Reviewerly/exHarmony huggingface dataset:
Evaluation of Semantic Answer Similarity Metrics

There are several issues with the existing general machine translation or natural language generation evaluation metrics, and question-answering (QA) systems are indifferent in that context. To build robust QA systems, we need the ability to have equivalently robust evaluation systems to verify whether model predictions to questions are similar to ground-truth annotations. The ability to compare similarity based on semantics as opposed to pure string overlap is important to compare models fairly and to indicate more realistic acceptance criteria in real-life applications. We build upon the first to our knowledge paper that uses transformer-based model metrics to assess semantic answer similarity and achieve higher correlations to human judgement in the case of no lexical overlap. We propose cross-encoder augmented bi-encoder and BERTScore models for semantic answer similarity, trained on a new dataset consisting of name pairs of US-American public figures. As far as we are concerned, we provide the first dataset of co-referent name string pairs along with their similarities, which can be used both for training and as a benchmark.
Study on the Feature Extraction of the Automatic Blood Type Reading System

To improve the efficiency of image analysis of automatic blood type reading system, a new feature extraction in image processing algorithms is presented. Image processing algorithm based on color channel separation and entropy processing is therefore proposed to extract the color characteristics and gray scale characteristics of blood type images. Under the circumstance of the red blood cell reaction phenomenon with complex diversity, the novel feature extraction algorithm adopts comprehensive extraction of color and gray scale features, which has a greater effect on the efficiency of image analysis than individual feature analysis. Compare to the traditional gray scale projection curve algorithm, the feature extraction of this system basically complies with the requirements of blood type reading.
Ranas de cristal

Guayasamin JM, runner RM, Valencia-Aguilar A, Franco- Mena D, Ringler E, Medina Armijos A, Morochz C, Bustamante L, Maynard RJ, Culebras J. 2022. Two new glassfrogs (Centrolenidae: Hyalinobatrachium) from Ecuador, with comments on the endangered biodiversity of the Andes. PeerJ 10:e13109 https://doi.org/10.7717/peerj.13109
Verifying Outsourced Computation in an Edge Computing Marketplace

An edge computing marketplace could enable IoT devices (Outsourcers) to outsource computation to any participating node (Contractors) in their proximity. In return, these nodes receive a reward for providing computation resources. In this work, we propose a scheme that verifies the integrity of arbitrary deterministic functions in the presence of both dishonest Outsourcers and Contractors who try to maximize their expected payoff. We compile a comprehensive set of threats for this adversary model and show that not all of these threats are addressed when combining verification techniques of related work. Our verification scheme fills the gap by detecting or preventing each identified threat. We tested our verification scheme with state-of-the-art pre-trained Convolutional Neural Network models designed for object detection. On all devices, our verification scheme causes less than 1ms computational overhead and a negligible network bandwidth overhead of at most 84 bytes per frame. Our implementation can also perform our verification scheme’s tasks parallel to the object detection to eliminate any latency overhead.
p-Meta

Data collected by IoT devices are often private and have a large diversity across users. Therefore, learning requires pre-training a model with available representative data samples, deploying the pre-trained model on IoT devices, and adapting the deployed model on the device with local data. Such an on-device adaption for deep learning empowered applications demands data and memory efficiency. However, existing gradient-based meta learning schemes fail to support memory-efficient adaptation. To this end, we propose p-Meta, a new meta learning method that enforces structure-wise partial parameter updates while ensuring fast generalization to unseen tasks. Evaluations on few-shot image classification and reinforcement learning tasks show that p-Meta not only improves the accuracy but also substantially reduces the peak dynamic memory by a factor of 2.5 on average compared to state-of-the-art few-shot adaptation methods.
Language of web: bynet discourse and Belarusian netspeak

It is proved that the modern Internet space creates a fundamentally new communication environment (social networks, chats, etc.), the capabilities of which, in turn, act as a trigger for linguistic transformations. It is the language of Internet communications that is today the field where new trends in language development are most actively formed. The functioning of the language in the network gives rise to a number of new phenomena. So, Internet discourse gives rise to such phenomena as massive abbreviations and an abundance of neologisms (including game ones), acronyms and backronyms, syngrahemics and supragrahemics, interlanguage hybrids, new tools for expressing subject-subject relations (formulas of politeness, for example) and many others. This poses new problems for both linguistics and philosophy of language. For example, it is shown that in the context of Internet communications, the classic dichotomy of verbal speech and written forms of language is blurred: on the one hand, in chats and forums, the language is formally represented by written texts, on the other – interactive dialogues actually set living one-time communication, which allows one to speak simultaneously, interrupt the interlocutor, respond immediately, etc., and all these are characteristic of verbal speech. It is concluded that if until now the main presenter of language in culture has clearly been fiction as embodying the established norm of the correct language, then today language practices (usus) come to the fore, reflecting the trends of linguistic evolution that are forming in the present continuous, that sets a new accentuation in modern culture, namely the prevalence of descriptive linguistics over prescriptive.
A Cyber-Physical Security Framework for Rail Transportation Data Systems

