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This study has mainly aimed to compare and contrast two completely different image processing algorithms that are very adaptive for detecting prostate cancer using wearable Internet of Things (IoT) devices. Cancer in these modern times is still considered as one of the most dreaded disease, which is continuously pestering the mankind over a past few decades. According to Indian Council of Medical Research, India alone registers about 11.5 lakh cancer related cases every year and closely up to 8 lakh people die with cancer related issues each year. Earlier the incidence of prostate cancer was commonly seen in men aged above 60 years, but a recent study has revealed that this type of cancer has been on rise even in men between the age groups of 35 and 60 years as well. These findings make it even more necessary to prioritize the research on diagnosing the prostate cancer at an early stage, so that the patients can be cured and can lead a normal life.

The research focuses on two types of feature extraction algorithms, namely, scale invariant feature transform (SIFT) and gray level co-occurrence matrix (GLCM) that are commonly used in medical image processing, in an attempt to discover and improve the gap present in the potential detection of prostate cancer in medical IoT. Later the results obtained by these two strategies are classified separately using a machine learning based classification model called multi-class support vector machine (SVM). Owing to the advantage of better tissue discrimination and contrast resolution, magnetic resonance imaging images have been considered for this study. The classification results obtained for both the SIFT as well as GLCM methods are then compared to check, which feature extraction strategy provides the most accurate results for diagnosing the prostate cancer.

The potential of both the models has been evaluated in terms of three aspects, namely, accuracy, sensitivity and specificity. Each model’s result was checked against diversified ranges of training and test data set. It was found that the SIFT-multiclass SVM model achieved a highest performance rate of 99.9451% accuracy, 100% sensitivity and 99% specificity at 40:60 ratio of the training and testing data set.

The SIFT-multi SVM versus GLCM-multi SVM based comparison has been introduced for the first time to perceive the best model to be used for the accurate diagnosis of prostate cancer. The performance of the classification for each of the feature extraction strategies is enumerated in terms of accuracy, sensitivity and specificity.

The purpose of this article is to (1) map the most important topics in the domain of sustainable business practices for entrepreneurial firms in emerging countries, (2) identify important terms in the various dimensions of sustainability in business and (3) identify the important practices and prioritize the practices.

This study has adopted a unique methodology that combines state-of-art scientometric analysis with the fuzzy nominal group technique (NGT) and fuzzy decision-making trial and evaluation laboratory (DEMATEL). Results obtained from the co-occurrence analysis in scientometrics were further mapped through NGT to obtain the list of the most important topics in the domain. The factors affecting sustainable business practices obtained through topic mapping were analyzed through fuzzy DEMATEL to obtain the cause-and-effect relation of variables.

The scale of firms, leadership, uncertainty, gender, country/location, education and tourism were found to be the factors affecting the sustainable business practices of entrepreneurial firms. The sustainable business practices for entrepreneurial firms were (1) innovation, (2) resilience, (3) policy, (4) business ethics and virtue ethics, (5) business model, (6) upcycling and value creation, (7) collaboration and (8) triple bottom line.

Policymakers in entrepreneurial firms, as well as other organizations, can implement the identified sustainable business practices to obtain optimum results and smooth functioning of the companies. The research framework obtained can be tested using exploratory methods.

Very few researchers have used the technique of scientometric analysis to identify the sustainable business practices of entrepreneurial firms, and to the best of the knowledge of the authors, no earlier researcher has attempted to use the technique of topic mapping, fuzzy NGT and fuzzy DEMATEL in combination.

Nature’s contribution to people (NCP) is a concept that specifically recognizes the relationship of “humans and the natural environment” similarly to concepts of “cultural landscapes” and consistent to “heritage.” These concepts are essential in incorporating a diverse range of stakeholders from different scales, which is important for policy and practice. The paper aims to review the existing peer-reviewed papers in the Philippines, using meta-analysis and systematic review. We addressed the significant interlinkages that help facilitate the transition and strengthen the correlation of cultural ecosystem services (CES) and NCP in a cultural landscape setting.

To distinguish and support claims for NCP from CES, we conducted a meta-analysis and systematic review based on the 30-existing peer-reviewed articles on the Philippine cultural ES in the lenses of “heritage” and “cultural landscape.”

The results generated a few numbers of the Philippine CES studies, yet it has increased cumulatively year by year consistent with previous international studies. We found that most studies are focused on topics associated with “Indigenous People, Ancestral Domains, Protected Areas/Landscapes, and Indigenous and Local Knowledge” on the linkages concurrently distinguishing NCP to CES, and may signify stronger economic valuation in uncovering the sociocultural dimensions of these scholarships through its relational values in the lenses of cultural landscape and heritage.

The authors limited the search to peer-reviewed journal articles published from online databases and did not consider Philippine University based and local publications to have a systematic review. This is to prevent underestimating the vast amount of CES literature and avoid gray literature that is not peer-reviewed; hence, being able to analyze and produce focused, yet, credible data.

