Information Exchange Research Articles

A Fast State-of-Charge (SOC) Balancing and Current Sharing Control Strategy for Distributed Energy Storage Units in a DC Microgrid

In isolated operation, DC microgrids require multiple distributed energy storage units (DESUs) to accommodate the variability of distributed generation (DG). The traditional control strategy has the problem of uneven allocation of load current when the line impedance is not matched. As the state-of-charge (SOC) balancing proceeds, the SOC difference gradually decreases, leading to a gradual decrease in the balancing rate. Thus, an improved SOC droop control strategy is introduced in this paper, which uses a combination of power and exponential functions to improve the virtual impedance responsiveness to SOC changes and introduces an adaptive acceleration factor to improve the slow SOC balancing problem. We construct a sparse communication network to achieve information exchange between DESU neighboring units. A global optimization controller employing the consistency algorithm is designed to mitigate the impact of line impedance mismatch on SOC balancing and current allocation. This approach uses a single controller to restore DC bus voltage, effectively reducing control connections and alleviating the communication burden on the system. Lastly, a simulation model of the DC microgrid is developed using MATLAB/Simulink R2021b. The results confirm that the proposed control strategy achieves rapid SOC balancing and the precise allocation of load currents in various complex operational scenarios.

24 Applying genomic analysis to refine unclassified renal cell carcinoma

Abstract Background Despite the improvements in genomic and pathological techniques to identify renal cell carcinoma (RCC), 2-6% of all patients with RCC cannot be classified into a particular subgroup, thus called “unclassified” RCC (uRCC). Ascertaining the genomic profile of those patients may help select proper treatment and find novel targets. Methods The American Association for Cancer Research (AACR) Project Genomics Evidence Neoplasia Information Exchange (GENIE) database v15.0 was used to select patients with RCC by using the OncoTree codes. All included patients were divided into four groups based on the most frequent subtypes of RCC: clear cell RCC (ccRCC), papillary RCC (pRCC), chromophobe RCC (chRCC), and uRCC. The Cancer Genome Atlas (TCGA) was additionally used to assess corresponding oncogenic signaling pathways. We employed the chi-squared test to compare categorical variables and applied the Benjamini-Hochberg correction to calculate Q-values, thereby controlling the false discovery rate. Results Overall, 1,990 tumor samples from 1,888 patients were evaluated. uRCC was observed in 184 patients (9.7%), whereas most had ccRCC (n=1339, 70.9%), followed by pRCC (n=224, 11.9%) and chRCC (n=141, 7.5%). Age distribution at sample sequencing was comparable between uRCC and other RCC subtypes (P>0.05). The proportion of female patients with uRCC was higher at 38.4%, compared to 26.5% in ccRCC (Q=0.002) and 16.3% in pRCC (Q<0.001), yet was comparable to chRCC at 48.6% (Q=0.210). The prevalence of uRCC was also greater among black patients, accounting for 8.6% vs. 2.1% in ccRCC (Q=0.001). Among patients with uRCC (n=224), the most common genomic alterations (GAs) were detected in NF2 (15.8%), SETD2 (15.8%), TP53 (13.9%), TERT (13.4%), and VHL (11.8%). NF2 alterations were also more prevalent in patients with uRCC than in patients with ccRCC (1.8%, Q<0.001), chRCC (0.7%, Q<0.001), and pRCC (5.8%, Q=0.058). Notably, median overall survival (OS) was poorer in uRCC patients with altered NF2 (n=29) than in those with unaltered NF2 (n=155, 30.7 vs. 87.1 months, p=0.058). Of patients with uRCC, 135 (72.5%) samples were from primary tumors and 39 (20.9%) from metastatic sites, with no difference in GA frequencies between the two. CDKN2A and CDKN2B were the most frequent co-mutated genes in uRCC (Q<0.001), followed by VHL and BAP1 (Q<0.001), and SETD2 and PBRM1 (Q=0.023). GAs in uRCC were primarily observed in pathways related to TP53 (42.8%), cell cycle (33.3%), PI3K (23.5%), and HIPPO (7.7%). Conclusions uRCC exhibited a unique genomic profile distinct from other common RCC subtypes. Notably, NF2 alterations were frequent and correlated with a poorer prognosis.

