Reviewerly/exHarmony huggingface dataset:
Contemporary Art and Virtual Reality: New Conditions of Viewership

The article aims to respond to the lack of studies on the relationships between contemporary visual arts and VR, focusing on the role of “storytelling” and identifying what distinguishes VR art projects from other contemporary VR uses, namely their criticism of the VR medium itself. VR has developed a new language in the last five years, based on specific visual grammar and allowing new narration forms. Visual artists have been attracted to VR in search of new modes of production and expose the negative impact of technology in our perception of reality, or else the new mediated ways of seeing and distanced interaction with the world around us. The first part is dedicated to the discussion of Canadian artist Jon Rafman’s View of Pariser Platz (2016) and American artist Jordan Wolfson’s Real Violence (2017), two of the first Oculus Rift-based art installations to develop a metalinguistic commentary on how VR, although promising immersion, produces, in fact, alienation, homogenization, brutalization and the loss of empathy. The article continues with a discussion on the recent rise of tech companies aimed at the production of contemporary artworks based on VR technology: Acute Art (London), Khora Contemporary (Copenhagen), and VIVE Arts (Taiwan). This is a new expanding field that is changing the ontology of artmaking and redefining the artist's role, mainly in light of the cooperation with technicians and programmers.
«Salvo i versi»: i 'Tre sonetti verdi' come saggio di «librettese»

The Study Centre Edoardo Sanguineti (www.centrosanguineti.unito.it), established at the Department of Humanities of the University of Turin in collaboration with the universities of Genoa, Milan and Salerno, is working to build an extensive and fully navigable archive, configured as a development of Sanguineti's Wunderkammer, a digital archival database which, over a period of five years, has collected a rich heritage of unpublished, unknown or dispersed documents, partly kept at the Centre and partly in related archives.In order to provide an example of the way in which these acquisitions allow us to approach the study of the author on a new basis, we propose here the analysis of a folder containing six sheets, three handwritten and three typed, found among the papers of the Fondo Eredi Sanguineti: in the three sheets written in biros we find the preparatory material and the various phases of elaboration of the 'Three Green Sonnets'.
Comparison of Neural Network Techniques for Text Data Analysis

The nation is currently deeply dissatisfied with the corruption of power. The incumbent government promised to create a fair society without fouls and privileges. However, the public is deeply distrusted by the prosecution's investigation of the justice minister. Korean society has very low national integrity due to corruption in public offices. In the past, corruption in public offices was mostly corruption in the form of livelihood, but it has now turned into corruption in power. This paper looks into the concept and theory of corruption in public office and tries to find alternatives.
Dried Fruit Jams (Dates and Raisins) / Siti Nur Atiqah Sukri

Kisma Enterprise is a company that offers food products which name as Yummy Tummy that has a long lasting period and high in nutrient as it made of dates and raisins which suitable to be taken in order to stay full and healthy. This food product is very easy to handle , to serve and suitable to be consume with bread. Yummy Tummy is also offered to all stage of community groups and can be as home food stocks. In addition, this product is also available to all customers at affordable price and high in quality. Besides, with a medium size of its packaging, it easy to bring whenever want to travel. Yummy Tummy is also contain with 100% of pure dates and raisins which give a best taste of jams to every consumers. This product has a high potential to growth as it made of fruit which can be eat by every religion. So, the changes for this product to gain high profit is high and it can be one of the favourite jams for the consumers. Other than that, the difference of Yummy Tummy compared to the others product is the uniqueness of its taste which cant be found from another product. This is because this product has never been produce by any firm so the unique of its taste can only be found in this Yummy Tummy. Hence, the potential for this product to grow further is bigger and the great of its taste will always loved by the consumers. The profitability of this product can be enhanced by the supportive results from the local people. Therefore, the marketing management will always ensure that this product will be known by the whole community of the country in order to achieve the high sales and profit.
병렬 말뭉치와 한국어 교육 연구

The purpose of this study is to review the issues related to parallel corpus and previous studies using parallel corpus, and also to examine how to use parallel corpus in the studies of Korean language education. This study starts by summing up the concept, types, and the structure of parallel corpus, and examining problems in construction and use. Next, we review the current trends of language research and language education research using parallel corpus, and then examine the trends of studies related to Korean language education, especially focusing on language contrastive studies. Finally, we would like to conclude what to consider when trying to use parallel corpus in studies of Korean language education, and the direction of the Korean language education research using parallel corpus in the future.
Motion Blur Corner Cases

