Reviewerly/exHarmony huggingface dataset:
TAMPER PROOF FILES USING SECURE RSA

In this paper we have introduced a secure RSA algorithm to create tamper proof file.There are several cases where we need to make tamper proof file for example to store a person's identity such as aadhar card, pan card, or any other legal paper etc [4].In this paper we used RSA-SHA256 algorithm to create file tamper proof.The RSA algorithm is based on asymmetric key cryptography also known as Public Key cryptography.Two keys are generated in RSA, One key used for encryption & other one which is only known to authenticate receivers can only decrypt messages.No other key can decrypt the message.The RSA algorithm is a well known public key cryptography algorithm and was one of the first great advances in public key cryptography [24].Even though it is an efficient algorithm it is vulnerable to attackers.With the help of all brute attacks, hackers can obtain private key.Many advancements have been done to improve RSA like BATCH RSA, MultiPrime RSA, MultiPower RSA, Rebalanced RSA, RPrime RSA etc [24].As the use of the internet is increasing exponentially, it is used for many applications like email, chatting, and transferring data.This paper focuses on tamper proof files using Secure RSA, which eliminates some loopholes of symmetric cryptography that might prevent a hacker from stealing and misuse of data.
Disparity Reconstruction from Light Field’s Multidirectional EPIs with Kalman filter

We modeled the generation of multidirectional Epipolar Plane Images (EPIs) as a linear dynamical system. Then we proposed a framework of disparity reconstruction from the multidirectional EPIs with Kalman filter to achieve anti-occlusion and anti-noise.
Poland’s Energy Transition: Towards an Ontology

This article depicts the process of creating a Poland’s energy transition ontology based on the extraction of domain-specific terminology from parliamentary debate transcriptions. Statements associated with the energy transition were taken from the Polish Parliamentary Corpus. Then, the corpora of statements was processed using TermoPL, a tool for extracting specialised domain terminology. Based on the generated list of key terms, an OWL ontology has been constructed using the Protégé editor. The resulting ontology comprises 90 classes, 119 instances and 11 data properties. The ontology is available online in two languages (Polish and English) for evaluation, further development or use in specialist applications in organisations.
Fostering the Adoption of DMP in Small Research Projects through a Collaborative Approach

In order to promote sound management of research data the European Commission, under the Horizon 2020 framework program, is promoting the adoption of a Data Management Plan (DMP) in research projects. Despite the value of a DMP to make data findable, accessible, interoperable and reusable (FAIR) through time, the development and implementation of DMPs is not yet a common practice in health research. Raising the awareness of researchers in small projects to the benefits of early adoption of a DMP is, therefore, a motivator for others to follow suit. In this paper we describe an approach to engage researchers in the writing of a DMP, in an ongoing project, FrailSurvey, in which researchers are collecting data through a mobile application for self-assessment of fragility. The case study is supported by interviews, a metadata creation session, as well as the validation of recommendations by researchers. With the outline of our process we also outline tools and services that supported the development of the DMP in this small project, particularly since there were no institutional services available to researchers
Container Damage Detection Algorithm Based on Fast-Solo

Industrial containers will produce various types of damage for a long time, and the early manual detection of damage has problems such as low efficiency, high cost, high rate of false detection, and high rate of missed detection. In this paper, a lightweight deep learning model Fast-Solo is proposed to realize the engineering application of container damage vision detection. The algorithm is based on the Solo model using a combination of GC-ShuffleNetV2, improved PAFPN, and DecoupledSolo-head. We collected 1275 damaged container images at the port site for sample training, and then used another 1000 normal samples and 644 damaged samples collected at the same port for the false detection rate and the missed detection rate testing, the final test had a false detection rate of 7.00 $$\%$$ , a missed detection rate of 4.35 $$\%$$ , and an inference speed of 22.44 fps.
Study shows nonprofits' DEI efforts impact donor decisions

Board LeadershipVolume 2022, Issue 183 p. 6-6 Articles Study shows nonprofits' DEI efforts impact donor decisions First published: 14 September 2022 https://doi.org/10.1002/bl.30226Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume2022, Issue183September/October 2022Pages 6-6 RelatedInformation
Characterization of the environment of teachers, students and parents of basic education based on the GQM Quality Model

In this paper it is presents a characterization of the environment of teachers who have given classes during the COVID-19 pandemic in basic education, as well as the students and guardian or parents, using the GQM Quality Model as a guide to generate a metric that measures in a certain way the environment of teachers and their way of teaching during social isolation supported and mediated by technology.
RDMA Congestion Control: It Is Only for the Compliant