Digital twin technology training and research in health higher education: a review

Healthcare strives to ensure overall physical, mental, and emotional well-being for individuals while managing limited resources efficiently. Digital technologies can offer cost reduction, improved user experience, and expanded capacity. In addition, modern automation technologies, which were implemented in industrial control systems or industrial automation control systems, are essential for ensuring the availability of societies’ critical cyber-physical systems (CPSs) and the services they provide, such as healthcare. This narrative literature review produces information that can be applied when planning and implementing an interdisciplinary biomedical and health informatics (BMHI) master’s education focused on the challenges of digitalization in the health sector. The review results that virtual human twins (VHTs) are revolutionizing healthcare by addressing people’s complex medical problems with real-time monitoring and precision care while digital twin (DT) technology can make the hospital’s operational processes resilient and efficient. Thus, future BMHI education must address these technologies with a multidisciplinary approach, including computer science, information science, engineering, basic sciences, health sciences, socio-behavioral sciences, and ethical, legal, and policy aspects. Collected and cumulative data is essential for cognitive DTs. A prerequisite for this data is information sharing between different CPSs. Better information sharing and the development of scalable cognitive DTs and VHTs, the provision of critical services, quality, and cost-effectiveness, as well as health, safety, and resilience, will improve. Similarities between peoples’ health information exchange and information needed for ensuring the resilience of CPSs exist. Since humans are in many ways more complex than CPSs, security engineers have a lot to learn from VHTs in maintaining the resilience of CPSs. Cross-sectoral research and cooperation with different disciplines are essential for the progress of both human health and the resilience of CPSs. Along with interdisciplinary research cooperation, educational cooperation should also be intensified.

Data as an enabler for better recycling in a circular economy

Recycling plays a crucial role in the circular economy (CE), as effective recycling ensures that materials enter a sustainable loop. Industry 4.0 (I4.0) has the capability to enhance recycling efficiency and support the development of more comprehensive infrastructure. However, existing value chain (VC) models do not form a closed material and product loop, and there is insufficient information exchange between recyclers and other stakeholders. This paper extends an existing VC model and discusses the information flow required under the background of the CE. It provides a reference model for a value network in a closed material loop, which enhances the traceability of resource use and location. By mapping out the information flow, the model facilitates enhanced communication and coordination among various stakeholders.

Digital Doctor: Patient Rights in the Era of AI Diagnostics

The rapid digitalization of healthcare has brought about new opportunities and challenges for patient empowerment. This comprehensive literature review explores the importance of transparent access to personal health information (PHI) in enabling patients to take control of their health in the digital age. The findings reveal that patients with access to their PHI report greater engagement in their care and improved health outcomes. The development of patient-centered health information exchanges (HIEs) and clinically integrated networks (CINs) can help bridge the gap between patients and their health data. To achieve patient empowerment in the digital age, healthcare organizations must prioritize the development of patient-centric tools and platforms that facilitate transparent access to PHI, while policymakers should consider regulations that mandate patient access to their health data and incentivize the adoption of interoperable electronic health record (EHR) systems.

A shared model-based linguistic space for transmitting our thoughts from brain to brain in natural conversations

Effective communication hinges on a mutual understanding of word meaning in different contexts. We recorded brain activity using electrocorticography during spontaneous, face-to-face conversations in five pairs of epilepsy patients. We developed a model-based coupling framework that aligns brain activity in both speaker and listener to a shared embedding space from a large language model (LLM). The context-sensitive LLM embeddings allow us to track the exchange of linguistic information, word by word, from one brain to another in natural conversations. Linguistic content emerges in the speaker's brain before word articulation and rapidly re-emerges in the listener's brain after word articulation. The contextual embeddings better capture word-by-word neural alignment between speaker and listener than syntactic and articulatory models. Our findings indicate that the contextual embeddings learned by LLMs can serve as an explicit numerical model of the shared, context-rich meaning space humans use to communicate their thoughts to one another.

