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1.
PLoS One ; 18(1): e0273124, 2023.
Artículo en Inglés | MEDLINE | ID: mdl-36662816

RESUMEN

PURPOSE: This study aimed to optimize the trade-in pricing strategy. To leverage market share, many sellers adopt trade-in strategy for advance selling, Customers can return their old products at a discount price when they buy new products. This can help increase the market share and decrease natural resource consumption. DESIGN/METHODOLOGY/APPROACH: We consider a seller who sells new-generation products over two periods: advance selling and regular selling. Based on the rational expectation equilibrium, we adopt dynamic programming to construct a two-period pricing model with three different trade-in strategies-only in period 2, in both periods, and not at all-explaining the trade-in strategy as a promotion tool used by a monopolist to discriminate for advance selling between new and old customers. FINDINGS: The results suggest that the optimal price is determined by the proportion of old customers, discount factor and product innovation level. Whether and when to give a trade-in rebate to old customers depends on these parameters. The seller's choice of optimal trade-in strategy depends on the threshold value of the new customer demand and trade-in demand. ORIGINALITY/VALUE: Most existing literature focuses on advance selling strategies and trade-in strategies. To the best of our knowledge, this is a pioneering study that adopts trade-in as part of the advance selling strategy.


Asunto(s)
Comercio , Recursos Naturales , Costos y Análisis de Costo , Conocimiento
3.
Radiography (Lond) ; 29(1): 227-233, 2023 Jan.
Artículo en Inglés | MEDLINE | ID: mdl-36608376

RESUMEN

INTRODUCTION: Understanding the current ICT-related experience is essential for planning and effectively implementing quality healthcare services. Hence, this study aims to assess the knowledge and utilisation of ICT among radiographers in Sri Lanka. METHODS: A descriptive cross-sectional study was conducted among 590 practicing radiographers in Sri Lanka. Data was collected through a postal survey using a structured self-administered questionnaire. The questionnaire consisted of three sections: socio-demographic characteristics, existing knowledge of ICT, and utilisation of ICT applications and facilities. RESULTS: A total of 416 radiographers returned the questionnaire giving a response rate of 70.5%. Considering the overall ICT knowledge, 24.0% of the respondents possessed good knowledge, while 54.3% and 21.6% reported having fair and poor knowledge, respectively. The knowledge of ICT was significantly associated with gender, age, level of education, duration of service, and previous ICT training experience (p < 0.05). Digital radiography and electronic patient record (EPR) systems were used by 8% and 17.8% of respondents, respectively. Inadequate ICT facilities (56.7%) were identified as the most significant challenge for radiographers to use ICT. CONCLUSIONS: The majority of the respondents in this study had a fair knowledge of ICT, and this knowledge was significantly associated with certain demographic factors. Further, it was found that access to certain ICT applications, such as digital radiography and EPR systems, is limited. Hence, this study highlighted the importance of providing systematic, comprehensive and regular ICT training programmes and improving access to ICT facilities for radiographers. IMPLICATIONS OF PRACTICE: The study provides insight into the significance of improving ICT literacy among radiographers in the field. In addition, the findings may draw policymakers' attention to improving radiographers' access to the latest technologies.


Asunto(s)
Técnicos Medios en Salud , Tecnología de la Información , Conocimiento , Humanos , Estudios Transversales , Tecnología de la Información/estadística & datos numéricos , Radiografía , Sri Lanka , Encuestas y Cuestionarios , Técnicos Medios en Salud/psicología
4.
Rev Paul Pediatr ; 41: e2021372, 2023.
Artículo en Inglés | MEDLINE | ID: mdl-36700566

RESUMEN

OBJECTIVE: This study aimed to create and validate an instrument to measure pediatric residents' knowledge about development and behavior. METHODS: This was a longitudinal study with the consecutive application of questionnaires to validate an instrument of analysis. The modified Delphi technique was used for validation, which involved judges who were selected based on their expertise. Judges, who were renowned for their knowledge of the subject and willing to participate, were chosen from different states of Brazil. A convenience sample was obtained. The original questionnaire included 45 open questions divided into 13 relevant thematic axes on development and behavior. RESULTS: After the third round using the Delphi technique, the whole questionnaire had a validity index of more than 80% on scope and relevance as well as all thematic axes, and the 44 final questions. CONCLUSIONS: The whole questionnaire was considered validated by the 14 expert judges who participated in the study.


