Reviewerly/exHarmony huggingface dataset:
A gateway-based interoperability solution for permissioned blockchains

&lt;p&gt;During the last years, interoperability has become one of the main challenges within blockchain research as blockchains increasingly require integration between each other. Indeed, blockchains work by design in silos of information as interoperability is not a native feature. The main efforts in the field target permissionless blockchains, such as Bitcoin and Ethereum. However, interoperability in permissioned blockchains remains as an almost untouched area of work as they introduce additional requirements focusing on privacy and identity. Although there are some interoperability solutions for permissioned blockchains, they are either high-level design proposals not providing concrete implementations or focus on interoperability issues between business applications and blockchain platforms. In this paper we propose a gateway-based platform-to-platform interoperability solution for permissioned blockchains, which comprises a detailed solution design and a reference implementation. The proposal was assessed through the development of a social security case scenario, based on the reference implementation and using two blockchain platforms: Hyperledger Fabric and Corda. &lt;/p&gt;
Binary self-dual codes of various lengths with new weight enumerators from a modified bordered construction and neighbours

In this work, we define a modification of a bordered construction for self-dual codes which utilises $λ$-circulant matrices. We provide the necessary conditions for the construction to produce self-dual codes over finite commutative Frobenius rings of characteristic 2. Using the modified construction together with the neighbour construction, we construct many binary self-dual codes of lengths 54, 68, 82 and 94 with weight enumerators that have previously not been known to exist.
Global Attention Improves Graph Networks Generalization

This paper advocates incorporating a Low-Rank Global Attention (LRGA) module, a computation and memory efficient variant of the dot-product attention (Vaswani et al., 2017), to Graph Neural Networks (GNNs) for improving their generalization power. To theoretically quantify the generalization properties granted by adding the LRGA module to GNNs, we focus on a specific family of expressive GNNs and show that augmenting it with LRGA provides algorithmic alignment to a powerful graph isomorphism test, namely the 2-Folklore Weisfeiler-Lehman (2-FWL) algorithm. In more detail we: (i) consider the recent Random Graph Neural Network (RGNN) (Sato et al., 2020) framework and prove that it is universal in probability; (ii) show that RGNN augmented with LRGA aligns with 2-FWL update step via polynomial kernels; and (iii) bound the sample complexity of the kernel's feature map when learned with a randomly initialized two-layer MLP. From a practical point of view, augmenting existing GNN layers with LRGA produces state of the art results in current GNN benchmarks. Lastly, we observe that augmenting various GNN architectures with LRGA often closes the performance gap between different models.
Mask Covered Face Recognition Using Haar Cascade Classifier and Fuzzy Logic

Right from the beginning of the COVID-19 outbreak, everyone is aware of the havoc caused by the pandemic. To curb its spread, every healthcare agency and civic body around the globe has been advising to wear masks. However, this necessary practice has posed a significant challenge for the modern-day Facial Recognition technology. Face recognition finds significant application in the security domain that demands speed and accuracy both simultaneously. This requires the system to be highly optimized and efficient. Through this paper, we present a novel approach using Haar cascade classifier for face detection with Local Binary Patterns Histograms (LBPH) face recognizer. This work further goes on to address the various problems that occur when the user wears a mask that covers a different area and percentage coverage of the face resulting in inaccuracies as various tests come with false negatives or false positives. This problem is addressed by making use of a fuzzybased system that decides the “threshold confidence score” needed to pass the authentication dynamically. Our proposed model for masked Face recognition achieves an accuracy of 86% when a Haar-feature-based cascade classifier with LBPH face recognizer is used standalone which further improves to around 97% when used in conjunction with a fuzzy system
Boundaries of quantum supremacy via random circuit sampling

Google's recent quantum supremacy experiment heralded a transition point where quantum computing performed a computational task, random circuit sampling, that is beyond the practical reach of modern supercomputers. We examine the constraints of the observed quantum runtime advantage in an extrapolation to circuits with a larger number of qubits and gates. Due to the exponential decrease of the experimental fidelity with the number of qubits and gates, we demonstrate for current fidelities a theoretical classical runtime advantage for circuits deeper than a few hundred gates, while quantum runtimes for cross-entropy benchmarking limit the region of a quantum advantage to a few hundred qubits. However, the quantum runtime advantage boundary in circuit width and depth grows exponentially with respect to reduced error rates, and our work highlights the importance of continued progress along this line. Extrapolations of measured error rates suggest that the limiting circuit size for which a computationally feasible quantum runtime advantage in cross-entropy benchmarking can be achieved approximately coincides with expectations for early implementations of the surface code and other quantum error correction methods. Thus the boundaries of quantum supremacy via random circuit sampling may fortuitously coincide with the advent of scalable, error corrected quantum computing in the near term.
Improving Students’ Reading Comprehension through Communicative Language Teaching(CLT)