Interoperability of Oral History Metadata: An Ontological Model

ABSTRACT This article presents the metadata characteristics of oral history collections and the challenges faced when attempting to provide long-term access to audio or video recordings. We propose an ontological model combining the International Committee for Documentation Conceptual Reference Model (CIDOC CRM) from the cultural heritage field with European Broadcasting Union Core (EBUCore) from the European audiovisual community. We form a mapping methodology with the goal of combining the strongest attributes from these two standards. The goal of this research is to generate a conceptual model for the description of oral history interviews in order to reveal the entities participating in the interviews, their semantics, and their relationships. The proposed model enables the meaningful exchange of information of audiovisual collections and their integration with other cultural heritage collections in the online environment.

Computational Argumentation-based Chatbots: A Survey

Chatbots are conversational software applications designed to interact dialectically with users for a plethora of different purposes. Surprisingly, these colloquial agents have only recently been coupled with computational models of arguments (i.e. computational argumentation), whose aim is to formalise, in a machine-readable format, the ordinary exchange of information that characterises human communications. Chatbots may employ argumentation with different degrees and in a variety of manners. The present survey sifts through the literature to review papers concerning this kind of argumentation-based bot, drawing conclusions about the benefits and drawbacks that this approach entails in comparison with standard chatbots, while also envisaging possible future development and integration with the Transformer-based architecture and state-of-the-art Large Language models.

Adoption of smart watches as wearable technology in TESOL education among university students

This research explores the key motivating factors that influence student engagement with wearable technology (WT) in teaching English to speakers of other languages (TESOL) education. The study employs a novel, integrated framework that merges elements from the established technology acceptance model (TAM), Flow Theory, and additional factors pivotal to WT's efficacy, namely content richness and personal innovativeness. TAM and Flow Theory are utilized to identify the variables that drive WT adoption. Data for the research was gathered through an online survey comprising 23 questions, distributed among students in the KSA, with a total of 468 participants. Analysis of the data was conducted using Smart PLS Software to evaluate the research model, constructs, and hypotheses. The findings reveal varying contributions of the model's main constructs to WT acceptance. Specifically, content richness and innovativeness significantly enhance the perceived usefulness of WT. Additionally, perceived ease of use is a strong predictor of perceived usefulness and behavioral intention. The results underscore a growing demand for WT in TESOL Education, highlighting its role in streamlining information exchange among students. The study underscores the significance of certain external factors in technology acceptance, offering a fresh perspective by incorporating a framework that links TAM's perceived usefulness and ease of use with user satisfaction, content richness, and innovativeness. Moreover, the inclusion of Flow Theory adds a unique dimension by assessing engagement and control over WT. The research contributes to understanding the underlying motivations for employing WT in TESOL Education, primarily aimed at enhancing the effectiveness of both instructors and students. A limitation of this study is its focused application of TAM and Flow Theory within a specific educational context, which may not fully capture the complex societal, psychological, and gender-specific factors influencing WT adoption across diverse settings.

TSMD-Net: A two-stage mixed dehazing network with feature fusion and multi-window self attention on Jetson board

