Reviewerly/exHarmony huggingface dataset:
Антология ненависти к книге: либрицид в истории и культуре

In this article, the author reveals the meaning of the term «libricide», and also speaks about the forms of libricide in history and culture. The basis of the arguments cited in the article formed the historical facts of the XX–XXI centuries and landmark works of art.
Collecting 3A Data to Enhance HCI in AIS

3A refers to content aware, context aware, and learner aware intelligent tutoring system (ITS) [2]. The idea behind this is that any ITS should be delivering content intelligently by knowing about the state of the user . The state of the user could be emotional or even physical. Almost all the ITS are more or less intelligent to deliver content. But less intelligent to know whether the learner is accepting the content. In addition, the context consists of two components: context of the content and context of the environment. It is easy for an ITS to be aware of the context of the content (e.g., calculus in case of integrals) but very few ITS take into account the context of the environment. For example, a learner is accessing content in a crowded environment from her cell phone and a learner is accessing content inside a library where it is calm. Contexts of these two learners are different. Moreover, the learner awareness includes emotional states as well as physical states of a learner. In this research our focus is to collect data by enabling a 3A learning system in AutoTutor [11]. AutoTutor is a conversation-based ITS that uses an expectation-misconception tailored dialogue to promote learning. Several questions involved in designing 3A enabled AutoTutor. How to collect 3A data without violating learners’ privacy is the most important one. All other design questions revolve around this.
Penerapan Model Pembelajaran Kooperatif Tipe Jigsaw untuk Meningkatkan Motivasi dan Hasil Belajar IPS Materi Manusia, Tempat, dan Lingkungan Pada Siswa Kelas VII G SMP Negeri 1 Adiwerna Tahun Pelajaran 2019 / 2020

Various problems that inform a teacher in the classroom are indicators that&#x0D; the learning motivation of students who receive the subject matter. If learning motivation is low, it will lead to low student learning outcomes because motivation is a determination and effort as a result of the interaction of the learning given by the teacher. The research objective was to increase learning motivation and improve social studies learning outcomes. The steps in the research through cycle I and cycle II include planning, implementing actions, monitoring and reflecting. The results showed that the application of the Jigsaw cooperative learning model could increase the social studies learning motivation from 68.75% in the first cycle to 78.13% in the second cycle. The application of the Jigsaw cooperative learning model could improve learning outcomes in the classical social studies subject from 81.25% in the first cycle to 87.50% in the second cycle. Based on all the results of the research, "Application of the Jigsaw Type Cooperative Learning Model to Increase Motivation and Social Studies Learning Outcomes of Human, Place, and Environment Material in Class VIIG Students of SMP Negeri 1 Adiwerna Academic Year 2019/2020" can be accepted.
Interaction Flexibility in Artificial Agents Teaming with Humans

Author(s): Nalepka, Patrick; Gregory-Dunsmore, Jordan P; Simpson, James; Patil, Gaurav; Richardson, Michael J | Abstract: Team interaction involves the division of labor and coordination of actions between members to achieve a shared goal. Although the dynamics of interactions that afford effective coordination and performance have been a focus in the cognitive science community, less is known about how to generate these flexible and adaptable coordination patterns. This is important when the goal is to design artificial agents that can augment and enhance team coordination as synthetic teammates. Although previous research has demonstrated the negative impact of model-based agents on the pattern of interactions between members using recurrence quantification methods, more recent work utilizing deep reinforcement learning has demonstrated a promising approach to bootstrap the design of agents to team with humans effectively. This paper explores the impact of artificial agent design on the interaction patterns that are exhibited in human-autonomous agent teams and discusses future directions that can facilitate the design of human-compatible artificial agents.
The Political Philosophy of Kwame Nkrumah on Neocolonialism and the Current Debt Situation in Africa

The paper examines the political philosophy of Kwame Nkrumah on Neocolonialism and the current debt situation in Africa. To achieve these objectives, the study used qualitative and content analysis method in analyzing the information generated for the study. Cases and instances from the content analysis showed that: most African countries were in debt almost as soon as they gained political independence. The amount of debt has been constantly rising since then. Findings of the paper observed that, currently African governments spend huge chunks of their annual revenue just to service loans, money that could go quite a distance in developing their economies. From this, it is evident that Africa’s wealth is being repatriated to the richer countries in the west, just like it was in the colonial days, but masked under “debt servicing”, and thus Nkrumah’s notion of economic colonialism. The paper concludes that decade and half after the massive debt forgiveness; African countries face another debt crisis, since 2013, the region’s debt has been on the rise, with the median debt ratio as percent of GDP increasing from 31 percent in 2012 to 57 percent in 2020. The study recommend that Fiscal policies will need to play a greater role in maintaining debt sustainability in the future, Capacity building and strengthening are needed at all levels, including in the area of debt and risk management, financial management, research, and knowledge generation to foster commensurate regulatory capacity.
An Anthropology Study: computer technology utilization in rural schools

