Reviewerly/exHarmony huggingface dataset:
First Impressions Matter! IVR Haptic Feedback Effect on User Perception Towards Non-Player Characters.

Feedback provided during Immersive Virtual Reality (IVR) experiences can be delivered through various modalities, such as auditory, visual, and haptic. Most VR systems support vibrotactile haptic feedback and, as several studies point, providing such feedback to users when they interact with Non-Player Characters (NPC) in IVR can have an impact on overall user experience, specifically emotional state, and Body Ownership Illusion. However, most studies regarding haptic feedback impact: (a) focus on users’ perception solely about themselves and do not examine the effect it may have on their perception about others, and (b) implement complex scenarios featuring multiple stimuli sources which may affect the overall users’ response. This work investigates the effect of vibrotactile haptic feedback on users' first impressions of NPCs and their surrounding space. Our evaluation results, provided by thirty (30) participants, showed that integrating vibrotactile haptic feedback for interactions with NPCs in IVR may positively affect users’ first impression of those and their surrounding space as well.
Embedded Basketball Motion Detection Video Target Tracking Algorithm Based on Deep Learning

With the rapid development of artificial intelligence, video target tracking is widely used in the fields of intelligent video surveillance, intelligent transportation, intelligent human-computer interaction and intelligent medical diagnosis. Deep learning has achieved remarkable results in the field of computer vision. The development of deep learning not only breaks through many problems that are difficult to be solved by traditional algorithms, improves the computer's cognitive level of images and videos, but also promotes the progress of related technologies in the field of computer vision. This paper combines the deep learning algorithm and target tracking algorithm to carry out relevant experiments on basketball motion detection video, hoping that the experimental results can be helpful to basketball motion detection video target tracking.
Aplikasi Image Enhancement untuk Peningkatan Kualitas Citra Ultrasonografi Ginjal

Combination of four filters namely gaussian filter, median filter, wiener filter, average filter were tested using two contrast enhancement techniques, intensity adjustment and histogram equalization, were tested to improve the quality of kidney ultrasound images. The research was conducted using 40 images, consist of 9 normal images, 17 hydronerfosis images, and 14 kidney stones images. The measured image quality were PSNR (Peak Signal to Noise Ratio) and MSE (Mean Square Error). The higher the PSNR and the lower the MSE, the better the image quality. Visual evaluation through questionnaires to clinicians has also been carried out to assess the visualization of the kidney and its abnormalities. The results of PSNR and MSE calculations showed that every image processings methods combinations produce different results in each image categories. However, whether in normal, hydronefrosis, or kindey stone categories, the combination of filters with image adjustment method gave the highest PSNR and lowest MSE. Meanwhile, the results of the visual evaluation from the clinicians showed that the best image enhancement technique in improving the visualization of abnormalities in kidney ultrasound images (Hydronephrosis and kidney stones) was the combination of a wiener filter with intensity adjustment, in accordance with the results of the PSNR measurement. Abstrak. Telah diuji kombinasi empat metode filter yaitu gaussian filter , median filter , wiener f ilter dan ave rage filter dengan peningkatan kontras, intensity adjustment dan histogram equalization untuk meningkatkan kualitas citra ultrasonografi ginjal. Penelitian dilakukan dengan menggunakan 40 citra, dengan rincian 9 citra normal, 17 citra Hydronerfosis, dan 14 citra batu ginjal. Kualitas citra yang diukur adalah PSNR dan MSE. Evaluasi visual melalui kuesioner terhadap klinisi juga telah dilakukan. Untuk citra normal, nilai PSNR tertinggi, yaitu 14.21 dan MSE terendah, yaitu 2.62 diperoleh pada kombinasi median filter dengan intensity adjustment . Untuk citra hydronefros is , PSNR tertinggi diperoleh pada kombinasi wiener filter dengan intensity adjustment , yaitu 4.42 dan nilai MSE terendah diperoleh pada kombinasi average filter dengan intensity adjustment , yaitu 3.37. Pada citra batu ginjal, nilai PSNR tertinggi diperoleh pada kombinasi wiener filter dengan intensity adjustment , yaitu 15.48, serta nilai MSE terendah merupakan kombinasi gaussia n filter dengan intensity adjustment , yaitu 3.23. Sementara itu, hasil evaluasi visual dari dokter klinisi menunjukkan bahwa teknik image enhancement yang paling baik dalam meningkatkan visualisasi abnormalitas pada citra USG ginjal hydronefrosis dan batu ginjal adalah merupakan kombinasi wiener filter dengan intensity adjustment , sesuai dengan hasil pengukuran PSNR.
PHILOSOPHICAL CURRENTS OF MODERNISM AND THE FIRST UKRAINIAN MUSICAL THEORIES