This chapter describes efficient ways to handle some corner cases in motion-blurred acceleration structures for ray tracing. We discuss the handling of geometries sampled at different time intervals, how to efficiently ound the movement of geometries undergoing linear transformation and linear deformation at the same time, and a heuristic for bounding volume hierarchy (BVH) construction that helps the surface area heuristic adapt to the presence of incoherent motion.
IMAGE ENCRYPTION BY USING 3D LOGISTIC CHAOTIC MAP: A STATE OF THE ART REVIEW

This paper proposes a new method of digital colour picture lossless encryption and decryption using 2D discrete Haar wavelet transform (DHWT) and 3D chaotic logistic plot. The proposed cryptosystem provides digital image protection by means of a cryptographic algorithm in the image frequency domain. For the decomposition of the image, the proposed method uses two levels of 2D DHWT. 2D DHWT is applied to the various colour components of the colour image for encryption, and then the encryption method is applied to the different sub-bands of each decomposition step, and the reverse encryption procedure is used for decryption with the inverse of the functions used in encryption. In order to verify the feasibility and robustness of the system, experimental results and security analysis such as brute force analysis, statistical analysis, occlusion and differential attack of the proposed method are presented.
Convolution Neural Network Based Emotion Classification Cognitive ModelforFacial Expression

Facial expression is a structured communicative approach in building relationships andinteracting with others. It can be easy to focus on sensitivity and emotional content of mentalstate, personality, behavioral and intention of persons.The human behavior model makesenlighten on automatic facial expression recognition system.In Human-Machine Interaction(HMI), recognition of facial expressions is automated and it is considered as importantcomponent of natural communication. The paper proposes Convolutional NeuralNetworks(CNN) based emotion classification cognitive model for facial expression.The modelclassifiespositive and negative images which significantly specify regions within an image andnetwork performance is depend on different training options. A rectangular box is drawn aroundthe facial image and output is formatted above the rectangular box. Kaggle facial expressionFER-2013 Databasewith seven facial expression labels as happy, neutral, surprise, fear, anger,disgust, and sad is implemented. The evaluation of model shows that accuracy of lab conditiontesting data set is comparing with proposed model, the highest accuracy for happy emotion with99%, followed by surprise with 98%, neutral with 96% and least accuracy for fear emotion with45%. Live validity test is obtained with a webcam resolution of 320x240 and the network inputlayer is 224x224 with 50 cm distance is maintained between the webcam and face.
Mini Fan With Temperature Sensor (T-FAN) / Raja Mohamad Shafiq Raja Othman

T-Fan company is an electrical fan company with new updated or upgraded technologies of fan itself. It is well-known as a direct seller of the fan with the latest technologies across the state. New updated fan technology was fan upgraded with the temperature sensor have been T-Fan company mainstay. T-Fan company was founded in January 2020, to sell fan products. T-Fan has plants that manufacture its products located in Perak. Location of the company is located on the outskirt of Ipoh, Perak which is near the manufacturing factory and raw materials suppliers ofproduct.T-Fan company is encompassing a range of premium innovative products that marketed through an independent direct-selling force. These include innovative technologies that implement in our product. Today, T-Fan Company continues to break new grounds as an attractive and rewarding business opportunity. It strives to make a difference in the communities in which it operates, by offering them the opportunity to create friendlier environment products for where everyone can participate.
SISTEM PEMBELAJARAN DIGITAL INTERAKTIF (SIPEMBERANI) MENDUKUNG PEMBELAJARAN ONLINE DI SEKOLAH MENENGAH DI KOTA PALU

Today's learning is one proof that civilization is increasingly sophisticated, but many still use conventional learning systems so that it limits the space for expressing the knowledge to be transferred. The outbreak of the Corona Virus Disease 19 (COVID 19) has also changed the learning system in Indonesia, especially in Palu City, which currently is conducting by full-time online learning system. Changes in the system have made it difficult for some subject teachers to adapt. This research designs an interactive digital learning system (Simberani) to support online-based distance learning during the Covid 19 pandemic. Sipemberani adopts the ADDIE (Analysis, Design, Develop, Implement, Evaluate) model and has tested where the system built is very helpful in online learning during a pandemic. It is proven from the results of a survey conducted that 87% agree with this system.
An approach to compress human genome sequence by delta computation and secure storage by Blockchain

In healthcare, DNA plays a vital role as it carries all genetic information about organisms; FASTA is the commonly used DNA sequence in text format. The size of this DNA data is too large that makes it difficult to store and manage; also securing this data is a big issue. Noval loosless compression techniques that can reduce size of these DNA data file is most appropriate solution, reducing the size also reduce the need of resources for transmission. Therefore, this work proposes an ASCII based compression algorithm, in which DNA characters are first converted into ASCII integers and then delta computed, afterwards LZW compression technique is applied on the computed result. For ensuring security of data, blockchain-based framework is used after compression module to make data immutable.In this paper, for methods like LZW and Huffman code, compression ratio comparisons were also determined for homosapiens and from the results it is clear that proposed algorithm shows good compression ratio for some randomly selected data sets. Another aim of this paper is to show benefits of using blockchain based framework in securing healthcare data.
Quantum Gates Robust to Secular Amplitude Drifts