Remote direct memory access (RDMA) networks enable low latency and low central processing unit utilization, and their widespread adoption in datacenters enables improved application performance. However, there are performance isolation concerns for RDMA deployed in a shared cloud environment. In particular, congestion control enforcement and congestion control algorithms in RDMA make the network susceptible to performance hacking attacks, which give the attacker extra bandwidth and cause severe congestion in the network. These attacks can increase short flow completion times by several orders of magnitude. We surface a fundamental tradeoff in congestion control between short flow completion time and performance isolation. We discuss this tradeoff and how existing approaches do not provide a robust solution. We also advocate that researchers incorporate performance isolation concerns into the design and evaluation of congestion control.
Polarization-randomized gateway against detector-blinding hacks of quantum key distribution

A quantum key distribution system -employing a key time-bin qubit and a security-pass polarization-randomized qubit- is shown to overcome a wide class of intercept-resend attacks adopting the use of faked-state light; including attacks based on blinding of single-photon avalanche detectors (SPADs).
No-Directional and Backward-Leak Uni-Directional Updatable Encryption Are Equivalent

Updatable encryption (UE) enables the cloud server to update the previously sourced encrypted data to a new key with only an update token received from the client. Two interesting works have been proposed to clarify the relationships among various UE security notions. Jiang (ASIACRYPT 2020) proved the equivalence of every security notion in the bi-directional and uni-directional key update settings and further, the security notion in the no-directional key update setting is strictly stronger than the above two. In contrast, Nishimaki (PKC 2022) proposed a new definition of uni-directional key update that is called the backward-leak uni-directional key update, and showed the equivalence relation by Jiang does not hold in this setting. We present a detailed comparison of every security notion in the four key update settings and prove that the security in the backward-leak uni-directional key update setting is actually equivalent to that in the no-directional key update setting. Our result reduces the hard problem of constructing no-directional key update UE schemes to the construction of those with backward-leak uni-directional key updates.
Semantic-Based Dynamic Service Adaptation in Context-Aware Mobile Cloud Learning

Abstract Self-adaptable system concerns on service adaptation whenever errors persist within the system. Changes in contextual information such as networks or sensors will affect the system’s effectiveness because the service adaptation process is not comprehensively handled in those contexts. Besides, the correctness to get the most equivalence services to be substituted is limitedly being addressed from previous works. A dynamic service adaptation framework is introduced to monitor and run a reasoning control to solve these issues. Hence, this paper presents a case study to proof the dynamic service adaptation framework that leverages on semantic-based approach in a context-aware environment. The evaluation of the case study resulted in a significant difference for the effectiveness at a 95% confidence level, which can be interpreted to confirm that the framework is promising to be used in operating dynamic adaptation process in a pervasive environment.
Multi-task Hierarchical Cross-Attention Network for Multi-label Text Classification

As the quantity of scientific publications grows significantly, manual indexing of literature becomes increasingly complex, and researchers have attempted to utilize techniques in Hierarchical Multi-label Text Classification (HMTC) to classify scientific literature. Although there have been many advances, some problems still cannot be effectively solved in HMTC tasks, such as the difficulty in capturing the dependencies of hierarchical labels and the correlation between labels and text, and the lack of adaptability of models to specialized text. In this paper, we propose a novel framework called Multi-task Hierarchical Cross-Attention Network (MHCAN) for multi-label text classification. Specifically, we introduce a cross-attention mechanism to fully incorporate text representation and hierarchical labels with a directed acyclic graph (DAG) structure, and design an iterative hierarchical-attention module to capture the dependencies between layers. Afterwards, our framework weighting jointly optimizes each level of loss. To improve the adaptability of the model to domain data, we also continue to pre-train SciBERT on unlabeled data and introduce adversarial training. Our framework ranks $$2^{nd}$$ in NLPCC 2022 Shared Task 5 Track 1 (Multi-label Classification Model for English Scientific Literature). The experimental results show the effectiveness of the modules applied in this framework.
Overview of the NLPCC 2022 Shared Task on Multimodal Product Summarization

We introduce the NLPCC 2022 shared task on multimodal product summarization. This task aims at generating a condensed textual summary for a given product. The input contains a detailed product description, a product knowledge base, and a product image. 29 teams register the task, among which 5 teams submit the results. In this paper, we present the task definition, the dataset, and the evaluation results for this shared task.
SELF-DETERMINATION OF PEOPLE WITH INTELLECTUAL DISABILITIES IN INDEPENDENT LIVING AND QUALITY OF LIFE