The article indicates some signs of the first decades of the twentieth century, associated with the transformation of philosophical views. Changes were manifested in the emergence of fundamentally new branches of knowledge, focused on a person, his essence, freedom of creative self-expression. The young Ukrainian the science of music was looking for its self-determination, subjectal encroachments, principles of ideological development, appropriate approaches and methodology. Significant influence in this case had the latest Western trends. The comparison of the most common Western European philosophers with the well-away ideas of the first professional musicologists who worked then in Kiev proves their connection. In the teachings on musical thinking and the structure of musical language, leading figures of the then Kyiv Music and Theoretical School B. Yavorsky and A. Butsky consciously or intuitively embodied the ideas of many modernist philosophers recognized in the West (especially E. Husserl, A. Bergson, V. Welflin). This proves that the first professional music experts in Ukraine in an ambiguous period of Ukrainian history were not only in the intellectual field of Western European philosophical thought, but on its basis developed their own promising scientific theories.
Development of Interactive Multimedia in Integrated Thematic Learning by Using Macromedia Flash in Grade IV Elementary School

This research is motivated by the lack of use of interactive, interesting and fun media for students, especially on technology-based media and during the learning process students have not been actively involved and are less involved in the process of using media. Technology-based learning media has not yet been developed because teachers only rely on theme books, MRT books, and other supporting books as sources as well as learning media, occasionally the teacher shows videos from YouTube. This study aims to determine the development of interactive multimedia in integrated thematic learning using Macromedia Flash in grade IV Elementary School in Padang City which is valid and practical.&#x0D; This type of research is Research and development (R&amp;D). The development model used in this study is the ADDIE model with the Analysis stage, the Design stage, the Development stage, the Implementation stage and the Evaluation stage.&#x0D; The results of the research developed, obtained the results of the validity level of learning media in integrated thematic learning with a total validation value of 86.4% in the very valid category. Furthermore, the results of practical trials of learning media in the form of interactive multimedia using Macromedia Flash in integrated thematic learning are stated to be very practical. This can be seen from the teacher's response and the student's response. Where the teacher response questionnaire scored 95% in the very practical category and 15 student response questionnaires scored 94.1% in the very practical category. Thus, the development of learning media in the form of interactive multimedia using Macromedia Flash in integrated thematic learning in grade IV Elementary School is very valid and very practical.
ACDC: Anonymous Crowdsourcing Using Digital Cash

Crowdsourcing applications are vulnerable to Sybil attacks where attackers create many accounts to submit bogus or malicious data at scale. The traditional approach to manage Sybil attacks is privacy invasive since it requires contributors to identify themselves when contributing data. In this paper we present a new reporting protocol which supports the anonymous submission of data to crowdsourcing systems by honest contributors, while identifying malicious individuals who attempt to submit multiple reports. Our approach builds on Chaum’s digital cash, and we demonstrate its practicality and deployability on mobile devices based on its low storage, network, runtime, and power requirements.
MOTIVATION FOR INDEPENDENT WORK AND SELF-EDUCATION AS THE MAIN ENGINE OF COMPUTER SCIENCE EDUCATION

The paper considers the main types of motivation. The results of research to determine the main motives for studying computer science and ICT in an agricultural university are presented. The assessment of the main motives in the current situation is given. The dependence of the ability to self-education on the level of motivation is considered. As you know, internal motivation pushes a student to study for the sake of learning (learning new things), in the process the student gets pleasure, experiences joy and even drive.
Students’ Perception of the Discovery learning Strategy in Learning Reading Comprehension at Widya Manggala Senior High School

Reading is a crucial skill for foreign language learners, and one the most learning strategy to promote reading is discovery learning. This study aimed at examining senior high school students’ perceptions of the use of the discovery learning strategy on reading comprehension. Involving 68 students of Widya Manggala Senior High School, the study collected data using a questionnaire and interviews. The quantitative data obtained from the questionnaire was analyzed by using the descriptive statistic, while the qualitative data obtained from the interview was analyzed descriptively. Findings revealed that the majority of the students have a positive and of the upper-medium level of perception of the use of the discovery learning strategy on reading comprehension. Although their perception is not very high, they realize that this strategy can make them more active and serious in the learning to read process.
Analysis of Moving Average, Weight Moving Average, Exponential Smoothing in predicting shoe prices