Asunto(s)
Conocimiento , Humanos , Niño , Estudios Longitudinales , Encuestas y Cuestionarios , Brasil , Técnica Delfos
5.
J Ethnobiol Ethnomed ; 19(1): 1, 2023 Jan 03.
Artículo en Inglés | MEDLINE | ID: mdl-36597154

RESUMEN

BACKGROUND: Baka hunter-gatherers have a well-developed traditional knowledge of using plants for a variety of purposes including hunting and fishing. However, comprehensive documentation on the use of plants for hunting and fishing in eastern Cameroon is still lacking. METHOD: This study aimed at recording plants used for hunting and fishing practices, using focus group discussion, interviews and field surveys with 165 Baka members (90 men and 75 women) of different age groups in 6 villages. RESULTS: The most frequent techniques used for hunting and fishing are the use of animal traps, fishing lines, dam fishing, hunting with dogs and spear hunting. We recorded a total of 176 plant species used in various hunting practices, the most frequently cited one being Zanthoxylum gilletii (De Wild.) P.G.Waterman, Greenwayodendron suaveolens (Engl. & Diels) Verdc., Microcos coriacea (Mast.) Burret, Calamus deërratus G.Mann & H.Wendl. and Drypetes sp. These plants are used for a variety of purposes, most frequently as hunting luck, psychoactive for improving the dog's scent and capacity for hunting, materials for traps, and remedies for attracting animals and for making the hunter courageous. CONCLUSION: Plants used for hunting purposes here are embedded in a complex ecological and cultural context based on morphological characteristics, plant properties and local beliefs. This study provides a preliminary report and leaves room for further investigations to improve the documentation of the traditional knowledge systems of the studied community.


Asunto(s)
Caza , Conocimiento , Femenino , Camerún , Grupos Focales , Encuestas y Cuestionarios , Humanos , Masculino , Plantas
6.
Cogn Sci ; 47(1): e13231, 2023 Jan.
Artículo en Inglés | MEDLINE | ID: mdl-36655940

RESUMEN

Since Tversky argued that similarity judgments violate the three metric axioms, asymmetrical similarity judgments have been particularly challenging for standard, geometric models of similarity, such as multidimensional scaling. According to Tversky, asymmetrical similarity judgments are driven by differences in salience or extent of knowledge. However, the notion of salience has been difficult to operationalize, especially for perceptual stimuli for which there are no apparent differences in extent of knowledge. To investigate similarity judgments between perceptual stimuli, across three experiments, we collected data where individuals would rate the similarity of a pair of temporally separated color patches. We identified several violations of symmetry in the empirical results, which the conventional multidimensional scaling model cannot readily capture. Pothos et al. proposed a quantum geometric model of similarity to account for Tversky's findings. In the present work, we extended this model to a more general framework that can be fit to similarity judgments. We fitted several variants of quantum and multidimensional scaling models to the behavioral data and concluded in favor of the quantum approach. Without further modifications of the model, the best-fit quantum model additionally predicted violations of the triangle inequality that we observed in the same data. Overall, by offering a different form of geometric representation, the quantum geometric framework of similarity provides a viable alternative to multidimensional scaling for modeling similarity judgments, while still allowing a convenient, spatial illustration of similarity.


Asunto(s)
Juicio , Conocimiento , Humanos
9.
Sensors (Basel) ; 23(2)2023 Jan 06.
Artículo en Inglés | MEDLINE | ID: mdl-36679456

RESUMEN

Sentiment classification is a key task in exploring people's opinions; improved sentiment classification can help individuals make better decisions. Social media users are increasingly using both images and text to express their opinions and share their experiences, instead of only using text in conventional social media. As a result, understanding how to fully utilize them is critical in a variety of activities, including sentiment classification. In this work, we provide a fresh multimodal sentiment classification approach: visual distillation and attention network or VisdaNet. First, this method proposes a knowledge augmentation module, which overcomes the lack of information in short text by integrating the information of image captions and short text; secondly, aimed at the information control problem in the multi-modal fusion process in the product review scene, this paper proposes a knowledge distillation based on the CLIP module to reduce the noise information of the original modalities and improve the quality of the original modal information. Finally, regarding the single-text multi-image fusion problem in the product review scene, this paper proposes visual aspect attention based on the CLIP module, which correctly models the text-image interaction relationship in special scenes and realizes feature-level fusion across modalities. The results of the experiment on the Yelp multimodal dataset reveal that our model outperforms the previous SOTA model. Furthermore, the ablation experiment results demonstrate the efficacy of various tactics in the suggested model.


