Reviewerly/exHarmony huggingface dataset:
ChatVQG: A VQG Dataset Containing Diversified Conversational Questions and Guiding Information for Proactive Chatting with the Elderly

With the increasing global aging problem, the application of NLP technology to elderly care services has become a crucial field of research. Currently, care chatbots utilized in hospitals, nursing homes, and other institutions can only passively provide services when elderly individuals express their needs actively. We propose that by combining VQG technology with care chatbots, they can provide proactive chat services to the elderly. However, existing VQG datasets are not designed for chat scenarios specific t o c hatting-with-elderly. To address t his, we developed a VQG dataset called ChatVQG. It includes multiple diverse questions for each picture, along with two guiding labels per question: question topic and question object, which assist in instructing the generation model. We proposed a prompt-based text-to-text method of guided question generation and a self-guided pipeline to implement proactive questioning. We used BLIP-2 as the baseline model and fine-tuned iton ChatVQG. The experimental results demonstrate the effectiveness of our proposed method and pipeline.
Prediction of CO2 Emissions Related to Energy Consumption for Rural Governance

In the context of rural revitalization, many industries have begun to shift towards rural areas. Industrial agglomeration not only brings economic growth to rural areas, but also increases local carbon emissions. This is particularly evident in some industrialized rural areas with high energy consumption. To accurately implement rural environmental governance, this study selected population, energy consumption, coal proportion, urbanization rate, and other factors as the influencing factors of carbon emissions. The grey correlation analysis method was used to obtain the correlation coefficient of the influencing factors. Then, the relationship between carbon emissions and economic growth, energy consumption, and other influencing factors was analyzed from multiple perspectives. In addition, this study constructed an energy consumption carbon emission prediction model based on deep learning networks, aiming to provide reference data for rural greenhouse gas emission reduction. These results confirmed that the correlation coefficients of the influencing factors of carbon emissions were all higher than 0.6, indicating that their carbon emissions were highly correlated. These test results on the dataset confirm that the RMSE values of the proposed model are all around 0.89, indicating its good prediction accuracy. Therefore, the proposed carbon emission prediction model can provide scientific and reasonable reference data for rural air governance.
Research on the Path of Improving Foreign Language Proficiency in Language Service Industry

With the rapid development of the global economy, foreign language proficiency has become increasingly important for individuals or businesses. As an important way to improve foreign language proficiency, the language service industry provides learners with various learning methods and platform resources. This article aims to explore the key role of the language service industry in improving foreign language proficiency, with a focus on learning methods such as language learning courses, language communication projects, online learning platforms, language exams, and practical applications. By conducting research on the learning paths of learners in improving their foreign language proficiency, the paper collected and analyzed data to evaluate the effectiveness of different learning path resources. Finally, by exploring various learning methods, the paper hope to help learners better utilize the platform resources provided by the language service industry and effectively improve their foreign language abilities.
Networking capabilities, entrepreneurial competencies, and performance of small and medium enterprises in Kenya

The general purpose of the study was to examine effect of networking capabilities (NC), entrepreneurial competencies (EC) on the performance of Small and Medium Enterprises (SMEs) in selected towns of the North Rift Region -Kenya. The study was anchored by the theoretical approach of Resource Based View. The study employed positivism research philosophy and explanatory research design and using a stratified random sampling technique. Sample size of 323 drawn from a population of 4596 Small and Medium Enterprises registered with the Uasin Gishu, Tranzoia and Nandi Counties was collected using self-administered questionnaires. Hayes Model 4 process Macro was used to analyse data and test the hypothesis. The study found that; networking capabilities significantly affects firm performance. In addition, entrepreneurial competencies mediate the relationship between networking capabilities and firm performance. The study established that firms with effective networking capabilities are more likely to achieve improved performance outcomes. This indirect relationship between networking capabilities and firm performance through entrepreneurial competencies highlights the importance of fostering and enhancing entrepreneurial competencies within the business context. The study contributes to knowledge by revealing a complimentary mediation and that entrepreneurial competencies mediates the relationship between networking capabilities and firm performance.
AI learns racial information from the values of vital signs