Quantum gates are typically vulnerable to imperfections in the classical control fields applied to physical qubits to drive the gates. One approach to reduce this source of error is to break the gate into parts, known as \textit{composite pulses} (CPs), that typically leverage the constancy of the error over time to mitigate its impact on gate fidelity. Here we extend this technique to suppress \textit{secular drifts} in Rabi frequency by regarding them as sums of \textit{power-law drifts} whose first-order effects on over- or under-rotation of the state vector add linearly. We show that composite pulses that suppress the power-law drifts $t^p$ for all $p \leq n$ are also high-pass filters of \textit{filter order} $n+1$ \cite{ball_walsh-synthesized_2015}. We present sequences that satisfy our proposed \textit{power law amplitude} $\text{PLA}(n)$ criteria, obtained with this technique, and compare their simulated performance under time-dependent amplitude errors to some traditional composite pulse sequences. We find that there is a range of noise frequencies for which the $\text{PLA}(n)$ sequences provide more error suppression than the traditional sequences, but in the low frequency limit, non-linear effects become more important for gate fidelity than frequency roll-off. As a result, the previously known $F_1$ sequence, which is one of the two solutions to the $\text{PLA}(1)$ criteria and furnishes suppression of both linear secular drift and the first order nonlinear effects, is a better noise filter than any of the other $\text{PLA}(n)$ sequences in the low frequency limit.
Rank Based Hindi News Recommendation System Using LSTM ANN Approach

With the enormous evolution of communication systems along with the electronic gadget, access to information has become easier. This affects daily life, as users demand information at a rate that is not required on a daily basis and present new challenges for content owners. In the field of news, this scenario is faced the most, given the large number of daily news articles and ephemeral time. New reading has also been affected by the more powerful mobile gadget. Rank based recommendation systems are often used to help content providers to filter out critical information and meaningful information’s based on the entered keywords by providing the data with the most relevant news portal. In this paper, a rank- based recommendation system has been presented by using the concept of Artificial Intelligence. The system has been designed by applying pre-processing (stop-word removal with word to vector) approach, feature extraction model (TF-IDF) scheme and then trained the model. The validation of model has been done by passing query words; output has been obtained in the form of most appropriate news portal, having maximum similarity score. The performance has been measured in terms of precision, recall, F-score and accuracy.
Globally optimizing QAOA circuit depth for constrained optimization problems.

We develop a global variable substitution method that reduces $n$-variable monomials in combinatorial optimization problems to equivalent instances with monomials in fewer variables. We apply this technique to $3$-SAT and analyze the optimal quantum circuit depth needed to solve the reduced problem using the quantum approximate optimization algorithm. For benchmark $3$-SAT problems, we find that the upper bound of the circuit depth is smaller when the problem is formulated as a product and uses the substitution method to decompose gates than when the problem is written in the linear formulation, which requires no decomposition.
Deep Networks Provably Classify Data on Curves

Data with low-dimensional nonlinear structure are ubiquitous in engineering and scientific problems. We study a model problem with such structure -- a binary classification task that uses a deep fully-connected neural network to classify data drawn from two disjoint smooth curves on the unit sphere. Aside from mild regularity conditions, we place no restrictions on the configuration of the curves. We prove that when (i) the network depth is large relative to certain geometric properties that set the difficulty of the problem and (ii) the network width and number of samples is polynomial in the depth, randomly-initialized gradient descent quickly learns to correctly classify all points on the two curves with high probability. To our knowledge, this is the first generalization guarantee for deep networks with nonlinear data that depends only on intrinsic data properties. Our analysis proceeds by a reduction to dynamics in the neural tangent kernel (NTK) regime, where the network depth plays the role of a fitting resource in solving the classification problem. In particular, via fine-grained control of the decay properties of the NTK, we demonstrate that when the network is sufficiently deep, the NTK can be locally approximated by a translationally invariant operator on the manifolds and stably inverted over smooth functions, which guarantees convergence and generalization.
Precise-robust position measurement of a linear motor based on the extended speed-up robust features algorithm and sawtooth stripe pattern