In discussing the world's technological advances, computers are the basis for this. Computer technology is used in almost every field. In the 21st century, computer technology is used in school education in almost every state. In developing countries such as Sri Lanka, the study of how computer technology can be used in rural schools attempts to improve the utility of computer technology in rural schools, identify problems in computer technology utilization in rural schools and provide suggestions. We have been tried through research.
Assessment of mass segmentation methods in 3-D ultrasound images

Breast cancer is the most common cancer between women worldwide. Although it is the leading cause of cancer death of women in the world, it can be prevented if it is detected and diagnosed at the early stages. There are various ways of detecting breast cancer varying from mammography to some basic clinical tests and procedures. Automated 3-D breast ultrasound (ABUS) is one of the most advanced breast cancer detection systems which is used as a complementary modality to mammography for early detection of breast cancer. However, it is notable that screening mammograms is so difficult and time consuming for radiologists due to the large variety in shape, size, and texture of 3-D masses in these images. Hence, computer-aided detection (CADe) systems could be considered as a second interpreter in order to assist radiologists to increase accuracy and speed. In this paper, we assess different approaches that have been implemented to segment masses in ABUS images. These approaches vary from pure image processing methods to deep neural networks based on which limits, advantages and disadvantages over each other have been compared.
Formation of students’ media competence on the basis of supervisory methods (on the example of English language)

This article describes briefly the history, formation and application of supervision of instruction and ultimate goal of supervision of classroom instruction on the basis of English language. Supervision, as a field of education practice with clearly delineated roles and responsibilities, did not fall from the sky fully formed. Rather, supervision emerged slowly as a distinct practice, always in relation to the institutional, academic, cultural, and professional dynamics that have historically generated the complex agenda of schooling.
Video Colorizing with Automatic Reference Image Selection

In studies to color black and white videos, it is aimed to make the colored video perceptually meaningful and visually attractive. In this way, old images from the past to the present can be visualized and presented to people in different ways. In this study, the video is colorized by using a model that colorizes images with Convolutional Neural Networks. In this reference-based colorizing study, the frames in the video are colorized according to an automatically determined reference photo. As a new approach different from existing studies, instead of choosing a reference photo for each frame, a system that automatically detects the scene transitions occurring in the video stream and automatically recommends the reference photo suitable for the content of each scene.
Actualization of the professional self-concept in the future orchestra conductors training

Professional training of orchestra conductors is traditionally aimed at performing primarily educational and creative tasks. At the same time, the inner world of a conductor as a leader of the ensemble still needs deeper study. In particular, formation of the conductor’s professional competence will not be effective without necessary personal qualities, self-awareness, self-concept, which involves a total reflection of his activities. The phenomenon of the orchestra conductor’s self-concept is presented not only as a set of ideas and attitudes towards oneself, which has certain characteristics, but also as a subject, which is entrusted with cultural and aesthetic professional responsibilities. The study of the self-concept will facilitate understanding the regulation and management of the internal process in the professional activities of the orchestra conductor. The study relevant because it can reorient the purpose of the educational process from the formation of knowledge, skills and abilities to a broad understanding of the multifunctionality of future conducting and orchestral activities.
Representation of Cognitive States by Shannon Entropy

In this study, we aim to measure the information content of anatomic regions using the functional magnetic resonance images recorded during complex problem solving (CPS) task. We propose an information theoretic method for analyzing the activity in anatomic regions. We estimate two types of Shannon entropy, namely, static and dynamic entropy, and investigate the relationship between the CPS task phases and the entropy measures for the underlying brain activity. We propose a novel method to estimate static and dynamic brain networks using Kulback-Leibler divergence and investigate the validity of the estimated brain networks by modeling two main phases of complex problem solving process. The suggested computational network model is tested using Support Vector Machines. The network models can successfully discriminate the planning and execution phases of CPS with more than 90% accuracy .
EXPERT SYSTEM SELECTION OF SUPERIOR BANANA SEEDS USING FORWARD CHAINING METHOD WITH WEB APPLICATION