In a generalizing perspective, NCP 1, 6, 8, 12, 13, 15, 16, 17 and 18 have the most realized positive correlations of the reporting categories to the Philippine CES studies. The majority of the context-specific perspective NCP has strong conceptual claims in the existing Philippine CES literature through the studies’ variables aside from NCP 3, 4, 5, 7, 8 and 11 that are still mostly in the nature of generalizing perspective.

In conclusion, our results imply that the previous and existing CES studies in the Philippines harbor more attributes presented by the NCP reporting categories. This is deemed more suitable, and may signify stronger economic valuation in uncovering the sociocultural dimensions of these scholarships through its relational values in the lenses of cultural landscape and heritage.

The literature on public procurement (PP) has increased significantly in recent years, and, to date, several reviews have been conducted to study this relevant subject. Nevertheless, a bibliometric analysis of the PP knowledge domain is still missing. To fill this knowledge gap, a bibliometric review is carried out to investigate the current state of PP research.

A total of 640 journal articles are selected from the Scopus database for the final analysis. The performance indicators of the literature are identified and explained through bibliometric analysis. Furthermore, the conceptual and intellectual structures are studied through a keyword co-occurrence network and bibliographic coupling.

The results of the review indicate that PP research has increased significantly in recent years. The top ten most productive journals, countries, authors and academic institutions are identified. The findings from the keyword co-occurrence network reveal six main research themes including innovation, corruption and green public procurement (GPP). By applying bibliographic coupling, the focus of PP research revolves around seven thematic areas: GPP, corruption, the role of small and medium-sized enterprises (SMEs) in PP, electronic PP, innovation, labour standards and service acquisition. The research potential of each thematic area is evaluated using a model based on maturity and recent attention (RA).

To the best of the authors' knowledge, this is the first study to successfully organise, synthesise and quantitatively analyse the development of the PP domain amongst a large number of publications on a large time scale.

This study aims to review recent advances towards the implementation of ANN and NLP applications during the budgeting phase of the construction process. During this phase, construction companies must assess the scope of each task and map the client’s expectations to an internal database of tasks, resources and costs. Quantity surveyors carry out this assessment manually with little to no computer aid, within very austere time constraints, even though these results determine the company’s bid quality and are contractually binding.

This paper seeks to compile applications of machine learning (ML) and natural language processing in the architectural engineering and construction sector to find which methodologies can assist this assessment. The paper carries out a systematic literature review, following the preferred reporting items for systematic reviews and meta-analyses guidelines, to survey the main scientific contributions within the topic of text classification (TC) for budgeting in construction.

This work concludes that it is necessary to develop data sets that represent the variety of tasks in construction, achieve higher accuracy algorithms, widen the scope of their application and reduce the need for expert validation of the results. Although full automation is not within reach in the short term, TC algorithms can provide helpful support tools.

Given the increasing interest in ML for construction and recent developments, the findings disclosed in this paper contribute to the body of knowledge, provide a more automated perspective on budgeting in construction and break ground for further implementation of text-based ML in budgeting for construction.

Design-based research (DBR) involves multiple iterations, and innovations are needed in analytical methods for understanding how learners experience a learning experience in ways that both embrace the complexity of learning and allow for data-driven changes to the design of the learning experience between iterations. The purpose of this paper is to propose a method of crafting design moves in DBR using network analysis.

This paper introduces learning experience network analysis (LENA) to allow researchers to investigate the multiple interdependencies between aspects of learner experiences, and to craft design moves that leverage the relationships between struggles, what worked and experiences aligned with principles from theory.

The use of network analysis is a promising method of crafting data-driven design changes between iterations in DBR. The LENA process developed by the authors may serve as inspiration for other researchers to develop even more powerful methodological innovations.

LENA may provide design-based researchers with a new approach to analyzing learner experiences and crafting data-driven design moves in a way that honors the complexity of learning.

LENA may provide novice design-based researchers with a structured and easy-to-use method of crafting design moves informed by patterns emergent in the data.

To the best of the authors’ knowledge, this paper is the first to propose a method for using network analysis of qualitative learning experience data for DBR.

This study aims to conduct a bibliometric analysis on knowledge management from journals in the Scopus database between 1988 and 2021. The paper covered the past three decades of publications and carried out performance analysis and science mapping analysis of articles.

The study uses bibliometrics, performance analysis and science mapping analysis of 1,016 articles extracted from the Scopus database. The study examined the scientific productivity of articles, productive authors, citable documents, most relevant institutions, cited countries, co-occurrence of keywords, thematic mapping, co-citations and collaboration of authors and countries. The study used Biblioshiny as a tool to carry out the performance analysis and science mapping analysis.

The results show that the number of publications has significantly increased in the past decade, 88.4% of authors contribute at least a single article, 8.3% of authors published two articles, 2% of the authors published three documents and 0.6% of the authors contribute four papers. The USA, China and Australia were the most productive countries in terms of the total number of citations and foreign collaborations. Journal of Knowledge Management, Knowledge Management Research and Practice, VINE Journal of Information and Knowledge Management and International Journal of Technology Management are the top outlets in the knowledge management literature.