Abstract The rail transport networks have become overwhelmingly digital, with a diverse range of data traffic flowing across systems to track, monitor, and control both electronic/electrical and mechanical subsystems. Introduction of advanced electronic platforms and communications across networks supporting mission-critical public services have significantly emphasized the challenge for detection, containment, and remediation of possible disruptions. Moreover, as the tendency for Internet-of-Things grows among field hardware and control systems, the added vulnerabilities further augment the potential for availability outages and hostile or non-premeditated disruptions to physical assets. Hence, there is a need to develop a cyber-physical perspective to analyze and assess cross-domain attack/defense scenarios and intricate physical repercussions of cyber breaches. The presented research aims to elaborate on characteristics of a comprehensive, holistic, and integrated cyber-physical framework in the context of rail transportation, where instead of the traditional data protection and privacy concerns, the focus revolves around safety-oriented operational resilience and integrity. As a main contribution of the research, the planning challenges involved with implementation of an enterprise-wide cybersecurity vulnerability management methodology are investigated at both strategic and tactical levels. Based on lessons learned from practical real-life project scenarios, best practices recommendations are proposed to mitigate the cyber risk more efficiently and enhance safety, availability, and integrity of the protected network and physical assets.
Trend Analysis in Sales Forecasting and Decision Support Systems AHP Method on the Selection of Types of Motorcycles PT. AHM

During the current Covid-19 pandemic, it has a direct impact on decreasing motorcycle sales at PT. Astra Honda Motor in large enough numbers, resulting in losses for the company. This study aims to analyze the forecasting of motorcycle sales in the future and supported by a decision support system in selecting the type of motorbike that consumers are most interested in. The method used in this research is the Trend method and the Analytical Hierarchy Process (AHP) method. The results of this study are based on the mean square error analysis, sales forecasting method at PT. Astra uses exponential trend analysis. The results of forecasting sales for the next 2 periods using the exponential trend analysis method are 2,715,032 units and 2,671,937 units, the sales levels tend to be the same as sales in the 2020 period. Meanwhile, the results of the decision support system analysis use the Analytical Hierarchy Process method (AHP), in choosing the type of motorbike that consumers are most interested in is an automatic motorbike at 0.63 with the preferred alternative is the fuel consumption aspect of 0.36.
Bringing AI into the Classroom: The Impacts of Gender and Major on English Proficiency

The purpose of this study is to determine whether the use of artificial intelligence (AI) improves English listening and reading proficiency. It focuses on whether its impacts differ by gender and major. The study was conducted in 2020 with 340 freshmen students in Korea. There were 182 male and 208 female students. The participants majored in different areas: 139 students majoring in aeronautics, 130 students studying policing and safety, 121 students studying in the arts department. The TOEIC test was adopted as pre- and post-tests to explore the impacts of using AI on English learning. To analyze the data, two-way ANOVAs were administered. The study found no interaction effects of gender or major on either listening and reading proficiency. However, gender and major, respectively, had significant impacts on listening. Regarding reading proficiency, major alone affected the students’ performance. Based on these findings, pedagogical implications are considered.
Improved detection algorithm of tank and armored vehicles based on YOLOV3-tiny

Target detection technology is a typical application in the military field. It can quickly and accurately find and identify all kinds of enemy vehicle targets in the battlefield, and respond to all kinds of battlefield targets more quickly, which has become the key to improve the battlefield situation. Because the battlefield environment is very complex, the traditional target detection algorithm is not ideal when detecting targets in complex scenes. Therefore, a target detection algorithm for armored vehicles of military tanks based on improved YOLOv3-tiny is proposed, which realizes the automatic detection of military targets in complex environments by deep learning. Firstly, based on YOLOv3-tiny algorithm, ResNext residual network is added to replace the original feature extraction network, which better improves the problem of missing and false detection of small targets and optimizes the convolution network structure. Then, the dense network is introduced, and the features of different layers are fused to realize feature reuse, which improves the efficiency of extracting better features of target vehicles, strengthens the network's ability to learn features, and improves the detection effect. Experimental results show that the recall rate and precision rate are increased by 4.62% and 3.79% respectively, the average precision rate is increased by 4.32%, and the frame rate can reach 78 frames/s.
Structural and Semantic Mapping of Application Programming Interfaces