Research related to forecasting is growing, starting with simple forecasting based on time or forecasting with certain criteria. Forecasting methods continue to be developed because they produce good models and can predict with high accuracy. The simplest method of forecasting is from the statistical value of the data, namely the average value or what is often called a moving average. Moving average calculates the next time prediction based on the previous time data and moves. The Moving Average (MA) method has several types, including Weight Moving Average (WMA), Autoregressions Moving Average (ARMA), and others. Referring to existing forecasting methods, we try to propose research related to the analysis of the MA, WMA, and Exponential Smoothing (ES) methods in forecasting shoe prices. The purpose of this research is to analyze the three methods in predicting the price of Adidas shoes. The data were taken from the Kaggle dataset and the analysis of the three methods used the MSE (Mean Squared Error) value. The forecasting analysis process uses the statsmodels library in Jupyter Notebooks. The MSE values ​​of the three methods are MA with 2 times 15484.68, MA with 3 times 24829.42, WMA 3 times 14239.74, WMA 4 times 18386.77, and ES 3 times 38349.34, ES 4 times 43102.42. The conclusion of this research is that the lowest MSE value is the best prediction method, namely WMA with 2 times MSE 7268.3.
Neural Network-Based Fixed-Complexity Precoder Selection for Multiple Antenna Systems

In this paper, we propose a neural network-based precoder selection method for multiple antenna systems that are equipped with maximum likelihood detectors. We train a fully connected neural network by supervised learning with novel soft labels that are derived from the error probability of maximum likelihood detection. The dimension of the input data is reduced by QR decomposition of the channel matrices, thereby reducing the number of nodes of the input layer. Furthermore, the dimension reduction improves the network accuracy. The number of connections between the layers are reduced by the network pruning technique, then the survived connections are retrained to recover the degraded accuracy due to the pruning. We also optimize the regularization method, considering not only network overfitting but also pruning and retraining. Our method achieves a near optimal bit error performance of the previous sphere decoding (SD)-based symbolic algorithm, of which complexity fluctuates depending on channel matrices. Unlike the conventional SD-based method, the complexity of the proposed method is fixed by the intrinsic characteristic of neural network, which is desirable from the perspective of hardware implementation. And the fixed complexity is lowered by pruning unimportant connections of the networks. With the aid of computer simulations, we show that the fixed complexity of the proposed method is close to the average complexity of the conventional SD-based symbolic algorithm, allowing only negligible degradation of the error performance.
Data Fusion Methods with Graded Relevance Judgment

Data fusion methods have been widely used in many information retrieval tasks. Its performance is affected by many factors including the data fusion algorithm used, the component retrieval systems involved, relevance judgment, the metrics used for evaluation, and others. Previously, data fusion research mainly focused on the data fusion methods and the component retrieval systems involved, but other factors such as relevance judgment and the metrics used for evaluation have not been addressed. As a matter of fact, relevance judgment is an important issue that affects many aspects of information retrieval and data fusion. The assumption of binary relevance judgment has been taken for all the previous research work in data fusion. However, this assumption is simplified and not satisfactory in many cases. Instead, graded relevance judgment is more general and able to deal with more complicated requirements. In this paper, we investigate data fusion methods, especially linear combination, to work with graded relevance judgment. Necessary updates are given for using those methods in the new situation. Experimented with two data sets in TREC, we find that data fusion is still an effective technology for performance improvement in general. Many of them are very competitive in a controlled environment, and linear combination with weights trained by multiple linear regression is the most stable in a more complicated environment.
On the Application of Robust Mean Shift Procedure for the Enhancement of Noisy Color Images

Image corruption due to noise disturbances severely decreases color image quality and therefore image enhancement is a vital step of the processing pipeline. Our approach modifies the standard Mean-Shift technique, so that the algorithm is able to work directly on noisy color images and offers very satisfying denoising results. The proposed Robust Mean-Shift is resistant to the mixed Gaussian and impulsive noise and can be used in various practical imaging tasks. The described technique has been validated on a database containing a variety of color images contaminated with various noise intensity levels and the obtained results show that it significantly excels the classical Mean-Shift algorithm. Image noise is to large extent suppressed, edges are sharpened and details are retained which enables the improvement of the image segmentation process.
The problem of pedagogical innovations and trends in the development of the educational environment

