Reviewerly/exHarmony huggingface dataset:
Explaining the Decisions of Convolutional and Recurrent Neural Networks

In this chapter we discuss the algorithmic and theoretical underpinnings of layer-wise relevance propagation (LRP), apply the method to a complex model trained for the task of visual question answering (VQA), and demonstrate that it produces meaningful explanations, revealing interesting details about the model’s reasoning. We conclude the chapter by commenting on the general limitations of current explanation techniques and interesting future directions.
Dependent Rules and Carrier Rules

Rule composition makes it possible to model an important kind of deviation from the rule independence criterion – cases in which the application of one rule is directly dependent on that of another, carrier rule. In such cases, the only use of the dependent rule is as part of a composite rule incorporating both the dependent and its carrier. Where the definition of a word form involves two carrier rules, it can further happen that the same dependent rule composes with both of them, engendering a pattern of multiple exponence that deviates from the unique sequence criterion. I discuss two cases of this sort of rule dependency: Limbu verb morphology exhibits a pattern in which dependent rules compose with their carrier rules; Sanskrit presents a pattern of the reverse sort, in which a carrier rule composes with its dependent.
Canonical Morphotactics

In this chapter, I discuss the preliminary assumptions of the rule-combining approach to morphotactics and advance the two fundamental hypotheses that underlie it: the morphotactic holism hypothesis and the morphotactic variety hypothesis (Section 1.2). In Section 1.3, I review previous proposals that provide empirical support for the morphotactic holism hypothesis, which (unlike the morphotactic variety hypothesis) is not a novel idea. In Section 1.4, I discuss the nature of canonical morphotactics, for which I introduce ten criterial characteristics, construed in rule-based terms. In Section 1.5, I give examples of phenomena that possess these characteristics as well as of phenomena that do not apparently possess them. The morphotactic phenomena to be analyzed in the following chapters deviate from some of these canonical characteristics, but reinforce conformity to others provided that a rule-combining approach is assumed. In Section 1.6, I anticipate the range of topics to be discussed in subsequent chapters.
Extending Canonical Morphotactic Criteria to Composite Rules

Besides affording a way of modeling deviations from canonical morphotactics, rule composition makes it possible to see apparently recalcitrant morphotactic patterns as conforming to canonical criteria if these are assumed to cover composite rules as well as simple rules. I examine an apparent deviation from the integral stem criterion in Sanskrit and apparent deviations from the rule opposition criterion in Latin, Limbu, and Sanskrit. Each of these phenomena can be reconciled with the canonical criterion from which it apparently deviates if this criterion is assumed to cover composite rules as well as simple rules. All of these are cases in which deviation from the minimal rule criterion facilitates conformity to other canonical morphotactic criteria.
Metaphysics of Corporeality in the Post-modern Thinking. A. Artaud’s Theater: Self-less Actions, Mercantile Identity Accents

The article is devoted to the experience of postmodern representation of the metaphysics of corporeality. The meaning of A. Artaud’s “Theatre of Cruelty” is shown as a living act of ontologization of the body through the pain phenomenon. The game of mercantile and thinking participant in the action is distinguished. The purpose of scientific research: to distinguish between psychological and metaphysical experiences as those that determine the bodily and carnal goals of the participants; accordingly, to show the actions of selfish and selfless roles with their ability to pass or block pain. Objectives of the research: to investigate the mechanisms of postmodern understanding of the metaphysics of the body through A. Artaud’s experience; to present the sphere of the Theater of Cruelty as the destiny of mankind to be a participant in the horrible and to be able to sympathize with it; to highlight the game of mercantile and selfless participant in ambiguous actions; to emphasize pain as a criterion of ontologizing the body; to show the places of the Theater of Cruelty in action on living examples. The scientific novelty lies in the view of the metaphysics of corporeality through the Theater of Cruelty and existential pain. Being a man of postmodern thinking, A. Artaud considers metaphysics in action and shows corporeality by a joint action, which is an event.
Hate Speech: A Pragmatic Assessment of the European Court of Human Rights’ Jurisprudence

Abstract This paper aims to offer a fresh start for addressing several conundrums relating to hate speech. The method of research combines a conceptual analysis with a possible model for evaluating the European Court of Human Rights’ (ECtHR) decisions on hate speech. First , drawing on a Gricean account of communication, the argument proposes a working definition of hate speech: hate speech is best understood as a public speech act, aimed at subordinating individuals, which causes harm to targeted groups. Second , the paper offers a taxonomy of the different forms of hate speech, based on their degree of explicitness and detachment from the speaker’s intentions. The most explicit forms of (harmful) hate speech – e.g., racial slurs, fighting words, or overtly sexist remarks – will be distinguished from implicit forms of (harmful) hate speech – e.g., innuendo, insinuation, and irony. Third , the author develops a categorical framework for hate speech that can be used as a standard for evaluating the jurisprudence of the ECtHR. The author also discusses three limitations of the model: a) the absence of a European consensus, b) puzzled speakers, and c) difficulty in determining harm.
Risky Translations: Securing TLBs against Timing Side Channels

