Reviewerly/exHarmony huggingface dataset:
Whither Programs as Specifications.

Unifying theories distil common features of programming languages and design methods by means of algebraic operators and their laws. Several practical concerns --- e.g., improvement of a program, conformance of code with design, correctness with respect to specified requirements --- are subsumed by the beautiful notion that programs and designs are special forms of specification and their relationships are instances of logical implication between specifications. Mathematical development of this idea has been fruitful but limited to an impoverished notion of specification: trace properties. Some mathematically precise properties of programs, dubbed hyperproperties, refer to traces collectively. For example, confidentiality involves knowledge of possible traces. This article reports on both obvious and surprising results about lifting algebras of programming to hyperproperties, especially in connection with loops, and suggests directions for further research. The technical results are: a compositional semantics, at the hyper level, of imperative programs with loops, and proof that this semantics coincides with the direct image of a standard semantics, for subset closed hyperproperties.
Quick Catch-Up With a Friend

This is a story about repeating yourself...The phone rang and I prevaricated about answering it. I was having about 5 simultaneous conversations - via text
Physical implementation of quantum nonparametric learning with trapped ions.

Nonparametric learning is able to make reliable predictions by extracting information from similarities between a new set of input data and all samples. Here we point out a quantum paradigm of nonparametric learning which offers an exponential speedup over the sample size. By encoding data into quantum feature space, similarity between the data is defined as an inner product of quantum states. A quantum training state is introduced to superpose all data of samples, encoding relevant information for learning in its bipartite entanglement spectrum. We demonstrate that a trained state for prediction can be obtained by entanglement spectrum transformation, using quantum matrix toolbox. We further work out a feasible protocol to implement the quantum nonparametric learning with trapped ions, and demonstrate the power of quantum superposition for machine learning.
PENGGUNAAN METODE BERMAIN PERAN UNTUK PENINGKATAN KEMAMPUAN BERBICARA PADA SISWA KELAS V SD INPRES TUREKISA KECAMATAN GOLEWA BARAT KABUPATEN NGADA

Indonesian language learning in 2013 curriculum generally aims to improve students' ability to communicate in Indonesian properly and correctly, both oral and written. The research questions are; how is the implementation of the role playing method in SD Inpres Turekisa and how are students' speaking abilities after using the role playing method?. This study uses study Classroom Action Research and the data were analyzed qualitatively. The use of role playing methods can improve the speaking skills of fifth grade students in the SD Inpres Turekisa because students play a daily role in their life. Role playing can relieve the teacher in teaching because it is more likely to achieve learning goals when compared to the use of lecture and question and answer methods. By acting alone, students will better understand and understand problems and they are also trained to portray the characters in the story. In addition, role playing can train students' speaking skills properly and correctly. The results shows that role playing method can improve students' speaking abilities with an average in each cycle, namely: cycle I: 2.82, cycle II: 3.64, and cycle III: 4.54. thus, it can be concluded that role playing through various children's stories can improve the speaking skills of fifth grade students very good.
A Massive Data Migration Framework

This document describes a standardized framework for implementing themassive data migration between traditional databases and big-dataplatforms on the cloud via Internet, especially for an instance ofHadoop data architecture. The main goal of the framework is to providemore concise and friendly interfaces for users more easily and quicklymigrate the massive data from a relational database to a distributedplatform for a variety of requirements, in order to make full use ofdistributed storage resource and distributed computing capability tosolve the bottleneck problems of both storage and computingperformance in traditional enterprise-level applications. Thisdocument covers the fundamental architecture, data elementsspecification, operations, and interface related to massive datamigration.
SOME ASPECTS OF THE PSYCHOLOGICAL AND PEDAGOGICAL SUPPORT FOR THE ADAPTATION OF FUTURE TEACHERS

