Reviewerly/exHarmony huggingface dataset:
A COMPARATIVE STUDY BETWEEN MULTIPLE CHOICE AND SHORT ANSWER TEST TOWARDS STUDENTS’ READING COMPREHENSION ACHIEVEMENT

This research was about a multiple choice comparative study and short answer on students' reading comprehension achievement in the ninth grade of SMPN 2 Ulaweng. The problem statement of this research was there a significant difference of the students' achievement in reading comprehension by using multiple choice test and their achievement on the short answer test?. The purpose of this research was to find out a significant difference of the students‟ achievement in reading comprehension by using multiple choice test and their achievement on he short answer test as the measure of reading comprehension.This study applied a quantitative design, with a sample of 40 students divided into 2 classes. The instrument used was in the form of a test which is divided into two types of multiple choice and short answer.The results of this study indicate that the students‟ achievement in multiple choice test, higher than students‟ achievement in the short answer test. The analysis of the mean score gap between the closed test and multiple choice in the test was different. The mean score of the multiple choice was 71.5 and 47.5 short answer. From the result the researcher concluded that multiple choice test is better than short answer test to increase students‟ achievement in reading comprehension at the ninth grade students of SMP Negeri 2 Ulaweng.
ASSISTÊNCIA FARMACÊUTICA NA ATENÇÃO PRIMÁRIA: DIFICULDADES, SUPERAÇÕES E PERSPECTIVAS NO PERÍODO DE PANDEMIA POR COVID-19

The present article entitled (In)Constitutionality Of The Circumstantiated Confession: Signed in the Criminal Procedure Code with the advent of the well-known "Anti-Crime Package ", the Criminal Non-Persecution Agreement brought several discussions about of the mandatory requirements for its concession.Despite having added to Brazilian legal system benefits related to criminal business justice, there is still such a significant dispute regarding one of its main requirements of art.28-A, the constitutional analysis of the detailed confession as a requirement mandatory required by current legislation, contrasting with principles and guarantees fundamental provisions of our Federal Constitution.To that end, this article aims to clarify and analyze the addictions possibility related to the confession detailed in the non-prosecution agreement based on the premise constitutional law, using bibliographic and jurisprudential research.it is postulated that, through the analyzed procedures, a discussion has been reached quite controversial about the constitutionality, and one should stick to primarily those that do not cause legal uncertainty to the Brazilian legal system.
Mobile Device Identification Based on Two-dimensional Representation of RF Fingerprint with Deep Learning

Radio frequency (RF) fingerprint representing the inherent hardware characteristics of mobile devices has been employed to classify and identify wireless devices for the security of Internet of Things (IoT). Existing works on RF fingerprinting are usually based on the amplitude or phase of RF signal envelope, which leads to relatively coarse features. Moreover, the classification performance over small sample dataset is poor. To solve the problem, a novel device identification method based on RF fingerprinting with on deep learning is proposed. In particular, the RF signal are transformed into two dimensional representations by image preprocessing. Then the gray images representing the RF fingerprints are classified by employing classical CNN. To verify the performance of the proposed approach, a testbed is constructed by using MATLAB build framework of gray image preprocessing. Extensive experiment results show that the identification accuracy can reach at least 90%. Even with the sample rate of 20Gsps. Particularly, the accuracy of iPhone can reach 100%. It is verified that the proposed method can effectively classify mobile devices even with small sample RF fingerprints represented two dimensional gray images,
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Research on Security Technology of Processor Branch Prediction

To improve the execution efficiency, modern processors have introduced branch prediction mechanism, but this also brings new vulnerabilities at the same time. In this paper, attack and defense techniques for processor branch prediction are investigated and classified. Attack techniques are divided into attacks against structural vulnerabilities and attacks against side channel. Also, defense techniques are divided into defense against branch predictors and defense against cache side channels. Then their introduction is given in detail. Next a branch prediction security architecture model is proposed, with its feasibility and security demonstrated. At last, this paper summarizes the shortcomings of the current defense techniques and looks forward to the future trend of branch prediction defense, which provides a reference for the design of processor branch prediction security.
DEVELOPMENT OF TEACHING MATERIAL FOR HIGH ORDER THINKING SKILLS IN READING COMPREHENSION AT STUDENTS MAN 2 MODEL MEDAN

