Reviewerly/exHarmony huggingface dataset:
BluePallet enters chemical e-commerce

BluePallet, an online platform designed to support commercial activity between chemical manufacturers, distributors, and suppliers, has debuted with $4 million in seed funding. The platform, developed with the National Association of Chemical Distributors (NACD), employs a technology called TradePass, which performs risk analysis in identifying potential business partners, BluePallet says. Thirty-seven NACD members are currently using the platform. Meanwhile, Knowde, an e-commerce venture for personal and home care chemicals, has added the palm oil supplier Musim Mas to its network.
On The Substitutivity of Variables

This paper examines the constraints for the decidability of a logical system byanalyzing the theories of undecidability in formal logic and recursive func-tions. The proof of the diagonal lemma requires the implicit premise that allformulas are closed under avariable composition, i.e., the composition of vari-ables in the formulas signatures. A variable composition is representable infirst-order logic if∀ψ∀k(⊢ψ(k)↔∃y(ψ∧y≡k))can be derived, e.g., froma semantic definition of the quantifiers. A further condition is the assump-tion of an interpretation providing the existence of what will be defined as anindeterminate variable signaturewith aconstant interpretation.A recursion theorem for formulas in analogy to the recursion theorem ofKleene (1943, pp.52-53) will be proved which covers the diagonal lemma as aspecial case. The chosen notation and reasoning intend to make the necessaryconditions for its provability explicit. It will be proved that the representabilityof variable composition and the existence of an indeterminate variable signa-ture to represent a constant interpretation are consequences of the recursiontheorem, i.e., equivalent to the existence of fixed points∀ψ∃φ(⊢φ↔ψ(⌜φ⌝)).These results give a reason why the negation of the diagonal lemma canbe proved for a predicative logic that contradicts these premises but holdsthe explicit condition of the diagonal lemma, i.e., a language of this logic iscapable of representing all computable functions, as has been shown as anon-expectable result in Solte 2020. The paper concludes with an outline ofa decidable structure of computable functions. I.e., it is possible to provide aninterpretation of a predicative logic without undecidability in this structure
Smart Task Assistance in Mixed Reality for Astronauts

Mixed reality (MR) registers virtual information and real objects and is an effective way to supplement astronaut training. Spatial anchors are generally used to perform virtual–real fusion in static scenes but cannot handle movable objects. To address this issue, we propose a smart task assistance method based on object detection and point cloud alignment. Specifically, both fixed and movable objects are detected automatically. In parallel, poses are estimated with no dependence on preset spatial position information. Firstly, YOLOv5s is used to detect the object and segment the point cloud of the corresponding structure, called the partial point cloud. Then, an iterative closest point (ICP) algorithm between the partial point cloud and the template point cloud is used to calculate the object’s pose and execute the virtual–real fusion. The results demonstrate that the proposed method achieves automatic pose estimation for both fixed and movable objects without background information and preset spatial anchors. Most volunteers reported that our approach was practical, and it thus expands the application of astronaut training.
Address and place name database of electric power intelligent customer service based on intelligent question and answer technology

Under the background of the rapid development of artificial intelligence, intelligent natural language processing technology has made rapid development. Different from the question answering system in other fields, the establishment of electric power Intelligent Customer Service System (ICSS) makes the construction of intelligent question answering system more challenging. This paper discusses and analyzes the design and implementation of intelligent question and answer system, the demand analysis of power ICSS and the construction process of address and place database. Through the function, performance and security test of power intelligent customer service, the test results show that the version of the release system runs stably and has been actually applied in the management of power customer service. After the launch of the power CSS, customers generally reflect that the effect is very good. They agree that the promotion of the power CSS in the power industry is an extremely important basic project to realize the hierarchical requirements of standardized management and operation.
Design and research of international student training management system based on cloud computing

When designing international student management information system, we should fully consider the needs of the users. International students have a short time to learn Chinese, especially when it comes to some of the proper nouns, they are often prone to ambiguity, so we can consider the multinational language requirements when designing the management system, so that international students can understand the relevant issues through their own language when they encounter problems. Therefore, this paper is based on cloud computing technology, the current popular Java EE development platform, and the mature MySQL database to design the academic management software. First, this paper analyzes cloud computing and the architecture used in this paper. Then, the overall structure of the system is given in this paper, taking into account the training needs of international students. Then a detailed design is given for each part. The designed system is also tested, and the test results show that the performance as well as the functionality of the system can meet the current requirements.
Improved mask detection based on YOLOv5s

