Digital Intelligence Technology-Driven Transformation and Innovation Research on Choreography Design

e13609 Background: Oncology is renowned for leading innovation in research and in care. However, digital innovation in cancer care and research appears to be limited relative to other therapeutic areas. Methods: A multi-stakeholder roundtable, co-hosted by the Digital Medicine Society (DiMe) and Moffitt Cancer Center, convened experts from 35 leading organizations in life science R&D, regulators, payers, innovators, and with core representation from cancer patients and patient experts. Discussions addressed the current state of digital innovation in cancer care, root causes of digital health innovation challenges in oncology, and identifying action-oriented approaches to collaborative solutions needed to advance the safe, effective, ethical, and equitable use of digital innovations in oncology. Results: There was consensus among roundtable attendees that digital innovation lags behind in oncology relative to other therapeutic areas. Challenges identified as ‘low hanging fruit’ for digital innovation include reducing patient administrative burden, supporting care navigation, optimizing decision making in care and research, optimizing clinical pathways, and improving how we monitor both performance status and safety. Reducing financial toxicity and disparities in disease burden must be imperatives of digital innovation in oncology. Access to care and health outcomes for all patients must also be improved. Impediments to digital innovation in oncology include a proliferation of digital point solutions as opposed to system level innovations; transactional digital solutions that do not promote ongoing engagement and reengagement for the lifetime of the patient journey; lack of trust among patients and clinicians; the absence of data sharing incentives and infrastructure; and business and payer disincentives to digital transformation. Conclusions: Digital innovation frameworks can support more effective and equitable approaches to care that are accessible, scalable, and inclusive, thereby reducing the burden of cancer. To achieve this, clinical, technical, and operational best practices necessary to develop, design, and deploy high-quality digital interventions into cancer care must be established. There is no reason for the successful adoption of digital interventions in oncology to lag behind other therapeutic areas. Intentional action with urgency is required by the multi-stakeholder community through a collaborative effort to realize the full promise of digital innovation for patients and the systems that support those who care for them.

Marine target detection is a crucial technology for developing and utilizing marine resources, and fast and accurate detection of marine organisms is of great research significance for sustainable development and protection of marine resources. In this paper, we first discuss the convolutional neural network and attention mechanisms in deep learning and then present the YOLO series of algorithms for target detection. Then, we take ResNeXt50 as the backbone network, introduce the global attention mechanism and ASFF module to establish the GA-YOLOv5s model for marine life target detection and recognition, and also design the training strategy of the model through migration learning. Simulation experiments are planned to verify the analysis after considering the feasibility of the GA-YOLOv5s model for marine target detection and recognition. The YOLO algorithm, based on multiple improved strategies, improves the mAP@0.5 of marine target detection and recognition by 5.68%. The detection speed of the model after incorporating the GAM module is 48.51FPS; the model using ASFF mAP@0.5 increased by 3.38%; and the average precision and recall of the model for marine target detection and recognition are 82.79% and 80.17%, respectively. Based on the YOLO algorithm, accurate detection and recognition of marine targets can be achieved, which provides reliable technical support for enhancing the exploitation and protection of marine resources.

In recent years, the relationship between digital transformation and innovation became very popular topics, attracting extensive attention, and inspiring a number of documents. Although much literature discusses the intersection of both fields, most works offer neither a complete nor a truly objective overview of the current state of research. Therefore, there is a need for a comprehensive and objective review of research themes to analyze the intersection. For this purpose, based on the literature collected from the Web of Science (WoS) database published between 1994 and 2021, co-word analysis was carried out to explore research themes and identify the most salient themes in digital transformation and innovation research. The results of scientific output show that digital transformation and innovation is attracting increasing academic interest of scholars from many countries and different fields. The distribution of high-frequency keywords shows that the research in this field is multidisciplinary, including not only many economic and management fields, but also many classical theories and research methods. The clustering results of keywords reveal five clusters of themes: diffusion and adoption of technology and innovation, digital innovation management, digital transformation management, digital platform and ecosystem, and digital entrepreneurship and economy. According to the results of strategic diagram and performance analysis, digital innovation management and digital transformation management are the mainstream of research, while digital platform and ecosystem and digital entrepreneurship and economy have strong development potential. This study provides a snapshot of the thematic development of digital transformation and innovation research, enabling researchers to better master the current situation and suggesting the development trend in the future.

