Reviewerly/exHarmony huggingface dataset:
On the Complexity of Configuration and Orchestration for Enabling Disaggregated Server Provisioning in Optical Composable Data Centres

Due to the limitations of traditional data center (DC) architectures, the concept of infrastructure disaggregation has been proposed. DC resources are separated into multiple blades to be exploited independently. As a result, composable DC (CDC) infrastructures are achieved, enhancing the modularity of resource provisioning. However, disaggregation introduces additional challenges that need to be carefully analyzed. One relates to the potential complexity increase on the orchestration and infrastructure configuration that need to be performed when provisioning resources to support services. This aspect is highly influenced by the distribution of resources at the physical infrastructure. As such, when analyzing the performance of a CDC, it becomes essential to also study the related operational complexity of the resource orchestration and configuration phases. Furthermore, the requirements of several tenant services may impose heterogeneous deployments over the shared physical infrastructure in the form of either disaggregated single-server or multi-server distributions. The associated orchestration/configuration cost is again highly influenced by the data plane architecture of the CDC. With these aspects in mind, in this paper, we provide a methodology for analysis of the complexity of resource orchestration for a service deployment and the associated configuration cost in optical CDCs, considering various service deployment setups. A selected set of CDC architectures found in the literature is employed to quantitatively illustrate how the data plane design and service deployment strategies affect the complexity of infrastructure configuration and resource orchestration.
SURVEY ON NFT MINT, BUY AND SELL WEB APPLICATION

Non-fungible tokens (NFTs) are rights that can be transferred to digital objects like photos, movies, or music.Since early 2021, the phenomena and its markets have experienced tremendous growth.Since a few years ago, the number of NFT marketplaces has been steadily increasing.Most of them use centralised systems for digital asset storage (files).This goes against the idea of decentralised systems.In this project, we suggest a safe exchange for trading non-fungible tokens, which represent digital assets.It will give users the ability to produce new digital assets and exchange them for Ethereum-based coinage.In addition, we want to investigate the technical viability of a decentralised file system that uses the IPFS protocol to store digital assets more securely.This is how we try to solve the file storage problem.Additionally, this project aims to promote the usage of blockchain technology.
Accomplishing and Optimizing Robotic Self-Navigation Intelligence for Warehouse Logistics through Sensor Fusion and Antenna Localization

Logistics automation has been the subject of many developments linking robotic hardware with improved quality and safety of work for warehouse employees. It is also a field where robotic navigation, route optimization and precise maneuvering are crucial to the competitiveness of the engineering product on the market. This research demonstrates a mathematical modeling method through which robots can navigate warehouse floors efficiently, using indoor positioning of high accuracy. Moreover, the paper also describes the hardware considerations taken into account when measuring the accuracy of the robot from achieving its destination on the floor plan. A prototype is creating, showing the sensor fusion interlinks for obstacle avoidance and distance mapping. Finally, the prototype and the algorithm are tested against eight static, as well as dynamic performance tests, in order to validate the performance of the system in static and dynamic interference environments. The goal of this paper is to present the engineering perspectives of optimizing a self-driving warehouse robot through utilization of the emerging technologies related to indoor positioning. This is presented through a prototype development of an Automated Guided Vehicle which will perform indoor positioning of itself across a warehouse floor plan and be able to avoid obstacles while driving towards its destination. Both the hardware description and the algorithmic modeling will be presented, accompanied by an extensive set of testing experiments, presented to determine the feasibility of our proposed developments in this field.
Cybercrime and Cryptocurrency as New Challenges for the Police

Advances in technology, easy access to the internet, inconsistent rules and regulations, inadequate police training on cybercrime, and the complexity of international or multiorganizational collaboration in police operations have created new forms of cybercrime. Illegal cryptomarkets/darknet marketplaces transactions on the hidden web use cryptocurrency as a payment method, which makes it difficult to trace the identity of sellers and buyers. The internet and Dark Web browsers have also provided tools for criminals to conduct cyberattacks on businesses, infrastructure, education, health care, government, and even individual citizens with little impunity. The cross-border nature of cybercrimes, lack of uniformity in regulations, difficulties in collecting digital evidence, and identifying the physical location of the perpetrators have proven to be challenging tasks for police. Lack of public awareness of police jurisdiction of cybercrimes and limited police training on cyber technology and digital evidence gathering are some critical gaps identified in this chapter.
Corpus methods