Bananas are native to Southeast Asia. The plant of the Musaceae tribe has the Latin name Musa paradisiaca. Banana production in Indonesia is quite large, even Indonesia became one of the largest banana producers in the world. National banana production continues to increase every year, for example from 2,308,379 tons (in 1988) to 2,417,760 tons (in 1989). The largest banana-producing region is located in Java (Suhardi et al, 2002). An expert system is a computer-based system that uses knowledge, facts, and reasoning techniques to solve problems that can usually be solved only by experts in the field. Forward Chaining is a search technique that begins with known facts, then matches those facts to the sections IF of the rules IF_THEN. Based on the results of the implementation found that the application program expert system could facilitate the farmers in the determination of seeds of banana seeds in accordance with the criteria and this application can run well and easy in its use.
학습자 말뭉치를 기반으로 한 중국어권 한국어 학습자의 목적격 조사 오류 연구

The purpose of this study is to analyze the aspects and causes of errors in Chinese Korean Learners’ use of the object particle ‘eul/reul’(을/를). The research was based on a large scale learner’s corpus. The study focuses on examing the following three aspects: 1) the development of error changes according to the learners’ Korean ability, 2) the cause of errors, and 3) substitution errors due to L1 interference. Of the 2,856 objective particle errors, substitution errors consisted of about 68% of the errors. It is worth noting that as the learners’ Korean abilities increased, so too did the rate of error, while the rate of substitution errors increased at a more gradual rate as learners’ fluency increased. In the analysis of the cause of errors, the results will confirm that intrusive interlingual interference caused an increase in error rates 42% substitution errors were due to the influence of the learners’ L1. These results can be interpreted to signify that L1 interference emerges more frequently as fluency increases. In the analysis of substitution errors, the subject particle, ‘i/ga’(이/가), was used in place of the object particle ‘eul/reul’(을/를) most often; mainly in the case of particles followed directly by predicates. As for other particles that substituted the objective ‘erl/reul’(을/를), the forth meanings of ‘erl/reul’(을/를) do not have the ‘V+Obj.’ sentence structure in Chinese. This study is to serve as an explanation of Chinese Korean learners’ objective case ‘eul/reul’(을/를) errors, as well as to help in researching pedagogical methods for these learners.
A Survey on Block Chain and Bitcoin – Challenges & Applications

Block chain is as of late presented and changing the advanced world conveying another point of view to security, flexibility and productivity of framework. While at first promoted by Bit Coin, Block chain is significantly more than an establishment for digital money. It offers a safe method to trade any sort of good administration or exchange. This paper exhibits an exhaustive review on Block chain Technology and Bit coin. Bitcoin has emerged as the most successful crypto currency since its appearance back in 2009. Besides its security robustness, two main properties have probably been its key to success: anonymity and decentralization. In this paper, we provide a comprehensive description on the details that make such crypto currency an interesting research topic in the privacy community. We perform an exhaustive review of the bitcoin anonymity research papers that have been published so far and we outline some research challenges on that topic.
Understanding the Effects of Mitigation on De-identified Data

Machine learning algorithms can play a significant role in peoples lives. The data used in these algorithms often contains sensitive information and can have inherent biases. We investigate the effects of the interaction between mechanisms designed to preserve privacy and to mitigate biases. The mechanisms employed for this investigation were k-anonymity for de-identification and re-weighting for bias mitigation. The experiments were threefold. First, we investigated the effects of mitigation on de-identified data. Second, we measured the effects of three data parameters: class imbalance ratio, privileged positive outcome ratio and unprivileged positive outcome ratio. Third, we assessed the utility of the mitigation mechanism in a healthcare context. Using real-world data, we tested the effects of different levels of de-identification. We primarily utilised three measures to indicate the procedures’ effects. First, for accuracy, we analysed simple accuracy and balanced accuracy rate. Second, we measured the number of positive outcomes for the privileged and unprivileged class and the disparate impact for fairness. Third, for utility, we measured the recall rate as well as a novel metric; recall ratio. We display these two metrics based on the classification threshold to indicate the trade-off between achieving high true positives while limiting overall positive outcomes. This trade-off is analogous to a medical testing scenario where the objective is to have high accuracy of true positives and minimise cost given overall percent positives.
Lossless JPEG image compression based on FPGA

- Recently, images became the dominant media material for transmitting or storing across different applications used by different people. So, there was a serious need for finding more effective and efficient image compression techniques to reduce the big size of such multimedia files. This paper proposes lossless JPEG image compression and decompression system based on FPGA. Generally, the proposed system consists of a software side and a hardware side. In the software side, the digital image file is prepared to be processed by the hardware side. The hardware side is proposed to be consists of two main processing circuits which are the prediction circuit for calculating the predicted value of each pixel in the image and the encoding circuit that was represented by a modified RLE (Run-Length-Encoder) to encode the result obtained through subtracting the predicted value from the real value for each pixel to produce the final compressed image file. The compression ratio obtained for the proposed system was equal to 1.7487, while the maximum data throughput that obtained was 71.718 MP/s.
Regression, encoding, control: an integrated approach to shared representations with distributed coding

