Expert Identification Research Articles

Enhancing the extended value chain of the aromatic plant sector in Italy: a multiple correspondence analysis based on stakeholders’ opinions

The aim of the study has been to understand the stakeholders’ stance, with respect to the different stages of Porter’s value chain, to learn what activities could create the most value to the future competitiveness of the Italian aromatic sector. The main challenges faced by stakeholders and possible future strategies have been investigated. A survey, consisting of four subsequent phases: creation of a focus group, identification of actors and experts, gathering of data, and processing of the data using descriptive statistics and Multiple Correspondence Analysis (MCA), has been performed. The stakeholders agreed that the Italian aromatic sector needs to enhance its value chain, but there is a polarisation of importance especially towards processors and retailers. Processors consider operations and outbound logistics as the most relevant primary activities, while retailers consider marketing and sales. Firm infrastructure and technology development are the more relevant support activities for retailers, while human resource management for processors. Farmers are apprehensive of imports, while processors agree that priority should be given to the bargaining power of retailers. Training of professionals emerges as an important future strategy to improve the extended value chain of the sector. The article investigates the extended value chain of the aromatic plant sector, according to Porter's model, in combination with a multivariate explorative tool (MCA). The results represent preliminary insights that can be used to diversify the role and sensitivity of different stakeholders, with respect to supply chain competitiveness and innovation.

Automated code compliance checking research based on BIM and knowledge graph

Automated code compliance checking plays an important role in moving the construction industry forward. While traditional drawing review relies on the identification of industry experts, the purpose of this study is to realize automatic code review by using BIM technology and knowledge graph technology. The method is based on knowledge graph to transform the specification provisions involved in the review of drawings into a computer-recognizable structured language using natural language processing technology to form a human–machine-readable knowledge graph pattern. For the review of BIM models, the BIM model information is exported and the global resource description framework of the building model is obtained in protégé, and the review report is finally obtained after mapping rules and review rules. Finally, the feasibility of the method is verified by an example. This study can effectively solve the problems of “manual dependency” and “inefficiency” in the process of review.

Prototyping of a lateral flow assay based on monoclonal antibodies for detection of Bothrops venoms

BackgroundBrazil is home to a multitude of venomous snakes; perhaps the most medically relevant of which belong to the Bothrops genus. Bothrops spp. are responsible for roughly 70% of all snakebites in Brazil, and envenomings caused by their bites can be treated with three types of antivenom: bothropic antivenom, bothro-lachetic antivenom, and bothro-crotalic antivenom. The choice to administer antivenom depends on the severity of the envenoming, while the choice of antivenom depends on availability and on how certain the treating physician is that the patient was bitten by a bothropic snake. The diagnosis of a bothropic envenoming can be made based on expert identification of the dead snake or a photo thereof or based on a syndromic approach wherein the clinician examines the patient for characteristic manifestations of envenoming. This approach can be very effective but requires staff that has been trained in clinical snakebite management, which, unfortunately, far from all relevant staff has. ResultsIn this article, we describe a prototype of the first lateral flow assay (LFA) capable of detecting venoms from Brazilian Bothrops spp. The monoclonal antibodies for the assay were generated using hybridoma technology and screened in sandwich enzyme-linked immunosorbent assays (ELISAs) to identify Bothrops spp.-specific antibody sandwich pairs. The prototype LFA is able to detect venom from several Bothrops spp. The LFA has a limit of detection (LoD) of 9.5 ng/mL in urine, when read with a commercial reader, and a visual LoD of approximately 25 ng/mL. SignificanceThe work presented here serves as a proof of concept for a genus-specific venom detection kit that could support physicians in diagnosing Bothrops envenomings. Although further optimisation and testing is needed before the LFA can find clinical use, such a device could aid in decentralising antivenoms in the Brazilian Amazon and help ensure optimal snakebite management for even more victims of this highly neglected disease.

How do ideas gain legitimacy in internal crowdsourcing idea development? Exploring the effects of feedback on idea selection

ABSTRACT Internal crowdsourcing offers new opportunities for ideas to gain legitimacy in idea development as not only managers but also experts are able to provide feedback to improve and subsequently accept ideas for further realisation. Given this far limited knowledge about how ideas gain legitimacy in idea development, this paper focuses on the influence of feedback, a main source of idea legitimacy in internal crowdsourcing. More specifically, this study aims to explore how feedback from different feedback providers (i.e., managers and experts) influences idea selection in internal crowdsourcing idea development. Based on text mining methods including sentiment, topic-model, and expert identification analyses, results reveal that feedback sentiment, feedback diversity and feedback amount play key roles in idea legitimisation. Specifically, these aspects of feedback influence idea acceptance in idea selection through the mediating role of idea revision in idea development and that this relationship is moderated by feedback providers. This study extends previous knowledge about the legitimisation process from the perspective of feedback in idea development by offering both a more comprehensive view, including different feedback aspects, and a more granular measurement of these, through the use of text analysis. Based on insights from the study, practical implications are presented for how to gain legitimacy from feedback for idea selection in internal crowdsourcing.