Asunto(s)
Análisis de Sentimientos , Medios de Comunicación Sociales , Humanos , Conocimiento
10.
Sensors (Basel) ; 23(2)2023 Jan 06.
Artículo en Inglés | MEDLINE | ID: mdl-36679474

RESUMEN

UAVs are widely used for aerial reconnaissance with imaging sensors. For this, a high detection performance (accuracy of object detection) is desired in order to increase mission success. However, different environmental conditions (negatively) affect sensory data acquisition and automated object detection. For this reason, we present an innovative concept that maps the influence of selected environmental conditions on detection performance utilizing sensor performance models. These models are used in sensor-model-based trajectory optimization to generate optimized reference flight trajectories with aligned sensor control for a fixed-wing UAV in order to increase detection performance. These reference trajectories are calculated using nonlinear model predictive control as well as dynamic programming, both in combination with a newly developed sensor performance model, which is described in this work. To the best of our knowledge, this is the first sensor performance model to be used in unmanned aerial reconnaissance that maps the detection performance for a perception chain with a deep learning-based object detector with respect to selected environmental states. The reference trajectory determines the spatial and temporal positioning of the UAV and its imaging sensor with respect to the reconnaissance object on the ground. The trajectory optimization aims to influence sensor data acquisition by adjusting the sensor position, as part of the environmental states, in such a way that the subsequent automated object detection yields enhanced detection performance. Different constraints derived from perceptual, platform-specific, environmental, and mission-relevant requirements are incorporated into the optimization process. We evaluate the capabilities of the sensor performance model and our approach to sensor-model-based trajectory optimization by a series of simulated aerial reconnaissance tasks for ground vehicle detection. Compared to a variety of benchmark trajectories, our approach achieves an increase in detection performance of 4.48% on average for trajectory optimization with nonlinear model predictive control. With dynamic programming, we achieve even higher performance values that are equal to or close to the theoretical maximum detection performance values.


Asunto(s)
Benchmarking , Conocimiento , Registros
11.
Sensors (Basel) ; 23(2)2023 Jan 12.
Artículo en Inglés | MEDLINE | ID: mdl-36679701

RESUMEN

Optical correlators are efficient optical systems that have gained a wide range of applications both in image recognition and encryption, due to their special properties that benefit from the optoelectronic setup instead of an all-electronic one. This paper presents, to the best of our knowledge, the most extensive review of optical correlators to date. The main types are overviewed, together with their most frequent applications in the newest contributions, ranging from security uses in cryptosystems, to medical and space applications, femtosecond pulse detection and various other image recognition proposals. The paper also includes a comparison between various optical correlators developed recently, highlighting their advantages and weaknesses, to gain a better perspective towards finding the best solutions in any specific domain where these devices might prove highly efficient and useful.


Asunto(s)
Electrónica , Dispositivos Ópticos , Frecuencia Cardíaca , Conocimiento , Reconocimiento en Psicología
12.
Sensors (Basel) ; 23(2)2023 Jan 12.
Artículo en Inglés | MEDLINE | ID: mdl-36679708

RESUMEN

Advances in machine learning have widened the range of its applications in many fields. In particular, deep learning has attracted much interest for its ability to provide solutions where the derivation of a rigorous mathematical model of the problem is troublesome. Our interest was drawn to the application of deep learning for channel state information feedback reporting, a crucial problem in frequency division duplexing (FDD) 5G networks, where knowledge of the channel characteristics is fundamental to exploiting the full potential of multiple-input multiple-output (MIMO) systems. We designed a framework adopting a 5G New Radio convolutional neural network, called NR-CsiNet, with the aim of compressing the channel matrix experienced by the user at the receiver side and then reconstructing it at the transmitter side. In contrast to similar solutions, our framework is based on a 5G New Radio fully compliant simulator, thus implementing a channel generator based on the latest 3GPP 3-D channel model. Moreover, realistic 5G scenarios are considered by including multi-receiving antenna schemes and noisy downlink channel estimation. Simulations were carried out to analyze and compare the performance with current feedback reporting schemes, showing promising results for this approach from the point of view of the block error rate and throughput of the 5G data channel.