RINGKASAN- This study aims to determine the development, validity and effectiveness ofdevelopment of Higher Order Thinking Skills (HOTS) teaching materials in reading comprehension. This research is a research and development (R&amp;D) using the ADDIE model (Analysis, Design, Development, Implementation, and Evaluation). The instrument used is a questionnaire for expert lecturers and students, interviews with teachers, and the results of the last test given to students. The test results from the validator through media design as a whole get very feasible criteria (88.33%) so that teaching materials can be used as teaching materials for students in the learning process. The results of the assessment of English Teaching Materials by experts on the substance of the material as a whole from the aspects that are considered to have received appropriate criteria (90%) so that the Teaching Materials can be used in the learning process.Keyword: Teaching Materials, High Order Thinking Skills, Development, Reading Comprehension.
The Use of Privacy-Preserving Techniques in Edge-Cloud Computing: A Study of Alternative Approaches to Face Recognition

Face verification is by far the most popular biometrics technology used for authentication since it is noninvasive and does not require the assistance of the user. In contrast, fingerprint and iris identification technologies require the help of a user during the identification process. Now the technology behind facial recognition has been around for years but recently as its grown more sophisticated is applications have expanded greatly. These days a third-party service provider is often hired to perform facial recognition. The sensitivity of face data raises important privacy concerns about outsourcing servers. In order to protect the privacy of users, this paper discusses privacy-preserving face recognition frameworks applied to different networks. In this survey, we focused primarily on the accuracy of face recognition, computation time, and algorithmic approaches to face recognition on edge and cloud-based networks.
Current Trends and Emerging Challenges in Scale Imbalance Problem Object Detection

1.1AbstractCurrently, handcrafted feature engineering is being replaced by deep learning-based models, which has given a tremendous boost to development of object detection technology. Object detection has become one of the most important and emerging application areas of deep learning. Object detection process is essentially based on one question like “what object is where in a given image”? Medical analysis and decision making, self-driving cars, surveillance, remote sensing technology etc. are some of prominent areas where this technology has been used. Nevertheless, with the divergence in deep learning-based object detection applications, imbalance problem is become a new research area to optimize the object detection training model. This paper mainly analyzes deep-learning based approaches to solve the scale imbalance problem in object detection. This type of imbalance usually occurs at two levels: feature level and Bounding box/ object level. This paper analyzes the main issues related to scale imbalance problem, and reviews the classical remedies that have been developed so far to address this imbalance in object detection. Through analysis, this paper discusses future research directions of object detection scale imbalance problem.
PENGARUH MODEL PEMBELAJARAN TERPADU TIPE CONNECTED BERBANTUAN MEDIA GAMBAR TERHADAP HASIL BELAJAR IPA

The objective of this study is to determine the differences of study’s product in learning science between students who learned with connected model assisted picture media and students who learned with the direct instruction model. The population of this study is all of the fourth grade students in SDN 49 Pare-Pare in Gugus IV, District, in academic year 2019/2020, numbered 186 people. The sample of this study are two classes; they are the students in IVA numbered 28 people as the experiment group, and the students in IVB SDN 46 Pare-Pare numbered 28 people as the control group. The researcher decided the sample through random sampling. The research design of this study is quasi experiment with Non Equivalent Post-test Only Control Group Design. The data of study’s product gathered with the objective test. Then, the data was analyzed by using descriptive statistics and inferential statistics (t-test). The result shown that there are significant differences of study’s product in learning science between the groups of students who learned with connected model assisted picture media and students who learned with the direct instruction model. Those differences can be seen based on the result, the t-test is higher than ttable (ttest=3,815&gt;ttable=2,021) with 5% significant. In other words, if both of those techniques compared, connected model assisted picture media have positive effect on the study’s product in learning science rather than direct instruction model.
Decentralized Cryptocurrency: A Potential Regulatory Strategy

Decentralized cryptocurrencies, such as bitcoin, use peer-to-peer software protocol, disintermediating the traditional intermediaries that used to be banks and other financial intermediaries, effectuating cross-border transfer. In fact, by removing the requirement for a middleman, the technology has the potential to disrupt current financial transactions that rely on a trusted authority or intermediary operator. Traditional financial regulation, which is largely based on the command-and-control approach, is ill-suited to regulating decentralized cryptocurrencies. The purpose of the present paper is to investigate the policy option most suitable for regulating decentralized cryptocurrencies. The paper argues that the combination of both direct and indirect regulatory approaches would be a feasible option for regulating decentralized cryptocurrencies. The absence of centralized authority and the borderless nature of decentralized cryptocurrencies would make them antithetical to centralized direct regulation. Therefore, regulators should focus on regulating intermediaries bridging the connection between the online world (crypto ecosystem) and the physical world (the point of converting crypto into fiat money). These intermediaries can work as passive actors or surrogate regulators who are indirectly responsible for implementing policy options on behalf of the central authority.
No boundary left behind in semantic segmentation