Self-determination means the possibility of each person to determine its actions and actions without external constraints. Independent living for people with disabilities is described by the concept of self-determination, autonomy, self-regulating, psychological empowerment and self-realization to be their key features. On the other hand, independent living and self-protecting behavior enhance internal motives, goals and aspirations of people with disabilities regardless of external inhibitors. In the development of self-determination, in childhood, family and school play, children of the typical population, while children with disabilities, the degree of disability, age, leaf, social skills, etc. emerge in key factors.
EXPOSURE OF THE BANKING SECTOR TO THE TERMS OF ECONOMIC GLOBALIZATION

If the twentieth century was called the century of technology and war, the nineteenth century without doubt has been called the century of information and communication. Advanced computer technology and borderless communication have made information, from all over the world, fly in a hundredth of a second. People also move more freely than 30-40 years ago. Land borders are almost extinct on developed continents and countries. In the current conditions of the global COVID 19 pandemic situation, on-line communication in every aspect of life is very important. Currently international conferences, workshops, symposia and most of the work is done virtually. This wave of technological and social developments has given a powerful impetus to the phenomenon that has emerged since the end of the nineteenth century, globalization. Ultimately, globalization itself means setting no boundaries, communicating without limits, and seeing everything as a whole. Liberalization of markets and integration into the world economy would find these countries unprepared institutionally and morally to the great pressures that economic opening would bring. Economic globalization, like any phenomenon, has its advantages and disadvantages. This paper will further highlight the negative aspects of globalization. Its negative impact is evident in all links of financial systems. This paper will focus more on the negative impact that the liberalization of countries in the banking sector may have, as an important part of the financial system. The first part of the paper analyzes globalization, as an inevitable phenomenon of our days. In the second part of the paper, the focus is on the banking sector. First, the benefits and costs of globalization are presented, followed by a summary of the risks that usually characterize the banking sector in its activity. In the last part of the paper, there are given the relevant conclusions and suggestions.
Factors Affecting Evaluation of Railway Bulk Freight Rate: A Novel Cloud Theory-Based Approach

Railway freight rates are seen as a key driving factor of global trade activities, influenced by numerous factors. Given the limitations of fuzziness and randomness of variable quantification in the previous studies, this paper proposes a cognitive cloud model of factors influencing railway bulk goods freight rates. In the cognitive cloud model, randomness and fuzziness are described by three parameters. Furthermore, a cloud generator including forwarding and backward cloud generators is designed to solve the bidirectional conversion between qualitative indicators and quantitative values. In addition, we propose a floating cloud gathering algorithm to determine the weight of the index system to solve the uncertainty problem in the transformation process of qualitative indicators. Finally, the cognitive cloud model and the adapted algorithm are used to perform an in-depth analysis of the affecting factors of Z Railway Bureau freight transport pricing.
Discussion on the experimental teaching practice of the course "Soil and Fertilizer Science"

The Soil and Fertilizer Science is a compulsory basic course in agronomy, horticulture, and other relative majors. And the experimental teaching part in this course is an important teaching link to develop students' practical application ability, and it has a positive contribution to students' learning theories of crop cultivation, rational fertilization and agricultural environmental protection and enhancing practical skills in agricultural production. To meet the cultivation target of research application talents in our university, we will discuss the teaching contents, teaching methods, and assessment methods of the experimental class to improve the research ability and innovative application ability of students and provide teaching references for the cultivation of research application talents.
Philosophical Results III: Formalizing Epistemic Proceduralism

Prior chapters argued for the intended interpretation (or use) of PLEN as a logic of epistemic norms. On the basis of that interpretation, this chapter uses the PLEN logic of epistemic norms to formalize epistemic proceduralism. More precisely, it shows that, given that protocols can be plausibly interpreted as structures representing or describing the structure of procedural epistemic norms, and protocol-theoretic formulae can be plausibly interpreted as statements expressing properties of epistemic norms, all of the clusters of principles that define epistemic proceduralism (per Chaps. 1 – 3 ) can be derived from the logic of protocols in PLEN. Indeed, with few exceptions, each corresponds to a provable theorem, property of protocols, property of EDGs, or suite of inference rules in PLEN. The exceptions can be derived by applying the protocol-theoretic deontic and norm application extensions of PLEN or exploiting the representation theorems.
Is the Current Deep Learning Paradigm Really the Future?