Abstract Background Bias in medical practice is multifaceted, including treatment variations across race-ethnicity, unconscious bias in healthcare providers’ attitudes, and bias in clinical scores. However, far less is known about the potential racial bias in routinely collected, essential information in clinical decision-making, namely vital signs. Research question Do vital signs embed racial information that can be learned by AI algorithms? Study Design and Methods Retrospective cohort study of critically ill patients between 2014 and 2015 from the multi-centre eICU-CRD critical care database involving 335 Intensive Care Units (ICU) based in 208 US hospitals, containing 200,859 patient admissions. We extracted 10,763 critical care admissions of patients aged 18 and over, alive during the first 24 hours after admission to ICU with recorded self-reported race as well as at least two measurement of heart rate, oxygen saturation, respiratory rate, and blood pressure. Pairs of racial subgroups were matched based on age, gender, admission diagnosis and APACHE IV scores. Traditional machine learning algorithms, including XGBoost and Logistic regression were used to predict self-reported race using values of vital signs as an input. Results AI models derived from only six vital signs can predict patients’ self-reported race with an AUC of 0.74 (± 0.022) between White and Black patients. Technologies used to measure oxygen saturation are a significant source of self-reported racial information (AUC of 0.72 ± 0.028), in addition to blood pressure measurements (AUC of 0.63 ± 0.035). Care delivery practices do not present a significant source of racial information (AUC of 0.57 ± 0.019). However, even when controlling for these known factors, self-reported race can still be learned from vital signs, whose origin we cannot currently explain. Interpretation Vital signs embed racial information that can be learned by AI algorithms, posing a significant risk to equitable clinical decision-making. Mitigating measures might be challenging, considering fundamental role of vital signs.
INTERACTIVE APPROACHES IN THE ELT CLASSROOM: A CONCEPTUAL STUDY IN THE EDUCATIONAL INSTITUTES OF BANGLADESH

In an effort to foster a positive learning environment in traditional English Language Teaching (ELT) classrooms, language experts advocate for the implementation of an interactive approach to enhance the effectiveness of education for learners. The interactive classroom encompasses various elements, including active participation in the learning process, active engagement in the exchange of ideas, and active involvement in communication with teachers. From the perspective of authority, learners are motivated to express their views, practises, and patterns of behaviour. Linguistic challenges are encountered by learners, necessitating their engagement in discussions with peers and educators in order to surmount these intricacies. The process of interaction fosters the development of innovative learning, since learners are able to effectively address psychological hurdles by engaging with others. The objective of this study is to examine the application of an interactive method in the English Language Teaching (ELT) classroom and to analyse the prevailing scenario of interactive education in Bangladeshi educational institutions.
Si-VirPraJa: Using an Immersive Technology to Learn Prehistoric Sites in Indonesia

Nowadays, studying prehistoric sites in Indonesia has become convenient because of the touch of technology. We no longer need to spend money, time, and energy to visiting the sites in person. Virtual Reality (VR) is the commonly used immersive technology for virtualizing prehistoric sites. Cutting-edge research is utilizing Virtual Reality (VR) technology to construct virtual environments of prehistoric sites, allowing people to learn and enjoy them with flexibility. However, in the context of learning, its use is still quite limited due to general features. Therefore, it is necessary to develop applications with more complete and interactive learning features. The aim of this study is to develop a web-based Si-VirPraJa (Prehistoric Virtual Site) application. We employed research and development (R&amp;D) to achieve the objectives of the research. Furthermore, we used the ADDIE development model, which includes analysis, design, development, implementation, and evaluation. We initiated the research by conducting a needs analysis study of the Si-VirPraJa App as expected by students and teachers. The needs analysis results formed the foundation for designing the application’s initial stage. Learning media experts tested it and provided assessments, suggestions, and comments. The Si-VirPraJa app, refined based on assessment results, suggestions, and comments from media experts, is implemented in a trial class to gather feedback from students and teachers. The findings suggested that students need a virtual tour-based application to study prehistoric sites in Indonesia. This necessary application must also include multiple features that facilitate learning. The findings from validation tests conducted by experts and trials class that the Si-VirPraJa application is viable for use as a learning media. The impact of using this application for learning is evident in students’ enhanced self-learning ability, improved comprehension of the material, and the generation of engaging and meaningful learning experiences.
Identifying Sources of Error in Underwater Photogrammetry via Sensitivity Analysis

In aiming for sub-millimeter 3D measurement accuracy for underwater objects such as shellfish in multi-view imagery, we investigate the effect of errors in camera extrinsic and intrinsic parameters, pixel feature matching, and optical system properties. Multi-view pixel ray intersection (triangulation) is used to calculate 3D object feature positions and by extension object dimensionality. By perturbing dependant variables we conduct a numerical sensitivity analysis for the error in dimensional measurement, and discover in order to achieve a measurement accuracy of less than 1mm, the pixel features must be localised to within 5 pixels, and error in camera translation and rotation must be no greater than 5mm and 0.5 degrees respectively. We also investigate environmental and systematic sources of error such as refraction through a thermocline, and find only minimal effects on the measurement error.
Secure Key Exchange Scheme and Blockchain-oriented Data Protection in the Internet of Vehicles