Microarchitectural side-channel vulnerabilities in modern processors are known to be a powerful attack vector that can be utilized to bypass common security boundaries like memory isolation. As shown by recent variants of transient execution attacks related to Spectre and Meltdown, those side channels allow to leak data from the microarchitecture to the observable architectural state. The vast majority of attacks currently build on the cache-timing side channel, since it is easy to exploit and provides a reliable, fine-grained communication channel. Therefore, many proposals for side-channel secure cache architectures have been made. However, caches are not the only source of side-channel leakage in modern processors and mitigating the cache side channel will inevitably lead to attacks exploiting other side channels. In this work, we focus on defeating side-channel attacks based on page translations.It has been shown that the Translation Lookaside Buffer (TLB) can be exploited in a very similar fashion to caches. Since the main caches and the TLB share many features in their architectural design, the question arises whether existing countermeasures against cache-timing attacks can be used to secure the TLB. We analyze state-ofthe-art proposals for side-channel secure cache architectures and investigate their applicability to TLB side channels. We find that those cache countermeasures are notdirectly applicable to TLBs, and propose TLBcoat, a new side-channel secure TLB architecture. We provide evidence of TLB side-channel leakage on RISC-V-based Linux systems, and demonstrate that TLBcoat prevents this leakage. We implement TLBcoat using the gem5 simulator and evaluate its performance using the PARSEC benchmark suite.
Optimal Parameters for Spatial Distribution Modeling of Global Horizontal Solar Radiation in Iraq

Solar radiation plays an essential role in all interior physical processes and the radiative budget of the earth-atmosphere system. However, information about the spatial distribution of global solar radiation or its components is limited and exclusive at some scientific centers that specialized in solar radiation physics. Based on daily data of global solar radiation from (1984) to (2004) available at (16) locations in Iraq retrieved from NASA e-archive, this study aims to determine the optimal parameters of the experimental model to estimate the amount of global solar radiation on a horizontal surface as a function of latitude only. The results showed that the suggested model which is mathematically expressed by the sum of sine of latitude is highly appropriate for estimation of global solar radiation in clear sky conditions after adjusting the parameters according to geographical location. Through comparison between modeled output and an independent measured, globally used, and satellite available data and based on overall results besides some validity metrics: MBE, RMSE, pRMSD, NSE, R2, and r; It can be concluded the proposed model is achievable with high accurate practically performance to calculate and estimate the horizontal global solar radiation (GH) in Iraq region.
APLIKASI MEDIA PEMBELAJARAN ONLINE MENGGUNAKAN METODE VIDEO VISUAL PADA SMKN 1 WAY TENONG KABUPATEN LAMPUNG BARAT

The desire for web-based learning is the need of teachers and understudies as learning residents. The scholarly network must envision the necessities and advancement of learning innovation applied at SMK Negeri 1 Way Tenong, West Lampung. Online sight and sound video-taking in strategies can be gotten from cell phone gadgets. The normal understudy and instructor are familiar with these gadgets to interface utilizing internet-based life in their correspondence. In this investigation, an online-based E-learning model was created using video accounts to encourage access to materials and tasks given to all understudies as per educational program 13 dependent on class and subject educators as indicated by the blueprints of showing projects and taking in program units from every instructor.
The Effect Of Providing Verbal Reinforcement On Students' Learning Behavior In Class V At Sdn Brangkal 2, Bandar Kedungmulyo, Jombang

This research was conducted by providing verbal reinforcement to the fifth grade students by giving a questionnaire sheet to find out the results of the learning carried out by the teacher. Lack of verbal reinforcement of learning behavior makes students have a negative nature. In this case the provision of verbal reinforcement has a positive impact on learning behavior which will increase student learning outcomes and teachers get learning objectives well.&#x0D; This study uses a quantitative approach with ex post facto research methods. The subjects in this study were students of class V SDN Brangkal 2, totaling 10 children. Data collection techniques using observation, questionnaires, and documentation. The data analysis used is to calculate the results of the questionnaire on verbal reinforcement and learning behavior followed by calculating the correlation coefficient. The research was conducted in the even semester of the 2020/2021 academic year.&#x0D; The research was conducted by giving a questionnaire sheet. The first is verbal reinforcement and the second is student learning behavior. The results of the research conducted at SDN Brangkal 2 showed that the results of the verbal reinforcement questionnaire were 59.2 and the results of the student learning behavior questionnaire were 59.7 of these results followed by the correlation test with the results of 0.94 which indicated that there was an effect of giving verbal reinforcement on behavior Student learning behavior is seen from the correlation coefficient interpretation guidelines. Thus Ho is rejected and Ha is accepted so that it is concluded that there is an effect of providing verbal reinforcement on the learning behavior of fifth grade students at SDN Brangkal 2, Bandar Kedungmulyo District, Jombang Regency.&#x0D; Keywords: Giving Verbal Reinforcement, Learning Behavior
ENSINO SUPERIOR EM SAÚDE ATRAVÉS DE ATIVIDADES DE EXTENSÃO UNIVERSITÁRIA DURANTE A PANDEMIA DE COVID-19: A TELEREABILITAÇÃO DE PACIENTE IDOSO COMO ESTRATÉGIA DE FORMAÇÃO DO FISIOTERAPEUTA