This paper proposes a novel network architecture for image semantic segmentation based on attention mechanisms placed on specific points inside a convolutional neural network. Attention is explored across our network to integrate information from object boundary and a baseline semantic segmenter (inner segmentation). We call our novel network Attention-fitted Fusion of boundary and Inner Segmentation (AFIS), which combines the two streams through a set of attention gates, forming an end-to-end network. We performed an extensive evaluation of our method over four public challenging data sets (Cityscapes, CamVid, Pascal Context, and Mapillary Vistas), finding superior results when compared with other twelve state-of-the-art segmenters, considering the same training conditions.
Digital audio watermarking based on the modulation of MCLT-coefficients

Audio data hiding techniques have various applications such as audio watermarking and steganography. This article provides a brief description of a new method of digital audio watermarking that has been developed based on a modulated complex lapped transform (MCLT). The new audio watermarking algorithm saves the sound quality of the marked signals. The experimental results show the dependence of the sound quality of the marked audio signal on the parameters of the marking method. Moreover, the results of the experiments show the influence of various attacks on the marked audio signal. Based on conducted experiments, it is concluded that the new method of digital audio watermarking can be used to confirm the authenticity of audio files distributed through the Internet or to confirm the integrity of the transmitted audio files.
Evaluation of E-learning using EDAS Method

Evaluation of eLearning versus traditional classroom learning Experience is a substitute, and it often is "Online Learning", "Distance Learning", “Virtual Learning”, “Mobile Learning”, "Digital Learning" or Referred to as “Distance Education”. E-learning and pedagogy should focus on participation. Those tasked with implementing e-learning must find a strategy within their organization to find a way to connect learners to content and enable collaboration while maintaining the concept of anytime, anywhere learning. DAS Evaluation Based on Distance from Average Solution method for Evaluation of E- Learning or appraising the alternatives Analysis, Design, Development, Implementation, and Evaluation. and Evaluation parameters in E-Learning Environment, Webpage Connection, Learning Records, Instruction Materials. Evaluation is got the first rank whereas is the Implementations having the Lowest rank. In this paper Evaluation of E-learning of EDAS Evaluation is got the first rank whereas is the Implementations having the lowest rank.
Comparative characteristics of Crystals-Kyber and Skelya key encapsulation algorithms (DSTU 8961-2019)

In recent years, there has been a significant amount of research related to the development of quantum computers. If such a computer were to be built, it would be able to break existing public-key cryptosystems that are currently used for many purposes. This will seriously affect the privacy and integrity of digital communications, etc. That is why special attention is currently being paid to post-quantum cryptography, the main goal of which is the development of cryptographic systems that are protected from both quantum and classical attacks, and will also be able to interact with existing communication protocols and networks. In view of the significant importance of the practical application of directional encryption algorithms, at the international and state level, special attention was paid to the implementation of the proposed requirements for key encapsulation protocols. Key-establishment algorithms (KEA) form a common secret – the key for a symmetric encryption algorithm. The paper considers two KEA algorithms that use algebraic lattices: one of the finalists of the 3rd round Crystals-Kyber and the Skelya algorithm (DSTU 8961-2019). The Kyber algorithm first performs asymmetric encryption of a 32-byte message, and then generates a shared secret. The Skelya algorithm performs the same actions, but for asymmetric encryption, it uses messages of any length that do not exceed the maximum possible. That is why the last algorithm can be used not only as a KEA algorithm, but also as an asymmetric encryption algorithm. According to the NIST Security level, the Kyber algorithm provides cryptographic 1, 3, and 5 security levels, and the Rock algorithm provides cryptographic 3, 5, and 7 security levels. The cryptographic stability that is ensured for both algorithms is determined by a set of parameters. Thus, the purpose of this work is to review the details of the implementation of each of the mentioned algorithms, to compare the speed of the key generation, encapsulation and decapsulation algorithms for the Kyber and Skelya algorithms in terms of key data lengths, and the encapsulation result and computational complexity of both algorithms.
Dual attention unit-based generative adversarial networks for low-light image enhancement