The research aims to find out whether the students reading comprehension can be improved through the use of the Communicative Language Teaching(CLT) method. In order to achieve the objectives, the researcher held action research at SMA N 5 Lhokseumawe, from 16- 19th March 2021. There were 2 cycles in which 2 meetings were held for each cycle. The subject of the study is the second year with the numbers of population 32 students. The instruments used were observation sheets, questionnaires, and tests. The result of the study is the problem of motivating students to read. This can be solved by using Communicative Language Teaching(CLT). Based on the questionnaire, all of the students said that the use of the Communicative Language Teaching(CLT) method was interesting. In line with the questionnaire result, the observation sheet also showed excellent results on students’ study habits. There was an improvement in students’ comprehension, it can be seen in cycle 1 which was 89.06 points, and cycle II which was 95.6 points. In this study, I suggest that the teachers should be able to use Communicative Language Teaching(CLT) as an alternative to motivating students learning.
The Implementation of Self-Directed Dialogue to Improve Students’ Speaking Ability

The purpose of this study was to find out the improvement of students speaking ability through the implementation of the self-directed dialogue technique, and student activities when the Self-directed Dialogue was applied to English subjects in the first grade of MA Darussalam, Beremi for the 2021/2022 academic year. In this study, the researcher used classroom action research as a research design by employing observation, tests, and documentation as techniques to gain the data. Observations were made to determine the application of self-directed dialogue techniques during the teaching and learning process while tests were used to measure student achievement in speaking ability. The subjects of this study were students in first grade of MA Darussalam Bermi with 21 students in the class. Researchers used qualitative and quantitative data analysis in calculating and analyzing data. The results of this study indicate that the self-directed dialogue technique can improve students' speaking ability. This can be seen from the results of a significant increase in each cycle. The score before implementing the technique was 48, the result of post-test 1 was 74.43, and post-test 2 was 84.43. This means that the students' speaking ability increases after applying the self-directed dialogue technique in the first grade of MA Darussalam Bermi in the 2021/2022 academic year.
Textual Error Analysis on the Use of Simple Present Tense in Writing Descriptive Text

Finding out the frequency, kind, causes, and effects of linguistic failures is the process of error analysis. This study aims to pinpoint students' mistakes when using the simple present tense to write a descriptive text. To complete the investigation, the researcher uses the qualitative approach. Students' mistakes affect the descriptive English content. Twenty junior high school students from west Jakarta were given writing prompts. Their text demonstrates how their sentences lost all of their original meaning. When asked to create an English descriptive text, they encountered challenges. Following an investigation of the students' English descriptive texts, twenty errors have occurred in the simple present tense; error of omission, error of selection, error of addition and error of ordering.
Persepsi Siswa Terhadap Pembelajaran Daring pada Masa Pandemi pada Tahun Ajaran 2020/2021

ABSTRACT&#x0D; The purpose of the study was to determine students' perceptions of online learning that had been implemented in the 2020/2021 school year. The research method used is qualitative research. The results showed: 1) Based on the questionnaire, 80% of students answered that they were not interested in online learning, students gave reasons including not having an android, the network was not smooth, and unable to buy internet quota. As well as by reason of difficulties in understanding lessons and boredom in carrying out learning activities at home. The conclusion of the study is that 8 out of 10 students are not interested in online learning. Then based on the results of teacher interviews, the difficulties experienced in the online learning process are also very diverse, including not all students have androids, the teacher's ability about online learning application technology is still relatively new, the media used is not varied.&#x0D; Keywords: Online Learning, Pandemic, Perception &#x0D;
Bandwidth-Efficient Transaction Relay for Bitcoin

Bitcoin is a top-ranked cryptocurrency that has experienced huge growth and survived numerous attacks. The protocols making up Bitcoin must therefore accommodate the growth of the network and ensure security. Security of the Bitcoin network depends on connectivity between the nodes. Higher connectivity yields better security. In this paper we make two observations: (1) current connectivity in the Bitcoin network is too low for optimal security; (2) at the same time, increasing connectivity will substantially increase the bandwidth used by the transaction dissemination protocol, making it prohibitively expensive to operate a Bitcoin node. Half of the total bandwidth needed to operate a Bitcoin node is currently used to just announce transactions. Unlike block relay, transaction dissemination has received little attention in prior work. We propose a new transaction dissemination protocol, Erlay, that not only reduces the bandwidth consumption by 40% assuming current connectivity, but also keeps the bandwidth use almost constant as the connectivity increases. In contrast, the existing protocol increases the bandwidth consumption linearly with the number of connections. By allowing more connections at a small cost, Erlay improves the security of the Bitcoin network. And, as we demonstrate, Erlay also hardens the network against attacks that attempt to learn the origin node of a transaction. Erlay is currently being investigated by the Bitcoin community for future use with the Bitcoin protocol.
EFL Students’ Perceptions on Using Picture Strip Story in Learning Speaking Skills