Single image dehazing is a pivotal endeavor focused on enhancing the quality of images by removing haze-induced noise. Achieving this goal requires a delicate equilibrium between retaining spatial intricacies and contextual understanding, particularly crucial in real-world scenarios where complexity is amplified. In response to this challenge, we present the Two-Stage Mixed Dehazing Network (TSMD-Net), designed to reconcile these conflicting objectives by leveraging the foundational U-Net architecture. Our approach entails a dual-phase strategy: initially assimilating contextual comprehension through encoder-decoder frameworks, followed by amalgamating it with high-resolution branches to uphold spatial integrity. To streamline the analysis and comparison of this architecture, we opt to substitute or eliminate nonlinear activation functions with multiplication operations, effectively mitigating system complexity. Furthermore, to foster seamless information exchange across hierarchical layers of the encoder-decoder at varying scales, we introduce the Feature Fusion (FF) mechanism, facilitating the integration of insights from higher layers progressively down to the base layer. This amalgamated data significantly enhances the fidelity of the original image transformation by harmonizing the inclusion of contextual feature maps with the preservation of spatial details, resulting in noise-free, high-quality images. Additionally, we propose the “Multi-Window Self Attention” (MWSA) mechanism, characterized by linear time complexity, as the central block of the encoder-decoder. This module mitigates the confined receptive fields inherent in convolutional neural networks (CNNs), enabling the aggregation of more comprehensive feature-map data. Subsequently, our TSMD-Net undergoes rigorous training and testing on both synthetic and real-world datasets, showcasing superior performance compared to current state-of-the-art (SOTA) networks while demanding fewer processing resources. To validate the robustness and practical utility of our methodology, we implement TSMD-Net on a low-end Jetson Nano board, confirming its effectiveness and efficiency in real-world settings.

Integrating telepathology and digital pathology with artificial intelligence: An inevitable future

Telepathology and digital pathology, enhanced with artificial intelligence (AI), represent groundbreaking technology advancements. These entities offer information exchange, enhanced teaching and research, and automated diagnosis with high precision through a computerized approach. Machine learning in pathology shows promise for both human and veterinary medicine, yielding favorable results and in some cases, surpassing the accuracy of human pathologists. This study aimed to highlight the significance of integrated AI with telepathology and digital pathology, outlining both its advantages and limitations while emphasizing the crucial role of pathologists in its implementation. A literature review was conducted to uncover publications and data on telepathology and AI, and their implementation in human and veterinary medicine. This approach has facilitated information exchange, enhancing both teaching and research. In addition, it facilitates the creation of innovative methods and offers more precise patient diagnoses, adhering to ethical and legal standards. This study delivers valuable and comparable data on telepathology, digital pathology, and AI integration. Given the continually emerging nature of these technologies, further studies are essential for their application to human and veterinary medicine. Keywords: artificial intelligence, diagnosis, telepathology.

Self-supervised visual-textual prompt learning for few-shot grading of gastric intestinal metaplasia

Gastric intestinal metaplasia (GIM) is a frequent lesion of the gastrointestinal tract, and its clinical grading can significantly reduce the risk of gastric cancer. Pre-trained vision–language models have demonstrated impressive generalizability in many domains. However, they suffer from the following limitations when applied to GIM grading: 1) Small GIM lesions of endoscopic images and their colour features are difficult to represent with global representations alone, 2) medical concepts are highly specialized, and their dependencies and semantics cannot be precisely represented and 3) Because of the scarcity of medical prior knowledge, multi-modal prompts are over-reliant on random initialization and fail to maintain semantic consistency. To address the above challenges, we propose a self-supervised visual–textual prompt (SVTP) learning strategy for few-shot GIM grading. In particular, image and colour prompts are simultaneously configured in the visual branch to use the colour information in lesion areas. Meanwhile, a coupling function is introduced to implement the exchange of high-dimensional information. Then, to enhance the encoding of complex information and model the dependencies between medical concepts, text prompts and an adapter are integrated into the textual branch. Finally, a three-dimensional contrastive learning (3DCL) strategy is proposed to enrich medical prior knowledge of prompts and maintain their semantic consistency, where three-modal prompts are projected into a unified 3D space for contrastive learning. We verified SVTP on a public endoscopic image dataset and a private GIM grading dataset. Experimental results demonstrate that SVTP has achieved SOTA grading performance on all datasets.