COVID-19 epidemic is not over. The correct wearing of masks can effectively prevent the spread of the virus. Aiming at a series of problems of existing mask-wearing detection algorithms, such as only detecting whether to wear or not, being unable to detect whether to wear correctly, difficulty in detecting small targets in dense scenes, and low detection accuracy, It is suggested to use a better algorithm based on YOLOv5s. It improves the generalization and transmission performance of the model by changing the ACON activation function. Then Bifpn is used to replace PAN to effectively integrate the target features of different sizes extracted by the network. Finally, To enable the network to pay attention to a wide area, CA is introduced to the backbone. This embeds the location information into the channel attention.
Unified Vision-Language Representation Modeling for E-Commerce Same-style Products Retrieval

Same-style products retrieval plays an important role in e-commerce platforms, aiming to identify the same products which may have different text descriptions or images. It can be used for similar products retrieval from different suppliers or duplicate products detection of one supplier. Common methods use the image as the detected object, but they only consider the visual features and overlook the attribute information contained in the textual descriptions, and perform weakly for products in image less important industries like machinery, hardware tools and electronic component, even if an additional text matching module is added. In this paper, we propose a unified vision-language modeling method for e-commerce same-style products retrieval, which is designed to represent one product with its textual descriptions and visual contents. It contains one sampling skill to collect positive pairs from user click logs with category and relevance constrained, and a novel contrastive loss unit to model the image, text, and image+text representations into one joint embedding space. It is capable of cross-modal product-to-product retrieval, as well as style transfer and user-interactive search. Offline evaluations on annotated data demonstrate its superior retrieval performance, and online testings show it can attract more clicks and conversions. Moreover, this model has already been deployed online for similar products retrieval in alibaba.com, the largest B2B e-commerce platform in the world.
Based on 11 Research Reports the Future Education Trend of Primary and Secondary Schools in Korea is Examined

The study focuses on 11 future education research reports released by the South Korean National Policy Research Institute from 2016 to 2022, and conducts qualitative research from four aspects: future education goals, future education content, future education learning and evaluation, and future education development strategies. The results show that future education goals not only focus on the social demand for education, but also on unleashing individual potential. The future education content includes ability education, multicultural education, future career education, human emotion education, global citizenship education, digital education, and etc. Future education methods are mainly personalized learning based on ICT technology, learner centered project learning, problem learning, inquiry learning, cooperative learning, formal learning, informal learning, and blended learning. The future education development strategy needs to improve public education and other systems. On the other hand, it is necessary for future education to reflect on the essence of education and the history of educational reform, and to consider the direction of future development from a macro and long-term perspective.
Mobile Devices and Sensors for an Educational Multimedia Opera Project

Interactive computer-based music systems form a rich area for the exploration of collaborative systems where sensors play an active role and are important to the design process. The Soundcool system is a collaborative and educational system for sound and music creation as well as multimedia scenographic projects, allowing students to produce and modify sounds and images with sensors, smartphones and tablets in real time. As a real-time collaborative performance system, each performance is a unique creation. In a comprehensive educational project, Soundcool is used to extend the sounds of traditional orchestral instruments and opera singers with electronics. A multidisciplinary international team participates, resulting in different performances of the collaborative multimedia opera The Mother of Fishes in countries such as Spain, Romania, Mexico and the USA.
Automating Exhibition Catalogue Creation

Automating Exhibition Catalogue Creation 2 with the tooling and data science.And although there are many initiatives out there to support training, it would appear -across the board -a lack of data science skills is a barrier for the majority of people, including authors and publishers.Hence, in an attempt to tackle this in our own modest way, ongoing contributions will involve workshops, classes, and libraries, and we will also share best practices and workflows such as these to put computational Jupyter Notebooks to write scripts to retrieve data, Quarto for collation and multi-format typesetting, and Git for storage, collaboration, and publishing.
Adoption of new technologies raises cybersecurity need

Significance These technologies are being adopted in the context of hybrid working and global digital supply chain integration. These technologies promise improved efficiency, service delivery and productivity, and access to new markets. However, they also intensify cybersecurity risks. Impacts High-profile cyberattacks against generative AI tools could slow innovation as critical sectors pause adoption. Startups with a higher risk tolerance will use major cyberattacks to develop new security solutions. Cybersecurity providers are likely to branch into providing legal and auditing services related to their software and hardware services.
Tourism Growth and Financial Sector Development Nexus: Evidence from Selected African Economies

