An Intelligent Mechanism to Automatically Discover Emerging Technology Trends: Exploring Regulatory Technology

Technology trend analysis uses data relevant to historical performance and extrapolates it to estimate and assess the future potential of technology. Such analysis is used to analyze emerging technologies or predict the growing markets that influence the resulting social or economic development to assist in effective decision-making. Traditional trend analysis methods are time-consuming and require considerable labor. Moreover, the implemented processes may largely rely on the specific knowledge of the domain experts. With the advancement in the areas of science and technology, emerging cross-domain trends have received growing attention for its considerable influence on society and the economy. Consequently, emerging cross-domain predictions that combine or complement various technologies or integrate with diverse disciplines may be more critical than other tools and applications in the same domain. This study uses a design science research methodology, a text mining technique, and social network analysis (SNA) to analyze the development trends concerning the presentation of the product or service information on a company's website. This study applies regulatory technology (RegTech) as a case to analyze and justify the emerging cross-disciplinary trend. Furthermore, an experimental study is conducted using the Google search engine to verify and validate the proposed research mechanism at the end of this study. The study results reveal that, compared with Google Trends and Google Correlate, the research mechanism proposed in this study is more illustrative, feasible, and promising because it reduces noise and avoids the additional time and effort required to perform a further in-depth exploration to obtain the information.

Theory-Based Problem Formulation and Ideation in mHealth Analysis and Recommendations

This article reports on an investigation into how to improve problem formulation and ideation in Design Science Research (DSR) within the mHealth domain. A Systematic Literature Review of problem formulation in published mHealth DSR papers found that problem formulation is often only weakly performed, with shortcomings in stakeholder analysis, patient-centricity, clinical input, use of kernel theory, and problem analysis. The study proposes using Coloured Cognitive Mapping for DSR (CCM4DSR) as a tool to improve problem formulation in mHealth DSR. A case study using CCM4DSR found that using CCM4DSR provided a more comprehensive problem formulation and analysis, highlighting aspects that, until CCM4DSR was used, weren’t apparent to the research team and which served as a better basis for mHealth feature ideation.

Método para captura e priorização de requisitos de futuros usuários de Habitações de Interesse Social

Resumo O valor do produto, como percebido pelo usuário, envolve interações complexas entre escolhas que estes realizam, em face de um grande conjunto de atributos positivos e negativos. Nesse contexto, é possível destacar a ausência de um procedimento que aproxime o valor recebido pelo usuário do seu valor desejado. O objetivo geral deste trabalho é propor um método para captura e priorização de requisitos de usuários para subsidiar o processo de concepção e projeto de empreendimentos habitacionais de interesse social (EHIS), com base em um estudo de caso no âmbito do Programa Minha Casa Minha Vida-Entidades. Como estratégia de pesquisa optou-se pela Design Science Research. O trabalho foi dividido em três fases, além de uma revisão de literatura. Na fase exploratória, adaptou-se a técnica de análise conjunta baseada em escolhas, para a realidade da pesquisa. A fase de desenvolvimento contemplou as seguintes etapas: (a)captura dos requisitos; (b) hierarquização e priorização desses requisitos e; (c) relação entre os modelos de preferência, e os tipos de família dos futuros usuários de habitações de interesse social (HIS). Com base na última fase, de análise e reflexão, foi proposto um método para captura e priorização de requisitos de usuários, com vistas à disponibilização desses requisitos para subsidiar o processo de concepção e projeto de EHIS.

Scalable Science Education via Online Cooperative Questioning

How can the scalable powers of peer learning and online technologies be most effectively used to support conceptual understanding in science education? This paper reviews cognitive science research on how people learn via question answering and authoring and evaluates a promising novel learning design that applies these principles.

