Reviewerly/exHarmony huggingface dataset:
NFFKD: A Knowledge Distillation Method Based on Normalized Feature Fusion Model

The aim of Knowledge Distillation (KD) is to train lightweight student models through extra supervision from large teacher models. Most previous KD methods transfer feature information from teacher models to student models via connections of feature maps at the same layers. This paper proposes a novel multi-level knowledge distillation method, referred to as Normalized Feature Fusion Knowledge distillation(NFFKD). The proposed model learns different levels of knowledge to improve the network performance. We proposed to use the hierarchical mixed loss(HML) module to minimize the gap between the intermediate feature layers of the teacher and the student, and the teacher-student gap is reduced by normalizing the logits. Experimental results have demonstrated that the proposed NFFKD shows superiority over several state-of-the-art KD methods on public datasets under different settings.
Research on the Problems Existing in the Application of Garden Maintenance Technology

In the modern city, the garden is an important part, it plays a role in beautifying people’s living environment, but also can purify the air, to the maintenance of natural ecological environment balance has played a role in promoting. Landscape engineering construction content and complex, especially the late maintenance work is very important, directly about the sustainable development of garden, it is easy to be ignored, so, to reasonable application of garden maintenance technology, make the garden engineering get higher comprehensive benefits, this paper focuses on the problems in the process of garden construction maintenance technology and solution strategy.
Security Ink Technology in Forensic Way

Forensic science is the emerging field of science to solve the different crimes in easy way.The prominence of forensic science has resulted from scientific and technological advances, raised reliance of enforcement agencies and judicial systems and its popularization through the mass media.Forensic proof is gathered, examined, evaluated, understood and conferred to create sense of a happening and supply investigative leads.Thanks to increasing the various techniques to try and do the crime, there should be some distinctive and numerous strategies to research it.Some of the crimes are well occurred, that in investigation there are not any clues and evidence would be found to more investigation.In recent time, the crime has been severally increased as the technology improves.As it is an important question for the security purpose.There are many counterfeit actions conducted in different ways.In this short review, it is explained that how the confidential documents are being duplicating and with the help of forensic science how the experts can examine the documents.The different types of documents are also mentioned in the review.It also described the forensic way of documents examination.It elucidated the documentation printing problems and various methods of printing with ink analysis.
Peramalan Jumlah Penderita DBD di Provinsi Jawa Barat dengan Metode Hybrid Sarimax-Ann

Indonesia is one of the tropical countries in the world, therefore Indonesia has two seasons, namely the dry season and the rainy season. Because it has two seasons, it can cause tropical diseases that is growing very fast is Dengue Hemorrhagic Fever (DHF). DHF is time series data tha can be collected annually and has a seasonal cycle. Because it is time series data, it can be forecasted using SARIMAX method, but SARIMAX is only able to solve linear problems and to overcone non-linear prolblems it can be solved using the ANN Backpropagation method. Therefore, in this study using the Hybrid SARIMAX-ANN method. The data in this study contained the dependent variable and the independent variable. The dependent variable is DHF data, while the independent variable is air humidity, air temperature, and rainfall data. The result obtained in this study, namely the factor that greatly affects DHF is air humidity. Forecasting result form Januari 2021 to June 2021 are 1.081, 960, 1.132, 1.103, 2.467, and 1.605. the it produces a MAPE value of 16,33% which means a good level of accuracy.
Multi-Qubit Quantum Compiler Based on Deep Q-Learning

The quantum computer is a device that performs calculations by using properties of quantum mechanics such as superposition and quantum entanglement and is a promising technology for solving problems that are currently infeasible to be solved by classical computers, such as the simulation of quantum states of complex molecules, quantum cryptography, and the brute-force search optimization of systems with several variables. However, the unique way in which information is processed and stored in quantum computers opens up a new field of study on how to optimize the implementation of algorithms on these devices to exploit the full potential that this technology can provide. In the conception of quantum computers, just like in classical computers, lies the compilation of algorithms. Because there is no deterministic form of defining the most efficient set of instructions that represent an algorithm in a given quantum computer, the quantum compilation is a problem that does not have a definitive solution, making it one of the focuses of research in the area of quantum computing. As quantum compilation can be modeled as the problem of searching a set of quantum gates to minimize the error between a target result and the searched result, deep learning presents a set of methods that can approach this problem. Therefore, this work aims to design a multi-qubit quantum compiler by using the deep Q-network, whereby the compiler learns the rules of how to transform an algorithm into instructions for a specific quantum computer. The outcome of this work is a trained deep Q-network model able to compile multi-qubit quantum algorithms that can be validated on a quantum computer with percentage accuracies varying from 54% up to 100% according to the size of the related quantum circuit.
Obstacles Faced around Mathematics Education in Nepal in Terms of Promoting Meaningful, Authentic and Inclusive Education

