Context Transfer Research Articles

Wearable Sensors in Other Medical Domains with Application Potential for Orthopedic Trauma Surgery-A Narrative Review.

The use of wearable technology is steadily increasing. In orthopedic trauma surgery, where the musculoskeletal system is directly affected, focus has been directed towards assessing aspects of physical functioning, activity behavior, and mobility/disability. This includes sensors and algorithms to monitor real-world walking speed, daily step counts, ground reaction forces, or range of motion. Several specific reviews have focused on this domain. In other medical fields, wearable sensors and algorithms to monitor digital biometrics have been used with a focus on domain-specific health aspects such as heart rate, sleep, blood oxygen saturation, or fall risk. This review explores the most common clinical and research use cases of wearable sensors in other medical domains and, from it, derives suggestions for the meaningful transfer and application in an orthopedic trauma context.

Rethinking Technology Transfer in a Colonial Milieu: Railways and Shifting Meanings of Travel in Late Colonial India

ABSTRACT The article reappraises nature of technology transfer in a colonial context by underlining how the colonised mediated and shaped what was ostensibly an imposition by the imperial administration. This wider point is illustrated by demonstrating the ways in which in the late nineteenth and early twentieth centuries, different groups of Indians used newly introduced railways to reconceptualise meanings of travel by adding new categories of travel while significantly modifying the extant ones. Crucially deviating from both ‘technology as imperialism’ and ‘technology as subversion’ historiographical paradigms, this article argues for a more nuanced appraisal of technology transfer, especially emphasising the role of users in shaping the impact of technology. Examining a diverse range of sources, viz., railway records (Annual Railway Reports and railway passenger statistics), newspaper reports and travelogues and pamphlets written by Indian railway travellers, the article claims Indians not only mediated the impact of trains on travel in late colonial India; but they shaped the outcome of this technology transfer in ways that reveals agency and remarkable involvement with a new mode of transit. In short, the article demonstrates dynamic interaction between imperial policies and responses of the colonised through the lens of technology transfer.

Entity Extraction for Research and Development Project Knowledge Graph

In the process of constructing a knowledge graph for research and develop (R&D) projects, entity extraction for R&D project abstracts helps to quickly understand project content and promote the application and transformation of research results. This article adopts a scientific entity recognition model based on BERT-IDCNN-CRF (BERT combined with Iterative Dilated Convolutional Neural Network and Conditional Random Field) for the entity extraction task in the construction of knowledge graph for R&D projects. This model uses BERT to extract semantic representations from abstract texts, and then uses IDCNN to deeply capture local and global features in the text. Combined with CRF to learn the context transfer relationship between text labels. Finally it achieved the precision of 69.3%, the recall of 65.8%, and the F1-score of 67.5% in scientific entity recognition. On the basis of this model, this article proposes a knowledge graph construction scheme for R&D projects, and constructs a knowledge graph centered on R&D projects, which includes 12 kinds of entities and 13 kinds of relationships.

Early Neolithic red-painted pottery from the Prandocin site, southern Poland. Indirect transfer in a technological context

The paper presents the results of specialized research on a small collection of artefacts of the Linear Pottery Culture in southern Poland. Among the 27 pottery fragments discovered at the Prandocin Site 1, a few painted fragments were identified. Such kind of painting style directly relates to the Želiezovce group of this culture in western Slovakia. Painted vessels are rarely found in the context of the Linear Pottery Culture in Lesser Poland (Małopolska), which is why special attention was given to raw material and technological studies of the ceramics. The study aimed to answer the question of whether the painted vessel was produced locally or if it representsevidence of direct migration of people, objects, or ideas from the areas of present-day western Slovakia at the turn of the 6th and 5th millennium BC.