Asunto(s)
Aprendizaje Profundo , Retroalimentación , Conocimiento , Aprendizaje Automático , Redes Neurales de la Computación
13.
J Health Organ Manag ; ahead-of-print(ahead-of-print)2023 Jan 23.
Artículo en Inglés | MEDLINE | ID: mdl-36659868

RESUMEN

PURPOSE: The authors review the literature on information behavior, an autonomous body of work developed mainly in library studies and compare it with work on knowledge mobilization. The aim is to explore how information behavior can contribute to understanding knowledge mobilization in healthcare management. DESIGN/METHODOLOGY/APPROACH: The authors conducted a narrative review using an exploratory, nonkeyword "double-sided systematic snowball" method. This is especially useful in the situation when the two traditions targeted are broad and relies on distinct vocabulary. FINDINGS: The authors find that the two bodies of work have followed similar trajectories and arrived at similar conclusions, with a linear view supplemented first by a social approach and then by a sensitivity to practice. Lessons from the field of information behavior can be used to avoid duplication of effort, repeating the same errors and reinventing the wheel among knowledge translation scholars. This includes, for example, focusing on sources of information or ignoring the mundane activities in which managers and policymakers are involved. ORIGINALITY/VALUE: The study is the first known attempt to build bridges between the field of information behavior and the study of knowledge mobilization. The study, moreover, foregrounds the need to address knowledge mobilization in context-sensitive and social rather than technical terms, focusing on the mundane work performed by a variety of human and nonhuman agents.


Asunto(s)
Administración de los Servicios de Salud , Humanos , Conocimiento , Práctica Clínica Basada en la Evidencia , Almacenamiento y Recuperación de la Información
14.
Artículo en Inglés | MEDLINE | ID: mdl-36673733

RESUMEN

The COVID-19 pandemic was accompanied by the rapid spread of misinformation through social media platforms. This study attempted to develop an online fake news game based on the inoculation theory, applicable to the pandemic context, and aimed at enhancing misinformation discrimination. It also tested whether perceived threat and persuasion knowledge serve as underlying mechanisms of the effects of the intervention on misinformation discrimination. In Study 1, we used online priming to examine the influence of inoculation on misinformation discrimination. In Study 2, we developed an online fake-news-game-based intervention and attempted to validate its effectiveness through a randomized controlled trial while also exploring the mediating roles of perceived threat and persuasion knowledge. In Study 1, brief inoculation information priming significantly enhanced the ability to recognize misinformation (F(2.502) = 8.321, p < 0.001, ηp2 = 0.032). In Study 2, the five-day game-based intervention significantly enhanced the ability to recognize misinformation (F(2.322) = 3.301, p = 0.038, ηp2 = 0.020). The mediation effect of persuasion knowledge was significant (ß = 0.025, SE = 0.016, 95% CI = [0.034, 0.075]), while that of perceived threat was not significant. Online interventions based on the inoculation theory are effective in enhancing misinformation discrimination, and one of the underlying mechanisms of this effect lies in its promotion of persuasion knowledge.


Asunto(s)
COVID-19 , Intervención basada en la Internet , Medios de Comunicación Sociales , Humanos , Comunicación Persuasiva , Pandemias , Conocimiento , Comunicación
15.
Artículo en Inglés | MEDLINE | ID: mdl-36673842

RESUMEN

To reduce the burden caused by an increased elderly population and to provide efficient service resources, scholars worldwide have proposed and applied smart elderly care. This paper summarizes the hotspots of the existing literature and explores the research frontiers to ignite future research. CiteSpace software was used to conduct a scientometric analysis of high-quality literature collected from both the China National Knowledge Infrastructure (CNKI) and the Web of Science (WOS). Based on the results of the basic situation description, this article highlights six research hotspots in CNKI and 11 research themes in WOS. In addition, it offers three major evolution stages and three future research directions for smart elderly care research. This paper provides a holistic overview of the smart elderly care literature from two major global databases. The results will contribute to healthcare policy designers, practitioners, and developers by giving them comprehensive knowledge and generating strategies to enhance elderly people's quality of life.


Asunto(s)
Conocimiento , Calidad de Vida , Humanos , Anciano , China , Bases de Datos Factuales , Predicción
16.
Artículo en Inglés | MEDLINE | ID: mdl-36673915