Over the past decade, the research on knowledge management construct has exploded because of the growing interest of researchers and practitioners in the field. Despite being a well-developed field, few studies have applied bibliometric analysis in the knowledge management literature. The study is more comprehensive in terms of the actors and methods involved in analyzing the scientific production of articles in the area of knowledge management.

This study aims to undertake a theoretical and technical exploration of the literature on Work Readiness (WR) through the implementation of a systematic literature review and bibliometric analysis. The present study addresses seven distinct research questions: (1) an examination of the descriptive features characterizing the literature on WR, (2) an analysis of trends in annual scientific publications related to WR, (3) the identification of the most pertinent and high-impact sources contributing to WR, (4) the delineation of the globally cited articles exerting the most influence on WR, (5) the determination of the most relevant countries associated with WR, (6) an evaluation of the outcomes derived from Bradford’s Law of Scattering and Lotka’s Law of scientific productivity in the context of WR, and (7) the identification of the prevailing research avenues that hold significance for future studies on WR.

The present study employed Systematic Literature Review (SLR) and bibliometric analysis mapping techniques to analyze 521 articles extracted from the Scopus database. The analysis utilized Biblioshiny software and VOSviewer software as the primary tools.

The findings reveal that WR constitutes a steadily expanding subject discipline, showcasing a notable 9.12% annual growth in scientific production spanning from 1975 to 2023. Australia, the USA, and Canada emerged as the most productive countries within the field of WR, as evidenced by their cumulative scientific production. The thematic map of keyword analysis suggests several burgeoning pathways for future researchers in the WR domain, including workplace learning, functional capacity evaluation, graduate WR, digital literacy, blended learning, resilience, and curriculum.

This study contributes to the WR discourse by providing a comprehensive literature review. The findings of this study hold significance for graduates, universities, employers, the higher education industry, and the broader community.

This study systematically reviewed existing literature on the impact of economic uncertainty on property performance to highlight focus areas and spur future research amid unprecedented global uncertainty levels. Conceptually, uncertainty levels and environmental dynamism are related to investors' risk judgement and decision-making.

Peer-reviewed journal articles published from 2007 to 2022 were assembled and arranged through the Scientific Procedures and Rationales for Systematic Literature Reviews (SPAR-4-SLR) protocol. The initial search produced 2,028 results from the Web of Science and Scopus databases, which were rigorously purified for a final dataset of 70 articles. These records were subsequently assessed through content analysis, bibliographic modelling, topic modelling and thematic analysis. Recurring themes were visualised using the VOSviewer software.

The existing literature suggests that economic uncertainty negatively impacts investment volumes, returns and performance. Research has also increased since 2018, with a strong emphasis on the housing sector and developed property markets. Commercial property and emerging markets account for only 10 and 8% of previous research, respectively.

These findings highlight the negative impact of economic uncertainties on property performance and investment volumes, which necessitate careful risk assessment. Given the high susceptibility of emerging and commercial property markets to uncertainty, these markets warrant further research amid ongoing uncertainty concerns across the globe.

Given current unprecedented levels of global uncertainty, the effects of economic uncertainty have received renewed interest. This study synthesised the current understanding of how different property markets respond to increased uncertainty and outlined future research directions to enhance understanding. Themes and relationships were also integrated into a conceptual map summarising the reported effects of economic uncertainty on housing, commercial property, investment and behaviour in the property market.

To examine the development of research into the relationship between business process outsourcing (BPO) and innovation, a bibliometric methodology utilizing quantitative analytical methodologies was used. With the aid of a visualization analysis of scientific publications, this study also assessed the state of BPO and innovation practices.

Using the Web of Science database, articles on BPO and innovation that published between 1992 and 2022 were retrieved. Records that had been extracted were examined in terms of publication year, nation, journal, subject area, authors and affiliations with organizations. The research on acupuncture for pain relief was visualized using the VOSviewer application.

An analysis of 219 original and review papers found that during the past 30 years, the overall number of publications has fluctuated constantly. The London University, the Copenhagen Business School and the London School of Economics were the institutions that produced the most articles in this topic. The three main categories of research that emerged from a network analysis based on the co-occurrence of keywords are innovation, outsourcing and performance.

A BP-innovation model must be created, and BPO must go beyond operational duties to incorporate management-wide shared strategic decisions in order to ensure improved performance of the firms. BPO enables a company's management to share knowledge and expertise about the strategic difficulties of outsourcing. A variety of technological and non-technological resources must also be considered when integrating an information technology (IT) infrastructure into BPO decisions in order to achieve greater performance.

Validity of the paper can be justified by it contribution to the existing knowledge. First, linking BPO and innovation – by integrating the arguments of various academics, the study unifies the disparate components and contentious discussions in the relationship between BPO and innovation. Second, this study highlights a research trend, significant studies, relevant terms and concepts in the real world. Third, the study provides future researchers with a tip for statistically analyzing BPO, particularly in light of innovation.