Modern healthcare providers rely upon Electronic Healthcare Records (EHR) systems to record patient data inside their own organization. Some healthcare providers share this data to facilitate patient care with other providers. Medical devices and healthcare providers can use differing standards of recording healthcare information. The Structural and Semantic Mapper Proxy API solution offers a practical way to tackles the issues of Structural and Semantic mapping of Application Programing Interfaces (API) in a healthcare context to enable connection of all existing systems to a healthcare providers EHR creating a single source of truth regarding the treatment of patients and enabling healthcare providers to bridge the gap between external EHR systems.
On the Effective Development and Management of University Alumni Resources

As colleges and universities gradually deepen their understanding of the value of alumni resources, more and more colleges and universities begin to pay attention to the development and management of alumni resources, and incorporate alumni work into the overall development plan. This paper will analyze the important role of alumni resources in the development of higher education, and put forward suggestions on how to reasonably and efficiently develop and manage alumni resources.
The Problem of Human Spiritual Experience in I. A. Ilyin’s Works

Introduction. The problem of spirituality is one of the topical in science and very important in practice. The article is devoted to the analysis of the concept in spiritual experience, developed by the famous Russian philosopher I. A. Ilyin. Materials and Methods. I. A. Ilyin considers spiritual reality as an integral part of the world, which every person inevitably has to face as an ontological basis for the need in spiritual experience. It has special properties that are inaccessible to sensory-empirical knowledge. Therefore, it cannot be detected using traditional methods of cognition and described using the usual categories of analysis of the material world. In order, to discover and comprehend it, special “spiritual organs – evidence, conscience, sense of justice, artistic vision, love” are required [6, p. 102]. Spiritual reality appears to a person in the form of subjective phenomena: moral, aesthetic, intellectual experiences. But this does not deny the fact of its existence. Conclusion. I. A. Ilyin has convincingly proved this in his works. A necessary condition for comprehending spiritual reality is the spiritual being of a person. As one gains spiritual experience, a cardinal change of a person takes place, his transformation into a “spiritual personality”. Spiritual experience is not innate, but every normal person is predisposed to assimilate it. It depends on himself, since the spiritual experience is perceived personally. Other people can create the necessary conditions for this, but they cannot replace the subject. The modern education system is incapable of forming genuine spiritual experience in the younger generation. I. A. Ilyin warned about the negative consequences of people’s lack of spirituality.
Layanan informasi untuk meningkatkan penyesuaian diri siswa

self-adjustment is an ability that students need to have in the transition period. Sometimes there are still students who have not been able to adjust themselves optimally. One of the efforts that can be provided is through information services. The purpose of this study was to determine whether information services were able to improve students' self-adjustment. This research is an experimental type of quantitative research with a one group pretest-posttest control group design. The population in this study was class VIIC MTsNegeri 2 Palu totaling 34 students. All students were used as research samples. To measure the level of adjustment of students used adjustment scale. Data were analyzed through descriptive and inferential statistics. The results showed that information services were able to improve students' self-adjustment
A Discussion on the Innovation of Physical Education in Colleges Under the New Media Environment

The social economy in China is undergoing a critical period of transformation and upgrading. New media technology is booming and is widely used in various fields. In the new media environment, the use of new media in the field of education has also garnered attention. With the popularization and dissemination of new media by modern college students, college physical education has ushered in not only new development opportunities, but also various challenges. In the new media environment, means such as flipped classroom will become an innovative trend, and teachers can further promote the innovative development of college physical education as well as improve the efficiency and quality of this kind of education through online education, short videos, social software, and other auxiliary methods [1]. Based on this, this paper makes a comprehensive analysis of the significance of using new media technology in college physical education and proposes corresponding strategies for the innovation of college physical education under the new media environment, in hope to provide some reference, improve the effectiveness of college physical education, and promote the concept of “lifelong physical education.”
Normative support of upbringing activities

