Building Concept System from the Perspective of Development of the Concept

Author(s):  
Cheng Xian-yi ◽  
Shen Xue-hua ◽  
Shi Quan
Keyword(s):  
2020 ◽  
Vol 2 (4) ◽  
pp. 62-67
Author(s):  
M. M. KHAYTANOVA ◽  

The article reveals: theoretical justifications of the concept of “financial risk” in relation to the sphere of entrepreneurship; methods for its identification and processing. Financial risk management is the activity of identification, assessment, control and monitoring of risks. In the course of the study, methods for managing financial risks in entrepreneurial activity and their classification were identified.


1986 ◽  
Author(s):  
G. MCPARLAND ◽  
D. BENNETT ◽  
J. COON ◽  
N. MITTERMEIER

2007 ◽  
Vol 33 (1) ◽  
pp. 105-133 ◽  
Author(s):  
Catalina Hallett ◽  
Donia Scott ◽  
Richard Power

This article describes a method for composing fluent and complex natural language questions, while avoiding the standard pitfalls of free text queries. The method, based on Conceptual Authoring, is targeted at question-answering systems where reliability and transparency are critical, and where users cannot be expected to undergo extensive training in question composition. This scenario is found in most corporate domains, especially in applications that are risk-averse. We present a proof-of-concept system we have developed: a question-answering interface to a large repository of medical histories in the area of cancer. We show that the method allows users to successfully and reliably compose complex queries with minimal training.


2003 ◽  
Vol 27 (2) ◽  
pp. 241-256 ◽  
Author(s):  
Aurea Maria Brandi Nardelli ◽  
James Jackson Griffith
Keyword(s):  

A opção por uma estratégia que conduza a mudanças efetivas no setor florestal requer o estabelecimento de uma visão compartilhada de sustentabilidade, que contribua para a consolidação de instituições e que oriente as respostas empresariais. Este estudo foi desenvolvido com o objetivo de identificar quais seriam os elementos que compõem a visão de sustentabilidade para o setor, a partir da opinião de diversos atores sociais que participam de seu campo organizacional. Aplicou-se a técnica de Mapeamento Conceitual, utilizando o programa CONCEPT SYSTEM versão 1.75 para processamento dos dados. As declarações geradas foram agrupadas em seis temas, que abrangeram elementos do manejo florestal ambientalmente adequado, socialmente justo e economicamente viável. Para compor a visão de sustentabilidade do setor florestal brasileiro, os participantes consideraram mais importantes os grupos de conceitos "Floresta e Sociedade" e "Conservação Ambiental". As respostas foram comparadas por segmento e considerou-se o nível de importância aplicado aos elementos da visão de sustentabilidade como um reflexo das regras, dos padrões e dos valores cognitivos dos representantes dos interesses econômicos, sociais e ambientais.


2021 ◽  
Vol 5 ◽  
Author(s):  
Yihuai Hu ◽  
Olha Khomenko ◽  
Wenxuan Shi ◽  
Ángel Velasco-Sánchez ◽  
S. M. Ashekuzzaman ◽  
...  