The article is devoted to the study of some aspects of psychological and pedagogical support for the adaptation of future teachers. Objective: to determine the impact of the proposed strategies of psychological and pedagogical support on the ability of students to adapt. The “Adaptability” (Multilevel Personality Questionnaire) questionnaire by A. Maklakov and S. Chermianin was used in the study to diagnose students of the 1st-6th years of bachelor’s and master’s degree programs of higher education at the faculty of arts of a pedagogical higher education establishment. The results of the introduction of strategies of psycho-pedagogical support showed that students grow their ability to regulate their interaction with the environment, that there is an increase in social contacts, social activity and self-esteem. It has been proven that the introduction of the proposed strategies of pedagogical support at the faculty of the arts of a pedagogical higher education establishment has a direct impact on the ability of students to adapt.
Kasualitatea eta kausalitatea sentsore bidez jasoriko datuen bidez sotutako diseinuetan: Lau saiakera praktiko

EnglishIn order to achieve a complex formal aesthetic or to simulate organicity, in the computational desgn is common to use pseudo random data produced by mathematical functions. In this article, the use of data collected by sensors that record a large amount of White noise is proposed as an alternative. Through four designs made by apparently random data is explored the effect that can have knowing the events that have produced such data. euskaraEstetika formal konplexua lortzeko edo organikotasauna simulatzeko xedearekin ohikoa da diseinu konputazionalean funtzio matematikoez sorturiko datu pseudo-aleatorioak erabiltzea. Artikuluan alternativa bezala zarata zuria asko jasotzen dituzten sentsoreen bitartez batutako datuak erabili izan dira. Lau diseinurekin, itxuraz aleatorioak diren datu horiek batzean leku izandako gertakarien ezagutzak diseinuaren pertzepzioan eta interesean izan dezakeen eraginaz mintzatuko gara
Detecting TCP Flows Inside EcryptedVPN Tunnels

Encrypted tunnels have made analyzing Internet traffic harder, when a virtual private network is used the flows become intertwined and thus lose their unique characteristics. These characteristics ...
“I HAVE A THOUGHT AND I AM THINKING IT” (CRITICISM OF THE AUDIT APPROACH IN HUMANITIES RESEARCH AND EDUCATION)

This article points out the problem of incompatibility of certain types of humanities research with the standard requirements to scientific paper, which have been developed in recent decades. In humanities studies, the process of reflection and development of a thought is often the main content of scientific work; however in the current standard this aspect is almost ignored. The standard set of requirements imposed upon papers by most scientific journals makes it difficult to obtain the full scientific status for those humanities works that are based on innovative conceptual approach and introduce new perspectives. The aim of this paper is to show the failure of the audit approach to humanities research and substantiate the necessity of extending the current format of a journal article giving it greater freedom and flexibility. In the paper the following methods are used: analysis of relevant literature, method of rationale, historical method, and comparative analysis. The proposed relaxation of the standard requirements to scientific article may stimulate humanities studies that have ground-breaking innovation but do not fit into the standard format. Moreover, it will contribute to the development of conceptual thinking of students of higher school humanities programs, which will create opportunities for more intensive development of the humanities.
Role of non-linear data processing on speech recognition task in the framework of reservoir computing

The reservoir computing neural network architecture is widely used to test hardware systems for neuromorphic computing. One of the preferred tasks for bench-marking such devices is automatic speech recognition. However, this task requires acoustic transformations from sound waveforms with varying amplitudes to frequency domain maps that can be seen as feature extraction techniques. Depending on the conversion method, these may obscure the contribution of the neuromorphic hardware to the overall speech recognition performance. Here, we quantify and separate the contributions of the acoustic transformations and the neuromorphic hardware to the speech recognition success rate. We show that the non-linearity in the acoustic transformation plays a critical role in feature extraction. We compute the gain in word success rate provided by a reservoir computing device compared to the acoustic transformation only, and show that it is an appropriate benchmark for comparing different hardware. Finally, we experimentally and numerically quantify the impact of the different acoustic transformations for neuromorphic hardware based on magnetic nano-oscillators.
A new guide for guided reading: More guided, more reading