Author(s): Henselman-Petrusek, Gregory; Giallanza, Tyler; Musslick, Sebastian; Cohen, Jonathan | Abstract: Artificial systems currently outperform humans in diverse computational domains, but none has achieved parity in speed and overall versatility of mastering novel tasks. A critical component to human success, in this regard, is the ability to redeploy and redirect data passed between cognitive subsystems (via abstract feature representations) in response to changing task demands. However, analyzing shared representations is difficult in neural systems with distributed nonlinear coding. This work presents a simple but effective approach to this problem. In experiments, the proposed model robustly predicts behavior and performance of multitasking networks on natural language data (MNIST) using common deep network architectures. Consistent with existing theory in cognitive control, representation structure varies in response to (a) environmental pressures for representation sharing, (b) demands for parallel processing capacity, and (c) tolerance for crosstalk. Implications for geometric (dimension, curvature), functional (automaticity, generalizability, modularity), and applied aspects of representation learning are discussed.
Report on VIP at the School of Education (2017-21): Five Year Review, Performance & Research Pathways

Vertically Integrated Projects (VIP) is an innovative HE pedagogy that was introduced to the University of Strathclyde from the Georgia Institute of Technology in 2012. Initially established for use within the fields of science and engineering, development work by the VIP Leader in the School of Education has resulted in several significant successes for the School, Faculty and University across the time of the current Review. Following a special invitation to present at Annual International Consortium Conference (Atlanta, US) in May 2017, this ongoing initiative was subsequently recognised internationally by the Georgia Institute of Technology as a 'World’s First' in bringing the pedagogy to the field of Humanities and Social Sciences. Using the original School of Education VIP as a lens, it is instructional to reflect on its operation and identify material impact across the term of the current review, together with also postulating on future potential actions. It is evident that through the work of their VIP Leader, the programme continues to grow successfully and now forms a key strategic component of the School of Education, Faculty of HaSS and wider University.
Dynamic Multi-Keyword Search for Secure Data Storage in the Cloud using Cuckoo Filter -

In current days cloud domain gained a tremendous increase of users attention by several small and large scale companies including Software, BPO, Medical, Schools and a lot more. Since there was very less security in the primitive clouds for storing and accessing the information from the remote locations, still there was a lot of demand for the data which is to be stored in the cloud. As we know that in primitive clouds, there are no concepts like privacy for the data in terms of encryption and message digest in order to provide data authorization. In current days cloud servers are almost dishonest in nature by omitting intentionally some qualified results to save computational resources and communication overhead. In this paper, we try to design a new protocol and analyze the importance of Cuckoo filter over encrypted cloud data to provide data search accurately by the cloud users. Here we try to encrypt the data using AES algorithm and try to generate MAC key for the data which is uploaded and downloaded by the cloud users. For data authorization we use MD5 algorithm and with the help of MD5 algorithm, we can generate a short signature to find out the data verification and finally we try to apply Cuckoo filter for data integrity. This cuckoo filter will try to store the data in duplicated manner and try to provide end user with original data.
Finding competitive keywords from query logs to enhance search engine advertising

A novel method is proposed to find competitive keywords for search engine advertising.The method can explore the keyword associations and their topic information hidden in query logs to identify effective keywords for advertisers.Extensive experiments show that the method can help advertisers not only to expand the choices of keywords but also to achieve competitive advertising.The method is demonstrated to outperform the existing methods for keyword suggestion in terms of the evaluation on not only relevance but also competitiveness. This study has proposed a topic based competitive keywords suggestion method called TCK to enhance search engine advertising. On the basis of query logs, the method explores the indirect associations between keywords and extracts the hidden topic information to identify competitive keywords. It can help advertisers not only broaden the choices of keywords but also carry out a competitive strategy for search engine advertising. Extensive experiments have been conducted to demonstrate the effectiveness of the proposed method. Results prove that the proposed method performs better than existing keyword suggestion methods, contributing greatly to the keyword suggestion advertising market.
Zero Pronouns Identification based on Span prediction

The presence of zero-pronoun (ZP) greatly affects the downstream tasks of NLP in pro-drop languages such as Japanese and Chinese.To tackle the problem, the previous works identified ZPs as sequence labeling on the word sequence or the linearlized tree nodes of the input.We propose a novel approach to ZP identification by casting it as a query-based argument span prediction task.Given a predicate as a query, our model predicts the omission with ZP.In the experiments, our model surpassed the sequence labeling baseline.