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The purpose of this paper is to describe and analyse the development and content of the Vulnerable Adults Act 2018 (hereafter “the Act”) in Singapore. It reports the parliamentary processes and deliberations.

A synthesis of publicly available research, policy documents, parliamentary debate, media reports and commentary.

The paper sets the Act’s development and aims in Singapore’s social and legal contexts. It notes the interface with other legislation and the focus of the Act on community and family abuse and neglect.

The paper suggests some areas for research including how the Act is used and its impact and also points to areas where the Act does not apply.

The paper outlines new professional powers and responsibilities and the role of government and community-based organisations.

This paper provides an early account of the genesis and aims of the new legislation, its powers and administration. Also, international comparisons are drawn.

Reflow soldering process is an important step of the surface mount technology. The purpose of this paper is to minimize the maximum warpage of shielding frame by controlling reflow soldering control parameters.

Compared with other reflow-related design methods, both time and temperate of each extracted time region are considered. Therefore, the number of design variable is increased. To solve the high-dimensional problem, a surrogate-assisted optimization (SAO) called adaptive Kriging high-dimensional representation model (HDMR) is used.

Therefore, the number of design variable is increased. To solve the high-dimensional problem, a surrogate-assisted optimization (SAO) called HDMR is used. The warpage of shield frame is significantly reduced. Moreover, the correlations of design variables are also disclosed.

Compared with the original Kriging HDMR, the expected improvement (EI) criterion is used and a new projection strategy is suggested to improve the efficiency of optimization method. The application suggests that the adaptive Kriging HDMR has potential capability to solve such complicated engineering problems.

Along with the ever growingWeb is the proliferation of objectionable content, such as sex, violence, racism, etc. We need efficient tools for classifying and filtering undesirable web content. In this paper, we investigate this problem through WebGuard, our automatic machine learning based pornographic website classification and filtering system. Facing the Internet more and more visual and multimedia as exemplified by pornographic websites, we focus here our attention on the use of skin color related visual content based analysis along with textual and structural content based analysis for improving pornographic website filtering. While the most commercial filtering products on the marketplace are mainly based on textual content‐based analysis such as indicative keywords detection or manually collected black list checking, the originality of our work resides on the addition of structural and visual content‐based analysis to the classical textual content‐based analysis along with several major‐data mining techniques for learning and classifying. Experimented on a testbed of 400 websites including 200 adult sites and 200 non pornographic ones, WebGuard, our Web filtering engine scored a 96.1% classification accuracy rate when only textual and structural content based analysis are used, and 97.4% classification accuracy rate when skin color related visual content based analysis is driven in addition. Further experiments on a black list of 12 311 adult websites manually collected and classified by the French Ministry of Education showed that WebGuard scored 87.82% classification accuracy rate when using only textual and structural content‐based analysis, and 95.62% classification accuracy rate when the visual content‐based analysis is driven in addition. The basic framework of WebGuard can apply to other categorization problems of websites which combine, as most of them do today, textual and visual content.

The purpose of this paper is to provide a view on situation, activity and goal awareness (SAGAware) in ubiquitous computing. It discusses these concepts, articulates their roles in scalability and prevalence of pervasive applications, and speculates the future development.

The paper is a visionary essay that introduces the background, elaborates the basic concepts and presents the authors' views and insights into SAGAware research in pervasive computing based on the latest state of the art of the development of pervasive computing and its applications.

SAGAware is closely related to the levels of automation and large‐scale uptake of pervasive applications. It is an interdisciplinary research area requiring collaboration and cooperation of multiple research communities.

The paper highlights the importance of the SAGAware research and further points out research trends and future research directions.

The paper helps stimulate research interests and draw attention of relevant researchers to this promising research area.

The paper pioneers the investigation of an increasingly important research theme, and presents an in‐depth view to its potentials and research trends.

This paper aims to serve two main purposes. In the first instance it aims to it provide an overview addressing the state‐of‐the‐art in the area of activity recognition, in particular, in the area of object‐based activity recognition. This will provide the necessary material to inform relevant research communities of the latest developments in this area in addition to providing a reference for researchers and system developers who ware working towards the design and development of activity‐based context aware applications. In the second instance this paper introduces a novel approach to activity recognition based on the use of ontological modeling, representation and reasoning, aiming to consolidate and improve existing approaches in terms of scalability, applicability and easy‐of‐use.

The paper initially reviews the existing approaches and algorithms, which have been used for activity recognition in a number of related areas. From each of these, their strengths and weaknesses are discussed with particular emphasis being placed on the application domain of sensor enabled intelligent pervasive environments. Based on an analysis of existing solutions, the paper then proposes an integrated ontology‐based approach to activity recognition. The proposed approach adopts ontologies for modeling sensors, objects and activities, and exploits logical semantic reasoning for the purposes of activity recognition. This enables incremental progressive activity recognition at both coarse‐grained and fine‐grained levels. The approach has been considered within the realms of a real world activity recognition scenario in the context of assisted living within Smart Home environments.

Existing activity recognition methods are mainly based on probabilistic reasoning, which inherently suffer from a number of limitations such as ad hoc static models, data scarcity and scalability. Analysis of the state‐of‐the‐art has helped to identify a major gap between existing approaches and the need for novel recognition approaches posed by the emerging multimodal sensor technologies and context‐aware personalised activity‐based applications in intelligent pervasive environments. The proposed ontology based approach to activity recognition is believed to be the first of its kind, which provides an integrated framework‐based on the unified conceptual backbone, i.e. activity ontologies, addressing the lifecycle of activity recognition. The approach allows easy incorporation of domain knowledge and machine understandability, which facilitates interoperability, reusability and intelligent processing at a higher level of automation.

The comprehensive overview and critiques on existing work on activity recognition provide a valuable reference for researchers and system developers in related research communities. The proposed ontology‐based approach to activity recognition, in particular the recognition algorithm has been built on description logic based semantic reasoning and offers a promising alternative to traditional probabilistic methods. In addition, activities of daily living (ADL) activity ontologies in the context of smart homes have not been, to the best of one's knowledge, been produced elsewhere.

The purpose of this paper is to review the state-of-the-art in adaptive user interface systems by studying their historical development over the past 20 years. Moreover, this paper contributes with a specific model combining three main entities (users, context and devices) that have been demonstrated to be always represented in these environments. Novel concepts that should be taken into account in these systems are also presented.

The authors first provide a review and a comparison of current user interface adaptive systems. Next, the authors detail the most significant models and the set of techniques used to, finally, propose a novel model based on the studied literature.

Literature solutions for adaptive user interface systems tend to be very domain dependant. This situation restricts the possibility of sharing and exporting the information between such systems. Furthermore, the studied approaches barely highlight the dynamism of these models.

The paper is a review of adaptive user interface systems and models. Although there are several reviews in this area, there is a lack of research for modelling users, context and devices simultaneously in this domain. The paper also presents several significant concepts that should be taken into account to bring an adaptive and dynamic perspective to the studied models.

The purpose of this paper is to investigate the risk factors for A‐shares listed on both Shenzhen and Shanghai Stock Exchange in China using variables from Akgun and Gibson.

The paper applies cross‐sectional regression on the orthogonal components by rearranging these risk variables into several principal components.

The results produced strong evidence that size and book‐to‐market (BM) ratio could be well explained by these alternative risk variables. Additionally, the alternative variables are better at explaining returns in terms of adjusted R‐squares.

The practical implication of the study is that investors can improve both their pricing of the investment risk and their management of the risk factors with the alternatives identified in the study.

The paper provides evidence in explaining the size and BM effects in China's stock markets.