Reviewerly/exHarmony huggingface dataset:
Points from the SENCo‐Forum

British Journal of Special EducationVolume 48, Issue 3 p. 393-396 Points from the SENCo-Forum Points from the SENCo-Forum The SENCo-Forum – how it began and continued K. Wedell, K. WedellSearch for more papers by this author K. Wedell, K. WedellSearch for more papers by this author First published: 11 October 2021 https://doi.org/10.1111/1467-8578.12378Read 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 onFacebookTwitterLinked InRedditWechat Volume48, Issue3September 2021Pages 393-396 RelatedInformation
Evidence-based Policy and Data-based Administration Law: Comparison and Implications of US and UK Laws

The purpose of this paper is to explore the role the data-based administrative law in data-based policy. To this end, the case of the US, which recently implemented the Evidence-based Policy Act, and the case of the UK, which actively uses public data for policy were analyzed. The Evidence-Based Policy Act of the US stipulates strategic and evaluation plans, evaluators and statistics officers for evidence-building, data advisory committees, etc. in relation to “evidence-building activities” that are closely related to the evaluation plans of the federal government. In relation to the use of public data produced by the federal government, the OPEN Government Data Act provides for a Strategic Information Resource Management Plan including the Open Data Plan, a Comprehensive Data Inventory, a Federal Data Catalogue, best practices related to data use, protection, provision and production, and committees to promote inter-agency data sharing agreements. With the aim of building a learning-oriented government organization, importance on “policy evaluation” and “policy questions”was placed. The UK's administrative data research is approaching a research network for public data. Started as part of the Secretary to the Treasury's Big Data plan in 2012, the Digital Economy Act of 2017 has a clear purpose of allowing researchers to use administrative data, as it provides a legal basis for researchers to access government data in a safe way. In this way, administrative data research acts as a bridge between government and academia. Based on such partnerships with academia, internal governance and active cooperation with the government are also being carried out. The UK recognizes the importance of public data, and the statistical agency functions as a data hub. Based on these discussions, certain implications were presented to the Korean situation as to what role data-based administration laws play in each country's data-based policies.
Towards a Phylogenetic Measure to Quantify HIV Incidence.

One of the cornerstones in combating the HIV pandemic is being able to assess the current state and evolution of local HIV epidemics. This remains a complex problem, as many HIV infected individuals remain unaware of their infection status, leading to parts of HIV epidemics being undiagnosed and under-reported. To that end, we firstly present a method to learn epidemiological parameters from phylogenetic trees, using approximate Bayesian computation (ABC). The epidemiological parameters learned as a result of applying ABC are subsequently used in epidemiological models that aim to simulate a specific epidemic. Secondly, we continue by describing the development of a tree statistic, rooted in coalescent theory, which we use to relate epidemiological parameters to a phylogenetic tree, by using the simulated epidemics. We show that the presented tree statistic enables differentiation of epidemiological parameters, while only relying on phylogenetic trees, thus enabling the construction of new methods to ascertain the epidemiological state of an HIV epidemic. By using genetic data to infer epidemic sizes, we expect to enhance understanding of the portions of the infected population in which diagnosis rates are low.
Blockchain-based Trusty Buyer Coalition Scheme Using A Group Signature

Without trust, buyers may not join a coalition. Despite the tremendous need for trustworthy relationships in buyer coalitions, no current buyer coalition scheme explicitly tackles confidence issues with blockchain technology. This study proposes an algorithmic design, the blockchain-based trusty buyer coalition scheme, to satisfy the trust requirement among different actors while forming the coalition. All activities forming a coalition through a decentralized public ledger can be explicitly examined. Consequently, the proposed algorithm can ensure anonymity within a community, resulting in trusting relationships. Furthermore, the proposed algorithm can ensure correctness and accountability by recognizing misbehavior and enforcing alternative forms of punishment. Additionally, the discovered algorithm can be applied to mobile commerce applications.
Analysis On The Effect Of Emotion Of Intonation Based Features With Reference To Assamese Emotional Speech Signals