Today, vehicles are becoming part of the Internet of Things, providing information to people on the move. This has led to the evolution of vehicular networks into the Internet of Vehicles (IoV), ensuring smooth and secure sharing of information among vehicles, people, and infrastructure. Vehicles function within exposed environments and public channels, which leaves them open to a range of threats and potential attacks. Therefore, this paper presents an authentication and key exchange scheme for vital entities in IoV as Vehicles, Roadside Units, and cloud servers. Additionally, the scheme employs blockchain technology to enhance IoV data security while maintaining decentralization. The Security analysis and performance assessment illustrate our protocol’s resilience against known attacks, while also minimizing costs compared to relevant approaches.
HTTP Header Reordering-based Covert Channel Protocol

Although the field of covert channels has received a lot of attention, there are still a few flaws in the current covert systems available in the literature. First, we discovered that some existing covert channel protocols are detectable. Second, the most related works proposed covert channel protocols that have low throughput or simply do not publish information about their throughput performance. Third, some systems do not use error correction and are thus susceptible to disruption. Considering the above major shortcomings into account, this study aims to create a covert channel with improved throughput without sacrificing security. This paper presents a new covert channel protocol that utilizes the fact that the order of HTTP headers can be changed without affecting its normal operation. The protocol was implemented using current development environments and tested under different scenarios. Performance evaluations showed that the proposed covert channel protocol was successful in obtaining a sufficient throughput improvement over existing protocols while maintaining security.
INTEGRATING 3D PRINTING IN PRE-SCHOOL EDUCATION: PERCEPTIONS FROM PRE-SCHOOL TEACHERS AND PROSPECTIVE TEACHERS

With the rapid advancements in technology, various educational technologies have been employed to facilitate the teaching process in the education system. One of the popular technologies is 3D printing, which finds applications from early childhood education to higher levels of instruction. This study aims to determine the perspectives of pre-school teachers and prospective teachers regarding the use of 3D printing technology in early childhood education. The study group consisted of 15 pre-school teachers and 17 prospective teachers. The research method employed was the case study approach. An online survey form with appropriate open-ended questions was utilized as the data collection tool. Data obtained from the study were analyzed through content analysis. The results revealed that pre-school teachers and prospective teachers have a superficial knowledge of 3D printing technology. Although the materials required for teaching varied based on the needs of children and teachers, certain common skills were emphasized in the instructional process. Some difficulties were encountered in acquiring these materials, which could be overcome by utilizing 3D printing technology. Furthermore, teachers and prospective teachers showed preferences for different features in the design of materials. In future studies, it is recommended to identify materials that captivate children's interests based on the perspectives of teachers and candidates. Providing necessary academic support to participants for material production and conducting similar studies in various disciplines are also suggested.
Students Perception on Lecture’s Implementation of Learning Teaching Midwifery

Implementation of learning teaching with test results of askeb I in DIII midwifery. The study design used in this research WA’s analytic survey with cross sectional approach. The population in this study were all second level students of fourth semester at the Academy of Obstetrics totaling 40 students, with a sampling technique using the total population is the entire population sampled as many as 40 students at the Academy of Midwifery. From the research results with a confidence level of 95% with the title student’s perception on lecture’s implementation of learning teaching with test results of askeb I obtained from 40 respondents there were 16 students who assumes the implementation of good learning as many as 16 respondents (40.0%), assumes the implementation of learning that is enough as many as 13 respondents (32.5%) and less assuming implementation of learning as much as 11 respondents (27.5%) with a statistical test of chi-square p value = 0.012 &lt;? = 0.05 means there is relationship of students perception on lecture’s implementation of learning teaching with test results of askeb I in DIII midwifery. In this study, researchers concluded that there is relationship of student’s perception on lecture’s implementation of learning teaching with test results of askeb I in DIII midwifery. Advice from researchers to the respondents in order to further improve the quality of learning that is better for the future.
Optimization and Development of Intelligent Management in Education in Teaching Management of Universities