From crowd to cloud: simplified automatic reconstruction of digital building assets for facility management

Purpose The purpose of this paper is to investigate the feasibility of an end-to-end simplified and automated reconstruction pipeline for digital building assets using the design science research approach. Current methods to create digital assets by capturing the state of existing buildings can provide high accuracy but are time-consuming, expensive and difficult. Design/methodology/approach Using design science research, this research identifies the need for a crowdsourced and cloud-based approach to reconstruct digital building assets. The research then develops and tests a fully functional smartphone application prototype. The proposed end-to-end smartphone workflow begins with data capture and ends with user applications. Findings The resulting implementation can achieve a realistic three-dimensional (3D) model characterized by different typologies, minimal trade-off in accuracy and low processing costs. By crowdsourcing the images, the proposed approach can reduce costs for asset reconstruction by an estimated 93% compared to manual modeling and 80% compared to locally processed reconstruction algorithms. Practical implications The resulting implementation achieves “good enough” reconstruction of as-is 3D models with minimal tradeoffs in accuracy compared to automated approaches and 15× cost savings compared to a manual approach. Potential facility management use cases include the issue and information tracking, 3D mark-up and multi-model configurators. Originality/value Through user engagement, development, testing and validation, this work demonstrates the feasibility and impact of a novel crowdsourced and cloud-based approach for the reconstruction of digital building assets.

Public and Private Enforcement in European Union Food Law

What type of enforcement is the most effective to punish violations of food law or to prevent them from occurring in the first place? This article examines the question of which mix of private and public enforcement exists in European Union (EU) food law and whether this mix corresponds to the recommendations of existing social science research. Based on this research, we contend that EU-determined enforcement mechanisms differ in effectiveness across Member States. New technologies have the potential to stimulate a novel mix of public and private enforcement tools at the EU and national levels.

Biomedical Applications of Iron Oxide Nanoparticles: Current Insights Progress and Perspectives

The enormous development of nanomaterials technology and the immediate response of many areas of science, research, and practice to their possible application has led to the publication of thousands of scientific papers, books, and reports. This vast amount of information requires careful classification and order, especially for specifically targeted practical needs. Therefore, the present review aims to summarize to some extent the role of iron oxide nanoparticles in biomedical research. Summarizing the fundamental properties of the magnetic iron oxide nanoparticles, the review’s next focus was to classify research studies related to applying these particles for cancer diagnostics and therapy (similar to photothermal therapy, hyperthermia), in nano theranostics, multimodal therapy. Special attention is paid to research studies dealing with the opportunities of combining different nanomaterials to achieve optimal systems for biomedical application. In this regard, original data about the synthesis and characterization of nanolipidic magnetic hybrid systems are included as an example. The last section of the review is dedicated to the capacities of magnetite-based magnetic nanoparticles for the management of oncological diseases.

Uncomfortable Decisions

Some decision-making processes are uncomfortable. Many of us do not like to make significant decisions, such as whether to have a child, solely based on social science research. We do not like to choose randomly, even in cases where flipping a coin is plainly the wisest choice. We are often reluctant to defer to another person, even if we believe that the other person is wiser, and have similar reservations about appealing to powerful algorithms. And, while we are comfortable with considering and weighing different options, there is something strange about deciding solely on a purely algorithmic process, even one that takes place in our own heads.What is the source of our discomfort? We do not present a decisive theory here—and, indeed, the authors have clashing views over some of these issues—but we lay out the arguments for two (consistent) explanations. The first is that such impersonal decision-making processes are felt to be a threat to our autonomy. In all of the examples above, it is not you who is making the decision, it is someone or something else. This is to be contrasted with personal decision-making, where, to put it colloquially, you “own” your decision, though of course you may be informed by social science data, recommendations of others, and so on. A second possibility is that such impersonal decision-making processes are not seen as authentic, where authentic decision making is one in which you intentionally and knowledgably choose an option in a way that is “true to yourself.” Such decision making can be particularly important in contexts where one is making a life-changing decision of great import, such as the choice to emigrate, start a family, or embark on a major career change.