Worldwide dairy processing plants produce high volumes of dairy processing sludge (DPS), which can be converted into secondary derivatives such as struvite, biochar and ash (collectively termed STRUBIAS). All of these products have high fertilizer equivalent values (FEV), but future certification as phosphorus (P)-fertilizers in the European Union will mean they need to adhere to new technical regulations for fertilizing materials i.e., content limits pertaining to heavy metals (Cd, Cu, Hg, Ni, Pb, and Zn), synthetic organic compounds and pathogens. This systematic review presents the current state of knowledge about these bio-based fertilizers and identifies knowledge gaps. In addition, a review and calculation of greenhouse gas emissions from a range of concept dairy sludge management and production systems for STRUBIAS products [i.e., biochar from pyrolysis and hydrochar from hydrothermal carbonization (HTC)] is presented. Results from the initial review showed that DPS composition depends on product type and treatment processes at a given processing plant, which leads to varied nutrient, heavy metal and carbon contents. These products are all typically high in nutrients and carbon, but low in heavy metals. Further work needs to concentrate on examining their pathogenic microorganism and emerging contaminant contents, in addition to conducting an economic assessment of production and end-user costs related to chemical fertilizer equivalents. With respect to STRUBIAS products, contaminants not present in the raw DPS may need further treatment before being land applied in agriculture e.g., heated producing ashes, hydrochar, or biochar. An examination of these products from an environmental perspective shows that their water quality footprint could be minimized using application rates based on P incorporation of these products into nutrient management planning and application by incorporation into the soil. Results from the concept system showed that elimination of methane emissions was possible, along with a reduction in nitrous oxide. Less carbon (C) is transferred to agricultural fields where DPS is processed into biochar and hydrochar, but due to high recalcitrance, the C in this form is retained much longer in the soil, and therefore STRUBIAS products represent a more stable and long-term option to increase soil C stocks and sequestration.


2021 ◽  
Author(s):  
Quoc V. Vy

This thesis proposes a new technique for speaker identification in captioning using three identifiers: image, name and colour. This technique was implemented as a proofof- concept system called the


2021 ◽  
Vol 13 (10) ◽  
pp. 250
Author(s):  
Luis A. Corujo ◽  
Emily Kieson ◽  
Timo Schloesser ◽  
Peter A. Gloor

Creating intelligent systems capable of recognizing emotions is a difficult task, especially when looking at emotions in animals. This paper describes the process of designing a “proof of concept” system to recognize emotions in horses. This system is formed by two elements, a detector and a model. The detector is a fast region-based convolutional neural network that detects horses in an image. The model is a convolutional neural network that predicts the emotions of those horses. These two elements were trained with multiple images of horses until they achieved high accuracy in their tasks. In total, 400 images of horses were collected and labeled to train both the detector and the model while 40 were used to test the system. Once the two components were validated, they were combined into a testable system that would detect equine emotions based on established behavioral ethograms indicating emotional affect through the head, neck, ear, muzzle, and eye position. The system showed an accuracy of 80% on the validation set and 65% on the test set, demonstrating that it is possible to predict emotions in animals using autonomous intelligent systems. Such a system has multiple applications including further studies in the growing field of animal emotions as well as in the veterinary field to determine the physical welfare of horses or other livestock.


Author(s):  
Sijia Liu ◽  
Yanshan Wang ◽  
Andrew Wen ◽  
Liwei Wang ◽  
Na Hong ◽  
...  

BACKGROUND Widespread adoption of electronic health records has enabled the secondary use of electronic health record data for clinical research and health care delivery. Natural language processing techniques have shown promise in their capability to extract the information embedded in unstructured clinical data, and information retrieval techniques provide flexible and scalable solutions that can augment natural language processing systems for retrieving and ranking relevant records. OBJECTIVE In this paper, we present the implementation of a cohort retrieval system that can execute textual cohort selection queries on both structured data and unstructured text—Cohort Retrieval Enhanced by Analysis of Text from Electronic Health Records (CREATE). METHODS CREATE is a proof-of-concept system that leverages a combination of structured queries and information retrieval techniques on natural language processing results to improve cohort retrieval performance using the Observational Medical Outcomes Partnership Common Data Model to enhance model portability. The natural language processing component was used to extract common data model concepts from textual queries. We designed a hierarchical index to support the common data model concept search utilizing information retrieval techniques and frameworks. RESULTS Our case study on 5 cohort identification queries, evaluated using the precision at 5 information retrieval metric at both the patient-level and document-level, demonstrates that CREATE achieves a mean precision at 5 of 0.90, which outperforms systems using only structured data or only unstructured text with mean precision at 5 values of 0.54 and 0.74, respectively. CONCLUSIONS The implementation and evaluation of Mayo Clinic Biobank data demonstrated that CREATE outperforms cohort retrieval systems that only use one of either structured data or unstructured text in complex textual cohort queries.


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