A dataset of desert plant images for deep learning recognition in Xinjiang in 2020–2021

Automatic recognition of desert plant types by machine vision can support the research on wind prevention and sand fixation, ecosystem value assessment, vegetation restoration and reconstruction, and reduce the dependence on plant expert identification. At present, the research on the machine discrimination model of desert plants mainly relies on the standardized high-quality plant specimen images, lacking the desert plant images obtained under complex natural conditions. This dataset provides typical desert plant images of Xinjiang that can be used for the model training of deep learning image classification, including 15,550 digital camera images of desert plants in Xinjiang obtained under different seasons, natural backgrounds and lighting conditions, and covering 19 typical desert plant types. Suaeda salsa has the smallest number of images and Artemisia desertorum has the biggest, 465 and 1,240 respectively, with a median of 800, which has met the training needs of mainstream deep learning model. This dataset can provide basic data for desert plant image segmentation, target detection and automatic recognition.

An Approach to Summarizing Product Reviews

Product reviews are an important feature of e-commerce because they influence the communicative behavior of a potential addressee (customers). Users often read online product reviews to get either general or specific information about a product or service. Besides, companies analyze customer reviews to improve their product quality or to adjust their marketing strategy. However, many reviews are unstructured and long. With the number of product reviews growing rapidly, reading a large number of reviews becomes a time-consuming process for both users and companies. Therefore, review summarization becomes a serious issue. In this paper, we propose a new approach to summarizing reviews of electronics and household appliances. The proposed approach makes it possible to structure information for every aspect category; it provides calculation sentiment score for each aspect category, and shows the most relevant sentences for each aspect. We used product reviews from Yandex.Market as target data. Our task was performed in five main phases: 1) expert identification of thematic aspect categories; 2) classifying sentences into the predefined aspect categories; 3) sentence classification into two classes—positive and negative—with calculating the number of both type sentences within each aspect category; 4) sentence ranking; 5) visualization of the results obtained in the previous phases. The quality of the algorithm for creating a resume from a large collection of reviews has been tested on five models of products from the following categories: coffee machines, robot vacuum cleaners, e-books, TV-sets, and washing machines.

Covid-19 vaccines, Di Bella therapy, alternative medicine and the "experts": who to believe?

The recent discussions on the efficacy and on the alleged harms caused by Covid-19 vaccines remind us of what happened 20 years ago with the Di Bella therapy, and always with alternative therapies, re-proposing a dilemma which, with the diffusion of communications though various media, is becoming increasingly topical: who is in the position to express opinions on technical topics in the health sector, worthy of being taken into consideration? The answer seems obvious: "the experts". But who decides who the experts are, and how do you recognize them? As paradoxical as it may seem, the only practicable system is to entrust the identification of experts to the experts themselves, the only ones able to recognize who can provide reliable answers on a specific problem. It is a system with huge flaws, but which in medicine has the advantage of forcing its interpreters to deal with the consequences of their choices, thus introducing a virtuous feedback mechanism with positive effects both on the selection of experts and on the decision-making mechanisms: it is therefore a system that seems to work in the medium-long term, but which in the face of an acute crisis is of little help to those who are not experts, but need the opinion of an expert.

The definition of a community paramedic: An international consensus

Community paramedicine is a globally evolving model of care where paramedics provide community-based, preventative and primary healthcare services. With increased global interest and adaptation of the community paramedicine model, there is a lack of a clear definition of the role of a community paramedic. This study sought to come to an international consensus on the definition of a community paramedic. A four-phase Delphi methodology was utilised to achieve a global consensus on the definition of a community paramedic. A systematic approach to expert identification was performed and reported in line with the Conducting and REporting of DElphi Studies standard. A total of 94 community paramedicine experts were identified and 76 experts consented to involvement in this Delphi. Response rate ranged from 81.6% (Phase 1) to 63.1% (Phase 2). Participants expressed the importance of community paramedic definition having components attributed to primary health care, health promotion, chronic disease management and advanced clinical assessment. Participants expressed that these are essential components of the community paramedic skill set, which distinguishes the role from other frontline paramedics. A final consensus with 91% agreement on the definition of a community paramedic was achieved. The four-phase Delphi achieved consensus on the definition of a community paramedic as follows: A community paramedic provides person-centred care in a diverse range of settings that address the needs of the community. Their practice may include the provision of primary health care, health promotion, disease management, clinical assessment and needs-based interventions. They should be integrated with interdisciplinary healthcare teams which aim to improve patient outcomes through education, advocacy and health system navigation. The adoption of the global consensus on the definition of a community paramedic will enhance efforts to promote the value of this specialist role, enabling a better understanding of how a community paramedic contributes to the wider healthcare system. [Media: see text]