This paper proposes a new deep learning paradigm in an attempt to provide a new way to break the limitations of existing deep learning. This paper re-examines the rationality of the existing deep learning paradigm, takes supervised learning as the research object, with focusing on the universality and interpretability of the model. Starting from the basic framework, a configurable supervised learning framework is explorably proposed. The complete design process under the proposed framework is demonstrated through a simple regression case, which verifies the feasibility and effectiveness of the framework. In addition, the inspiration of the deep learning paradigm proposed in this paper should be more worthy of attention and consideration.
Exploration and Practice of Ubiquitous Teaching Mode of College English

This research creates an environmental resource system and teaching model for ubiquitous college English learning by creating the media technology conditions for ubiquitous college English learning, allocating resources, and optimizing college English teaching design.Through the extensive application of this model, the problems of the compression of class hours in college English teaching, the lack of ubiquitous English learning resources and platforms, the lack of students' autonomous learning ability and weak English application ability have been effectively solved.It improves the efficiency and effect of college English teaching, and cultivates a team of teachers with high language teaching ability, educational technology level and innovative spirit.This model has the characteristics of practicability and innovation, and its staged achievements have been publicized and reported by the media for many times, which has strong reference and promotion value for the reform and practice of ubiquitous college English teaching in China.
Teaching project management in a virtual environment: The Virtual Scrum Simulator (ScrumSim)

The Scrum Simulator (ScrumSim) is an interactive multiplayer VR simulation that places the participant in a virtual collaboration environment, in order to train them in the use of a project management methodology i.e., Scrum. In VR, the participants as a team, with the assistance of two avatars, perform intuitive tasks in sprints, cooperate, discuss, interact with the environment and receive feedback on their performance and tasks. The novelty of this approach lies not only in the unique design elements but also in the use of avatars and the utilisation of in-game data (task efficiency and communication).
More Sanity Checks for Saliency Maps

Concepts are powerful human mental representations used to explain, reason and understand. In this work, we use theories on concepts as an analytical lens to compare internal knowledge representations in neural networks to human concepts. In two image classification studies we find an unclear alignment between these, but more pronounced, we find the need to further develop explanation methods that incorporate concept ontologies.
FAKE NEWS DETECTION IN HINDI NEWS USING A PASSIVE CLASSIFIER

During this modern time when people have such easy access to social media and internet, they have become very connected and sometimes it takes less than a minute for any piece of information to get viral.Consequently, fake news is spreading very easily and quickly on those platforms which lead to inappropriate actions and consequences.Sometimes this fake information is spread by people intentionally to create chaos among the people.The aim of this paper is to create a model wherein it classifies each piece of information provided to it into two categories, either non-hostile, fake, offensive or defamation.In order to accomplish the project's objective, we have suggested the algorithm term frequency -inverse document frequency.It is a statistical technique for determining how pertinent a word is in a group of documents.It is widely used for information retrieval and summarization.This method is used to calculate the term frequency of each word and further classify the words according to the occurrence in each particular type of document in the training dataset.Furthermore, the testing dataset uses this information to find the nature of the text document.This method is proposed for the natural language "Hindi" because of the unavailability of such fake news classifiers in this language.
Governance content, financial risk and innovation: A panel data analysis

The effects of governance content characteristics, financial risk, financial development, and innovation infrastructure variables on the size of patent applications in advanced nations during the post-crisis period are examined in this research. For the 2010-2015 period, a panel dataset of 29 advanced economies was employed. The paper uses a Poisson and a Negative Binomial framework to accommodate national heterogeneity and dispersion concerns. According to the estimation results, financial development and financial risk index benefit patent applications, research and development expenditure, intellectual property rights, and gross fixed capital creation. In addition, according to this study, controlling corruption and upholding the rule of law boost innovation, whereas regulatory quality inhibits innovation in advanced economies.
Short-term prediction of bitcoin value based on ARIMA model

As the world's first and by far the most important cryptocurrency, Bitcoin's price has a strong volatility, which in turn may bring huge profits to investors or return to the original point overnight. Coupled with the dominance of Bitcoin in the currency market and its innovative nature, in summary, both from the perspective of investors and from the perspective of the country as a whole, such research on Bitcoin value prediction will have important practical and practical value. This article selects the daily value of Bitcoin from NASDAQ from January 2021 to March 2021 as data, and will use the ARIMA model and SPSS software to predict prices for the next seven days. By finding the relative error between the predicted value and the actual value in the next seven days, it is found that the values are very small, indicating that the prediction effect of the model is good, and the ARIMA model can be selected as a short-term prediction of the value of Bitcoin.