EDUCATIONAL CONSTRUCTION WORKS CARRIED OUT IN EDUCATIONAL INSTITUTIONS IN THE DIRECTION OF THE EFFICIENCY OF THE DEVELOPMENT OF THE MODERN EDUCATION SYSTEM

Today we are already members of the information society. A characteristic feature of the information society is the penetration of information technologies into all areas of human life, intensive development of the information industry and knowledge. This is a new type of society formed as a result of the development of ICT, which is also called the knowledge society. Here, the main condition of human well-being is knowledge, information and their effective application. This society enables the exchange of information across time, space and political boundaries. In this society, important social decisions are made based on science to improve the quality of life in all parameters. The information society enables the interaction of different cultures and the self-affirmation of each society. In addition to capital and labor, knowledge also becomes the main factor of production. Modern network technologies change the structure of the economy and give new meaning to the concepts of time and space. The status of education is getting higher. The task of the education system is to stimulate the development of the economy, to provide specialist training in accordance with the rapidly changing demands of society and the labor market.

Organizing for Information Exchange: Modularity, Relational Contracts, and Virtual Bargaining

Organizing for Information Exchange: Modularity, Relational Contracts, and Virtual Bargaining

The Comparison of Newly Diagnosed Invasive Breast Patient Cohorts in Genomics Evidence Neoplasia Information Exchange Biopharma Collaborative (GENIE-BPC) and Other Real-World Databases.

Oncology databases that integrate genomic and clinical data have become valuable resources for precision medicine. However, the generalizability of these databases has not been comprehensively assessed. To describe the demographics, clinical characteristics, treatments, and overall survival of breast cancer cohorts in GENIE-BPC and three other databases. This study utilized GENIE-BPC, SEER, SEER-Medicare, and Merative MarketScan Research Databases. Women with invasive breast cancer were identified through EHR, cancer registries or ICD-9/10-CM codes. The ages were 18+ years or per database requirement. Treatments were based on EHR or HCPCS/NDC codes in claims. Overall survival was estimated as time from diagnosis to death. Of female breast cancer patients in GENIE-BPC (n = 775), SEER (n = 548 336), SEER-Medicare (n = 68 914), and Marketscan (n = 109 499) databases, the median ages at initial diagnosis were 44, 62, 74, and 57 years, respectively. A greater proportion of patients in GENIE-BPC, compared to SEER/SEER-Medicare, had higher nuclear grades (%III-%IV: 57% vs. 26%/24%), advanced disease stage (%IV: 25.3% vs. 5%/3.6%), percent of triple negative breast cancer (19.7% vs. 10.2%/8.5%), and receipt of chemotherapy (85.0% vs. NA/22.3%). The 1-, 3-, and 5-year overall survival rates were lower in GENIE-BPC (78.5%, 60.5%, 55.5%) than in SEER (95.8%, 89.5%, 85.5%) and SEER-Medicare (91.6%, 81.4%, 75.0%). Breast cancer patients in GENIE-BPC were younger, had more advanced disease, had a higher proportion of triple negative breast cancer and recipients of chemotherapy, and had poorer overall survival. Researchers must use statistical adjustment when extrapolating results (e.g., biomarker prevalence) from GENIE-BPC to the larger breast cancer population.

Abnormal communication internet-connected vehicle platoon dynamical modelling and characteristics study

With the advent of the vehicle interconnection era, all the internet-connected vehicles (i.e. ICVs) can communicate with each other through the whole platoon, and great changes of the dynamical motion characteristics in traffic flow system is happening. The wireless communication system palys more and more important roles to keep traffic flow system stable and safe. However, communication failure is a common phenomenon, and an ICV in a platoon will inevitably lose its connection with other vehicles sometimes. So it is necessary and meaningful to study ICV’s dynamical characteristics under abnormal communication conditions. The study firstly analyzed the information exchange mechanism among ICVs and classify communication failure into three modes. Secondly, by considering normal and abnormal communication conditions, a car-following model for internet-connected vehicle flows with bidirectional mean expected velocity field was proposed. Thirdly, the ICV platoon system stable state condition was deduced based on linear stability theory. Finally, full simulation logical scenarios were set to support the theoretical analysis results considering the ICV system’s stability and communcation states comprehensively. As for the abnormal communication state simulations, the leading vehicle, last vehicle, and middle vehicle communication failure scenarios were selected as typical examples. The study conclusions are (i) for bidirectional communication ICV platoon system, forward-looking and backward-looking mean expected velocity field terms show different influences on its stability, (ii) sudden abnormal communication failures can dramatically destroy the vehicle platoon stability, and (iii) different vehicle position communication failure has different effects on the system stability.