Completing the incomplete: bridging human resource management and knowledge transfer in a disruptive context

ABSTRACT The efficiency and service quality of healthcare organisations is driven by effective knowledge transfer among healthcare professionals. Specialised medical units are complex organisations where professionals with different profiles need to work together and coordinate closely in their daily tasks. A deeper understanding of the antecedents of knowledge transfer is likely to shed light on how medical units deliver effective service quality in a disruptive context. In this study, we draw on the ability, motivation and opportunity (AMO) framework and self-determination (SDT) theory. Data was gathered in 2021 through an electronic questionnaire. Structural equation models and bootstrapping method were employed, in a sample of 506 medical specialists (61% men, 39% women), to examine whether AMO HR practices positively impact on knowledge transfer during the COVID-19 pandemic. The results show that strategic leadership only mediates the effect of AMO HR practices on knowledge transfer when it fosters resilience among medical specialists.

GENERATIVE ADVERSARIAL NETWORKS FOR IMAGE SYNTHESIS AND STYLE TRANSFER IN VIDEOS

In computer vision and artistic expression, the synthesis of visually compelling images and the transfer of artistic styles onto videos have gained significant attention. This research addresses the challenges in achieving realistic image synthesis and style transfer in the dynamic context of videos. Existing methods often struggle to maintain temporal coherence and fail to capture intricate details, prompting the need for innovative approaches. The conventional methods for image synthesis and style transfer in videos encounter difficulties in preserving the natural flow of motion and consistency across frames. This research aims to bridge this gap by leveraging the power of Generative Adversarial Networks (GANs) to enhance the quality and temporal coherence of synthesized images in video sequences. While GANs have demonstrated success in image generation, their application to video synthesis and style transfer remains an underexplored domain. The research seeks to address this gap by proposing a novel methodology that optimizes GANs for video-challenges, aiming for realistic, high-quality, and temporally consistent results. Our approach involves the development of a specialized GAN architecture tailored for video synthesis, incorporating temporal-aware modules to ensure smooth transitions between frames. Additionally, a style transfer mechanism is integrated, enabling the transfer of artistic styles onto videos seamlessly. The model is trained on diverse datasets to enhance its generalization capabilities. Experimental results showcase the efficacy of the proposed methodology in generating lifelike images and seamlessly transferring styles across video frames. Comparative analyses demonstrate the superiority of our approach over existing methods, highlighting its ability to address the temporal challenges inherent in video synthesis and style transfer.

ML-Based Teaching Systems: A Conceptual Framework

As the shortage of skilled workers continues to be a pressing issue, exacerbated by demographic change, it is becoming a critical challenge for organizations to preserve the knowledge of retiring experts and pass it on to novices. While this knowledge transfer has traditionally occurred through personal interaction, it lacks scalability and requires significant resources and time. IT-based teaching systems have addressed this scalability issue, but their development is still tedious and time-consuming. In this work, we investigate the potential of machine learning (ML) models to facilitate knowledge transfer in an organizational context, leading to more cost-effective IT-based teaching systems. Through a systematic literature review, we examine key concepts, themes, and dimensions to understand better and design ML-based teaching systems. To do so, we capture and consolidate the capabilities of ML models in IT-based teaching systems, inductively analyze relevant concepts in this context, and determine their interrelationships. We present our findings in the form of a review of the key concepts, themes, and dimensions to understand and inform on ML-based teaching systems. Building on these results, our work contributes to research on computer-supported cooperative work by conceptualizing how ML-based teaching systems can preserve expert knowledge and facilitate its transfer from SMEs to human novices. In this way, we shed light on this emerging subfield of human-computer interaction and serve to build an interdisciplinary research agenda.