数字化创新是指不同主体对数字化资源进行重新组合的活动，以产生新的产品、服务、流程、商业模式。通过对数字化创新领域核心期刊论文进行内容分析，归纳了数字化创新过程和结果两个视角下的概念内涵，厘清了数字化创新的技术和管理两方面的特征，比较了数字化创新与IS创新、IT创新的区别，对数字化创新价值创造的机理归纳了主体、架构、行动三方面的理论解释，并梳理了其价值创造的效率、融合、生成三种方式，结合数字化创新的重要意义，讨论了数字化创新未来研究的方向。本文的研究有助于系统性梳理数字化创新的知识脉络，有助于促进数字化创新的进一步研究。

Both visible and infrared images are important sources of intelligence information on the battlefield, and air‐to‐ground reconnaissance by UAV is an important means to obtain intelligence. However, there are great challenges in ground target detection and tracking, especially in complex battlefield environments. Aiming at the problem of insufficient accuracy of target detection by a single type of sensor in the battlefield environment at this stage, a target detection method by fusion of visible and infrared images is proposed in this paper, which is called ReconnaissanceFusion‐YOLO (RF‐YOLO), and with the help of infrared imagery, it can effectively improve the accuracy of target detection in the case of insufficient light. The performance of target detection in the battlefield is significantly improved by introducing two key innovative modules: dual feature fusion (DFF) module and feature fusion corrector (FFC) module. The DFF module enhances multi‐channel feature fusion through a novel concatenation and channel‐wise attention mechanism, while the FFC module performs feature correction between parallel streams using spatial and channel‐wise weights, addressing noise and uncertainty in different modalities. These modules are integrated on top of a dual‐stream YOLO architecture, allowing for effective fusion of visible and infrared information. RF‐YOLO was trained and evaluated using the FLIR data set, containing 5142 pairs of strictly aligned visible and infrared images. Results demonstrate that RF‐YOLO significantly outperforms benchmark networks in terms of robustness requirements. Specifically, the large model of RF‐YOLO achieves an mAP of 0.831, which is a significant improvement compared to the YOLOv5l inf benchmark's 0.739. This represents an improvement of over 12% in detection accuracy. Additionally, RF‐YOLO offers a Nano version that balances accuracy and speed. The Nano version achieves an mAP of 0.765, while maintaining a model size of only 11.5 MB, making it suitable for deployment on UAV edge computing devices with limited resources. To validate the practical applicability of our approach, this paper successfully implements target detection and tracking on a real UAV's edge computing device using the ROS system and SiameseRPN, combined with the proposed RF‐YOLO. Real‐world flight tests were conducted on an internal playground, demonstrating the effectiveness of our method in actual UAV applications. The system achieved a processing rate of approximately 10 fps at 640 × 640 resolution on an NVIDIA TX2 edge computing device, showcasing its real‐time performance capability in practical scenarios. This study contributes to enhancing UAV‐based battlefield reconnaissance capabilities by improving the accuracy and robustness of target detection and tracking in complex environments. The proposed RF‐YOLO method, along with its successful implementation on a real UAV platform, provides a promising solution for advanced military intelligence gathering and decision‐making support.

YOLO algorithm has high real-time monitoring speed and average accuracy, and also has great advantages for target detection in complex Marine environment. The research of the algorithm must be applied to the equipment eventually, but in most cases, the storage capacity of the equipment is limited, and at the same time, it needs to meet the requirements of high-precision detection. Therefore, this paper proposes an improved Marine biometrics algorithm for YOLOv5 network, which uses GhostNet's idea and introduces GhostBottleneck into YOLOv5. It can be used as a plug and play module to upgrade the existing convolutional neural network. It can reduce the computation of the network and ensure the precision of the network. On this basis, CBAM module is introduced, which combines spatial attention mechanism and channel attention mechanism, and uses multiscale maximum pooling layer to increase the range of receptive field, which can significantly improve the accuracy of image classification and target detection. The experimental results show that compared with the original YOLOv5, the improved model occupies much less storage space and has a greater improvement in the identification accuracy of Marine organisms.

