Reviewerly/exHarmony huggingface dataset:
Regulating Gatekeeper Artificial Intelligence and Data: Transparency, Access and Fairness under the Digital Markets Act, the General Data Protection Regulation and Beyond

Abstract Artificial intelligence (AI) is not only increasingly being used in business and administration contexts, but a race for its regulation is also underway, with the European Union (EU) spearheading the efforts. Contrary to existing literature, this article suggests that the most far-reaching and effective EU rules for AI applications in the digital economy will not be contained in the proposed AI Act, but in the Digital Markets Act (DMA). We analyse the impact of the DMA and related EU acts on AI models and underlying data across four key areas: disclosure requirements; the regulation of AI training data; access rules; and the regime for fair rankings. We demonstrate that fairness, under the DMA, goes beyond traditionally protected categories of non-discrimination law on which scholarship at the intersection of AI and law has focused on. Rather, we draw on competition law and the FRAND criteria known from intellectual property law to interpret and refine the DMA provisions on fair rankings. Moreover, we show how, based on Court of Justice of the European Union jurisprudence, a coherent interpretation of the concept of non-discrimination in both traditional non-discrimination and competition law may be found. The final section sketches out proposals for a comprehensive framework of transparency, access and fairness under the DMA and beyond.
Research on the Development Opportunities and Paths of Digital RMB Internationalization Under the Background of Great Power Competition

At present, the global political economy is experiencing a crisis of great power competition. At the same time, the new industrial technology revolution accompanied by the process of digital economic globalization is quietly changing the way of human production, life and consumption. In this comprehensive context, digital currency, as the carrier of future monetary value, has ushered in a fast track of development. The digital RMB "e-CNY" of the People's Bank of China has stood on the stage of monetary history in the form of legal tender through national credit endorsement. As a digital financial currency with national credit endorsement, how can digital RMB further expand its influence and international currency stickiness? What are the competitive advantages, development opportunities and development paths of digital RMB internationalization? How does the internationalization of digital RMB affect the diversified innovation and development of the global financial system? This paper attempts to analyze and study many factors of the development of digital RMB internationalization under the background of great power competition, introduces the concepts of digital currency ecological index K<sub>e</sub>, digital currency market density index K<sub>d</sub>, digital currency market willingness index K<sub>q</sub> and digital currency market competitiveness index K<sub>c</sub>, and puts forward the calculation formula design of digital currency ecological index K<sub>e</sub>. Secondly, according to the topic hypothesis, the core competitiveness model of digital RMB internationalization leading strategy is creatively proposed, and the development path model of digital RMB internationalization is summarized and summarized on the basis of the above discussion. Finally, this paper gives some reference opinions on the development path of digital RMB internationalization. This paper provides a research approach on the development path of digital RMB internationalization based on the dual role of great power competition and digital economy development, and provides some reference for the policy of digital RMB internationalization.
Analisis Faktor Penghambat dan Upaya Peningkatan Literasi pada Siswa Kelas 1 di SDN Pabean Kabupaten Probolinggo

Currently reading literacy in Indonesia is very low, due to a lack of interest in reading. This has happened since childhood, we are not used to reading. Reading literacy is the ability to understand in the form of written language needed by society. Mastery of literacy is important for increasing the achievements of the millennial generation in achieving success. Literacy cultivation must be carried out early on and realized because it is the main capital in creating an intelligent nation. Literacy activities are really needed for students to improve their reading quality. However, it is very unfortunate, when the Covid-19 pandemic hit Indonesia, it resulted in a decrease in the quality of children's literacy, especially at the Kindergarten level who will enter Elementary School. The method of this research is in the form of interviews and observations of grade 1 elementary school teachers, namely by increasing the reading and writing literacy culture movement for grade 1 students of SD Pabean Probolinggo. Based on the results of the interviews and observations that we conducted, it was stated that of the 29 students, there were 8 students who could read and 22 students who could not read. Where this shows that, the level of students' writing ability is higher than reading ability.
Lighting Search Algorithm with Convolutional Neural Network-based Image Captioning System for Natural Language Processing