Attention to the issues of organizing educational work with students intensiﬁ ed after the recognition by the President of the Russian Federation V.V. Putin education “federal function”. Legislative acts regulating the educational function, issues of documenting education in educational organizations that implement programs of secondary vocational education are considered. In accordance with the instruction of the Ministry of Education of the Russian Federation, mock-ups of the Exemplary Work Program of Education and the Exemplary Calendar Plan of Educational Work were developed. According to the requirements of the Federal Law of December 29, 2012 No. 273-FZ “On Education in the Russian Federation”, managers and teachers of educational organizations must create such conditions for the student so that, as part of the development of the chosen qualiﬁ cation, he has the opportunity to show the best sides of character, join the corporate culture future place of work, record successes and achievements. The law provides that in the course of the implementation of academic disciplines in an activity form (including all types of practical training), each student will be oﬀ ered the opportunity to build a personal trajectory to achieve positive feelings and attitudes towards Russian civil (basic) norms and traditional spiritual and moral values, i.e. to form personal results (to follow the path of their achievement). The algorithm for the implementation of the working program of education is analyzed in detail.
An Advanced Amalgam of Nature-Inspired Algorithms for Global Optimization Problems

Large-scale global optimization problems are ambitious and quite difficult to handle with deterministic methods. The use of stochastic optimization techniques is a good choice for dealing with these problems. Nature-inspired algorithms (NIAs) are stochastic in nature, computer-based, and quite easy to implement due to their population-based nature. The Grey wolf optimizer (GWO) and teaching-learning-based optimization are the most recently developed and well-known NIAs. GWO is based on the preying strategies of grey wolves while TLBO is based on the effect of the influence of a teacher on the output of learners in a class. NIAs are quite often stuck in the local basins of attraction due to the improper balancing of exploration versus exploitation. In this paper, an advanced amalgam of nature-inspired algorithms (ANIA) is developed by employing GWO and TLBO as constituent algorithms. Initially, an equal number of solutions are assigned to both NIAs to perform their search process of population evolution; then, in later iterations, the number of solutions are allocated to each constituent algorithm based on their individual performance and achievements gained by each algorithm in the previous iteration. The performance of an algorithm is determined at the end of iteration by calculating the ratio of total updated solutions to the total assigned solutions in the amalgam. The proposed strategy effectively balanced the exploration versus exploitation dilemma via compelling the parent algorithms to show continuous improvement during the whole course of the optimization process. The performance of the proposed algorithm, ANIA is evaluated on recently designed benchmark functions of large-scale global optimization problems. The approximated results found by the proposed algorithm are promising as compared to state-of-the-art evolutionary algorithms including the GWO and TLBO in terms of diversity and proximity. The proposed ANIA has tackled most of the benchmark functions efficiently in the parlance of evolutionary computing communities.
Tangential Cover for 3D Irregular Noisy Digital Curves

This paper presents a discrete structure, named adaptive tangential cover (ATC), for studying 3D noisy digital curves. The structure relies mainly on the primitive of blurred segment of width $$\nu $$ and on the local noise estimator of meaningful thickness. More precisely, ATC is composed of maximal blurred segments of different widths deduced from the local noise values estimated at each point of the curve. Two applications of ATC for geometric estimators of 3D noisy digital curves are also presented in the paper. The experimental results demonstrate the efficiency of ATC for analyzing 3D irregular noisy curves.
Features of the Structure of V.S. Bayevsky’s Biographical Essays&#x0D; on Historians

The article is devoted to V.S. Bayevsky, the Smolensk scientist and writer,&#x0D; and his analysis of biographical essays about historians from the cycle of video&#x0D; lectures for graduate students «The History of Science in Scientists’ Biog-&#x0D; raphies». The selected essays contain information about the life and work of out-&#x0D; standing historiographers of the XIX century, such as S.M. Solovyov and&#x0D; V.O. Klyuchevsky. Digitized lectures from Bayevsky’s personal archive represent&#x0D; a unique theoretical material according to the presented factual information based on a large source base. The study of the proposed essays made it possible to identify the features of their structure by determining the ways of constructing&#x0D; the concept of the scientists’ personality.
Ludus: An Optimization Framework to Balance Auto Battler Cards

Auto battlers are a recent genre of online deck-building games where players choose and arrange cards that then compete against other players' cards in fully-automated battles. As in other deck-building games, such as trading card games, designers must balance the cards to permit a wide variety of competitive strategies. We present Ludus, a framework that combines automated playtesting with global search to optimize parameters for each card that will assist designers in balancing new content. We develop a sampling-based approximation to reduce the playtesting needed during optimization. To guide the global search, we define metrics characterizing the health of the metagame and explore their impacts on the results of the optimization process. Our research focuses on an auto battler game we designed for AI research, but our approach is applicable to other auto battler games.
EIGHT LISTENING SKETCHES AND AN INTERVIEW WITH JOAN LA BARBARA

Abstract Eight ‘listening sketches’ form the basis of an interview with experimental vocalist and composer Joan La Barbara. The conversation, a retrospective of La Barbara's compositions, is divided into four sections: Early experiments; Multi-track works; Words; New and recent works – pandemic times.