This article tests the tourism growth and financial sector development nexus. Data came from the World Bank and IMF for the years 1995-2020 from 43 selected African economies. We applied System GMM and dynamic CCEMG to estimate short–run effects and JKS Granger non-causality test for causality, FMOLS and FGLS to estimate long–run effects and sets of co-integration tests for co-movements. The findings support mutual reinforcing effects for both inbound tourism growth and financial sector development. Outbound tourism should be monitored and controlled for its negative effects; inbound tourism should be facilitated and promoted for its positive effects. Political stability and trade openness policies should be a priority for both sectors, while foreign direct investments should be monitored and controlled for their ambiguous impacts. In this work, we are able to show that increases in international tourism activities and developments in the financial sector mutually impact each other.
Detecting Replicated Files in the Cloud

Abstract: Now-a-days all are using the cloud server to store their data and provides many features suitable for the users or customers. We have cloud servers like Google Cloud Platform,Microsoft Azure etc. For cloud also sometimes there will be storage problem to store the data of the users. We need the security to the data stored in the cloud. For hospitals and some private companies, the data should be secure and confidential. So we need both storage and thesecurity to our data stored in the cloud. Authorized Client-Side Deduplication Using CP-ABE here proposed which provides the security and provides Deduplication in the cloud.
English Anxiety and Course Achievement among Korean EFL Graduate Students in an Online English Course

Language anxiety is notorious for having a negative effect on SLA.However, some studies have produced inconsistent results, which seems to be caused by socio-cultural differences.The present study explores a potential relationship between English anxiety and course achievement among Korean EFL graduate students taking an online English course.To this end, the Foreign Language Classroom Anxiety Scale(FLCAS), a background survey, weekly learning logs, four assignments, and the final exam were administrated to 142 participants enrolling a 15-week English reading course at a graduate school of professional studies in Seoul.The data were analyzed using descriptive statistics and the FLCAS was compared with the final course scores.The results showed that test anxiety received the highest mean(3.72),followed by a fear of negative evaluation(3.71),and communication apprehension(3.61)was the lowest.In this regard, a number of students reported that they stopped or gave up studying English for a long time, had difficulty memorizing vocabulary, and felt pressure to take the final exam in real time.Moreover, students who obtained higher final grades exhibited higher anxiety than those who got lower grades, which implies that the higher the English course achievement, the higher the levels of English anxiety.However, all high-anxious students did not show higher final grades than low-and moderate-anxious students.In other words, significant differences in course achievement across the three levels of anxiety were not found.The findings demonstrated that advanced students who get high grades also experience high levels of English anxiety, and poor academic performance does not always stem from high levels of anxiety.In this regard, Korean EFL learners' high English anxiety is not seen as an index of low English course achievement.
An Interpretation of h, e and R indices from the Viewpoint of Riemann Zeta Function

The h-index is an indicator, which measures both the productivity and the effect of citation of the publications for an individual scientist or scholar, journal or institution. Besides, R-Index and e-Index are also significant as h-index ignores the information of excess citation beyond h-core zone. The h-index alone conveys partial citation information, which becomes complete only when it is countered with e Index and R-Index. The h, e and R-indices are defined as the positive square roots of h-core citation, net excess citation and total citation respectively. The h-Index holds only integral values and is a discrete variable, whereas e and R-indices may have any positive value, which are continuous variables. This paper shows that the ratio of total to excess citation, i.e.(R/e)2 may be expressed as an infinite series of h-core to total citation, i.e., (R/e)2 Also, the ratio of total citation to net excess citation is explained in the light of Riemann Zeta Function (ζ(r)). It is found that only few Zeta Functions (from ζ(2) to ζ(6)) may interpret the said ratio.
The Development of Polysynchronous-Based E-Learning For EFL Class