To improve the accuracy and robustness of linear motor mover position detection, a linear motor displacement measurement method is proposed based on the extended speed-up robust features algorithm and sawtooth stripe image. First, a sawtooth stripe image is constructed as the target image. To optimize the target image with strong robustness, the spatial frequency and image standard deviation are introduced as the image quality evaluation indices. Second, a line scan camera fixed on the linear motor is used to capture the target image signals in real time. The sequential sawtooth stripe signals are preprocessed by filling sampling to improve the matching rate of feature points. To satisfy the real-time requirement of mover position detection, the singular value decomposition is used to reduce the dimension of the preprocessed image. Subsequently, an improved speed-up robust features algorithm is used to achieve sub-pixel displacement measurement. Finally, the actual displacement of the mover can be calculated by the calibration coefficient of the measurement system. Simulation and comparative experiments show that the proposed sawtooth stripe image has better robustness, in contrast with the fence image and aperiodic sinusoidal image in references. It is also demonstrated that the proposed method has higher accuracy and anti-interference performance than other methods under different conditions.
Improving The Students’ Reading Comprehension On Narrative Text By Using Fable At Eighth Grade Of MTs Al – ManaarPTPN IV Pulu Raja

The research was aimed to improve the students’ reading comprehensionon narrative text by using fable. The subject of this study was the eighth gradestudents of MTs Al – Manaar PTPN IV Pulu Raja in 2020/2021 academic year. Itwas consisted of one class and 27 students as respondents. The object of thisresearch was to improve the students’ reading comprehension on narrative text byusing fable. This research of this study was conducted by using classroom actionresearch. The technique of analyzing the data was qualitative and quantitativeresearch. The qualitative data were taken from observation. While the quantitativedata were taken from tests consist of pre – test and post – test. Based on the resultof the data analysis, it shows that there was an improvement in the students’reading comprehension on narrative text after using fable. In pre – test thestudents mean was 33,51or it was 0 %. All of the students did not reach the KKM.After doing the post – test, there was an improvement in the result of the students’mean. The students’ mean in the post – test cycle I was 55,74 or it was 22.22%,and the students’ mean in the post – test cycle II was 80,74 or it was 85,18%. Inother words the students’ reading comprehension on narrative text was improved.And based on the observation sheet and documentation, it was showed that theexpression and excitement of the students were also improved.
한국과 이스라엘 무기의 수출경쟁력에 관한 연구 : 무기 수출다각화를 중심으로

Korea and Israel have a lot of similarities in terms of their geopolitical characteristics as well as security and defense industry environment. However, it is undeniable that Israel has an edge over Korea looking at an arms export achievement aspect so far. In particular, it is necessary to pay attention to the case of Israel in terms of diversification of arms exports. Therefore, the purpose of this study is to contribute to the establishment of Korea's advanced arms export strategy in the future by empirically analyzing export diversification factors through the vector error correction model among the factors that influenced the export competitiveness of Korea and Israel during 1992-2020. As a result of the study, it was analyzed that the diversification of arms exports between Korea and Israel has positively affected the increase in arms exports, and it was confirmed that Israel in particular achieved a higher level of export diversification than Korea. This implies that there is a need to establish an export strategy in the direction of strengthening export diversification for the continued and stable expansion of arms exports in Korea.
Anisotropic diffusion filter for region enhancement in segmentation of breast ultrasound images / Nurul Ain Fatehah Abdullah, Nurul Asyiqin Mohd Fauzi and Nur Ain Amiruddin

Filtering is a process of removing noise in the images without blurring and preserving the boundaries between homogenous regions. It is an essential pre-processing technique before proceeding to the segmentation process. However, filtering had the difficult)' of locating the meaningful region and boundaries which causes some severe blurring problems. Therefore, Anisotropic Diffusion Filter (ADF) method was used as the pre¬ processing technique in order to enhance the region of interest in the breast ultrasound images. ADF is a smoothing technique that controls the diffusion rate by using an edge stopping function to avoid over blurring on the images. Twenty breast ultrasound images were acquired from the radiologist to test the application ADF as an image enhancement technique. In order to evaluate the quality of filtered image. Mean Squared Error (MSE) and Peak Signal-to-Noise Ratio (PSNR) were calculated by comparing ADF with another filtering method which is Integral Filter. The MSE results show ADF has the lowest value of 9.2550 compared to Integral Filter at 49.4672. Whereas, PSNR of filtered image with ADF is 31.3484 higher than Integral Filter, 16.9034. This implies filtered image with ADF has the best quality image compared to Integral Filter. Subsequently, the image segmentation testing on filtered ultrasound images has been done by implementing the Seed Based Region Growing (SBRG) technique. The performance of segmentation results is measured in terms of accuracy based on the percentage relative error obtained by comparing with the area of segmented results without using ADF and with ADF. As a result, the percentage relative error of segmented areas with ADF is I 0% which implies the accuracy of 90% while percentage relative error without ADF is 17.05% with an accuracy of 82.95%. Therefore, it is proven that ADF is the best option in enhancing breast ultrasound images and gives improvement to the segmentation process.