Corpus linguistics involves the computer-aided study of language data on a large scale and is used for study in many fields, both in and beyond linguistics. This chapter outlines its basic methods. We begin by outlining what a corpus is, how to design and build it, and moreover enhance it through, for example, tagging. We then turn to key techniques in corpus linguistics, specifically, concordances, collocations and keywords. Along the way we will introduce some of the key tools in the field, and comment on well-known corpora.
IDEALI: Intuitively Localising Connected Devices in Order to Support Autonomy

Localisation-capable technologies are becoming more readily available as off-the-shelf components. In this paper, we highlight the need for such a service in the field of health and autonomy, especially for disabled people. We then explore this idea through a study that leverages this localisation functionality. We introduce a model for Semantic Position Description (SPD) (“The pill organiser in on the kitchen table”) as well as various algorithms that transform raw distance estimations to SPD related to proximity, alignment and room identification. Two measurement campaigns have been conducted. The first one focused on algorithm performance and exploited the LocURa4IoT testbed. The second confronted the system's output (SPDs) to real user perception in a smart-home environment. This experiment involved ten human participants in the Maison Intelligente de Blagnac. The results indicate that both processes (human and machine perception) converge 90% of the time. This convergence confirms the relevance of our locaisation-based approach and encourages future explorations of its application to various domains.
From the Editors: Demystifying the Specialized Language Teaching (ESP) and Digital Technologies in Vocational Higher Education

This journal is organized and published by UPT. Bahasa Politeknik Negeri Ujung Pandang and dedicated to contributing to the growth of applied linguistics studies. On behalf of the editorial board members, we are happy to announce and launch this first volume of Research and Innovation in Applied Linguistics-Electronic Journal (RIAL-EJ). This journal aims to publish scholarly articles in the area of applied linguistics, vocational English, and English for Specific Purposes (ESP), such as business English, English for engineering (mechanical, chemical, civil, and electrical engineering), English for health, and English for marine professionals. The central theme of this issue is “Demystifying the Specialized Language Teaching (ESP) and Digital Technologies in Vocational Higher Education” and the extent to which PBLL and the affordances of digital technology contribute to vocational English learning. In this volume, we publish five featured articles (3 research articles, one review article, and one interview article). The articles underwent several stages, including initial screening from the editorial board, blind review from two anonymous reviewers, multiple round revisions, proofreading, and copyediting process, plagiarism check with the iThenticate, and article production stage.
Kemampuan Numerasi Pada Siswa Tunarungu

This study aims to determine and describe the numeracy skills of deaf students. The method used in this research is the Systematic Literature Review method. The research subjects in this case were high school-LB students. After going through the inclusion and quality test stages, the literature reviewed was 5 articles. The results and findings in the articles show that there are several indicators in describing numeracy skills. The indicators of numeracy ability in question are (1) being able to use various kinds of numbers and symbols related to basic mathematics to solve problems in various contexts of daily life, (2) Analyzing information displayed in various forms (graphs, tables, charts). , diagrams and so on), and (3) interpret the results of the analysis to predict and make decisions. With the intellectual results of deaf students there is no difference compared to students without hearing loss, but have a longer time in the learning process.
9. Eating Disorder Discourse in a Diet and Fitness App Community: Understanding User Needs Through Exploratory Mixed Methods

Eating disorders remain little understood by the public, and sensationalist stories in the media have done little to dispel simplistic and reductionist perspectives. This edited volume uses a range of language-centred approaches to provide much needed critical in-depth analysis and interdisciplinary synthesis. The book
Retracted: Prevention and Nursing Research of PICC Catheter-Related Complications in Patients with Digestive System Malignant Tumor Based on Smart Medical Block Chain

[This retracts the article DOI: 10.1155/2021/5519722.].
Comparing product quality between translation and paraphrasing: Using NLP-assisted evaluation frameworks