Pedagogical innovations are an important component of the educational environment both in the period of its sustainable development and in times of change and transformation. Characteristic features of new ideas of educational and pedagogical space are their dynamism and continuity. If the educational system has its fundamental stages of development (approval, functioning, transformation), the practically oriented cluster of pedagogy is always focused on progress in the form of changes, improvements, and transformations. The purpose of scientific exploration is to structure and systematize pedagogical innovations in the main segments of the educational environment. The article aims to determine the differences between the declarative elements of innovative educational strategies and the practical implementation of pedagogical innovations demanded by time and reality. The methodological basis for scientific research is concentrated around general scientific, scientific-pedagogical, and philosophical-scientific segments. Prospective directions of pedagogical innovations research is to determine the role in the development of the educational environment and to develop mechanisms to overcome the problems associated with pedagogical innovations in the education system. So, the range of problematic issues on pedagogical innovations concerns the following moments: the mismatch between the needs of the educational environment and innovative manifestations; risks caused by the aggressiveness of innovation and its negative impact on the fundamental educational principles; socio-cultural realities that do not allow the implementation of educational innovation in different dimensions (global, regional, professional).
Fine-grained Access Control Method for Blockchain Data Sharing based on Cloud Platform Big Data

Blockchain technology has the advantages of decentralization, de-trust, and non-tampering, which breaks through the limitations of traditional centralized technology, so it has gradually become the key technology of power data security storage and privacy protection.In the existing smart grid framework, the grid operator is a centralized key distribution organization, which is responsible for sending all the secret credentials, so it is easy to have a single point of failure, resulting in a large number of personal information losses.To solve the problems of inflexible access control in smart grid data-sharing framework and considering the limitation of multi-party cooperation among grid operators and efficiency, an attributebased access control scheme supporting privacy preservation in smart grid is constructed in this paper.A fine-grained access control scheme supporting privacy protection is designed and extended to the smart grid system, which enables the system to achieve fine-grained access control of power data.A decryption test algorithm is added before the decryption algorithm.Finally, through performance analysis and comparison with other schemes, it is verified that the performance of this system is 7% higher than the traditional method, and the storage cost is 9.5% lower, which reflects the superiority of the system.Full optimization of the access policy is achieved.It is proved that the scheme is more efficient to implement the coordination and cooperation of multiple authorized agencies in the system initialization.
Compressed Video Quality Assessment for Super-Resolution: A Benchmark and a Quality Metric

We developed a super-resolution (SR) benchmark to analyze SR capabilities to upscale compressed videos. The dataset for the benchmark was collected using video codecs of 5 different compression standards. We assessed 17 state-of-the-art SR models using our benchmark and evaluated their ability to preserve scene context and their robustness to compression artifacts. To get an accurate perceptual ranking of SR models, we conducted a crowd-sourced side-by-side comparison of SR results. We also analyzed the results of the benchmark and developed an objective quality assessment metric based on existing best-performing objective metrics. Our metric outperforms other video quality metrics by Spearman correlation with subjective scores for the task of upscaling compressed videos.
Mediating meaning in booktalk: Reading Clubs as third spaces

Various studies have shown that South Africa has low levels of school literacy. This is exacerbated when schools are located in low socio-economic settings where schools have a dearth of resources to be mobilised to develop literacy practices. This article reports on a qualitative study of classroom reading clubs where learners read novels in groups once a week. In particular it focuses on discussions within two reading clubs to explore how learners took up different positions to talk about books and how together they constructed a shared understanding. The study suggests how through talk learners have an opportunity to think and this thinking is made visible to researchers. The article suggests that classroom reading clubs can sites to develop reading strategies reasoning in response to literature. Keywords: reading clubs, critical thinking, booktalk, dialogism, discussion
Rolling Gaussian Process Regression with Application to Regime Shifts

Gaussian Process Regression (GPR) can be applied to the problem of estimating a spatially-varying field on a regular grid, based on noisy observations made at irregular positions.In cases where the field has a weak time dependence, one may desire to estimate the present-time value of the field using a time window of data that rolls forward as new data become available, leading to a sequence of solution updates.We introduce "rolling GPR" (or moving window GPR) and present a procedure for implementing that is more computationally efficient than solving the full GPR problem at each update.Furthermore, regime shifts (sudden large changes in the field) can be detected by monitoring the change in posterior covariance of the predicted data during the updates, and their detrimental effect is mitigated by shortening the time window as the variance rises, and then decreasing it as it falls (but within prior bounds).A set of numerical experiments is provided that demonstrates the viability of the procedure.
Speaking Problems in Vocational High School

This study aims to find the difficulties when speaking English which are mostly faced by vocational students. This study used qualitative research methods. This research instrument is observation and interviews. Based on the results of the observation and interviews, it was found that students found speaking difficulties like (1) pause, (2) fillers, (3) mental problems, (4) lack of ideas, (5) grammatical error, (6) poor vocabulary. Speaking skill is very important for us because serves to maintain and establish social relations, and the transactional functions, which focus on the exchange of the informations. Therefore, it is necessary to conduct research to solve the problem of speaking difficulties experienced by students, so that there are improvements for the future and students' speaking skills are increasing