Slice-to-slice context transfer and uncertain region calibration network for shadow detection in remote sensing imagery

Although current methods based on deep learning (DL) have been widely employed in shadow detection tasks, the cluttered background and complex shadow features in remote sensing images (RSIs) make shadow detection still a challenging task. In this paper, we apply a neural network combined with a distance transformation algorithm to RSI shadow detection for the first time and propose a novel slice-to-slice context transfer and uncertainty region calibration network (SCUCNet). First, an interslice context semantic transfer (SCT) module is proposed to explore the connections among spatial pixel information and extract sufficient global contextual information via interslice feature transfer. This process helps alleviate the interference of multiscale differences and complex backgrounds on the detection results. Second, to further optimize the initial output mapping, calibrate the uncertainty region, and enhance the feature representation, we propose a plug-and-play uncertainty region awareness and calibration (URAC) module combined with a distance transform algorithm, which introduces only 0.09 M parameters. The quantitative results show that the proposed model outperforms state-of-the-art methods for shadow detection in RSIs, achieving an Intersection over Union (IoU) of 88.33% on the aerial imagery dataset for shadow detection (AISD). In addition, extensive experiments and visualizations further prove the validity and interpretability of our method, and the proposed method can effectively mitigate the interference caused by multiscale differences, morphological diversity, spectral similarity and heterogeneity.

Knowledge Representations: Individual Differences in Novel Problem Solving.

The present study investigates how the quality of knowledge representations contributes to rule transfer in a problem-solving context and how working memory capacity (WMC) might contribute to the subsequent failure or success in transferring the relevant information. Participants were trained on individual figural analogy rules and then asked to rate the subjective similarity of the rules to determine how abstract their rule representations were. This rule representation score, along with other measures (WMC and fluid intelligence measures), was used to predict accuracy on a set of novel figural analogy test items, of which half included only the trained rules, and half were comprised of entirely new rules. The results indicated that the training improved performance on the test items and that WMC largely explained the ability to transfer rules. Although the rule representation scores did not predict accuracy on the trained items, rule representation scores did uniquely explain performance on the figural analogies task, even after accounting for WMC and fluid intelligence. These results indicate that WMC plays a large role in knowledge transfer, even when transferring to a more complex problem-solving context, and that rule representations may be important for novel problem solving.

Supervisors’ Roles in Training Program Culture, Training Intrinsic Motivation and Knowledge Transfer: an Empirical Study

Purpose: This study examines the mediating role of training intrinsic motivation in the relationship between supervisors’ roles in training program culture and knowledge transfer in the Malaysian public sector. Thus, the research question is, “what is the effect of the supervisors’ roles in training program culture, training intrinsic motivation on knowledge transfer in the public sector context?”
 
 Theoretical framework: The framework of the study is adopted from the attributes of (1) leadership, (2) social learning, (3) beliefs and (4) employee performance. This framework aims to provide an understanding of how these variables affect the supervisors’ roles in training program culture, intrinsic motivation and knowledge transfer.
 
 Design/methodology/approach: A cross-sectional study was used to collect 544 survey questionnaires from employees at different divisions/departments in the Malaysian public sector. The SmartPLS is utilized to evaluate the quality of the study’s instrument and subsequently test the study’s hypotheses.
 
 Findings: The structural equation modelling test indicated that knowledge transfer is affected by supervisors’ roles in training program culture. Hence, the effect of supervisors’ roles in the administration of training programs on knowledge transfer is mediated by training intrinsic motivation. This finding will benefit supervisors, managers and operation employees, as well as studies related to training intrinsic motivation in dynamic organizations.
 
 Research: In the theoretical context, this study confirmed that the training’s intrinsic motivation is an effective mediating variable in the relationship between supervisors’ roles in training program culture and knowledge transfer. Meanwhile, in the managerial implication, supervisors should provide direction and assistance to subordinates and practice open communication to help them enhance performance. A communication technique relevant to the work environment will help employees increase knowledge transfer and public sector performance in the future.
 
 Originality/value: This study is to refine the role of supervisors and create a culture of effective training in public sector culture. These findings should be considered by the public sector in the context of training programs.

