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This study aims to trace the transformation in the form of apartment building and the connotations it has in understanding the changes that occurred in the Jordanian society’s lifestyle over the past five decades.

A comparative case study analysis has been conducted amongst 170 apartments, covering 70 design attributes related to aspects of appearance, spatial organisation, parking and access to building, outdoor space and finishing. This was followed by experts and households solicitation to help giving more confidence on the validity and reliability of findings regarding the sorts and justifications for the changes that have taken place in the form of apartments over the studied time frame.

The results reveal changes in design attributes indicating particular alterations in people’s lifestyle. New interests act in formulating recent housing design attributes. People seem to turn into a more open social life within public community but more privatised living amongst family members. People are becoming more attached to indoor modernised lifestyle, in homes and public areas where activities take place. This entails pursuing a more comfortable, facilitating and enjoyable life that presents luxury and tranquillity.

Understanding the relationship between transformations in the built form of apartment buildings and the associated social alterations provides useful insights towards improving housing provision to better match the ever-changing demands of people and respond to alterations in their lifestyles.

This study aims to compare the local climate characteristics of Angkor Wat, Borobudur and Prambanan parks and determine effective strategies for mitigating thermal conditions that could suit Borobudur and Angkor Wat.

The study employed local climate zone (LCZ) indicators and ten-year historical climate data to identify similarities and differences in local climate characteristics. Satellite imagery processing was used to create maps of LCZ indicators. Meanwhile, microclimate models were used to analyze sky view factors and wind permeability.

The study found that the three tropical large-scale archaeological parks have low albedo, a medium vegetation index and high impervious surface index. However, various morphological characteristics, aerodynamic properties and differences in temple stone area and altitude enlarge the air temperature range.

Based on the similarities and differences in local climate, the study formulated mitigation strategies to preserve the sustainability of ancient temples and reduce visitors' heat stress.

The local climate characterization of tropical archaeological parks adds to the number of LCZs. Knowledge of the local climate characteristics of tropical archaeological parks can be the basis for improving thermal conditions.

With the rapid increase in the consumption of electrical and electronic innovations, responsible management and recycling of electronic waste (e-waste) or waste electrical and electronic equipment (WEEE) has been a significant concern for the governments, stakeholders, researchers and industry practitioners around the world. Consumer awareness, disposal behaviour and perception are chief facets of designing sustainable management strategies. Although researchers have widely studied e-waste over many years, the research focusing on consumer awareness about e-waste recycling has gained momentum recently. This paper aims to systematise the existing literature and explore future research prospects on household e-waste sorting behaviour.

Web of science (WoS) core collection was searched using selected keywords to identify relevant articles published from 2001 to 2021. The search resulted in 1,156 research articles published from 2001 to 2021. After a detailed study, 85 articles were shortlisted for in-depth review. The review was conducted based on global trends, top journals, most prolific authors, most active e-waste research countries, and institutions centring on consumer participation in e-waste disposal and recycling behaviour. The present research has also identified around eleven factors that seem to have a bearing on consumer behaviour towards storage, disposal and recycling of e-waste.

E-waste research has gained increased attention in the last five years. The majority of the studies has focused on motivational factors and ignore the risks associated with handling e-waste. The present study reports the pertinent issue of lack of awareness among the masses about e-waste handling and disposal. Thus, bringing to the fore the lack of awareness programmes and initiatives. The analysis presents the gaps in the literature and future research agendas.

The review article will help in providing an in-depth understanding of consumer behaviour towards storage, disposal and recycling of e-waste and delineates the future direction of research that may be undertaken in this field of study.

This study aims to predict China's carbon emission intensity and put forward a set of policy recommendations for further development of a low-carbon economy in China.

In this paper, the Interaction Effect Grey Power Model of N Variables (IEGPM(1,N)) is developed, and the Dragonfly algorithm (DA) is used to select the best power index for the model. Specific model construction methods and rigorous mathematical proofs are given. In order to verify the applicability and validity, this paper compares the model with the traditional grey model and simulates the carbon emission intensity of China from 2014 to 2021. In addition, the new model is used to predict the carbon emission intensity of China from 2022 to 2025, which can provide a reference for the 14th Five-Year Plan to develop a scientific emission reduction path.

