiffness and strength anisotropy. These features - anisotropy of asymptotic state boundary surface and the effect of normal consolidation on stress paths and stiffness anisotropy - have been included into the newly proposed hypoplastic model. In the paper, it is first demonstrated that the model predictions compare well with experimental data from element tests on Singapore clay and improve predictions over original hypoplastic model. Secondly, numerical simulations of Nicoll highway excavation focusing on specific cross-section within the collapse area are presented, showing good fit between inclinometer data and simulations up to the final stages immediately preceding the excavation collapse. The simulation results are compared for previous version of the hypoplastic model, along with Mohr-Coulomb model with effective and total stress parameters. Subsequently, the influence of the model parameters on simulation results is studied and it is shown that the parameters affecting extension strength are more significant than parameters affecting pre-failure non-linearity. [ABSTRACT FROM AUTHOR]

Globalization has influenced the conduct of scientific research in a number of expected and unexpected ways. At the same time the emergence of specific scientific fields has also influenced the texture and trajectory of globalization. In this paper the relationship between globalization and genomics is analyzed. Much like the globalization of traditional manufacturing, genomics research represents a phase of global bio-capitalism. With specific reference to Singapore, the possible social, economic and political effects of the rapid global circulation of scientists, knowledge, capital and DNA are examined in this paper. [ABSTRACT FROM AUTHOR]

This paper revisits the concept of state autonomy in the context of globalization. Earlier literature either considered state autonomy from the social forces in broad institutional and cultural terms or from the dominant classes in a restrictive sense. However, in either case the focus remained on domestic/national society, not the global society. The discussion of relative autonomy of the state began among the Marxists in the 1970s and then graduated into the mainstream social sciences in the 1980s and 1990s. In the upshot, the notions of developmental state and the embedded autonomy have significantly added to our knowledge of the role of the state. This paper broadens the idea of embedded autonomy by locating the sources of embeddedness in both local as well global institutions and norms. The paper uses the Singapore case to illustrate some of the possibilities and limitations of the reconfigured role of the state in the face of globalization. [ABSTRACT FROM AUTHOR]

The lived, and oftentimes silenced, experiences of "foreign workers" articulate the negotiation of power relations between "citizen" and "foreigner", and "Us" and "Them". These are translated into discursive practices that, in effect, legitimize and entrench differences — hence, inequalities — that effectively discipline the "foreign worker" as "not one of Us". By taking the example of Bangladeshi construction workers in Singapore as a case study, I argue in this paper that the workspaces of "foreign construction workers" in Singapore typify that of a "total institution", which correspondingly moulds the worker into a discursive ideal — the "good, docile Other". Such impositions and productions of Otherness, however, face rupture as workers (re)negotiate, (re)work, and (re)inscribe their everyday lives through the employment of what James Scott (1985, 1987) terms "everyday 'resistances'" in rising above that which subjugates them. I will present in this paper primary data elicited and collated from direct participant observation, fieldwork, and in-depth interviews conducted in a construction project in Singapore. [ABSTRACT FROM AUTHOR]

The public transport market in most global cities is dominated by diesel buses, which can have significant adverse impacts on the environment and human health. To reach carbon neutrality, many public transport operators are attempting to replace their existing bus fleets with electric buses (EBs). This paper develops a generic bus replacement model to help public transit (PT) operators progressively renew their existing bus fleets so as to reach particular electrification goals within a given planning horizon. Unlike existing studies, our model more comprehensively considers the external costs, which include external climate costs, external health costs and used battery recycling costs/profits. Furthermore, by incorporating different incentives, variants on the model can be adopted to investigate how different government incentives can affect the replacement behaviors of PT operators. Finally, our proposed approach is applied to real-world data from a bus operator in Singapore which is aiming to achieve a 100% cleaner energy bus fleet within 20 years. The experiments indicate that an EB subsidy can effectively accelerate the electrification process, and a 25% EB subsidy could achieve full electrification eight years earlier than if no EB subsidy were applied. Moreover, we explore how the diesel tax and diesel bus (DB) tax affect EB replacement. Our experiments suggest a 10% diesel tax rate can achieve good results but imposing a DB tax will not encourage PT operators to purchase EBs earlier. • A novel model for the bus fleet replacement problem is proposed. • Various external costs that borne by the society and environment are considered. • Our approach evaluates different policy incentives. • Our real case study provides managerial insights for PT operators and policymakers. [ABSTRACT FROM AUTHOR]

Expert commentaries are an avenue in which individuals and the organisations they represent position themselves on issues that are relevant to stakeholders. This paper considers the motivations for writing them, assessing this through two conceptual lenses: issue management and cultural, symbolic and economic capital. By writing an expert commentary an individual manages the way an issue is perceived and in doing so gains either immediate economic capital in the form of payment or symbolic or cultural capital which may in the future be converted into economic capital through increased career opportunities or promotion. We analyse expert commentaries in the Singapore news media and surveys their authors to investigate what prompted them to contribute their articles. We bring together (organisational) thinking on issue management and (individual) thinking on self-promotion as reflected in expert commentaries and suggest lessons for issue management through expert commentary. • Thought leadership is an issue-management tactic that organisations use to position their corporate image. • We investigate expert commentaries and the commercial, promotional and organisational background of their writers. • We survey writers to investigate how they hope to manage an issue and what forms of capital they gain or convert to do so. • Results and discussion centre on five topics from the earlier literature on issue management. • Commentaries are a form of indirect issue management: writers gain symbolic, cultural and reputational capital. [ABSTRACT FROM AUTHOR]