Paramyxoviridae do gênero Morbillivirus, que acomete geralmente cães e outros animais da ordem Carnívora, tem distribuição mundial e pode provocar alterações em diferentes sistemas do organismo animal, como o digestório, respiratório, oftálmico, tegumentar e neurológico, sendo que as alterações neurológicas podem permanecer ABSTRACT: Canine distemper is a serious infectious disease caused by a virus (Canine distemper virus -CDV) belonging to the family Paramyxoviridae of the genus Morbillivirus that usually affects dogs and other animals of the Carnivorous order, has a worldwide distribution and can cause changes in different systems of the animal organism, such as digestive, respiratory, ophthalmic, integumentary and neurological, and neurological changes may remain as sequelae.Neosporosis is caused by the protozoan Neospora caninum, it is considered of extreme importance, due to its high power of contagion and lethality, having a worldwide distribution.The animals have encephalomyelitis and myositis, and in many cases there are neurological sequelae.Often in both distemper and neosporosis conventional treatments are ineffective for complete remission of neurological signs, so the veterinarian may opt for treatments or therapies that aim to improve the patient's quality of life.The objective of this paper is to report the case of a canine patient diagnosed with distemper and co-infection with neospora caninum and demonstrate the importance of integrative therapies used with a focus on improving quality of life, such as physiotherapy, acupuncture and ozone therapy.
Discriminative Transfer Learning for Driving Pattern Recognition in Unlabeled Scenes

Abstract: Driving behavior has a large impact on behaviour of driver. The lack of a labeled data problem in a driving scene substantially hinders the driving pattern recognition accuracy. However, modeling driving behavior under the dynamic driving conditions is complex, making a quantitative analysis of the the driving behaviour. In this paper, the Driver behaivor dataset was collected from dataset repository. Then, we have to implement the pre-processing techniques. Then, the system is developed the machine learning algorithm such as Random forest and Support Vector Machine algorithm. The experimental results shows that some performance metrics such as accuracy, precision, recall and f1-score. By using the ML is, to classify the Aggressive, normal, slow.
Sorting Real Numbers in Constant Time Using n^2/log^cn Processors

We study the sorting of real numbers into a linked list on the PRAM (Parallel Random-Access Machine) model. We show that n real numbers can be sorted into a linked list in constant time using n2 processors. Previously n numbers can be sorted into a linked list using n2 processors in O(loglogn) time. We also study the time processor trade-off for sorting real numbers into a linked list on the PRAM (Parallel Random Access Machine) model. We show that n real numbers can be sorted into a linked list with n2/t processors in O(logt) time. Previously n real numbers can be sorted into a linked list using n3 processors in constant time and n2 processors in O(loglogn). And then we show that input array of n real numbers can be sorted into linked list in constant time using n2/logcn processors for any positive constant c. We believe that further reduction on the number of processors for sorting real numbers in constant time will be very difficult if not impossible.
Empirical Research on Realizing, Evaluating, and Validating a Conceptual Breast Cancer e-portal Model with Arabic Content

This paper presents an empirical research that realizes a previous research of a conceptual breast-cancer e-portal model with Arabic content. The paper starts with briefing the previous research, after that, it highlights the gaps need to be bridged and the problems need to be solved. A real development of an e-portal prototype is done for achieving the research goal. This e-portal prototype has applied the conceptual model of the previous research.
Facebook's Crisis Management Strategy in Response to Users' Information Breach

Facebook exposed a vast amount of personal information about its users.This study will pay attention to Facebook's crisis management strategy in response to a severe issue involving users' information breach on 19 March 2018.
Theoretical investigation of ultrafast binary data patterns recognition based on VCSEL-SA