Speech is a communicational source of exchanging information between human begins. Emotional speech is another precious source through which human begins expressed their internal feelings. Emotion is promoted by some particular situations, and the emotion recognition from human speech  is  considered as a most vital  subject in the field  of human-computer interfaces (HCIs) to identify with  people. Analyzing on Pitch and Formant of different gender speakers in different emotions such as Angry and normal and two different software,  in Assamese language for observing the variation between them by applying Two-way ANOVA testing is presented in this paper. The main objective of current work is to detect the effect of emotions, sex and Software’s on extracted features from recorded Assamese emotional speech of different gender in selected age group. Results of analysis of variance testing varies that emotion and sex both has significantly effect on both extracted features in recorded voices by distinct software.
METHOD FOR CONSTRUCTING NONLINEAR WAVELET CODE TO ENSURE DATA INTEGRITY IN COMMUNICATION CHANNELS

A method for constructing a nonlinear wavelet code (NVC) to ensure data integrity in communication channels, taking into account current threats to information security in a modern dynamic stochastic environment, is proposed. A special place among the methods of combating threats to the integrity of information is occupied by noise-resistant encoding. The article presents a computationally effective method for ensuring data integrity in communication channels by using nonlinear transformations and wavelets. The approximation of the wavelet transform refers to the division of the signal into approximating and detailing components. Continuous and discrete wavelet transforms are widely used [2] for signal analysis in modern communication channels. The set of functions defining the wavelet transform belongs to the space of square-integrable functions on a straight line and provides a necessary condition for constructing constructions of nonlinear codes based on the theory of wavelet decomposition. As is known, in the process of wavelet analysis, the signal is decomposed along the orthogonal basis formed by shifts of the wavelet function. A distinctive feature of this approach is that convolution of the signal with wavelets allows us to identify the characteristic features of the signal in the area of localization of these wavelets. To perform computational calculations, you need a set of scaling function coefficients and a wavelet. The wavelet transform matrix depends on the coefficients of the scaling function. The results presented in the article describe a new approach to ensuring data integrity in communication channels using nvcs. A computational example is presented.
SPENT<sup>+</sup>: A Category- and Region-aware Successive POI Recommendation Model

To facilitate successive Point-of-Interests (POI) recommendation, the categories of POIs and the regions where POIs are located are seldom considered in existing models. In view of this, we extend a state-of-the-art model SPENT, named SPENT <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">+</sup> , by taking the category and the region into considerations. In SPENT <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">+</sup> , we formulate category- and region-aware check-in sequences, design the similarity trees to aggregate similar features, and finally establish the category latent vectors and region latent vectors, respectively. The above two latent vectors are aggregated as the category-region-aware latent vectors. Therefore, the category-region-latent vectors are sent to an LSTM together with conventional check-in sequences to improve successive POI recommendation. We conduct two real datasets, Gowalla and Foursquare, and compare with state-of-the-art methods in experiments. Results show that SPENT+ outperforms the baselines in terms of precision and recall.
The management of the process of forming university students’ tolerance in the conditions of digitalization of higher education

The article deals with the formation of students’ tolerance and management of this process. The aim of the article is to cover theoretical and empirical aspects of the management of students’ tolerance formation. A special focus is made on the role of tolerance in modern society and for the educational system as well as on the contradictions which determine the relevance of tolerance in the university environment. Tolerance is a complex, multifaceted phenomenon which touches all aspects of student life. Entering the university, young people find themselves surrounded by many different personalities who have their own values and beliefs in life. This calls for the necessity to respect and accept a different opinion and a different way of life. Therefore, nowadays the formation of tolerance acquires special importance in educational institutions as it is tolerance which is the basis of effective communication in a politically cultural society like the Russian Federation. So the formation of tolerance is a social order as it is impossible to develop the educational system unless this aspect is included. We scrutinized relevant literature on the issue and came to the conclusion that the formation of tolerance can be only achieved by means of democratic management and students’ conscious choice of tolerant attitudes and behavior, which excludes any pressure or foisting. The study involved the choice of methods and an algorithm, which comprised the diagnosis of the mentioned parameters, conducting a formative experiment, repeated check of the parameters and performing a statistic analysis of the results. The study was carried out on the base of the Institute of Foreign languages, RUDN University (Russia). The research results allow drawing a conclusion about high effectiveness of the implemented actions aimed at the formation of students’ tolerance.
Fully Secure Lattice-Based ABE from Noisy Linear Functional Encryption