Recently, deep learning models have become more prominent due to their tremendous performance for real-time tasks like face recognition, object detection, natural language processing (NLP), instance segmentation, image classification, gesture recognition, and video classification. Image captioning is one of the critical tasks in NLP and computer vision (CV). It completes conversion from image to text; specifically, the model produces description text automatically based on the input images. In this aspect, this article develops a Lighting Search Algorithm (LSA) with a Hybrid Convolutional Neural Network Image Captioning System (LSAHCNN-ICS) for NLP. This introduced LSAHCNN-ICS system develops an end-to-end model which employs convolutional neural network (CNN) based ShuffleNet as an encoder and HCNN as a decoder. At the encoding part, the ShuffleNet model derives feature descriptors of the image. Besides, in the decoding part, the description of text can be generated using the proposed hybrid convolutional neural network (HCNN) model. To achieve improved captioning results, the LSA is applied as a hyperparameter tuning strategy, representing the innovation of the study. The simulation analysis of the presented LSAHCNN-ICS technique is performed on a benchmark database, and the obtained results demonstrated the enhanced outcomes of the LSAHCNN-ICS algorithm over other recent methods with maximum Consensus-based Image Description Evaluation (CIDEr Code) of 43.60, 59.54, and 135.14 on Flickr8k, Flickr30k, and MSCOCO datasets correspondingly.
S-BAN: Secure Blockchain-based Networking Strategy for Privacy-Preserving DSM

Demand-side management (DSM) is an essential tool in smart power grids to enable efficient energy utilization. In DSM, customers send their fine-grained energy consumption data to the utility company (UC). This fine-grained data can reveal private information about the customers. Hence, many privacy-preserving proposals are made to overcome such a threat. However, existing mechanisms do not satisfy both customer anonymity and data unlinkability. To address this limitation, we propose a blockchain-based anonymous networking strategy called (BAN) that uses group signatures and unique random identifiers on top of a blockchain network to provide the desirable features. However, our security analysis reveals that adopting anonymous signatures on top of blockchains opens the door to other forms of cyber-attacks, such as denial-of-service (DoS), man-in-the-middle (MitM), and traffic analysis attacks. Hence, we propose a secure BAN (S-BAN) network that upgrades the BAN to enable secure and privacy-preserving DSM. The S-BAN is based on a novel onion routing with blockchain interconnected servers strategy (ORBITS). Our implementation of the proposed strategy demonstrates low computation and communication overheads.
Learning to Follow and Generate Instructions for Language-Capable Navigation

Visual-language navigation (VLN) is a challenging task that requires embodied agents to follow natural language instructions to navigate in previously unseen environments. However, existing literature put most emphasis on interpreting instructions into actions, only delivering “dumb” wayfinding agents which cannot actively use natural language to communicate with humans. In this article, we devise <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Lana</small> , a <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><u>la</u>nguage-capable</b> <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</u> avigation <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a</u> gent which is able to not only execute human-written navigation commands, but also provide route descriptions to humans. This is achieved by simultaneously learning instruction following and generation with only one single model. More specifically, two encoders, respectively for route and language encoding, are built and shared by two decoders, respectively, for action prediction and instruction generation, so as to exploit cross-task knowledge and capture task-specific characteristics. Throughout pretraining and fine-tuning, both instruction following and generation are set as optimization objectives. We further extend <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Lana</small> by exploiting object semantics during route encoding. This leads to <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Lana+</small> , a more powerful framework that simulates the way humans refer to landmarks for instructions composition and wayfinding. We empirically verify that, compared with recent advanced task-specific solutions, <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Lana</small> attains better performances on both instruction following and generation, with nearly half complexity. In addition, endowed with language generation capability, <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Lana</small> can explain to humans its behaviors and assist human's wayfinding. Benefiting from landmark information, <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Lana+</small> exhibits even more impressive performance. This work is expected to foster future efforts towards building more trustworthy and socially-intelligent navigation robots.
VaPr: Variable-Precision Tensors to Accelerate Robot Motion Planning

High-dimensional motion generation requires nu-merical precision for smooth, collision-free solutions. Typically, double-precision or single-precision floating-point (FP) formats are utilized. Using these for big tensors imposes a strain on the memory bandwidth provided by the devices and alters the memory footprint, hence limiting their applicability to low-power edge devices needed for mobile robots. The uniform application of reduced precision can be advantageous but severely degrades solutions. Using decreased precision data types for important tensors, we propose to accelerate motion generation by removing memory bottlenecks. We propose variable-precision (VaPr) search optimization to determine the appropriate precision for large tensors from a vast search space of approximately 4 million unique combinations for FP data types across the tensors. To obtain the efficiency gains, we exploit existing platform support for an out-of-the-box GPU speedup and evaluate prospective precision converter units for GPU types that are not currently supported. Our experimental results on 800 planning problems for the Franka Panda robot on the MotionBenchmaker dataset across 8 environments show that a 4-bit FP format is sufficient for the largest set of tensors in the motion generation stack. With the software-only solution, VaPr achieves 6.3% and 6.3% speedups on average for a significant portion of motion generation over the SOTA solution (CuRobo) on Jetson Orin and RTX2080 Ti GPU, respectively, and 9.9%, 17.7% speedups with the FP converter. More details are available at sites.google.com/nvidia.com/vapr.
Tutoría de acompañamiento académico desde la virtualidad en tiempos de COVID-19: experiencias de transformación en el nivel superior