Abstract. With the increase of remote sensing image acquisition methods and the number of remote sensing image data, the traditional manual annotation and recognition methods can no longer meet the needs of the present production life. This study explores the use of deep learning techniques to improve the efficiency and accuracy of target detection in remote sensing satellite images, especially for small targets. Traditional target detection methods often face challenges in recognition accuracy and processing speed due to the specificity and complexity of satellite images, such as large size, variable lighting conditions and complex background. Therefore, this paper adopts the YOLOv5 model and introduces the CBAM (Convolutional Block Attention Module) attention mechanism, which significantly improves the detection of small and dense targets. Experimental validation, using the improved YOLOv5 model on the VisDrone2021 dataset, demonstrates that the model improves the mean average percision (mAP) by 1.9% while maintaining realtime performance. This paper provides new ideas for remote sensing image processing, especially for applications in the fields of urban planning and automatic driving, etc. Despite the progress made in this study, the detection of small targets in remote sensing images, the limited classification accuracy and the detection of dynamic targets still need further research.

The study on the elements of music stage space in musicals has in particular significant implications as comprehensive theatrical art combined with various fields including music. This paper classified special characteristics between stage design in terms of visual, spat ial and objet’s points by the scenes of remarkable numbers of 『Notre Dame de Paris』 and analyzed how the stage design and music has heightened the effect interactively. In additio n to this, it has been investigated how the music and space expression described and charact erized effectively in harmony. Consequentially, the stage of 『Notre Dame de Paris』 is sym bolized with the simplicity of designs without emptiness using visual and spatial elements and objet appropriately. From the musical point of view, the numbers of 『Notre Dame de Pari s』 played a role in giving a plot and depicting character’s conflict including symbolic son gs. In stage design, there are dramatic changes of stage with configurations of huge objet and structural symbol so that the different background and situation has meaningful polysem ous functions in space and time. These kind of designs of stage in 『Notre Dame de Paris』 are contemporary approach to express restrained symbolism in space of theater. The music with lyric melodies and dynamic rhythms in 『Notre Dame de Paris』 also convey the literary narrative of the spectacle French musical.

Economic and social prosperity heavily relies on well‐maintained highways. However, road maintenance faces challenges due to limited funding and resources, with potholes posing significant safety risks. This work introduces a pothole detector designed to detect and estimate pothole areas for timely maintenance. It enhances detection by modifying the YOLO algorithm, using the Xception backbone, and integrating attention mechanisms to improve the prediction of small or clustered objects. Xception’s depthwise separable convolutions enhance feature extraction, outperforming the standard YOLO algorithm in detecting small, irregular potholes and preventing overfitting. The improved YOLO model, along with spatial and channel attention mechanisms, focuses on relevant regions and refines important features specific to pothole areas. Accurate area estimation is achieved through computer vision and traditional segmentation processes. A custom dataset, including the MakeML pothole dataset, a Kaggle dataset, and real‐time footage of Kerala roadways, is used for training and validation. Performance evaluation with mean average precision (mAP) and average precision (AP) metrics shows the pothole detector’s superiority, effectively identifying potholes under various conditions and ensuring safe road infrastructure.

The innovation of digital technology to expedite the establishment of sustainable productivity that aligns with the “double carbon” objective is a crucial approach to balancing environmental considerations with development, hence fostering the high-quality advancement of organizations. This paper analyzes panel data from listed companies in China between 2010 and 2023 to assess the level of digital technology innovation through digital technology patents and investigates the effect of this innovation on the carbon emissions of enterprises within the industrial chain. The findings indicate that: Digital technology innovation (EDIG) in focused firms exhibits asymmetric effects, enhancing upstream firms’ UPCE while diminishing downstream firms’ DOCE; EDIG facilitates UPCE by expediting information dissemination and reinforcing organizational interdependence, while concurrently suppressing DOCE through the enhancement of supply chain resilience and product competitiveness. Various categories of environmental laws exert distinct regulatory impacts on the correlation between EDIG and UPCE (DOCE). The extent of carbon reduction resulting from enterprises’ digital technology innovation varies due to the supply chain relationships between the two enterprises and the differing conditions of the focused enterprises, with the influence of various types of technological innovation on the carbon emissions of upstream and downstream enterprises being notably robust. Consequently, it is imperative to enhance the research, development, and implementation of digital technology innovation, comprehend the carbon reduction pathway mechanisms associated with enterprise digital technology innovation, and offer sustainable development insights to other developing nations as enterprises adopt measures to facilitate carbon peak and carbon neutrality through digital technology innovation.