Review of approaches and methods for identifying experts in organizational research

In scientific studies, three approaches are used to identify experts in organizational research: sociological, behavioral, and cognitive. In the sociological approach, the emphasis is on the socio-political status of a person. The behavioral approach focuses on how choices are made in situations of uncertainty. In the cognitive approach, the subject of the thought process is considered directly. The article shows the limitations of each of the approaches. Methods for identification of experts in organizational research in domestic and foreign scientific studies are given. Methods are considered: social acclamation, political influence, problem situation, personal involvement, external cues, self-ratings, past performance, knowledge tests, psychological traits. The advantages and disadvantages of each method are shown. Expert identification methods provide a set of opportunities for researchers of organization and organizational behavior, depending on the need for: expert judgment or expert knowledge; expert evaluation procedures or the product of professional activity; knowledge of a topic, a problem, highly specialized markets or representation of the interests of specific actors, groups, ideas, concepts. The author uses general logical research methods: induction, deduction, analysis, synthesis, scientific abstraction, comparison and contrasting.

Source Code Expert Identification: Models and Application

Source Code Expert Identification: Models and Application

Source Code Expert Identification: Models and Application

Source Code Expert Identification: Models and Application

Source Code Expert Identification: Models and Application

Source Code Expert Identification: Models and Application

”Voi tulla mitä vaan vastaan”: Epävarmuus ja yhteiskehittämistä muokkaavat käytännöt osallistuvassa budjetoinnissa

Harnessing the unexpectedness in co-creation: How uncertainty shapes the practices of co-creation in participatory budgeting? Recently, co-creation has been promoted as a bottom-up approach for fostering democratic processes relating to the knowledge production in governance. Participatory budgeting, which enables citizens to work with professionals or other stakeholders to design and decide how common funds are allocated, is considered as a form of co-creation. Based on empirical data collected in the city of Tampere and in the municipality of Inari, the article scrutinizes participatory budgeting, specifically where the diversity of participants and working cultures of local administrations introduce uncertainty in co-creation. To facilitate co-creation, there is a need to distinguish different practices of co-creation and identify their enabling or restricting elements. The article distinguishes among six practices:1) organizational commitment, 2) identification of actors and initiation of collaborative partnerships, 3) resourcing, 4) leadership, 5) identification of expertise and knowledge,and 6) emotional work.

Autumn poisoning hazards for pets

In the autumn, plants commonly produce their fruits, nuts and seeds, and fungi their fruit bodies (mushrooms). Some of these are poisonous and hazardous to pets. In addition to mushrooms, warm wet weather may promote the growth of mould producing tremorgenic mycotoxins, including on food waste, compost and windfall fruits and nuts. There is also a risk of exposure to luminous novelties and fireworks associated with autumnal events such as Halloween and in the UK, Bonfire Night. For pets that ingest mushrooms, expert identification of the suspect mushroom is highly recommended to identify animals as risk of severe poisoning. Many mushrooms only cause gastrointestinal upset, but others cause neurological effects, renal and/or liver damage. Tremorgenic mycotoxins cause rapid-onset whole-body tremors and seizures. Ingestion of luminous novelties usually only produces a taste reaction which rapidly resolves. Fireworks generally only cause gastrointestinal signs but there is a potential risk of metal poisoning, although this is uncommon. Conkers and acorns are commonly eaten by dogs in the autumn and typically cause only gastrointestinal signs, but there is the risk of obstruction and occasionally more significant signs. Management of autumnal hazards is supportive but advice from a poisons information service should be sought if necessary.

Domain expertise extraction for finding rising stars

The field of expertise extraction utilizes published research enabling communities to highlight and identify the skills of researchers within specific scientific domains. This can be useful for evaluating research performance, and in the case of rising stars, in identifying top scientific talent. Previous research has harvested a range of publication indicators in an effort to identify expertise and talent. These include content indicators, citation metrics, and also the position of a researcher within a full collaboration network of scientists. The existing mechanism of expertise extraction utilizes all papers attributed to a scientific author, thereby potentially neglecting their specific or specialized expertise. Here we show that a tensor decomposition technique when applied to the problem addresses a number of useful problems. This includes better identification of individual expertise, as well as an integrated appraisal of an author’s role in an extended scientific network. The technique will afford new analyses of knowledge production which consider specialisation and diversity as core elements for further analysis. More generally the tensor decomposition techniques presented in this paper can be applied to a range of scientometric problems where multi-modal data is encountered.