The temporary closure of schools associated with COVID-19 has led to the transformation of the substantive functions of universities, including tutoring for academic support, encouraging teachers to make use of various virtual media to provide continuity to the student support processes during the so-called emergency education. The objective of this paper is to document the experiences about the changes in the tutorial task in a public university in the southeast of Mexico, as well as the strategies and resources used to systematize the tutorial processes from the virtuality, because of the social isolation measures. The experience is analyzed taking into consideration five central aspects: 1) institutional dispositions for virtual tutoring, 2) teachers' collaborative work, 3) support materials for virtual tutorial follow-up, 4) student support through Microsoft Teams and 5) evaluation of virtual tutorial action. Likewise, the results of this experience, collected through a census in which undergraduate students who used the program during the pandemic period participated, are analyzed. The findings indicate changes in the tutorial practice in this period and highlight its value as a space for the attention of the academic and personal needs of the student body. In addition, a discussion is introduced on the feasibility of new lines of action for the diversification of this strategy based on the permanent integration of virtual environments to the already existing modalities of attention.
Foreword to the special section on 3D object retrieval 2023 symposium (3DOR2023)

• Foreword to the 16th Eurographics Symposium on 3D Object Retrieval (3DOR2023). • Research into methods and evaluation techniques for shape retrieval are presented. • It contains 9 full technical papers and 3 SHREC full papers.
Investigating syntactic priming cumulative effects in MT-human interaction

A question that deserves to be explored is whether the interaction between English language learners and the popular Google neural machine translation (GNMT) system could result in learning and increased production of a challenging syntactic structure in English that differs in word order between speakers first language and second language.In this paper, we shed light on this issue by testing 30 Brazilian Portuguese L2 English speakers in order to investigate whether they tend to describe an image in English with a relation of possession between nouns using a prepositional noun phrase (e.g. the cover of the book is red) or re-use the alternative syntactic structure seen in the output of the GNMT (e.g. the book cover is red), thus manifesting syntactic priming effects. In addition, we tested whether, after continuous exposure to the challenging L2 structure through Google Translate output, speakers would adapt to that structure in the course of the experiment, thus manifesting syntactic priming cumulative effects.Our results show a robust syntactic priming effect as well as a robust cumulative effect.These results suggest that GNMT can influence L2 English learners linguistic behaviour and that L2 English learners unconsciously learn from the GNMT with continuous exposure to its output.In this research, we aim to investigate whether web-based popular translation tools such as google neural machine translation (GNMT) are capable of influencing the language behaviour of the English students that use them for learning purposes. We also investigate whether English students learn from the output of the systems and how this learning takes place, i.e., whether consciously or unconsciously.
Automation of health care management system through software

In these modern times, people prefer convenience over traditional methods. This text describes the benefits of implementing a software system in Polyclinic #5. The system enables patients to make online appointments with doctors, eliminating the need to wait in long queues. Additionally, it eliminates the hassle of managing physical medical cards as all records can be accessed digitally. The software also facilitates communication among employees through a chat room and allows for sending reports to the chief physician. For pharmacists, the system provides the ability to check the availability of medicines. Moreover, the software automates tasks, provides schedules for employees, and enables effective management of the team. The system architecture involves subsystems and user access from different devices. Users include the chief physician, doctors, receptionists, nurses, pharmacists, laboratory technicians, and patients. The system development follows an iterative and incremental approach. It concludes with the implementation of off-the-shelf software that simplifies patient appointments, ensures secure medical records, enhances staff communication, and streamlines management and inventory control.
Fine-Grained Style Control in VITS-Based Text-to-Speech Synthesis

In this paper, a fine-grained style controllable speech synthesis model based on VITS is presented. To achieve fine-grained emotional speech, global and local emotion features are extracted using GST and LST, respectively. A multi head cross-attention mechanism is used to align the text with emotion features, achieving prosodic control on the text side. Experiments demonstrate that the original text encoder of VITS is not capable of handling both text and emotion features simultaneously. Therefore, an emotion-text encoder is proposed, which significantly improves the ability of the prior encoder and enables fine-grained emotion speech synthesis. Results show that the system achieves the highest levels of naturalness, style conversion ability, and speech quality in synthesized speech. Audio samples are publicly available ( https://lunar333.github.io ).
UTILIZATION OF A PICO HYDRO POWER PLANT AT AL-IKHLAS ISLAMIC BOARDING SCHOOL IN MALANG REGENCY