The results show that if the Chinese government does not take effective policy measures in the future, carbon emission intensity will not achieve the set goals. The IEGPM(1,N) model also provides reliable results and works well in simulation and prediction.

The paper considers the nonlinear and interactive effect of input variables in the system's behavior and proposes an improved grey multivariable model, which fills the gap in previous studies.

This paper aims to report on the bibliometric research trends on the application of machine learning/intelligent systems in the prediction of food contamination and the surveillance of foodborne diseases.

In this study, Web of Science (WoS) core collection database was used to retrieve publications from the year 1996–2021. Document types were classified according to country of origin, journals, citation and key research areas. The bibliometric parameters were analyzed using VOSviewer version 1.6.15 to visualize the international collaboration networks, citation density and link strength.

A total of 516 articles across 6 document types were extracted with an average h-index of 51 from 10,570 citations. The leading journal in publications was Science of the Total Environment (3.6%) by Elsevier and the International Journal of Food Microbiology (2.5%). The United States of America (USA) (24%) followed by the People's Republic of China (17.2%) were the most influential countries in terms of publications. The top-cited articles in this study focused on themes such as contamination from packaging materials and on the strategies for preventing chemical contaminants in the food chain.

This report is significant because the public health field requires innovative strategies in forecasting foodborne disease outbreaks to advance effective interventions. Therefore, more collaboration need to be fostered, especially in developing nations regarding food safety research.

The effect of using microcrystalline cellulose (MCC) as an additive in coating paint films for non-stick coatings was studied in this work. This paper aims to discuss the benefits of MCC blended in the coating paint film that consists of poly(methyl methacrylate) (PMMA) and dammar.

PMMA and dammar mixed at a specific Wt.% ratio with xylene as its solvent. Two sets of mixtures were prepared, where one mixture contained MCC and another, without. The mixtures were applied to metal substrates as coating paint films. The performance of the non-stick coating paint film was observed through the adhesive test between adhesion layers on the coating paint film and also through the cross-hatch test for the adhesion of the non-stick coating paint film to the metal substrate. The results correlate with the surface roughness and glossiness tests.

The results showed that for the coating paint films, Sample B consisted of 80:20 Wt.% ratio of PMMA-dammar with an addition of 5 Wt.% MCC had an excellent performance as non-stick coating paint films. The MCC formed microparticles on the surface of the coating paint film sample and this causes the coating paint film samples with MCC to develop a rougher surface compared to the coating paint film without MCC. Sample B coating paint film had the highest average surface roughness (Ra) of 383 µm. The cross-hatch test showed the coating paint film with the addition of MCC had stronger adhesiveness on the substrate’s surface thus prevents the coating from peeling off from the surface.

The developed coating paint film in this study would be suitable for outdoor applications to prevent illegal advertisements and stickers.

MCC added to the coating paint film improves the surface performance as a non-stick coating.

Multipliers that form the basic building blocks in most of the error-resilient media processing applications are computationally intensive and power-hungry modules. Therefore, improving the multiplier’s performance in terms of area, critical path delay and power has become an important research area. This paper aims to propose two improved multiplier designs based on a new approximate compressor circuit to reduce the hardware complexity at the partial product reduction stage. The proposed approximate 4:2 compressor design significantly reduces the overall hardware cost of the multiplier. The error introduced by the approximate compressor is reduced using a new technique of assigning inputs to the compressors in the partial product reduction structure.

The multiplier designs implemented using the proposed approximate 4:2 compressor are targeted for error-resilient applications. For fair comparisons, various multiplier designs, including the proposed one, are implemented in MATLAB. The quality analysis is carried out using standard images, and metrics such as structural similarity index are computed to quantify the result of proposed designs with the existing architectures. Next, Verilog gate-level designs are synthesized to compute area, delay and power to prove the efficacy of the proposed designs.

Exhaustive error and hardware analysis have been carried out for the existing and proposed multiplier architectures. Error analysis carried out using MATLAB proves that the proposed designs achieve better quality metrics than existing designs. Hardware results show that area, the power consumed and critical path delay are reduced up to 39.8%, 51.7% and 15.9%, respectively, compared to the existing designs. Toward the end, the proposed designs impact is quantified and compared with existing designs on real-time image sharpening and image multiplication applications.