ChildProtect: A parental control application for tracking hostile surfing content

The emergence of the Internet and social media has provided a ground conducive to the rapid development of violent ideas and online malicious behavior, and even to rising the share of hostile content (hate speech, fake news, etc.). Such behavior raises concerns about children who are overly exposed to the internet and likely misusing the online content. Unwantedly, they can stumble upon dangerous websites inciting them to violence, terrorism and radicalization. Motivated by the efforts towards confronting these malicious activities, we propose a new parental control application, called ChildProtect. The main purpose of our application is to monitor children’s activities on the Internet, protect them from hostile postings and online threats, prevent the radicalization, and eventually alert and inform their parents. Hence, we introduce a framework composed of two main sides, namely backend and frontend. The frontend presents the Childprotect’s functionalities offered to parents. Unnecessary, the backend constitutes the application’ kernel, which aims at performing a deep content-analysis of the online child’s activities. In this side, we distinguished various steps, including the collecting and managing of the child’s browsing history, as well as mining and analyzing the collected data for identifying its hostile valence. We build a dictionary containing dangerous vocabulary frequently used for online hostility. The findings of our proposed method were evaluated using expert identification. The conducted experiments demonstrated that our method is effective, consistent, and outperforms the results of its competitors in the literature.

Expert identification for ethics expertise informed by feminist epistemology-Using awareness of biases and situated ignorance as an indicator of trustworthiness.

The notion of moral expertise poses a variety of challenges concerning both the question of existence of such experts and their identification by laypeople. I argue for a view of ethics expertise, based on moral understanding instead of on moral knowledge, that is less robust than genuine moral expertise and that does not rely on deference to testimony. I propose identification criteria that focus mainly on the awareness and communication of implicit biases and situated ignorance. According to the account of ethics expertise presented in this paper, the expert's testimony is not an epistemic reason for the layperson's belief, but merely an epistemic influence. The epistemic reasons for the layperson's belief are largely independent from the expert. But there is still some epistemic risk involved in the proposed method of knowledge transfer, and therefore criteria for the identification of a trustworthy expert are necessary. The risk involved in knowledge transfer can be both due to willful manipulation and due to the expert's implicit biases and situated ignorance. While willful manipulation cannot really be avoided, the influence from biases and ignorance can be minimized. I argue that the best way to do this is if the expert is aware of their own biases and ignorance and communicates them. Combined with evidence of the expert's education in moral philosophy and experience with the topic in question, this gives the layperson the best chance to identify someone who can really help them consider all relevant aspects of a situation and come to a better justified decision.

Topical Issues of Expert Identification in the Forensic Authorship Studies

Within the school of forensic expertology, in the context of modern challenges of digitalization, the current problems of forensic and expert identification are considered to establish the author of a controversial speech work posted on the Internet, an information and media language personality. Based on the analysis of the main stages of the process of expert identification of the author of the text, the need for their correction and addition is revealed in connection with significant changes in the linguistic personality manifests itself mainly in a virtual environment. The necessity of developing a classifier of the author’s idiolect features with an indication of their identification significance, as well as the use of quantitative statistical methods for analyzing speech works using computer technology, is substantiated.

Analysis of community question‐answering issues via machine learning and deep learning: State‐of‐the‐art review

AbstractOver the last couple of decades, community question‐answering sites (CQAs) have been a topic of much academic interest. Scholars have often leveraged traditional machine learning (ML) and deep learning (DL) to explore the ever‐growing volume of content that CQAs engender. To clarify the current state of the CQA literature that has used ML and DL, this paper reports a systematic literature review. The goal is to summarise and synthesise the major themes of CQA research related to (i) questions, (ii) answers and (iii) users. The final review included 133 articles. Dominant research themes include question quality, answer quality, and expert identification. In terms of dataset, some of the most widely studied platforms include Yahoo! Answers, Stack Exchange and Stack Overflow. The scope of most articles was confined to just one platform with few cross‐platform investigations. Articles with ML outnumber those with DL. Nonetheless, the use of DL in CQA research is on an upward trajectory. A number of research directions are proposed.

Capabilities of the Chromatek-DHA Software for Determining the Quality of Automobile Gasoline

The article addresses factors able to influence the results of determining the performance characteristics of gasoline using calculation methods. The author presents the results of a study of three brands of automobile gasoline conducted by means of gas-liquid chromatography with Chromatek-DHA software. The calculated operational characteristics of gasoline have been compared with the results of their analysis by standardized methods. The article demonstrates the possibility of using data on the group hydrocarbon composition in solving expert identification tasks regarding automobile gasoline that has not been exposed to external factors.