As a result of the effects of COVID-19 spread, the Indonesian government issued a new policy in the educational sector instructing all educational units and institutions to carry out an online learning activity that can be held virtually and accessed everywhere and every time. To support online learning either in real-time or at different times, it usually uses a learning management system (LMS) in which students have more than sufficient time to read and understand the material and discuss it based on their availability. The LMS or e-learning currently implemented at UM Lamongan has several obstacles, such as an unsupported system to do the learning process and less than optimal bandwidth or limited access, so the users prefer to use other platforms. This study aims to develop e-learning media and adapt the system to the needs of learning English. In addition, e-learning media which can be used as asynchronous learning media can be integrated into learning media which are also commonly used for synchronous learning so that all learning processes can be monitored and disciplined. Moreover, the achievement of competence in learning English can be exceeded maximally. This research employed the research and development (R&amp;D) method with the ADDIE model. The researcher used a descriptive quantitative approach. The assessment instruments used were test scores, interviews, observations, and interviews. The parties involved in this research were English lecturers, students, online learning media experts, and English learning material experts.&#x0D; Keywords: online learning, LMS, Polysynchronous, EFL
Electromyogram‐Based Lip‐Reading via Unobtrusive Dry Electrodes and Machine Learning Methods (Small 17/2023)

Electromyogram-Based Lip-Reading Systems In article number 2205058, Petar M. Djurić, Shanshan Yao, and co-workers present the design of a truly natural and robust electromyogram-based lip-reading system that can capture speech-relevant lip gestures and decode lip movements for speech. The system allows for a mechanically imperceptible, skin-friendly, visually unobtrusive platform for tracking and interpreting lip movements with minimal interference.
Legal linguistic templates and the tension between legal knowledge representation and reasoning

There is an inherent tension between knowledge representation and reasoning. For an optimal representation and validation, an expressive language should be used. For an optimal automated reasoning, a simple one is preferred. Which language should we choose for our legal knowledge representation if our goal is to apply automated legal reasoning? In this paper, we investigate the properties and requirements of each of these two applications. We suggest that by using Legal Linguistic Templates, one can solve the above tension in some practical situations.
The impact of Duolingo in developing students’ linguistic competence: an aspect of communicative language competences

Abstract This paper reports the impact of a type of m-learning on developing students’ linguistic and communicative competence in English as a second language. This study is a Mexican-based case using Duolingo to improve virtual courses in higher education students whose first language is Spanish. This study is a quasi-experimental research that analyzed pre-test and post-test results on a sample of 40 participants (control group of 20 participants and experimental group of 20 participants). The measuring instruments were designed for this specific study and focused on testing the six components of linguistic competence according to CEFR at level A2 (2018). A pilottest was previously conducted, and pre-test (0.81) and post-test (0.98) coefficients were considered acceptable according to Cronbach’s Alpha. This study addressed the following questions: a) How does Duolingo contribute to the development of linguistic competence in higher education students and support English learning in virtual courses via the m-learning methodology? and b) Which components were improved in student´s linguistic competence after using Duolingo? Results revealed a profound improvement in the experimental group participants. The post-test result of the experimental group is superior ( M=43.75) compared with the control group (M=30.35), mainly in the phonological control (+5.20) and the orthographic control (+2.65) compared with the control group, whose score slightly increased primarily attributed to the English virtual classes.
Analysis and Comparison for Innovative Prediction Technique of Breast Cancer Tumor using k Nearest Neighbor Algorithm over Support Vector Machine Algorithm with Improved Accuracy

Aim: The main objective of this study is to compare the efficiency of the k-Nearest Neighbor (KNN) and Support vector machine (SVM) algorithms in detecting breast cancer tumors and to examine their improved accuracy, sensitivity, and precision. Materials and Methods: The data for the research of Innovative breast cancer prediction using machine learning algorithms is taken from UCI Machine Learning Repository. The sample size of the innovative technique involves two groups KNN (N=20) and SVM (N=20) according to clincalc.com by keeping alpha error-threshold at 0.05, confidence interval at 95%, enrollment ratio as 0:1, and power at 80%. The accuracy, sensitivity, and precision are calculated using MATLAB software. Result: Accuracy (%), sensitivity (%), precision (%) are compared using SPSS software using an independent sample t-test tool. The accuracy of the k-Nearest Neighbor is 93.38% (p&lt;0.001) while the accuracy of the Support vector machine is 97.50%. The sensitivity rate is 90.85% (p&lt;0.001) for k-Nearest Neighbor whereas the results of Support vector machine sensitivity is 95.83%. The precision of k-Nearest Neighbor is 98.48% (p&lt;0.001) whereas the results of Support vector machine precision is 100%. Conclusion: The support vector machine algorithm appears to have performed better than the k-Nearest Neighbor with improved accuracy in Innovative breast cancer prediction.