Translation and paraphrasing, as typical forms in second language (L2) communication, have been considered effective learning methods in second language acquisition (SLA). While many studies have investigated their similarities and differences in a process-oriented approach, little attention has been paid to the correlation in product quality between them, probably due to difficulties in assessing the quality of translation and paraphrasing. Current quality evaluation methods tend to be either subjective and one-sided or lack consistency and standardization. To address these limitations, we proposed preliminary evaluation frameworks for translation and paraphrasing by incorporating indices from natural language processing (NLP) tools into teachers’ rating rubrics and further compared the product quality of the two activities. Twenty-nine translators were recruited to perform a translation task (translating from Chinese to English) and a paraphrasing task (paraphrasing in English). Their output products were recorded by key-logging technique and graded by three professional translation teachers by using a 10-point Likert Scale. This rating process adopted rubrics consisting of both holistic and analytical assessments. Besides, indices containing textual features from lexical and syntactic levels were extracted from TAASSC and TAALES. We identified indices that effectively predicted product quality using Pearson’s correlation analysis and combined them with expert evaluation rubrics to establish NLP-assisted evaluation frameworks for translation and paraphrasing. With the help of these frameworks, we found a closely related performance between the two tasks, evidenced by several shared predictive indices in lexical sophistication and strong positive correlations between translated and paraphrased text quality according to all the rating metrics. These similarities suggest a shared language competence and mental strategies in different types of translation activities and perhaps in other forms of language tasks. Meanwhile, we also observed differences in the most salient textual features between translations and paraphrases, mainly due to the different processing costs required by the two tasks. These findings enrich our understanding of the shared ground and divergences in product quality between translation and paraphrasing and shed light on the pedagogical application of translation activities in classroom teaching. Moreover, the proposed evaluation framework can also bring insights into the development of standardized evaluation frameworks in translation and paraphrasing in the future.
Immersive VR for Real Estate: Evaluation of Different Levels of Interaction and Visual Fidelity

This work presents a study on how an immersive virtual environment's level of interaction and fidelity can affect the quality of experience (QOE) in a real estate context.Four versions of the virtual space were created with the level of interaction and the level of fidelity varying between them.The QoE dimensions considered in this work are user satisfaction, lighting quality, interior space quality, and interaction features.The sample comprises 28 participants, of which 21 are men and 7 are women, aged between 18 and 29 years.Results show that, overall, the level of fidelity is more relevant when the level of interaction is low, assuming the movement around the apartment is statistically higher in highfidelity experiences.
Knowledge societies: power, justice and governance

From the dual formulation of the knowledge problem as one where scientific explanation and policy making are at odds, to the re-formulation of the problem in terms of universal human rights, the chapter reviews prominent perspectives of knowledge and power. The democracy of knowledge emerges as a distributed cognitive republic, where both epistemic capacity and decision-making engage all stakeholders. Consequently, there is a need for an extended peer community where science and other sources of actionable knowledge can be thoroughly scrutinized. As a prerequisite to establishing the universal right to knowledge, epistemic justice requires decolonization. Hence, knowledge governance is enabled by an appropriate global regime and effective knowledge citizenship. Additionally, knowledge-based governance for the Anthropocene requires a multi-level, flexible epistemological and political framework, for which the capital system appears particularly well suited. The alignment of global knowledge system will require the resonance of all knowledge agents, objects, and contexts.
The mobile Silk Road: digital economy and the e-yuan

Chapter 5 observes that no country is as enthusiastic as China in embracing the digital world. In the same vein, no country is as keen as China in welcoming the digital economy. The chapter discusses the growth of China's digital economy; the emergence of its digital currency or e-yuan; how this currency goes from wide domestic use to increasing global use; what sort of impact the new money will bring to the global financial architecture; and how Western countries, in particular the US, would respond to the financial challenge posed by China, as the West has been dominating the global financial system since the end of the Second World War. The chapter points out that China's active promotion of the use of the digital yuan has not been matched with similar efforts by the West to develop their central bank digital currencies. When the US realises the potential significance of the Chinese move, it tries to catch up in the game while responding negatively to China.
Using Answer Set Programming for HPC Dependency Solving

Modern scientific software stacks have become extremely complex, using many programming models and libraries to exploit a growing variety of GPUs and accelerators. Package managers can mitigate this complexity using dependency solvers, but they are reaching their limits. Finding compatible dependency versions is NP-complete, and modeling the semantics of package compatibility modulo build-time options, GPU runtimes, flags, and other parameters is extremely difficult. Within this enormous configuration space, defining a “good” configuration is daunting. We tackle this problem using Answer Set Programming (ASP), a declarative model for combinatorial search problems. We show, using the Spack package manager, that ASP programs can concisely express the compatibility rules of HPC software stacks and provide strong quality-of-solution guarantees. Using ASP, we can mix new builds with preinstalled binaries, and solver performance is acceptable even when considering tens of thousands of packages.
Multipass Hierarchical View Grouping Method for Efficient 6DoF Video Streaming

A novel six degree-of-freedom (6DoF) video streaming method based on multipass hierarchical view grouping is proposed herein. The proposed method divides the source views into multiple groups based on the position of each source view and then separately encodes the groups of source views into independent bitstreams. Subsequently, it streams the encoded bitstreams based on the user's position and viewport. This method can increase the number of basic views and atlases for enhanced video quality, while reducing the number of source views to be reconstructed at the decoder side. Experimental results show that the proposed method significantly improves both objective and subjective qualities at the slightly increased bitrate. In addition, the proposed method achieves a decoding speedup of 37.62% owing to the reduced number of source views.
Research on Automatic Balance Patch Technology Through AI Analysis

