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Encouraging socio‐economic development in developing countries has resulted in many changes in the lifestyle of communities. Changes in dietary patterns are one of the main outcomes from the rapid socio‐economics advancement, for example excessive intake of fat, high‐protein diet (animal protein), salt and preservatives. Chronic diseases such as diabetes, coronary artery disease, hypertension and cancer are mostly related to diet. With the community becoming more nutrition and health conscious, one of the challenges faced is to make sure that the information and knowledge on diet and healthy lifestyle gets across to the community. This paper presents a model of web‐based diet system (WebDIET) that attempts to make diet information and menu plans that are customised to local preference more accessible via the use of Internet. The system is to be used by dieticians who serve as administrators and the public who are the end users. The dietary standard adapted in developing the system is Recommended Dietary Allowances (RDA) for Malaysia. The Malaysian Dietary Guidelines was also referred as it emphasises on Malaysian diet. The system consists of six modules namely Authentication Module, Menu Plan Module, Diabetic Menu Plan Module, Food Selection Module, Disease Info Module and Feedback Module. Diabetic menu plan module models the reasoning process employed by dieticians in suggesting menu plans. The planning task is solved using an artificial intelligence technique through the case‐based reasoning (CBR) approach. CBR, generally describes, the process of solving the current problem based on the proposed solution of similar problems in the past. Nearest Neighbour Algorithm was used to compute the similarities in weighted average. Tools used for the development of the system are Microsoft Visual Interdev, Microsoft FrontPage 2000, while HTML, VBScript and JavaScript are the scripting languages used to develop the system.

The purpose of this paper is to propose a method to have more accurate results in comparing performance of the paired information retrieval (IR) systems with reference to the current method, which is based on the mean effectiveness scores of the systems across a set of identified topics/queries.

Based on the proposed approach, instead of the classic method of using a set of topic scores, the documents level scores are considered as the evaluation unit. These document scores are the defined document’s weight, which play the role of the mean average precision (MAP) score of the systems as a significance test’s statics. The experiments were conducted using the TREC 9 Web track collection.

The p-values generated through the two types of significance tests, namely the Student’s t-test and Mann-Whitney show that by using the document level scores as an evaluation unit, the difference between IR systems is more significant compared with utilizing topic scores.

Utilizing a suitable test collection is a primary prerequisite for IR systems comparative evaluation. However, in addition to reusable test collections, having an accurate statistical testing is a necessity for these evaluations. The findings of this study will assist IR researchers to evaluate their retrieval systems and algorithms more accurately.

In a system-based approach, replicating the web would require large test collections, and judging the relevancy of all documents per topic in creating relevance judgment through human assessors is infeasible. Due to the large amount of documents that requires judgment, there are possible errors introduced by human assessors because of disagreements. The paper aims to discuss these issues.

This study explores exponential variation and document ranking methods that generate a reliable set of relevance judgments (pseudo relevance judgments) to reduce human efforts. These methods overcome problems with large amounts of documents for judgment while avoiding human disagreement errors during the judgment process. This study utilizes two key factors: number of occurrences of each document per topic from all the system runs; and document rankings to generate the alternate methods.

The effectiveness of the proposed method is evaluated using the correlation coefficient of ranked systems using mean average precision scores between the original Text REtrieval Conference (TREC) relevance judgments and pseudo relevance judgments. The results suggest that the proposed document ranking method with a pool depth of 100 could be a reliable alternative to reduce human effort and disagreement errors involved in generating TREC-like relevance judgments.

Simple methods proposed in this study show improvement in the correlation coefficient in generating alternate relevance judgment without human assessors while contributing to information retrieval evaluation.

The Internet of Things (IoT) is becoming increasingly popular in agribusiness to help increase food production capacity for the ever-expanding global population. This chapter provides a holistic overview of the latest trends around the applications of IoT in agriculture. We begin by giving an overview of IoT and its capabilities, followed by a deep dive into the practical and realistic aspects of leveraging IoT into the agroecosystem. IoT is already being used for many intelligent agriculture applications, such as open-field agriculture, controlled environment agriculture (greenhouse), livestock breeding, agricultural machinery, and more. This chapter examines those applications and ventures beyond the farm into several other aspects of the ecosystem, including storage, warehouse ambiance control, agri-data analytics and decision control, logistics, environmental safety, etc. The contents of the chapter would be based on extensive studies and empirical analysis of the latest research papers on this subject from around the globe, accurately interpreted and transformed by the authors in light of their academic background and professional experience in the digital transformation arena.

The construction industry is a major generator of waste, which has a high potential to yield a substantial amount of waste into the economy as a valuable resource. Waste trading (WT) is a sustainable strategy for improving resource utilisation and transitioning the construction industry towards the circular economy. However, resource recovery through WT is greatly impeded by several barriers which have not been highlighted in previous research. This paper aims to determine the barriers for implementing effective WT practices in the Australian construction and demolition (C&D) sector.

To achieve the aim of this research, a triangulation approach of quantitative and qualitative methods has been used. This mixed-method approach combines a comprehensive literature review, a questionnaire survey using an expert forum and semi-structured interviews with industry experts.