In this paper, we discussed some major obstacles that are existing in promoting meaningful, authentic and inclusive education in Nepal in case of mathematics education based on the experiences and reflections gained from the study of various creations of different authors. However, many Nepalese teachers are still using the traditional method of teaching in which a teacher is regarded as the only source of information and the learners as the vessels that need to be filled with knowledge; the modern concept of mathematics learning does not treat the students as the passive listeners as mentioned in the traditional approach. Creative learning in mathematics is the best learning approach as the demand of modern education fosters the engagement of the learners. Moreover, to make fruitful learning in mathematics with active involvement of the learners, there may arise some obstacles in our context. Therefore, this work is intended to explore the major obstacles faced around mathematics education in Nepal in terms of promoting meaningful, authentic and inclusive education. Indeed, from our in-depth study, we highlighted curriculum, pedagogical approaches, teachers’ role, evaluation process, political issues, social exclusion and location of schools as the emerging obstacles in developing meaningful, authentic and inclusive education in our context.
Assets and community engagement

opinion Share on Assets and community engagement: a roundtable with HCI researchers and designers Authors: Lucy Pei University of California, Irvine University of California, IrvineView Profile , Edgard David Rincón Quijano Universidad del Norte Universidad del NorteView Profile , Angela D. R. Smith University of Texas at Austin University of Texas at AustinView Profile , Reem Talhouk Northumbria University Northumbria UniversityView Profile , Frederick van Amstel Universidade Tecnológica Federal do Paraná Universidade Tecnológica Federal do ParanáView Profile Authors Info & Claims InteractionsVolume 29Issue 5September - October 2022 pp 44–47https://doi.org/10.1145/3554975Published:30 August 2022Publication History 0citation573DownloadsMetricsTotal Citations0Total Downloads573Last 12 Months573Last 6 weeks312 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my Alerts New Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Computing semantic similarity of texts based on deep graph learning with ability to use semantic role label information

Abstract We propose a deep graph learning approach for computing semantic textual similarity (STS) by using semantic role labels generated by a Semantic Role Labeling (SRL) system. SRL system output has significant challenges in dealing with graph-neural networks because it doesn't have a graph structure. To address these challenges, we propose a novel SRL graph by using semantic role labels and dependency grammar. For processing the SRL graph, we proposed a Deep Graph Neural Network (DGNN) based graph-U-Net model that is placed on top of the transformers to use a variety of transformers to process representations obtained from them. We investigate the effect of using the proposed DGNN and SRL graph on the performance of some transformers in computing STS. For the evaluation of our approach, we use STS2017 and SICK datasets. Experimental evaluations show that using the SRL graph accompanied by applying the proposed DGNN increases the performance of the transformers used in the DGNN.
Theoretical usability of an innovative device for post-infarction rehabilitation: Observational study with rehabilitation nurses

Background: Cardiac rehabilitation programs are essential for recovering and maintaining functional capacity in patients with acute myocardial infarction.Current programs have high dropout rates and require more motivational features.Objectives: To assess and compare the usability of two prototypes of an innovative rehabilitation device for post-infarction patients.Methodology: This is a quantitative observational study using a 5-point Likert-type scale with 16 nurse specialists in rehabilitation, selected through snowball sampling.Results: The quantitative analysis showed a three-dimensional assessment of the prototypes with mean scores of 4, indicating usability and intention to use.Both prototypes were considered useful, functional, and easy to learn and use, with few differences reported on the three dimensions.The ease of learning was more consensual in the Alpha prototype. Conclusion:The two developed prototypes present high usability scores and are very similar, demonstrating great potential for effectiveness in the intended context.
Pandemic Fatigue: An Analysis of Twitter Users’ Sentiments Against the COVID-19 in Indonesia

Indonesian society is undergoing a shift of behavioral patterns towards the coronavirus (COVID) 19 indicating the symptoms of the pandemic fatigue phenomenon. Pandemic fatigue is defined as a gradual demotivation to adhere to recommended protective behaviors. Pandemic fatigue might reduce the effectiveness of health protocols and accelerate the spread of the virus. This study aims to examine the pandemic fatigue sentiment of Indonesian twitter-users chronologically and the factors causing the development of pandemic fatigue sentiment. The method of this study includes digital ethnographic theory using sentiment analysis based on the Valence Aware Dictionary for Sentiment Reasoning (VADER) algorithm and topic modelling using Latent Dirichlet Allocation (LDA) analysis. The results showed a pattern of sentiment degression towards health protocols indicating the pandemic fatigue phenomenon. The factors causing the sentiment degression were influenced by three themes: (1) public criticism of the government's efforts to handle the spread of COVID-19, (2) experience in implementing health protocols, and (3) statements that against the government’s efforts to handle the spread of COVID-19. Based on the results of sentiment analysis and topic modelling, this study presents a public policy design referencing the World Health Organization (WHO) framework for community reinvigoration in the midst of pandemic fatigue that could be used for the government to undertake broader reforms to public health and social care for Indonesian society.
LITERATURE REVIEW: GROUP GUIDANCE SELF-MANAGEMENT TECHNIQUE AS AN ALTERNATIVE INTERVENTION FOR STUDENT SELF-CONTROL