Guided reading and particularly the use of levelled texts has become the norm in many classrooms as a way of differentiating reading instruction in the classroom. But is it delivering on its promise? Is the demand for compliance having a negative impact on innovation? And is it time to work smarter not harder?
Specific Parameter-Free Global Optimization to Speed Up Setting and Avoid Factors Interactions

Meta-heuristics utilizing numerous parameters are more complicated than meta-heuristics with a couple of parameters for various reasons. In essence, the effort expected to tune the strategy-particular parameters is far more prominent as the quantity of parameters increases and furthermore, complex algorithms are liable for the presence of further parameter interactions. Jaya meta-heuristic does not involve any strategy-specific parameters and is a one-stage technique. It has demonstrated its effectiveness compared to major types of meta-heuristics and it introduces various points of interest, such as its easy deployment and set-up in industrial applications and its low complexity to be studied. In this work, a new meta-heuristic, Enhanced Jaya (EJaya) is proposed to overcome the inconsistency of Jaya in diverse situations, introducing coherent attraction and repulsion movements and restrained intensity for flight. Comparative results of EJaya in a set of benchmark problems including statistical tests show that it is feasible to increase the accuracy, scalability and exploitation capability of Jaya while keeping its specific parameter-free feature. EJaya is especially suitable for a priori undefined characteristics optimization functions or applications where the set-up time of the optimization process is critical and parameters tuning and interactions must be avoided.
Embodied View-Contrastive 3D Feature Learning.

Predictive coding theories suggest that the brain learns by predicting observations at various levels of abstraction. One of the most basic prediction tasks is view prediction: how would a given scene look from an alternative viewpoint? Humans excel at this task. Our ability to imagine and fill in missing information is tightly coupled with perception: we feel as if we see the world in 3 dimensions, while in fact, information from only the front surface of the world hits our retinas. This paper explores the role of view prediction in the development of 3D visual recognition. We propose neural 3D mapping networks, which take as input 2.5D (color and depth) video streams captured by a moving camera, and lift them to stable 3D feature maps of the scene, by disentangling the scene content from the motion of the camera. The model also projects its 3D feature maps to novel viewpoints, to predict and match against target views. We propose contrastive prediction losses to replace the standard color regression loss, and show that this leads to better performance on complex photorealistic data. We show that the proposed model learns visual representations useful for (1) semi-supervised learning of 3D object detectors, and (2) unsupervised learning of 3D moving object detectors, by estimating the motion of the inferred 3D feature maps in videos of dynamic scenes. To the best of our knowledge, this is the first work that empirically shows view prediction to be a scalable self-supervised task beneficial to 3D object detection.
DEVELOPMENT OF MODULAR EDUCATIONAL PROGRAMMES BASED ON THE FORMATION COMPETENCIES

Development of modular educational programmes based on the formation of trainees’ competencies solves the problem of ensuring a unified approach for the construction of educational programmes of specialties. The implementation of requirements of the Bologna process to ensure the quality of higher education in accordance with the Dublin descriptors implements the novelty of the research in the framework of the modular technology of education in Kazakhstan. The aim of the study is to reveal the process of development of modular educational programmes through the organization of pedagogical process of Formation of Professional competence of trainees. The primary methods used are theoretical generalization, justification and systematization. The study design includes discussions of authors from different countries, definitions of main meanings, schemes, figures, tables. The key results of study is to reveal the Structure, Model, Scheme and stages of the organization of pedagogical process of Formation of Professional competence. Specific asked questions for research in general prospects of implementation of modular educational programmes are formulated in the conclusion.
ANALYSIS OF SARAH KENYON’S MOTIVATION THROUGH HER NEEDS IN MARRY HIGGINS CLARK’S ALL AROUND THE TOWN