Understanding TMS and knowledge transfer in the social media mobile App context

PurposeKnowledge transfer which refers to the communication of knowledge from a source so that it is learned and applied by a recipient has long been a challenge for knowledge management. The purpose of this study is to understand influencing factors of transactive memory system (TMS) and knowledge transfer.Design/methodology/approachDrawing on the theories of communication visibility, social distance and flow, this study develops a research model. Then, data are collected from users of the social media mobile App. Partial least squares-structural equation modeling (PLS-SEM) is employed to analyze data.FindingsTMS is a valid second-order construct in the social media mobile app context, which is more reflected by credibility. Meanwhile, communication visibility and social distance each have positive effects on TMS which further has a positive effect on knowledge transfer. Flow has a positive effect on knowledge transfer.Practical implicationsDevelopers of the mobile App should carefully consider the role of information and communication technology (ICT) in supporting TMS and knowledge transfer. They should consider recommendation algorithm so that the benefit of communication visibility can be retained. They should design the feature to classify users based on similarity so as to stimulate users' feeling of close social distance. They should keep on improving features based on users' holistic experience.Originality/valueThis study incorporates the perspectives of communication visibility, social distance and flow to understand TMS and knowledge transfer, presenting a new lens for research.

Corporate Social Responsibility Knowledge Transfer in Interfirm Networks

This study investigates the effects of the alliance network structural properties on corporate social responsibility (CSR) knowledge transfer in the interfirm network context. Alliances and partnerships allow firms to access valuable CSR knowledge. While most research investigating knowledge transfer focuses on the dyadic level, the current research investigates CSR knowledge transfer within the interfirm network context. By integrating data from multiple datasets, this study investigates how a firm centrality and brokerage in its interfirm network influence its acquisition of CSR knowledge. The findings of 298 firms show that firm betweenness centrality and network brokerage enhance CSR knowledge transfer from its alliance partners. To the contrary, the greater the number of alliance partners (i.e., degree centrality), the weaker is the firm's ability to acquire CSR knowledge.

KNOWLEDGE TRANSFER AND ORGANIZATIONAL CAPABILITIES

Today’s Economy is rapidly facing changes in globalization and Knowledge-based products and services. The survival and performance of an organization are influenced by its ability and speed in Developing knowledge-based competencies among the employees (Salina and Fadzilah,2008) According to Goh, SC. (2002), One of the major challenges an organization faces are managing its knowledge assets. Increasingly, knowledge transfer is seen as a basis for competitive advantage. Organizations always face issues with the kind of information, competencies, and expertise that are essential for it to take widespread advantage of available opportunities (Husnain et al., 2021). In addition to these competencies, an organization must possess unique features that competitors find difficult to imitate while operating in the same market and industry (Sousa and Rocha 2019; Sohail et al., 2020). This paper explores, in-depth, the role that key strategic organizational capabilities play in facilitating or preventing knowledge transfer. The paper converses knowledge transfer in an organizational context, then discusses significant organizational capabilities that trigger knowledge transfer and further discuss how these organizational capabilities influence the ability to transfer knowledge, an important area of knowledge management. Each of these key capabilities and their influence on Knowledge transfer is discussed separately and then integrated into a framework to explain how effective knowledge transfer can be managed in an organization with such capabilities. Conclusions are drawn about the complexity of knowledge transfer and the need to take a balanced approach to the process.

Persistent effects of acute trauma on Pavlovian-to-instrumental transfer.

In humans, an acutely traumatic experience can lead to post-traumatic stress disorder (PTSD), which is often characterized by changes in anxiety and motivation months after trauma. There are few demonstrations of the persistent motivational effects of an acute stressor in rodent approaches to PTSD. In two experiments, we evaluated the persistent effects of a battery of footshocks in one context on appetitive Pavlovian conditioning, instrumental learning, and Pavlovian-to-instrumental transfer (PIT) in a different context. In Experiment 1, a battery of footshocks before appetitive training caused deficits in single-outcome PIT (SO-PIT) in male Long Evans rats. The same battery of footshocks after appetitive training, but before testing had little effect on SO-PIT overall, but there were some deficits in within-stimulus expression of SO-PIT. In Experiment 2, the battery of footshocks had no effect on sensory-specific PIT in male or female rats, but two sex differences emerged: males showed more generalized fear from the aversive to the appetitive context compared to females, and females showed less evidence for sensory-specific PIT compared to males. Males showed robust sensory-specific PIT, with clear extinction and spontaneous recovery of the sensory-specific PIT effect across test sessions. These findings show that (a) an acute trauma can have persistent effects on general motivational processes and (b) in sensory-specific PIT, females may show transfer through generalized motivational processes, whereas males may rely on specific features of the cues and outcomes to augment instrumental responding selectively. We discuss implications for current approaches to stress and motivation in preclinical approaches to PTSD.