In response to the current problems of outdated management concepts, lack of personalized teaching, unreasonable evaluation systems, and outdated curriculum settings in university teaching management, this article would use educational intelligent management systems to study the optimization and development of university teaching management. By constructing an intelligent management system for education, this article describes the use of student registration management, course scheduling management, and teaching management functions. This article applies it to the teaching management of universities to better carry out intelligent teaching, exam management, and course management, promote the upgrading of school management concepts, and provide a more reasonable evaluation system. This article conducted a survey on students from School A and found that they rated the application of educational intelligent management systems in university teaching management at 9.29 points or above (out of 10 points), and the average score of the 20 students selected after use was 9.535 points. This article applies intelligent management of education to teaching management, which can raise teaching management's bar and increase its efficacy over time. It can also help develop exceptional talent and raise educational standards.
COMPLEX GOLD-ANTIMONY MINERALIZATION IN THE PROCESS OF MINERAGENIC EVOLUTION OF TERRANE STRUCTURES IN ASIA

The main results of studies of the basic mineralogical aspects of the formation, localization, and material composition of complex Au-Sb mineralization are summarized and structured. The results of studying the mineragenic evolution of Au-Sb objects in a number of terrane structures in Asia are recommended for prediction and evaluation.
BPDAC: A Blockchain Based and Provenance Enabled Dynamic Access Control Scheme

Access control is widely used technology for securing sensitive resources of information systems, such as personal data managed by cloud-based data store and sensitive data stream collected by smart devices. Existing access control systems mainly adopt centralized architecture and static access control models, including Access Control List, Role-based Access Control and Attribute-based Access Control. However, these systems fail to meet the increasing requirements of behavior based dynamic access control or requirements of owner initiated autonomous access control without relying on trustworthy third parties and suffer inherent drawbacks of single point of failure or dishonesty. To this end, a novel blockchain-based and provenance enabled dynamic access control scheme called BPDAC is proposed. Specifically, it collects and stores data provenance on blockchain to enable behavior-based dynamic access control; in particular, the quick lookup table structure is designed to speed up access control evaluation based on provenance with increasing complexity. It also provides specifications for formulating access control policies based on provenance. It utilizes a set of smart contracts on blockchain to enable decentralized and reliable autonomous access control. A prototype system is implemented on the Hyperledger Fabric and experiments are conducted to show that the proposed scheme is practically feasible and scalable in terms of the performance metrics of throughput and latency.
The Generalized Similarity Measures Based on Complex Interval-valued Hesitant Fuzzy Sets and Their Applications in Pattern Recognition and Medical Diagnosis

In this study, we investigate a novel conception called complex interval-valued hesitant fuzzy set (CIvHFS) as the modification of some prevailing conceptions such as interval-valued complex fuzzy set (IvCFS) and interval-valued hesitant fuzzy set (IvHFS), to tickle the data or information which have intricate and haziness in the genuine life dilemmas. The CIvHFS carries the membership grade in the model of a finite subset of numerous interval values which contains in the unit disc of a complex plane. We also propound the operational laws of the investigated conception. Further, we establish certain vector similarity measures (VSMs) and weighted VSMs (WVSMs) in the setting of CIvHFS, including the Jaccard similarity measure (JSM), Dice similarity measure (DSM), and Cosine SM (CSM), et al. Along with this, we also investigate hybrid VSM and weighted hybrid VSM relying on the CIvHFS. Moreover, we present some CIvHFS generalized exponential and non-exponential based SMs. To portray the usefulness and advantages of the developed SMs in genuine life, we employ these SMs to solve pattern recognition and medical diagnosis. Finally, to assess the dependability and rationality of the developed SMs, we compare the investigated SMs with certain prevailing SMs.
Comparative Analysis of Deadlock Detection Algorithm based on Blockchain

The aim of the study is to compare the deadlock detection algorithms in distributed systems with respective Blockchain technology presented in this paper. Today, detecting deadlocks in distributed systems is a very important challenge. Without the proper deadlock detection mechanism, the system can get stuck in a reject state. The goal of this work is to figure out which algorithm is more suitable for deadlock detection in Blockchain technology based on these factors i-e Security, Time, Performance, Communication, and Correctness. Under the positivism paradigm. The descriptive research design and distributed technique are used to minimize the occurrence of deadlock and to identify the deadlock in parallel collective operation verified up to maximum threads. The algorithms for deadlock detection that are compared in this study are Scalable deadlock detection, Push-relabel algorithm, Knapp’s, Fulgor, and Consensus based on Blockchain technology. Blockchain technology provides a secure environment and helps to build trust. According to this paper, the Fulgor algorithm is more effective at removing deadlocks and maintaining communication security between distributed systems. Both controlled and uncontrolled environments are tested with different algorithms and are compared to define efficiency side-by-side. Deadlock detection requires identifying some properties and message delays in the global state of the distributed system. The number of common parameters has been identified in the selected algorithms to detect deadlocks in a distributed system