This research discussed the analysis of Sarah Kenyon, as the main character in Marry Higgins Clark’s All Around the Town novel by applying the psychological approach. The researcher aimed at revealing character motivation and her personality type based on her need fulfillment in this story. The researchers chose this novel as a subject for this research because of curiosity in gaining more comprehension about other characters which is hopefully can give the elaboration toward previous research about this novel. Therefore, the researchers conducted the analysis of Sarah Kenyon by applying Maslow’s hierarchy of needs and Hippocrates’ four personality types. The result of this research showed that Sarah Kenyon is the protagonist character. In addition, based on her need portrayal in the novel the researcher concluded that love and belongingness is the dominant need as motivation for Sarah to fulfill her needs. Besides, the researcher found out that Sarah’s personality is belonging to the phlegmatic character. Her phlegmatic temperament gave a good influence toward her need fulfillment process. Due to her kind-hearted, she accepted treatment from other people kindly too. Also, she had good friends and beloved people who always came to give her support and help to face a hard situation. So, even though Sarah met an obstacle in fulfilling her needs, she finally could make it through. Penelitian ini membahas karakter utama pada novel All Around the Town karya Marry Higgins Clark dengan menggunakan pendekatan psikologi. Penelitian ini bertujuan mengungkap motivasi dan tipe kepribadian pada karakter ini berdasarkan pemenuhan kebutuhannya dalam cerita novel tersebut. Peneliti memilih novel ini sebagai subjek penelitian atas dasar rasa ingin tahu dan hasrat untuk menggali informasi penting tentang karakter lain yang diharapkan dapat memberi semacam elaborasi terhadap penelitian sebelumnya yang juga dilakukan pada novel ini. Maka dari itu, peneliti melakukan analisa pada karakter Sarah Kenyon dengan mengaplikasikan teori hirarki keutuhan oleh Maslow dan teori empat jenis keperibadian oleh Hippocrates. Hasil penelitian ini menunjukan bahwa Sarah Kenyon merupakan karakter protagonis. Sebagai tambahan, berdasarkan kebutuhan yang tergambar di dalam novel tersebut, peneliti menyimpulkan bahwa kebutuhan akan cinta dan keterlibatannya dalam berhubungan dengan orang lain merupakan kebutuhan yang sifatnya dominan sebagai motivasi untuk Sarah memenuhi kebutuhannya. Disamping itu, peneliti juga menemukan bahwa kepribadian Sarah tergolong ke dalam kelompok karakter plekmatis. Kepribadiannya sebagai karakter plekmatis memberikan pengaruh yang baik terhdap proses pemenuhan kebutuhannya. Karena kebaikan hatinya, maka ia diperlakukan dengan baik juga oleh orang lain. Juga, ia memiliki teman-teman yang baik, orang-orang tercinta yang selalu dating untuk member dukungan juga bantuan untuk menghadapi kesulitan yang ada. Maka dari itu, meskipun Sarah menemui kesulitan dalam memenuhi kebutuhannya, pada akhirnya ia berhasil melewatinya dengan baik.
Electrostatic forces approach to color edge detection based on cubical voxel adjacencies

In this paper we study a modification of the original method by B. Bouda et al. for edge detection in color images based on electrostatic forces. We examine the effect of substituting the twelve diagonal neighbor voxels that are 12-adjacent to the voxel at the center by other types of the voxel adjacencies in the calculation of the electrostatic forces. We present a theoretical background of electrostatic forces for each types of neighbor voxels which conduct to a number of color edge detector versions. The proposed method is tested and compared with some other methods with satisfactory results.
PENGARUH ALOKASI WAKTU PEMBELAJARAN BAHASA INDONESIA TERHADAP MINAT BELAJAR SISWA SMK

This research was motivated by the lack of enthusiasm of students when learning Indonesian in the afternoon, resulting in a large number of activities carried out by students outside of learning. This scientific article has the intention to see the effect of time allocation on students' interest in learning Indonesian learning in class X of SMK Informatics Fithrah Insani. This study uses descriptive qualitative methods. The research technique uses open and closed questionnaire techniques and observation by observing objects directly. All students of SMK Informatika Fithrah Insani were chosen as the population. Class X as many as 46 students were taken into the study sample. The researcher proposed a problem statement as follows 1) whether there was an effect of time allocation on students' learning interest in learning Indonesian. The results of the research prove that the allocation of time for Indonesian language learning given at the last hour influences students' interest in learning Indonesian.
Comparative Analysis of PyTorch and Caffe Frameworks.