Since early warning is significant to ensure high-quality tunneling boring machine (TBM) construction, a real-time prediction method based on TBM data is proposed. To solve the "black box" problem of prediction by artificial intelligence (AI) methods, the causal explainable gated recurrent unit (CX-GRU) is developed to achieve real-time prediction for TBM parameters. The approach is implemented in a tunnel construction project in Singapore and the results indicate that CX-GRU performs well with the R square score are 0.9140 and 0.9184 in real-time prediction for thrust force and soil pressure. The causal discovery component can increase the computational efficiency of model training by 8.8% on average. According to the SHAP analysis of prediction results, the thrust force is more sensitive to the input TBM features, while the soil pressure is more sensitive to historical data. The CX-GRU is more reliable and efficient when applied to TBM projects than traditional methods. • A causal explainable method with gated-recurrent-unit neural network (CX-GRU) is proposed. • Global causal discovery is responsible for the screening of input features by their adjacency matrix. • Local causal discovery is responsible for the mining of additional features in each input sample. • R2 of thrust force and soil pressure can reach 0.9140 and 0.9184, respectively, in real-time prediction. • The proposed method can maintain acceptable robustness for the multi-step prediction. [ABSTRACT FROM AUTHOR]

In recent discussions, the role of the Internet in facilitating democratization has been either exaggerated or underestimated. The general consensus seems to be that that the Internet will eventually go the way of other technologies of communication such as the radio and television that failed to live up to their expected role of agents of democratization. Rather than empower marginal groups and constituencies, the Internet could even contribute to more subtle and omnipotent forms of social control through surveillance. This paper examines these positions by focusing on the Singapore case. The possibilities for the expansion of civil society and the emergence of a robust public sphere as a consequence of the wiring up of the country are examined. The key argument of the paper is that although the Internet does indeed contribute to enhanced surveillance capabilities, its potential for circumventing existing forms of regulation and expanding the limited public sphere in Singapore is also very real. [ABSTRACT FROM AUTHOR]

The objective of this paper is to map the sociological context in which the cultural economy of technology of Singapore exists. Taking a socio-historical perspective, this paper argues that the development of Singapore as a technological 'intelligent island' must take centre stage in relation to the sociological analysis of modern Singapore's political, economic, and socio-cultural structure. This involves a critique of theories of the information society and empirical research on East Asian developmental states. The aim is to chart the development of technology in Singapore, from its founding as a colonial port-city to its current status as an 'intelligent island', and to situate this development in its social context. In addressing the issue of the global expansion of localized technological knowledge hubs, I argue that while these technological 'hubs' are increasingly linked in complex political, economic and social networks, one must also account for the developmental trajectory of each particular 'hub' and to explain the socio-cultural complex of societies, which promote themselves as such. This paper intends to demonstrate how this construction of a technological nation state is neither a context-free project nor one that is free of complex historical antagonisms and contradictions. [ABSTRACT FROM AUTHOR]

This paper examines the socio-economic role of pawnshops in Singapore. It suggests that pawnshops are a barometer of socio-economic changes in Singapore. The changing style and operation of pawnshops es explored, as is the changing varieties of the items pledged. The research shows that pawnshops have adopted a new image and continue to have a significant role in modern Singapore. This paper also suggests that pawnshops serve cash strapped individuals, who ironically are not necessarily poor. Through data collected on redemptions and pledges, it is found that a high redemption rate both in number and amount reflects a period of economic growth; the reverse in true when the redemption rate falls. [ABSTRACT FROM AUTHOR]

• A Stirling engine based gasification CCHP system with food waste was introduced. • The optimal equivalence ratio was determined based on the cold gas efficiency. • Levelized total cost and primary energy saving ratio were used to optimize systems. • The monthly energetic, economic, and environmental analysis was conducted. • Sensitivity analyses of efficiencies, costs and CO 2 emission were carried out. Due to the tar contamination caused by the gasification process of biomass, the internal combustion engine (ICE) based gasification cogeneration systems require complicated gas cleaning devices to purify producer gas. In this paper, a Stirling engine based gasification combined cooling, heat and power (CCHP) system was introduced, which has the capability of mitigating tar condensation and contamination. The gasification CCHP system, including the gasification system, the Stirling engine system, and the absorption chiller system, can provide electricity, heat and cooling for a commercial building. The effects of the equivalence ratio on syngas composition and cold gas efficiency of the gasification process were analyzed herein. The optimal systems in Singapore and Shanghai can save respectively 75.9% and 70.5% levelized total cost compared to a conventional reference system. The Stirling engine based CCHP system had advantages over the ICE systems on overall consideration of the levelized total cost and the primary energy saving ratio. The monthly energetic, economic and environmental performance of the CCHP systems was evaluated under different modes and the above two systems' primary energy saving ratios, operation cost reduction ratios and CO 2 equivalent reduction ratios respectively reached 0.886, 0.462 and 0.701 in Singapore and 0.908, 0.535 and 0.710 in Shanghai in annual operation. The outcomes of this paper contribute to the design and deployment of such a CCHP system, and the developed models and analysis framework can be extended to different climate areas. [ABSTRACT FROM AUTHOR]

This paper studies the effects of ride-sharing among those calling on taxis in Singapore for similar origin and destination pairs at nearly the same time of day. It proposes a simple yet practical framework for taxi ride-sharing and scheduling, to reduce waiting times and travel times during peak demand periods. The solution method helps taxi users save money while helping taxi drivers serve multiple requests per day, thus increasing their earnings. A comprehensive simulation study is conducted, based on real taxi booking data for the city of Singapore, to evaluate the effect of various factors of the ride-sharing practice, e.g., waiting time, extra travel time, and taxi fare reduction. The results demonstrate that ride-sharing could serve 20%–25% more taxi booking requests and reduce traveler waiting time during peak hours. It also indicates that there is a reduction in travel distance of approximately 2–3 km per taxi trip on average, which is approximately 20%–30% of the average ride distance. [ABSTRACT FROM AUTHOR]