Unified monitoring and online maintenance technology of substation secondary equipment

Abstract To meet the needs of the promotion of “equipment ownership” and the implementation of a centralized monitoring mode in substations, a technical scheme of unified monitoring, online operation, and maintenance for secondary equipment in substations is proposed, considering the monitoring, operation, and maintenance requirements of secondary equipment such as protection devices and automation devices. A secondary equipment monitoring real-time gateway is arranged in Security Zone I. The comprehensive operation status data of various secondary equipment is collected, analyzed, processed, diagnosed, and applied through various apps, to realize heterogeneous access, on-demand deployment, and flexible expansion. The master station is designed with functions such as human-machine interaction and remote analysis for secondary device monitoring and operation. GSP, MQTT, and other service-oriented and message mechanism communication protocols are adopted between the substation and the master station to meet the diversified and easily expandable information exchange requirements. Through the factory test, it is verified that the scheme can realize the panoramic perception of the operation state of the secondary system and effectively improve the ability of abnormality diagnosis and processing.

Longitudinal variability of complexities associated with equatorial electrojet and its coupling with Solar Quiet Daily variation Sq field

The large-scale solar quiet (Sq) current and the Equatorial Electrojet (EEJ) current are two structures produced by electric current in the Earth’s ionosphere. For a long time, the characteristics of these two currents, particularly whether the EEJ is an extended portion of the Sq current has been a hot topic within the community. This study examined magnetic data obtained from ground-based magnetometers at 6 representative stations for the year 2009 and for geomagnetically quiet days (Ap⩽3). The selected stations are along the magnetic equator in the South America (Huancayo), Africa (Ilorin; Addis Ababa), and the Philippines (Langkawi, dip latitude -2.32o; Davao, dip latitude -1.02o; Yap, dip latitude -1.49o). Results showed that both current systems are complex, and this complexity varies significantly from one longitudinal station to another. The strongest and weakest complexity were found in Huancayo and Ilorin, respectively. Afterwards, using four entropy quantifiers (Phase synchronization, Mutual Information, Ensemble Symbolic Coupling Traces, and S-independence), this study examined the relationship between the EEJ and Sq currents. Results revealed clearly a significant information exchange between both currents; that is, the Sq and EEJ currents are indeed coupled. As a step further, using the transfer entropy approach, a directional investigation was carried out to ascertain the direction of information flow between the Sq and EEJ stations. Observations revealed that due to the weak coupling obtained over the African sectors, only the currents over these stations exchanged information. This study further discussed the possible physical mechanisms responsible for the identified variabilities.

Organizing for Information Exchange: Modularity, Relational Contracts, and Virtual Bargaining

Organizing for Information Exchange: Modularity, Relational Contracts, and Virtual Bargaining

Peer Review Statement

All papers published in this volume have been reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing. • Type of peer review: Single Anonymous • Conference submission management system: Morressier • Number of submissions received: 146 • Number of submissions sent for review: 124 • Number of submissions accepted: 77 • Acceptance Rate (Submissions Accepted / Submissions Received × 100): 52.7 • Average number of reviews per paper: 3 • Total number of reviewers involved: 16 • Contact person for queries: Name: Xuexia Ye Email: xx.ye@keoaeic.org Affiliation: AEIC Academic Exchange Information Centre