Recombination in digital innovation: Challenges, opportunities, and the importance of a theoretical framework

Digital innovation is rapidly reshaping society, affecting fundamental aspects of our everyday activities and lives. This development is accompanied with benefits as well as social dilemmas. In this paper we approach this class of challenges in IS digital innovation research. We investigate how social challenges are attended in research agendas, and reflect upon social challenges emerging from a digital service innovation project. Based on the empirical case, we present a scenario that illustrates how social challenges can unfold in digital service innovation. The case exemplifies three conflicts of interest that are used to discuss implications for the research agendas for digital innovation. We propose that explicit attention is paid to social and ethical challenges, taking a large scale and interdisciplinary approach on social and ethical challenges in digital ecosystems.KeywordsDigital innovationresearch agendassocial and ethical challengessocial dilemmas

Digital transformation in HRM of the modern business service sector in Finland and Poland

Aim/Purpose Although the latest review on digital innovation was made in 2018 (included articles up to 2017), the purpose of this study is to explore and examine opportunities for research in digital innovation and transformation for both researchers (including graduate students) and practitioners. A conceptual model is proposed. Background Digital innovation is omnipresent today, as it has penetrated deep into the structure and psyche of individuals, communities, organizations, institutions and governments. We find ourselves in a quagmire of opportunities risks and uncertainties, where ubiquitous technological interconnectedness form a new paradigm enabling industry to innovate and grow. All humanity is faced with these disruptive digital pressures. Yet, relatively there is little research done. Unfortunately, a coordinated effort for such a seriously important phenome-non does not exist. Methodology A structured literature review approach was conducted, the results of which were used for a qualitative approach, using nVivo, to extract insights and understanding. Findings This study identifies the extent of research done in the different areas of digital innovation and transformation and puts the results into perspective. Scholarly research is scarce, dispersed and diverse, lacking any direction or cohesion. Research on transformation is more than innovation and in both cases those that study their relationships with human or society are a handful. A conceptual model is proposed by integrating knowledge gained from the literature, the integral theory and the concept of impact assessment. Impact on Society This study shows that the integration of human agency digital innovation research and practice is primary. Researchers and practitioners can use the conceptual model to help them expand and extend their work.

Aim/Purpose This article presents the results of reviewing journal outlets where research in digital innovation and transformation are published. Our aim is to make the case for a much-needed journal dedicated research and practice in the digital innovation / transformation and human / humanity sphere. Background Digital innovation has become part of our daily lives whether we are aware of it or not. Over 4 billion people are using blockchain, IoT, cloud computing, mobile technologies, social media and artificial intelligence, yet very little is understood of their effects on humans. Research in this area is relatively scarce and dispersed across diverse types of journals. The few articles published in the area of digital innovation and humanity provide just a hint on the importance of the subject matter. Ultimately, we need to understand what technology is for humans. Is the digitalization phenomenon a utopia or a dystopia? What we really need is a truly human-centered transformation of digital innovation. Methodology The Publish and Perish literature search desktop application and Google search engine were used to identify journals that have published in the area of digital innovation with a focus on humanity. SCIMAGO was used to understand the subject area clusters of these journals. Findings There is relatively little research in the digital innovation and humanity arena. Articles are scarce and dispersed over a diversified range of journal subject areas. Only two journals are concentrated on publishing research in the area of digital innovation. No journals were found in humanity and digital innovation. Impact on Society In this article, we stress the need for a journal in digital innovation and humanity as an outlet for the work of researchers, practitioners, and educators. The article inaugurates the first paper for the journal. The journal will act as an outlet for researchers, practitioners, and educators and provide a forum for knowledge sharing and collaboration with the ultimate goal of improving human quality of life.