Al-Ikhlas Yatim Dhuafa Islamic Boarding School is ± 12.6 km from Malang City. If you look at it geographically, the location of this community service program is located at coordinates 7°58'27.0"S 112°48'14.8"E. To support activities in this tourist area, electrical energy is really needed, especially for lighting facilities and charging electronic equipment. This Community Service Program will be implemented between April and November 2022 with activities in the form of building a pico hydro power plant in the Al-Ikhlas Yatim Dhuafa Islamic Boarding School area, Singosari District, Malang Regency. In carrying out this community service program, there is one activity partner, namely the Al-Ikhlas Yatim Dhuafa Islamic Boarding School with a total of 6 personnel. The results of this community service program are the installation and operation of a pico hydro power plant with a capacity of 1000 watts. This pico hydro power plant can meet electricity needs in the Islamic boarding school area with a total power of around 450 watts. In order for the pico hydro power plant to operate according to its capacity, it is necessary that the operation and maintenance of the system equipment be carried out correctly and on a schedule. For this reason, the transfer of knowledge and skills to work partners, namely the management of the Al-Ikhlas Yatim Dhuafa Islamic Boarding School, has been carried out.
TEACHING ENGLISH AT A1 MOVERS CLASS AND A2 FLYERS WITH COMMON EUROPEAN FRAMEWORK REFERENCE (CEFR) AT JUNIOR HIGH SCHOOL JAMBI CITY

This article describes the activities of implementing the CEFR-based communicative language approach at the junior high school level. There are 16 students involved and are at the level of Movers A1 and Flyers A2 based on the CEFR concept. The main purpose of this activity is to provide an English learning experience that is different from what is applied in schools. This activity avoids the use of grammatical theory based and prioritizes oral communication activities that connect students with the real environment. Activities using media that are already available in the learning environment of students and learning topics are designed according to the needs of students. The activity is very structured and involves five aspects of assessment, namely Range of Vocabulary, Accuracy, Fluency, Interaction, and Coherence.
Komunikowanie nauki: narzędziownia

The aticle presents several different ways of popularizing scientific knowledge. It is not scientific in the sense that it is not a report on a systematic study of the literature or empirical research. It is a tool room: a repository we can turn to in search of tools to help us solve a problem. The article offers three tools. The first is a typology of forms of participation in science. I treat the typology as a tool, too, because defining a problem can be seen as part of the problem-solving process. It's important to understand that there are different forms of science popularization and citizen science participation: each form requires different competencies and will work in a different situation. It's also important to understand that there is a difference between science communication (i.e., what scientists do as part of their work) and science communication (i.e., dissemination of scientific results outside of science). These are two different modes of communication and require separate skills. The second tool is a set of heuristics that may be of interest to those already parsing science communication, but having difficulty communicating science. The last tool is a proposal for a science popularizer's checklist. It is based on my own experience. Anyone interested in science communication can check this tool in action, modify it for themselves, or create their own list, which I encourage you to do.
Study of Mineral Paragenesis and Silver Occurrence in Portales Stratabound Cu-(Ag) Deposit, Valparaíso Region, Chile

Preview this conference paper: Study of Mineral Paragenesis and Silver Occurrence in Portales Stratabound Cu-(Ag) Deposit, Valparaíso Region, Chile, Page 1 of 1 < Previous page | Next page > /docserver/preview/fulltext/2214-4609/2023/third-eage-workshop-on-mineral-exploration-in-latin-america-the-role-of-mining-in-the-energy-transition/Mallea,_J._EAGE_gp-17-42-Mallea-Javier-1.gif
Research on financial risk management under asset-light operation mode

As the competition among enterprises becomes more and more fierce, the shortcomings of the traditional operation mode of enterprises begin to appear. They all begin to try the transformation of light assets to reduce the pressure brought by procurement cost or labor cost. Asset-light enterprises focus on product research and development and marketing, and the rest of the business will be completed by suppliers in the form of outsourcing, but the corresponding risks also appear. The capital structure of asset-light enterprises has particularity, which makes it difficult to identify financial risks. How to identify, prevent and control financial risks is the focus of current asset-light enterprises. Taking Li Ning as an example, this paper studies its financial risk management under the asset-light operation, and puts forward targeted measures such as dispersing financing risks, strengthening the control of investment activities in advance, and strengthening the management of operational activities, so as to improve the financial risk management mechanism formulated by the enterprise.