Constructing lattice-based fully secure attribute-based encryption (ABE) has always been a challenging task. Although there are many selective secure ABE schemes from the hardness of learning with errors (LWE) problem, it is hard to extend them to fully security, since the dual system technique in pairing-based cryptography cannot be applied to lattice-based constructions.In this paper, we take a different approach: constructing fully secure ABE from another primitive called noisy linear functional encryption (NLinFE) which can be constructed from LWE problem. We give a fully secure ciphertext-policy ABE scheme for CNF formulae which security relies on the security of NLinFE and hardness of LWE. Since current constructions for NLinFE only satisfy bounded collusion security, our resulting scheme is also bounded collusion only, but it can be easily extended into unbounded security if unbounded NLinFE can be shown to exist. Also, since existing NLinFE schemes are inefficient, we give a new construction for NLinFE with better efficiency, hence our ABE construction is more efficient than other existing bounded collusion ABE/FE schemes.
Peningkatan Keterampilan Menulis Aksara Jawa Menggunakan Media Audio Visual di Sekolah Dasar

The purpose of this study was to improve writing skills in Javanese script through audio-visual media for fifth graders at SDN Karangdadap for the 2019/2020 academic year. The subjects of this research are fifth grade teachers and fifth grade students at SDN Karangdadap with a total of 25 students. This type of research is classroom action research (CAR) which consists of two cycles. Each cycle consists of four stages, starting from planning, action, observation and reflection. Data were collected through observation, interviews, and tests. The valid data used are source triangulation and technique triangulation. The data were analyzed using an interactive analysis model consisting of data collection, data collection, and drawing conclusions or levers. The conclusion of this research is that audio-visual media can improve writing skills of Javanese script in fifth grade students of SDN Karangdadap in the 2019/2020 academic year.
Enhancement Detection DDoS Attacks Using Hybrid N-Gram Techniques

DDoS attacks have always been a concern of cyber experts. To detect DDoS attacks, there are several methods that can be used. One of the methods used in this research is the N-Gram technique. The n-Gram technique analyzes the payload of data packets that enter the network to obtain attack patterns, data is captured and analyzed after which it is compared with net data packets. The chi-square distance value that is close to 1 indicates that the two packages are very similar, so that the data packet is not an attack. A value less than 1 means the data packet is categorized as an attack. In this research, the threshold for determining the level of attack can be lowered to obtain a very high detection accuracy. As a result, the 2-Gram technique has a detection accuracy rate with the lowest false positive value of around 13% with the highest true positive ratio reaching a value of 99.98%.
Freedom of Expression and Hate Speech in Ethiopia: Observations (Amharic)

Freedom of expression is one of the human rights enshrined under International human right instruments. However, hate speech in the course of exercising this right has the potential to pose threats on the peace and security of nations and wellbeing of individuals. This has brought about arguments in favor of limitations to expression and against the limitations owing to unintended adverse impact of such limitations in the exercise of freedom of expression. In the Ethiopian case, ‘Hate Speech and Disinformation Prevention and Suppression Proclamation No. 1185/ 2020’ has been enacted. The Proclamation indicates prohibited acts of hate speech and its exceptions. In particular, the generic terms contained in the definition given to ‘hate speech’ need to be carefully examined. However, the implications of provisions that set exceptions to ‘hate speech’ in the new law have not yet been subject to adequate academic discourse. This article examines these issues. By consulting different international human rights instruments, experience of other countries and scholarly literature, the article examines the appropriateness, constitutionality and implications of the Proclamation on the right to freedom of expression. Moreover, it indicates potential challenges that the exceptions will pose on the process of implementing the Proclamation in real court cases.
아로마 에센셜 오일 흡입이 자율신경계 반응, 뇌파 및 집중력에 미치는 효과