Deep learning is a model of machine learning whose demand is rapidly increasing. It can change the view of artificial intelligence and achieve the goal significantly. With many deep learning frameworks available, the choice of selection becomes difficult. In this paper, two deep learning frameworks namely PyTorch and Caffe are analysed, with various parameters and deep learning architectures. The frameworks are implemented for specific applications and results are compared to make the better choice.
NEURO-PSYCHOLOGICAL APPROACH TO TEACHING GENERAL ENGLISH TO THE FIRST YEAR STUDENTS OF THE TRANSLATION DEPARTMENT

The work deals with the problems of improving General English teaching materials for undergraduates in terms of the neuro-psychological trends in Foreign Language Teaching Methodology and developing a tutorial based on the knowledge of students’ cognitive styles caused by the individual profile of the functional asymmetry of the brain, i.e. we aim at proposing the methods of neuropsychological approach implementation in the educational process. The topicality of the research is attributed to the lack of teaching materials applying neuro-psychological approach, though it is proved to be productive, as its implementation is known to help the process of mastering a foreign language. The primary methods used are as follows: observation, pedagogical experiment, statistical processing of data. Neuro-psychologically grounded teaching methodology forms the basis of the English language successful mastering, as it takes into account such extremely important features of the student as the profile of his inter-hemispheric asymmetry, which in its turn determines the specific cognitive style, and hence the type of mastering the foreign language.
Do you care more about preserving our ...

Do you care more about preserving our indigenous #Ghanaian languages?Did you know..? there is a #Twi and other Ghanaian languages Wikipedias? Register here: http://bit.ly/TwiWiki
Business Crime Reduction Schemes: An examination of operation, management and best practice

This report presents the findings of a study into the operation of groups of commercial organisationswhich come together to reduce the impact of theft, violence, anti-social behaviour and other crimes andassociated behaviours on their businesses.We refer to such groups as Business Crime Reduction Schemes (Schemes), a term used in this report toinclude Business Crime Reduction Partnerships (BCRPs), shopwatch schemes, pubwatch schemes,schemes provided by shopping centres for the benefit of their tenants, and other similar operations.The report draws upon data gathered through a national survey of Scheme managers conducted betweenOctober 2018 and January 2019 to consider the design, focus, management, governance, membership andcollaborative activities of Schemes and identify the key characteristics, achievements, challengesencountered and points of best practice concerning their activity. These are presented as key findingsthroughout the report and as a series of guiding principles for such Schemes.
A Study of Online Hate Speeches: Legitimation Processes by Nigerian Political Actors

Online social media offers platforms for political gladiators to engage in hate speeches as a means to perpetual power contestation. This in turn demands total restructuring of political institutions, through different legitimation strategies. The current study highlights hate speeches’ legitimation process and its entrenchment as a contemporary societal cultural object. The paper extends Vaara’s et al (2006) and Johnson’s (2006) application of the theory of legitimacy in products marketing to the evaluation of political hate speeches’ legitimation process. Data comprising of twenty-five (25) excerpts on hate speeches from Politically Exposed Persons across Nigeria were purposively selected from online media sources. The study revealed that any particular hate speech of political gladiators is a cultural product marketed by the elites through the legitimisation processes of innovation, local validation, diffusion and generalalidation with its negative influence on Nigeria’s political institutionalisation processes.Key Terms: Evaluation, Discourse, Hate Speeches, Ideology, Context