Using a method in the teaching-learning process that is by the condition of students to maximize the purpose of English learning. In the Indonesian context, limited time to learn speaking skills for EFL students is still one of the issues found in the classroom. The method that can be used to maximize the process of teaching and learning is picture strip story. This research aimed to find out the EFL students' perception of using picture strip stories in learning speaking skills. The participants of this research consisted of twelve students. The writer collected data by using focus group discussions with a semi-structured interview. The researcher used data display, condensation, drawing, and verification in data analysis. The result of this research was positive perceptions from EFL students toward using picture strip stories in learning speaking skills, such as improving students' confidence to speak with others, developing the students' proficiency in language competence, improving students' motivation, and adding the eggar the students to learn speaking skills.
Unsupervised Controllable Generation with Self-Training

Recent generative adversarial networks (GANs) are able to generate impressive photo-realistic images. However, controllable generation with GANs remains a challenging research problem. Achieving controllable generation requires semantically interpretable and disentangled factors of variation. It is challenging to achieve this goal using simple fixed distributions such as Gaussian distribution. Instead, we propose an unsupervised framework to learn a distribution of latent codes that control the generator through self-training. Self-training provides an iterative feedback in the GAN training, from the discriminator to the generator, and progressively improves the proposal of the latent codes as training proceeds. The latent codes are sampled from a latent variable model that is learned in the feature space of the discriminator. We consider a normalized independent component analysis model and learn its parameters through tensor factorization of the higher-order moments. Our framework exhibits better disentanglement compared to other variants such as the variational autoencoder, and is able to discover semantically meaningful latent codes without any supervision. We demonstrate empirically on both cars and faces datasets that each group of elements in the learned code controls a mode of variation with a semantic meaning, e.g. pose or background change. We also demonstrate with quantitative metrics that our method generates better results compared to other approaches.
Enhanced Technique for Multiple Face Detection Based on LBPH (Local Binary Patterns Histograms): A Review

Abstract: Facial recognition has long been an active study area because of its lack of modelling requirements and the wide range of applications. Because of this, daily tasks are increasingly being completed electronically rather than with pen and paper. Currently, computer vision is a broad topic that deals with complex programming by using input images and videos to carry out automatic tasks including detection, recognition, and classification. Face recognition and its applications have recently been regarded as one of the most successful image analysis applications, especially over the past few years. Even deep learning approaches, they are superior to the typical human visual system. Face Recognition is a special technology that uses distinctive facial traits to identify or confirm a person
Key technology of crop precision sowing based on vision principle

In the process of precision planting of crops, due to many external environmental interference factors, low precision of sowing technology and large relative errors, the growth of crops is seriously affected. To solve this problem, machine vision technology is introduced to study the key technology of crop precision sowing based on vision principle. After preprocessing the crop image, the corresponding histogram is established. The segmentation threshold method is used to gray the image and determine the best threshold, so that the image has a good recognition effect. According to the growth height and color analysis of crops in the image, predict the growth of crops and realize the precision sowing of crops. The comparative experimental results show that under the application of the new sowing technology, the estimation accuracy of crop planting area is high, the recognition accuracy of planting position is also high, and the fertilization uniformity is close to the actual data, which can provide an important basis for improving the quality of crop sowing.
Study of Different Algorithms on Opinion Mining

Abstract: Social media is critical in today's world for exchanging information and disseminating ideas. A person's emotional impact has a significant impact on their day-to-day life. Sentiment analysis is a form of text mining that locates and pulls out subjective information from sources, allowing a company to track discussions online and monitor social sentiment about their brand, product, or service. Simply put, sentiment analysis helps determine the author's attitude towards a topic. Positive, neutral, or negative pieces of writing are classified by sentiment analysis software. Deep learning algorithms and various functions of natural language processing helps to interpret the written or spoken sentiments regarding a topic. An ecosystem where millions of bytes of data are produced daily has enabled sentiment analysis to be a key tool for interpreting these huge chunks of data. The purpose of this work is to conduct a sentiment analysis on "tweets" by making use of a variety of machine learning algorithms. The study will make an attempt to categorise the polarity of the tweet as either positive, negative, or neutral. In the event that a tweet has only positive, negative, or neutral components, the label assigned to the tweet will be determined by the sentiment that predominates.
QR Code Attendance System with SMS Notification