The area, delay and power metrics of the multiplier can be improved using an approximate compressor in an error-resilient application. Accordingly, in this work, a new compressor is proposed that reduces the hardware complexity in the multiplier architecture. However, the proposed approximate compressor, while reducing the computational complexity, tends to introduce error in the multiplier. The error introduced by the approximate compressor is reduced using a new technique of assigning inputs to the compressors in the partial product reduction structure. With the help of the approximate compressor and a technique of input realignment, hardware efficient and highly accurate multiplier designs are achieved.

The purpose of this paper is to propose a new method to solve the incompressible natural convection problem with variable density. The main novel ideas of this work are to overcome the stability issue due to the nonlinear inertial term and the hyperbolic term for conventional finite element methods and to deal with high Rayleigh number for the natural convection problem.

The paper introduces a novel characteristic variational multiscale (C-VMS) finite element method which combines advantages of both the characteristic and variational multiscale methods within a variational framework for solving the incompressible natural convection problem with variable density. The authors chose the conforming finite element pair (P₂, P₂, P₁, P₂) to approximate the density, velocity, pressure and temperature field.

The paper gives the stability analysis of the C-VMS method. Extensive two-dimensional/three-dimensional numerical tests demonstrated that the C-VMS method not only can deal with the incompressible natural convection problem with variable density but also with high Rayleigh number very well.

Extensive 2D/3D numerical tests demonstrated that the C-VMS method not only can deal with the incompressible natural convection problem with variable density but also with high Rayleigh number very well.

House price fluctuations send vital signals to many parts of the economy, and long-term predictions of house prices are of great interest to governments and property developers. Although predictive models based on economic fundamentals are widely used, the common requirement for such studies is that underlying data are stationary. This paper aims to demonstrate the usefulness of alternative filtering methods for forecasting house prices.

We specifically focus on exponential smoothing with trend adjustment and multiplicative decomposition using median house prices for Sydney from Q3 1994 to Q1 2017. The model performance is evaluated using out-of-sample forecasting techniques and a robustness check against secondary data sources.

Multiplicative decomposition outperforms exponential smoothing at forecasting accuracy. The superior decomposition model suggests that seasonal and cyclical components provide important additional information for predicting house prices. The forecasts for 2017–2028 suggest that prices will slowly increase, going past 2016 levels by 2020 in the apartment market and by 2022/2023 in the detached housing market.

We demonstrate that filtering models are simple (univariate models that only require historical house prices), easy to implement (with no condition of stationarity) and widely used in financial trading, sports betting and other fields where producing accurate forecasts is more important than explaining the drivers of change. The paper puts forward a case for the inclusion of filtering models within the forecasting toolkit as a useful reference point for comparing forecasts from alternative models.

To the best of the authors’ knowledge, this paper undertakes the first systematic comparison of two filtering models for the Sydney housing market.

Despite the potential of virtual fitting rooms (VFRs) to enhance the consumer experience, their adoption is in the preliminary stages. Little is known about inherent reasons why consumers would adopt VFRs. As consumers' attributional processes can be influenced by their enduring chronic traits, this study aims to investigate the influence of chronic regulatory focus on consumers' VFR adoptions via consumers' perceptions of value provided by VFRs. Additionally, the mediating effects of perceived functional and experiential values were examined. Further, the moderating effect of prior VFR experience was tested to allow for variations in consumer experiences.

Data were collected via an online survey of 480 consumers who have at least heard of VFRs via convenience sampling. Established measures were utilized to develop the survey questionnaire. Data were analysed using structural equation modelling to test the main model with mediation effects as well as multi-group comparisons to test the moderating effect.

Empirical results revealed that respective chronic regulatory foci, as preconceived factors that drive consumers' differences in processing, exerted significant influences on consumers' perceptions of VFRs, which, in turn, positively influenced their adoption intention. Also, perceived values mediated the relationship between regulatory foci and consumers' adoption intention. Further, prior VFR experience moderated the relationship between regulatory focus and perceived value.

The paper empirically tested the importance of chronic regulatory foci in understanding consumers' cognitive and affective attributional processes, explaining inherent psychological reasons why consumers would (not) adopt VFRs.