Increased cognitive load in immersive virtual reality during visuomotor adaptation is associated with decreased long-term retention and context transfer

BackgroundComplex motor tasks in immersive virtual reality using a head-mounted display (HMD-VR) have been shown to increase cognitive load and decrease motor performance compared to conventional computer screens (CS). Separately, visuomotor adaptation in HMD-VR has been shown to recruit more explicit, cognitive strategies, resulting in decreased implicit mechanisms thought to contribute to motor memory formation. However, it is unclear whether visuomotor adaptation in HMD-VR increases cognitive load and whether cognitive load is related to explicit mechanisms and long-term motor memory formation.MethodsWe randomized 36 healthy participants into three equal groups. All groups completed an established visuomotor adaptation task measuring explicit and implicit mechanisms, combined with a dual-task probe measuring cognitive load. Then, all groups returned after 24-h to measure retention of the overall adaptation. One group completed both training and retention tasks in CS (measuring long-term retention in a CS environment), one group completed both training and retention tasks in HMD-VR (measuring long-term retention in an HMD-VR environment), and one group completed the training task in HMD-VR and the retention task in CS (measuring context transfer from an HMD-VR environment). A Generalized Linear Mixed-Effect Model (GLMM) was used to compare cognitive load between CS and HMD-VR during visuomotor adaptation, t-tests were used to compare overall adaptation and explicit and implicit mechanisms between CS and HMD-VR training environments, and ANOVAs were used to compare group differences in long-term retention and context transfer.ResultsCognitive load was found to be greater in HMD-VR than in CS. This increased cognitive load was related to decreased use of explicit, cognitive mechanisms early in adaptation. Moreover, increased cognitive load was also related to decreased long-term motor memory formation. Finally, training in HMD-VR resulted in decreased long-term retention and context transfer.ConclusionsOur findings show that cognitive load increases in HMD-VR and relates to explicit learning and long-term motor memory formation during motor learning. Future studies should examine what factors cause increased cognitive load in HMD-VR motor learning and whether this impacts HMD-VR training and long-term retention in clinical populations.

Vertical handoff technique using context transfer cross-layer P-SIP Scheme for IMS based LTE-WiMAX architecture

Next-generation heterogeneous wireless networks provide flexibility to access IP multimedia services (IMS) anywhere at any time and with always-on connectivity in various networks. IMS service allows to include various networks to provide seamless data services and helps to reduce the delay that occurred during the handoff process. Long-term evolution (LTE) is the fastest emerging mobile communication technology in the current networking field. We proposed an interworking architecture of LTE and Worldwide Interoperability for Microwave Access (WiMAX). The key goal is to provide seamless services in heterogeneous networks. We proposed an algorithm to reduce this IMS delay using Cross-layer and Context Transfer Prior –SIP (P-SIP) scheme using Media Independent Handover (MIH) services. Performance metrics of Integrated LTE- WiMAX architecture in terms of VHO latency, signaling overhead cost, and packet loss are analyzed

Knowledge recontextualization by returnee entrepreneurs: The dynamic learning perspective