Recently, the scale of the video game industry has become large, and several developers are rapidly producing and releasing games in accordance with the changes in the market. However, due to the lack of manpower, time, and budget of small developers, there is a problem that the game testing can not be done in depth. To resolve this problem, in this paper, we propose a model that balances the game using ML-Agent, which is a unity machine learning asset. We created AI models that took a lot of trial and error for accurate testing, and in addition, we improved the accuracy of the balance by reliably recording the win rate according to the number of characters.
Blockchain and Artificial Intelligence-based Solutions for Healthcare Management: Liver Disease Detection as a Case Study

The issue of privacy in clinical data restricts data sharing among various organizations because of legal and ethical concerns. Every medical organization (hospital, research center, testing lab, etc.) needs to protect personal and medical data privacy and confidentiality while also sharing data with efficient and accurate learning models for various diseases. This paper addresses a method that combines machine learning approaches on blockchain network for classification of patients with liver disease or not, while maintaining the privacy and enabling data sharing. The contribution of this paper is five-folds: (i) To deal with the liver disease dataset, data preprocessing phases are utilized (i.e., missing data treatment, data normalization, and data transformation). (ii) For feature reduction, two feature selection models are used: correlation feature selection (CFS) and wrapper metaheuristic (PSO+KNN). For training the proposed global model, the selected features (10, 4, 3) from the three models (all features, CFS, PSO+KNN) are distributed to the shared blockchain network. (iii) To detect liver disease in the preprocessed dataset, three machine learning methods are proposed: random forest, decision tree (J48), and Naïve Bayes. (iv) The distributed network (blockchain) will publish the results of the liver disease diagnosis on the network. (v) The smart contract shares the data and diagnosis between the medical organizations for future processing. An empirical study is executed to validate the relevance of our suggested framework for early diagnosis of liver disease using blockchain and machine learning models. The experimental results showed that feature selection using the wrapper metaheuristic (PSO+KNN) with a random forest model achieves the best performance with the minor features for detecting liver disease with an accuracy of 99.9 compared to 99.2, 89.2 for Naïve Bayes, and J48, respectively.
Scaling Workloads

SQL Server provides multiple technologies that allow DBAs to horizontally scale their workloads between multiple databases to avoid lock contention or to scale them horizontally between servers to spread resource utilization. These technologies include database snapshots, replication, and AlwaysOn Availability Groups. This chapter discusses the considerations for these technologies and demonstrates how to implement them.
Encryption

Encryption is a process of obfuscating data with an algorithm that uses keys and certificates so that if security is bypassed and data is accessed or stolen by unauthorized users, then it will be useless, unless the keys that were used to encrypt it are also obtained. This adds an additional layer of security over and above access control, but it does not replace the need for an access control implementation. Encrypting data also has the potential to considerably degrade performance, so you should use it on the basis of need, as opposed to implementing it on all data as a matter of routine.
Web Tool for Evaluating Photovoltaic Opportunitie for Potential Prosumers

The paper might be an impetus addressed to a wide range of possible beneficiaries or just stakeholders, from state authorities, to businesses and simple individuals, to contribute to the development of photovoltaic systems in Romania. To begin with, the main economic, strategic and environmental arguments that support the development of these systems, which can be effective in the areas of the Earth where 93% of its inhabitants live, are synthesized. It is shown that in terms of the total amount of solar energy received per square meter, for an entire year, Romania is on a modest 182-nd position. However, it is demonstrated by calculation that only by using 0.22% of the unpopulated and undamaged surface of our country for PV systems, the entire national electric energy requirement could be provided. A tool developed in Python that allows estimating the photovoltaic potential of the roof of a normal-sized residential building is presented in detail. Based on all the costs involved (both the investment effort and the subsidized or non-subsidized price of the kWh) an encouraging result is obtained regarding the recovery time of the invested money.
Influence of large-scale PV station construction on regional air temperature

This study analyzes the variation characteristics of the air temperature of the Gonghe photovoltaic (PV) station in Qinghai based on the measured data, and discusses the impact of PV development on the temperature. The results show that under the height of 2.5m of the Gonghe PV station in the desert area, the daytime temperature has a warming effect in spring and summer, and the PV power station has a cooling effect in autumn and winter. Under different seasonal conditions, the temperature increase range of PV stations is small during the day, but it has a significant cooling effect at night, which is characterized by the minimum cooling in summer, and the maximum cooling in winter is 2.33°C.