Based on a vertical-cavity surface-emitting laser with saturated absorber (VCSEL-SA) subject to optical injection, we proposed an ultrafast pattern recognition scheme of four-bit binary data and theoretically investigated the recognition performances. The results show that, patterns recognition of different four-bit binary data at Gb/s rate can be realized by adjusting the injection weight of each bit number and optimal weight values can be determined. Although noise has some influences on the patterns recognition speed and accuracy, this proposed system has a certain robustness to noise on the whole. These results provide a promising application prospect for VCSEL-SA based ultrafast photonic neuromorphic system in pattern recognition field.
Research on partial null compensator with double-sided switching off-axial reflector

Wavefront-based aspheric metrology techniques generally require a compensation lens to compensate for the primary aberrations. To expand the adaptability of the surface to be tested, this paper proposes and demonstrates a partial null compensator structure that can switch between the front and back mirror sides. The presented compensator comprises two sets of off-axis reflecting parts and a pre-compensation spheric lens in an integrated structure. An appropriate off-axis reflection combination mode can be selected for the range of the conic coefficient of the measured surface. With the simulation result, the presented compensator can adapt to a large-scale variation of the surface conic coefficient K from -10 to +10. The average residual wavefront aberration is no more than 1λ (PV) and 1/4 λ (RMS). The results show that the proposed structure can be efficiently applied to wavefront detection or interferometer for data post-processing.
Confidence Judgement Network: An Efficient Sample Filter for Lifelong Distillation

Unlabeled raw data of the real world collected by the edge computing platforms can be utilized to improve the performance of the lightweight deep learning models by using Lifelong Distillation (LD) method. However, not all the raw data samples are equally beneficial to such a process. In this paper, we propose a novel Confidence Judgement Network (CJN) to refine the raw data and to accelerate the LD processing. First, we design a new CJN model and use it to filter easy samples. Second, we scissor Lite-HRNet to get a slimmed student network—Half-LiteHRNet for knowledge distillation. Finally, we apply the new LD+CJN method to train our new image segmentation network, receiving a 39.4% reduction in network size and a 17.1% reduction in calculation load. Experiments show that, the new CJN model successfully improves LD by a roughly +3.96% increase in AP with a tiny cost, a negligible 0.038% rise in calculation load.
ONLINE LEARNING: NEW OPPORTUNITIES OR THREATS?

The article examines the problems of online distance learning at universities in Kyrgyzstan in the context of the pandemic coronavirus, indicates its features. Here is the example of the analysis of the students satisfaction of the International Faculty of Osh State University with online learning, the pros and cons of this format of learning are indicated. Questioning of 390 students showed a number of problems in the organization of online learning. As shown by analysis of responses, only 25% of respondents answered that they were satisfied with online learning. At the same time, 75% of students expressed dissatisfaction with this form of learning and named a number of disadvantages. All of these problems raise questions about whether online learning is not a threat to the learning youth, whether it gives the level of knowledge, skills and abilities required by state educational standards and real practice? Particular attention in the article is paid to the mechanisms of solving the problems of online learning in order to use its unique opportunities in the development of education. The materials of the article were tested at the international conference «Educational Strategies and Innovations in the Age of Digitalization» held on October 5-6, 2022 in the American University of Central Asia.
Library Automation with E-Granthalaya Software

The effect of ICT has changed the "Traditional Libraries" in to "Automated Libraries".Libraries were served as "Hybrid Libraries" and new forms of libraries are "Digital Libraries" & "Virtual Libraries".This paper is concentrated on the Library Automation its requirements and various components needed with special reference to E-Granthalaya software.
ON THE ROLE OF ADDITIONAL PROFESSIONAL EDUCATION IN THE DEVELOPMENT OF DIGITAL SKILLS OF SCHOOL TEACHERS (ON THE EXAMPLE OF KYRGYZSTAN)

The article is devoted to the study of the problem of developing digital skills among school teachers in Kyrgyzstan. The rapid development of digital technologies dictates new needs in the education system associated with modern equipment and software, primarily with the training of teaching staff. The authors review the legal acts regulating additional vocational education in Kyrgyzstan. The results of a study conducted among secondary school teachers are proposed to study the level of their digital literacy. The materials of the article were tested at the international conference "Educational strategies and innovations in the era of digitalization", which was held on October 5-6 at the American University of Central Asia.
A Novel Collaborative Consistent Learning for Person Re-Identification

In this paper, we propose a new collaborative consistency learning method for person ReID that improves generalization and robustness to label noise without introducing additional inference costs. First, sophisticated heterogeneous auxiliary branches are introduced in particular intermediate layers of the lightweight person ReID network to extract more accurate and efficient pedestrian feature information. The leading network and the auxiliary branches are trained collaboratively on the same training data to obtain feature information from different perspectives. In addition, a cooperative consistency loss function is proposed to maximize the consistency between the viewpoints for mutual complementation and regularization to improve the model performance. The experimental results on the market1501 dataset show that the collaborative consistency learning method can significantly improve performance.