Purpose: This study was an experimental research study to examine the effects of aroma essential oil inhalation on autonomic nerve system response, electroencephalogram and concentration. Methods: The participants were 92 healthy adults: 32 in the experimental group, 30 in the placebo group, and 30 in the control group. In the experimental group, lemon and rosemary oil were mixed in a ratio of 4: 1, and 0.1 ml was dropped on gauze and then naturally inhaled for a total of 30 minutes. The application for the placebo group was 0.9% saline solution, and for the control group, no treatment. To determine the effects, the autonomic nervous system response was measured by applying Canopy 9 Plus 4.0 before the experiment and at 10, 20, and 30 minutes after the experimental application, and an electroencephalogram was taken using QEEG-8. The computerized neurocognitive function test for measuring concentration was given before the experiment and at 30 minutes after the treatment. Results: There were no significant differences in the homogeneity tests for general characteristics and for the dependent variables prior to the experiment. There was a significant difference in sympathetic nervous activity between the experimental group, placebo group, and control group (F=3.78, p=.027), and the experimental group had higher sympathetic nervous activity than the control group. There was no statistically significant difference on the electroencephalogram between the ⍺ and beta waves of the three groups. The Stroop Color-Word interference test (color) of the three groups for concentration measurement was significantly different between pre test and at 30 minutes after the treatment (F=7.40, p=.001), and the score for the experimental group increased compared to the control group. Conclusion: The findings showed that the inhalation of aroma essential oil activated the sympathetic nervous system and partially increased the level of concentration.
Medicine reminder and monitoring system for secure health using Internet of things.

Internet of things IoT is a system of internet-connected devices which collect and transfer data over a wireless network without human intervention. Smartphones, wearable devices like health band or smart watch are examples of IoT. IoT works on four component sensors, network communication, analytics cloud and application. Non adherence to treatment is a major reason for poor control of diseases like hypertension, diabetes which ultimately leads to complications. Medicine reminder apps and smart devices can be very helpful to overcome this problem. Smart watches and devices have applications which can monitor persons heart rate, blood oxygen, body temperature, blood pressure, ECG etc. Readings of these parameters can be shared with a doctor who is connected through internet. In critical situation immediate intervention can be done by the physician by advising appropriate medicine. Thus use of IoT is crucial in monitoring of health of the individual. In Covid-19 pandemic patients are being monitored and treated form distance with the help of internet connected smart devices. Shortage of skilled human resources in health care sector can be addressed by using this technology. Its will be a boon for health services in public sector. Considering the economical turnover of IoT in health care sector globally, adopting this technology in India is need of hour.
A Stepwise Approach for High-Dimensional Gaussian Graphical Models

We present a stepwise approach to estimate high dimensional Gaussian graphicalmodels. We exploit the relation between the partial correlation coefficientsand the distribution of the prediction errors, and parametrize the model in termsof the Pearson correlation coefficients between the prediction errors of the nodes’best linear predictors. We propose a novel stepwise algorithm for detecting pairsof conditionally dependent variables. We compare the proposed algorithm withexisting methods including graphical lasso (Glasso), constrained `l1-minimization(CLIME) and equivalent partial correlation (EPC), via simulation studies andreal life applications. In our simulation study we consider several model settingsand report the results using different performance measures that look at desirablefeatures of the recovered graph.
Forecasting and Testing the Transformation Potential of Videogames

The article presents the analysis of methodological approaches put into practice in psychological researches and devoted to transformation potential of videogames. There are certain grounds for suppositions concerning the reasons of contradictory scientific speculations about the peculiarities of computer games impact on gamers. The article gives the description of the original model of videogames analysis according to which a videogame is presented as a complex of components reflecting the presence and the degree of intensity of game peculiarities and mechanisms. The author explained the advantages of its application, and operating algorithm. “The Witcher 3: Wild Hunt” videogame has been analyzed as an example to demonstrate transformation potential. The study showed that the experience of playing “The Witcher 3: Wild Hunt” contributes to a high level of internality in frustration and professional and social internality of gamers, as well as their firm stand in taking risk.
Formalization of the “Immaterial Features” Conveyed by the Iconographic Cultural Heritage Entities

The “digitization practices” used up-to-now to produce digital counterparts of the iconographic Cultural Heritage entities – paintings, drawings, sculptures, frescoes, mosaics, murals etc. – have mainly focused on the “physical” (dimensions, materials, supports, painting etc. techniques …) aspects of these entities. This means that all the “immaterial features” that characterize these items – from the stories/narratives they tell to all sort of feelings, memories, evocations and aesthetic experiences they can evoke in their end-users – are largely neglected. We argue that, to take correctly these immaterial aspects into account, we must use particularly powerful and expressive knowledge representation systems. In this context, the paper presents and discusses then in some detail the formal representations, obtained using the NKRL’s (Narrative Knowledge Representation Language) tools, of complex iconographic situations that characterize two masterpieces of the Renaissance period. The results obtained, even if very preliminary, show that NKRL should be borne in mind as a useful tool for properly representing in digital format the “immaterial features” above.