This study has explored a wide range of barriers to the practices of WT in the C&D sector, which have been categorised based on six perspectives. From a collective perspective, the technical barriers were found to be most important among other categories. The key individual barriers found in this study include the following: the high cost associated with sorting and processing of waste on-site, lack of consistent waste data and reporting system at project, industry and national level, insufficient secured and established market for reusable/recycled waste materials, lack of communication and coordination among stakeholders, lack of user-friendly and active web-based waste exchange systems (with reliable waste information) and lack of incentives from the government to encourage market development. Overcoming these barriers collectively would enable the wide application of WT, which in turn, would have a positive impact on the economy, environment and efficiency of the industry.

The outcomes of this study are based on the data collected only in the state of New South Wales (NSW) in Australia which is considered as the limitation of this study.

This study contributes to the body of knowledge of C&D waste management (WM) by providing the theoretical and practical implications of closing the loop material cycle by highlighting the importance of economic and environmental benefits of WT. In this study, WT has been recognised as a sustainable strategy to manage waste by identifying the barriers impeding the wider application of effective trading practices in the C&D sector. The findings are useful to WM businesses engaged to establish new circular business models and to government/regulatory bodies in developing initiatives and incentives aiming to promote WT strategies and market platforms. Further research is suggested to test and validate the findings from other jurisdictions of Australia.

Online images can convey sensory-based elements affecting digital users' emotions and digital engagement. The purpose of this study is to investigate which image-based features are more effective in conveying and stimulating particular emotions and engagement towards organizations operating in the food industry.

An online experimental survey was implemented. Two image-based features, narrativity and dynamism were chosen. The stimuli comprise four images, one with high and one with low level of narrativity, and one with high and one with low dynamism, published by a food company on its official Instagram account. Food-identity, emotional appeals and digital visual engagement behaviours were measured. A total of 141 students between 19 and 25 years old of a European University completed the questionnaire. Data was analysed through SPSS software using t-test analysis.

Results show that both narrativity and dynamism impact digital users' emotions and it was found to impact digital visual engagement attitude. Food involvement was measured in terms of food identity impact the effects of specific image-based features on emotions and visual engagement.

The study focuses on only two visual social semiotics features – narrativity and dynamism – and therefore, only partially captures the potentialities of images in digital communications.

This study provides professionals with empirical evidence and insights for effectively planning a visual social media strategy.

This paper contributes to the stream of research in social media communications by investigating the visual social semiotic features of images published online by a food company.

In online social network analysis, the problem of identification and ranking of influential nodes based on their prominence has attracted immense attention from researchers and practitioners. Identification and ranking of influential nodes is a challenging problem using Twitter, as data contains heterogeneous features such as tweets, likes, mentions and retweets. The purpose of this paper is to perform correlation between various features, evaluation metrics, approaches and results to validate selection of features as well as results. In addition, the paper uses well-known techniques to find topical authority and sentiments of influential nodes that help smart city governance and to make importance decisions while understanding the various perceptions of relevant influential nodes.

The tweets fetched using Twitter API are stored in Neo4j to generate graph-based relationships between various features of Twitter data such as followers, mentions and retweets. In this paper, consensus approach based on Twitter data using heterogeneous features has been proposed based on various features such as like, mentions and retweets to generate individual list of top-k influential nodes based on each features.

The heterogeneous features are meant for integrating to accomplish identification and ranking tasks with low computational complexity, i.e. O(n), which is suitable for large-scale online social network with better accuracy than baselines.

Identified influential nodes can act as source in making public decisions and their opinion give insights to urban governance bodies such as municipal corporation as well as similar organization responsible for smart urban governance and smart city development.

This paper aims to investigate the relationship between a sustainable university brand and the intention of international students to study at Universiti Sains Malaysia (USM), one of Malaysia’s premier universities. Moreover, the study explored the moderating effect of opinion leaders on the intention of international students to study at USM.

A survey involving 391 international students was conducted using a self-assessment questionnaire, data from which were analysed using partial least squares structural equation modelling.

Empirical data show that USM’s sustainability brand had a positive impact on international students’ intention to study at the university, but opinion leaders had no significant sway in influencing this decision. This finding could be attributed to USM’s established reputation as a sustainable university, which helps cement its standing as the top choice for international students.

This research only focussed on international students at one Malaysian university. Hence, the findings are not generalisable, in particular, to illuminate the experiences of students at non-Malaysian institutions, whose contexts are inevitably different than Malaysia’s.

This study offered a dimensional insight into the university management on the pivotal branding of sustainability as one of the important tools for attracting international students to study at the university. In light of the findings, it is suggested that universities magnify their efforts to support the sustainable agenda, to help create a sustainable university brand that adds value to the interests of stakeholders.

Universities are continuously faced with challenges in terms of branding. Besides, not many universities are branded as sustainable universities despite the high involvement in sustainability-focused activities. Research has scarcely focused on the influence of the “sustainable university brand” on the marketing effort of the university to international students. In studies where this topic was highlighted, they focused on the opinion leader as the moderating influence of the choice of university amongst international students.