Effective knowledge recontextualization is key to successful knowledge transfer in cross-cultural context. This paper explores how returnee entrepreneurs in Vietnam learn to recontextualize their overseas knowledge while establishing new ventures back in their home country. Our dynamic learning process model suggests that (1) in the pre-founding phase, an interactive vicarious learning and intuitive learning mechanism enables returnees to make sense of overseas knowledge; (2) during the founding phase, blended learning mechanism – the balancing act between market response versus market imposing - helps returnees manage the paradoxical cross cultural tension, importantly (3) in the growth phase, the cycling between unlearning and relearning helps them discard, select and recreate new knowledge in the pursuit of sustainable entrepreneurial growth. The study advances the literature on knowledge recontextualization by clarifying key underpinning learning mechanisms essential for ensuring “effectiveness” outcomes. It also contributes to the work on returnee entrepreneurship and entrepreneurial learning by demonstrating how international entrepreneurs learn overtime to thrive in a conflicting cultural context.

Recovering from Financial Implications of Flood Impacts—The Role of Risk Transfer in the West African Context

In many West African river basins, households regularly experience floods and the associated impacts. In the absence of widely accessible formal risk transfer mechanisms (e.g., insurance), households often have to cope with financial impacts. Only a few studies have explored the financial effects of floods on agriculture-dependent households in the region and the role formal and informal risk transfer plays in their mitigation. This study addresses this gap, explores flood impacts with financial implications for households, and researches the existing strategies to mitigate them. Moreover, it aims to better understand how different measures influence the recovery process. The study draws on primary data from a household survey (n = 744) in the Lower Mono River basin, combined with stakeholder workshops and semi-structured interviews, and applies a generalized linear model to the survey data. The results reveal four flood impact types with financial implications: agricultural, material, health, and trade. Moreover, a shortened recovery time is significantly associated with assistance from savings groups and cooperatives—groups originally not formed to help during floods. In light of the severe and frequent flood impacts, effective and publicly accepted adaptation measures are needed to enable favorable conditions for creating sustainable and accessible risk transfer mechanisms.

Two-Stage Octave Residual Network for End-to-End Image Compression

Octave Convolution (OctConv) is a generic convolutional unit that has already achieved good performances in many computer vision tasks. Recent studies also have shown the potential of applying the OctConv in end-to-end image compression. However, considering the characteristic of image compression task, current works of OctConv may limit the performance of the image compression network due to the loss of spatial information caused by the sampling operations of inter-frequency communication. Besides, the correlation between multi-frequency latents produced by OctConv is not utilized in current architectures. In this paper, to address these problems, we propose a novel Two-stage Octave Residual (ToRes) block which strips the sampling operation from OctConv to strengthen the capability of preserving useful information. Moreover, to capture the redundancy between the multi-frequency latents, a context transfer module is designed. The results show that both ToRes block and the incorporation of context transfer module help to improve the Rate-Distortion performance, and the combination of these two strategies makes our model achieve the state-of-the-art performance and outperform the latest compression standard Versatile Video Coding (VVC) in terms of both PSNR and MS-SSIM.

Student ability and difficulties with transfer from a block-based programming language into other programming languages: a case study in Colombia

ABSTRACT Background and context Transfer is a process where students apply their learning to different contexts. This process includes using their knowledge to solve problems with similar complexity, and in new contexts. In the context of programming, transfer also includes being able to understand and use different programming languages. Objective This study explores: (a) student ability to transfer from a block-based programming language into another block-based programming language; (b) student ability to transfer from a block-based programming language to a text-based programming language; (d) student ability to transfer their learning within the same programming language; and (d) the difficulties students had to transfer in these contexts. Method A group of students participating in a program called Coding For Kids explained three different programs in different programming languages during an interview protocol. The students used the programming language MakeCode, and worked on transfer activities in Scratch and Python. Findings The results suggest that while most students are able to transfer between block-based programming languages, most of them struggle to explain a program in a text-based programming language, and to solve a new coding challenge. Implications Instructional designers should consider different strategies to facilitate student transfer into professional programming languages, which is particularly difficult for non-English speakers.