RESUMEN

Current knowledge creation and mobilization efforts are concentrated in academic institutions. A community-engaged knowledge hub (CEKH) has the potential for transdisciplinary and cross-sectorial collaboration between knowledge producers, mobilizers, and users to develop more relevant and effective research practices as well as to increase community capacity in terms of knowledge production. Objective: To summarize existing original research articles on knowledge hubs or platforms and to identify the benefits, challenges, and ways to address challenges when developing a CEKH. Methods: This study followed a systematic integrative review design. Following a comprehensive search of academic and grey literature databases, we screened 9030 unique articles using predetermined inclusion criteria and identified 20 studies for the final synthesis. We employed thematic analysis to summarize the results. Results: The focus of the majority of these knowledge mobilization hubs was related to health and wellness. Knowledge hubs have a multitude of benefits for the key stakeholders including academics, communities, service providers, and policymakers, including improving dissemination processes, providing more effective community interventions, ensuring informed care, and creating policy assessment tools. Challenges in creating knowledge hubs are generally consistent for all stakeholders, rather than for individual stakeholders, and typically pertain to funding, resources, and conflicting perspectives. As such, strategies to address challenges are also emphasized and should be executed in unison. Conclusions: This study informs the development of a future CEKH through the identification of the benefits, challenges, and strategies to mitigate challenges when developing knowledge hubs. This study addresses a literature gap regarding the comparisons of knowledge hubs and stakeholder experiences.


Asunto(s)
Conocimiento , Políticas , Universidades , Instituciones Académicas
17.
Artículo en Inglés | MEDLINE | ID: mdl-36673945

RESUMEN

Tourists have been attracted to world heritage sites (WHSs) by their Outstanding Universal Value (OUV). In view of the Stimulus-Organism-Response (S-O-R) framework and the theory of attitude and behavior, by employing 563 tourist samples from Mount Sanqingshan National Park, and using structural equation modeling, we examine tourist behavioral intention for heritage conservation, and the following conclusions were drawn: (1) the S-O-R theory revealed the behavioral intentions of tourists to protect WHSs; (2) as a stimulus, tourists' value perception and destination attachment were positively affected by the OUV attractiveness, and their perceived value had a positive influence on heritage conservation, although the hypothesis of destination attachment to heritage conservation was not supported; (3) heritage-conservation education and knowledge positively influenced tourists' behavioral intentions towards heritage protection, and tourists' heritage protection attitude had a positive influence on their behavioral intention; and (4) a framework of the influence mechanism for tourists' heritage conservation based on the S-O-R theory was proposed, while tourists' cognitive and affective attitudes impacted on heritage protection intention which, in turn, further enhanced the tourists' perception of the OUV. Conclusively, the measures and implications were proposed for improving conservation and management of WHSs, in particular to achieve the sustainable development of the tourist industry and world heritage sites.


Asunto(s)
Actitud , Intención , Desarrollo Sostenible , Conocimiento , Parques Recreativos
18.
Nat Commun ; 14(1): 54, 2023 Jan 04.
Artículo en Inglés | MEDLINE | ID: mdl-36599862

RESUMEN

It has long been a norm that researchers extract knowledge from literature to design materials. However, the avalanche of publications makes the norm challenging to follow. Text mining (TM) is efficient in extracting information from corpora. Still, it cannot discover materials not present in the corpora, hindering its broader applications in exploring novel materials, such as high-entropy alloys (HEAs). Here we introduce a concept of "context similarity" for selecting chemical elements for HEAs, based on TM models that analyze the abstracts of 6.4 million papers. The method captures the similarity of chemical elements in the context used by scientists. It overcomes the limitations of TM and identifies the Cantor and Senkov HEAs. We demonstrate its screening capability for six- and seven-component lightweight HEAs by finding nearly 500 promising alloys out of 2.6 million candidates. The method thus brings an approach to the development of ultrahigh-entropy alloys and multicomponent materials.


Asunto(s)
Aleaciones , Médicos , Humanos , Entropía , Minería de Datos , Conocimiento
19.
Artículo en Inglés | MEDLINE | ID: mdl-36627845

RESUMEN

This study aimed to compare the knowledge and interpretation ability of ChatGPT, a language model of artificial general intelligence, with those of medical students in Korea by administering a parasitology examination to both ChatGPT and medical students. The examination consisted of 79 items and was administered to ChatGPT on January 1, 2023. The examination results were analyzed in terms of ChatGPT's overall performance score, its correct answer rate by the items' knowledge level, and the acceptability of its explanations of the items. ChatGPT's performance was lower than that of the medical students, and ChatGPT's correct answer rate was not related to the items' knowledge level. However, there was a relationship between acceptable explanations and correct answers. In conclusion, ChatGPT's knowledge and interpretation ability for this parasitology examination were not yet comparable to those of medical students in Korea.


Asunto(s)
Estudiantes de Medicina , Humanos , Evaluación Educacional/métodos , Conocimiento , República de Corea , Inteligencia Artificial
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