Abstract: The attendance maintenance system is the major performance evaluation of the student. In recent periods, the student attendance is maintained in the system manually and updated in the particular college server. Several attendance systems have been proposed based on manual presence. This is a highly important problem. The administration requires careful follow-up, taking care of it and not being lenient. The previous systems are inefficient in term of processing time and low in accuracy. Smart Attendance System using QR Code with SMS Notification will be developed for helping lecturers to manage student attendance. To ensure the student attends in the classroom, QR code contained the time information was generated and displayed at lecturer presentation. The student only needed to scan the displayed QR code and face using ESP32 CAM. The code was then sent to the server for attendance process.
The administrative efficiency of the faculties of physical education and sports sciences in the Kurdistan Region - Iraq Using total quality standards

The importance of this study lies in the topic it deals with, its modernity in the educational administrative field and related to the philosophy of total quality management, and the effectiveness of its application in the field of sports management. Especially in the faculties of physical education and sports sciences. The research problem was to estimate and know the degree of effectiveness of the college's performance using the college's total quality standards. The aim of the research is to know the effectiveness of the performance of the college’s performance using the quality standards when managing the college. The human field included: (Dean of the College, Associate Dean, heads of branches and officials of administrative units) of the College. The descriptive approach was used, which is concerned with describing the various aspects of total quality management and for its relevance with the research procedures. As for the research sample, it was deliberately selected and made up of (the dean of the college, the assistant dean, heads of branches and officials of administrative units) of the College of Physical Education and Sports Sciences / Salah al-Din University - Erbil. (42) individuals. To complete the research, the research used the following tools: 1- Scientific sources. 2- A questionnaire form. In this regard, a questionnaire was used for the study (Al-Osaili, Raja Zuhair, 2007) to suit its axes and paragraphs and the nature of this study after presenting it to the experts to find out its adaptation to the environment in which the research is applied. The research reached several conclusions, including: - The efficiency of the administrative body in the College of Physical Education and Sports Sciences / University of Salah al-Din - Erbil - Iraq, is good in terms of planning, method of performing exams, creating an appropriate organizational climate, developing educational means and teaching methods, and changing and developing curricula. - The efficiency of the administrative body in the College of Physical Education and Sports Sciences / University of Salah al-Din - Erbil - Iraq in using information technology is not at the level required to develop the educational performance of the college. The research recommended several recommendations, including: Adopting comprehensive quality standards in the college administration in order to improve its performance level. The college administration adopts the use of modern information and communication technology in planning
Actual Problems of Implementation of State Policy in the Field of Education in Municipalities of the Russian Federation

The article is devoted to the current state of implementation of state policy in the field of education in the territories of Russian municipalities. A special place in the article is given to the delimitation of powers in the field of education between state authorities and local self-government bodies. The article presents current data on the implementation of the National Project “Education” in the territories of municipalities and highlights the actual problems of the activities of local governments involved in the implementation of the state policy of the Russian Federation in the education.
Job engagement for physical education teachers in secondary schools in the city of Mosul

Research aim to:-Structure a job engagement scale for physical education teachers in secondary schools in the city of Mosul -Identifying the level of occupational involvement of physical education teachers in secondary schools in the city of Mosul.The descriptive approach was used by survey method.The construction and final application samples included (146.98)teachers, respectively, of physical education teachers in secondary schools in the city of Mosul, distributed among middle, secondary and preparatory schools.Arithmetic mean, standard deviation, simple correlation, Gittmann equation and Cronbach's alpha coefficient.The researchers drew several conclusions, the most important of which are -The validity of the occupational involvement scale by physical education teachers, which was built by the researchers on middle, secondary and middle schools in the city of Mosul.-The degree of occupational involvement of physical education teachers in middle, secondary and preparatory schools in the city of Mosul is at a (very good) level.Therefore, the researcher recommends:-Holding intensive educational seminars and courses that encourage job engagement in all other specializations in secondary schools in the city of Mosul.-Applying the job engagement scale to other samples of all specializations.-Develop an evaluation form for the performance of physical education teachers in secondary schools that includes all aspects of their work in order to ensure the objectivity of the evaluation and circulate it to all secondary schools throughout Iraq