Images taken in low-light conditions would have insufficient light intensity and high noise. Many existing methods could not work very well in low-light environments, such as the noise and artifacts in dark conditions will be more obvious when enhanced. Therefore, low-light image enhancement is a challenging task in computer vision. To solve this problem, this paper proposes a lightweight generative adversarial network with dual-attention units to enhance underexposed photos. There is only a simple two-layer convolution in the generator section, and a dual-attention unit is added between the two convolutions to suppress the noise generated during the enhancement process and the deviation of color reduction. Then, non-local correlations of the image are used in the spatial attention module for denoising. Ours low-light image enhancement network is guided by the channel attention module to optimize redundant color features. In addition, the ideas of PatchGAN and Relativistic GAN are combined in the discriminator section to make the discriminator a better measure of the probability of changing from absolute true or false to relative true or false. The experiment results show that, our method could get better enhancement effects on low-illumination image datasets, which has more natural color, better exposure, and less noise and artifacts.
Organizers

Organizers and program committee for the Intelligent Narrative Technologies 2012 AIIDE Workshop
The development of teacher creativity in making creative learning materials at experimental state elementary school 2 Sleman

In the era of the Covid-19, distance learning with interesting learning materials is needed to avoid boredom and burnout. Online distance learning requires the use of the internet and the readiness of teachers to process learning materials. In reality, internet use is limited to teachers and students in urban areas that have better information and technology. Therefore, the development of teacher creativity in making creative learning materials, especially in making creative media, needs to be used as a follow-up to overcome Online learning problems. Internet information technology, which was previously used as a source of information, must now be used as a media aid in Online learning, especially at the level of basic education. After a 42-hour workshop with discussions; (1) Creative and interesting learning with a literary approach; (2) Making interesting and creative learning media, and; (3) Learning technology and its handling. The teachers of Experimental State Elementary School 2 have obtained recipes for making creative learning media that are able to attract stronger attention to children when participating in online learning. Teachers have also been able to prepare PowerPoint for interesting and not boring subjects
STUDENTS' ATTITUDE TOWARDS THE USE OF FILM SEQUENCES TO IDENTIFY THE DEVELOPMENTAL CHARACTERISTICS OF PEOPLE WITH INTELLECTUAL DISABILITIES

The current study highlights the attitude of students toward the use of film sequences, as educational resources used in the course of Psychopedagogy of people with intellectual disabilities, in the online learning environment. The participants in the study were students (N = 28) in the 2nd year, who follow the Special Psycho-pedagogy study program. The research method was a questionnaire-based survey. The working tool contains 23 questions, which were developed by the authors for this research. In the introductory part, in addition to the synthesis of the specialized literature, we briefly presented the aspects related to the management of the university course, in a pandemic context, by presenting the ways in which the film sequences were used to achieve the objectives of the discipline. The results of the descriptive study show that students show a positive attitude towards the use of film sequences in teaching, learning, and final assessment activities. Thus, the students consider that the film sequences used in the course activities facilitate the understanding of the theoretical information from the course support, about the particularities in the development of people with intellectual disabilities. Additionally, the film sequences used for assessing knowledge in the final exam took students out of their comfort zone of passively taking the theoretical information and giving an answer during the online assessment tests. The research findings highlight the practical implications and future directions of research to ensure good management of course activities in the online learning environment.
Dual Reconstructive Autoencoder for Crowd Localization and Estimation in Density and FIDT Maps

This paper proposes crowd estimation technology to help authorities make the right decisions in times of crisis. Specifically, deep learning models have faced these challenges, achieving excellent results. In particular, the trend of using single-column Fully Convolutional Networks (FCNs) has increased in recent years. A typical architecture that meets these characteristics is the autoencoder. However, this model presents an intrinsic difficulty: the search for the optimal dimensionality of the latent space. In order to alleviate such difficulty, we propose a dual architecture consisting of two cascaded autoencoders. The first autoencoder is responsible for carrying out the masked reconstruction of the original images, whereas the second obtains crowd maps from the outputs of the first one. In this way, our architecture improves the location of people and crowds in Focal Inverse Distance Transform (FIDT) maps, resulting in more reliable count estimates concerning a single autoencoder architecture.
MODERN INTERACTIVE METHODS OF DISTANCE LEARNING AND THEIR ROLE IN SPECIALIST PROFESSIONAL COMPETENCE FORMATION

Modern interactive methods of distance learning and their role in specialist professional competence formation are considered. In modern conditions the role and place of distant learning forms and the use of modern information innovative technologies keep on growing. In electronic learning different methods of educational information provide can be used: from traditional printed editions to the most modern computer technologies ( radio,TV, audio and video broadcasting, audio conferences, e-learning, Internet conferences, Internet broadcasting ). Today distant learning is one of the key directions in renewal of all links in educational system of Ukraine.