Student’s self-control is one of the problems that often occurs in completing assignments, so techniques are needed to overcome these self-control problems. The purpose of this article is to explain group guidance self-management techniques as an alternative intervention for student self-control. The method used in this research is library research. The research implementation process is as follows: 1) topic selection; 2) exploration of information; 3) determining the focus of the research; 4) collection of data sources; 5) preparation of data presentation; and 6) preparation of the report (Mirzaqon &amp; Purwoko, 2018). The study in this research is related to self-management strategies through group guidance for student’s self-control so that students are able to manage time well.
THE EFFECT OF THINK ALOUD STRATEGY ON STUDENTS’ READING COMPREHENSION AT THE TENTH GRADE OF SMK SWASTA SITI BANUN

This study aims to determine the effect of think aloud strategy on students’ reading comprehension at the tenth grade of smk swasta siti banun. The data collection technique was used to measure students’ learning outcomes in the form of assignment questions carried out on the pretest and posttest. The data analysis technique used is normality test using F test, homogeneity test and hypothesis testing using t test. The hypothesis in this study was tested by t-test at a significant level = 0.05. From the calculation of the data it was seen that t-count &gt; t-table (3,41&gt; 1,67). Thus the null hypothesis is that Ho is rejected and Ha is accepted. From the results, it can be concluded that there is a significant effect of Think Aloud Strategy on Students’ Reading Comprehension at Tenth Grade of SMK Swasta Siti BanunKeywords: Reading comprehension; Think Aloud Strategy; Thinking Hard.
Development of Rujuku Mobile Learning Apps on Integer Operation Material as Alternative Media

Since the Covid-19 pandemic in early 2020, Indonesia has implemented distance education by optimizing the use of technology. Therefore, the researcher developed the Rujuku Mobile Learning Apps Development on Integer Operation Material in Class VII SMP/MTs to support the implementation of distance learning during the pandemic. This study aimed to develop the RUJUKU application and determine student responses in learning after using the developed media. This development research uses the ADDIE method. The data collection technique used a questionnaire with data processing techniques analyzed using percentage data analysis techniques. The results showed that RUJUKU was suitable for use, attractive, and easy to use. This is based on the validation results in terms of material, an average of 89.70%, and in terms of media, an average of 88.81%. Student response is quite good, with a percentage of 89.06%. Based on that result, this research significantly impacted the integers' learning process of addition and subtraction operations during this pandemic.
Correction to: Non-Interactive Zero-Knowledge Proofs with Fine-Grained Security

In an older version of this paper, there was an erroneous insertion of an equation on page 315. This has been removed.
Review of "The Algorithm Design Manual, 3 <sup>rd</sup> ed. by Steven S. Skiena Springer, 2020 793 pages, Hardcover, $99.99"

The Algorithm Design Manual is an aptly named undergraduate-level textbook that takes a utilitarian approach to presenting algorithms as a collection of off-the-shelf technologies that can be adapted to obtain practical solutions to real-world problems. Its intended audience is aspiring and practicing professional programmers, and its pedagogical emphasis is on facility in application rather than rigorous implementation or analysis of these technologies.
Life Motivation in Autobiography of Nick Vujicic Life Without Limits Literary Learning Perspective

&#x0D; &#x0D; &#x0D; &#x0D; This study describes Nick Vujicic's life motivation which includes extrinsic and intrinsic motivation to fulfill his life needs in his autobiography "Life Without Limits" from a literary learning perspective. The research method used is descriptive qualitative. The research results in Nick Vujicic's autobiography "Life Without Limits" show that Nick gets extrinsic motivation from his family, especially his father and mother, who encourage, mobilize, and direct Nick to make ends meet. Motivation from his parents encourages Nick to get the intrinsic motivation within himself to encourage himself to carry out his daily activities (physiological needs), feel secure about his future (need for security and protection), and feel loved and accepted by himself. Friends and family (the need to have and love) with a physical condition without arms and legs. Extrinsic and intrinsic motivation plays an important role that needs and complements each other in facing every difficulty and challenge in life, thus enabling Nick to fulfill his life's needs and get through his dark times&#x0D; &#x0D; &#x0D; &#x0D;
RESIDUAL ATTENTION BI-DIRECTIONAL LONG SHORT-TERM MEMORY FOR VIETNAMESE SENTIMENT CLASSIFICATION

Sentiment classification is a problem of assessing and estimating values of people’s opinions, sentiments, and attitudes to products, services, individuals, and organizations. Sentiment analysis helps companies understand their customers for improving marketing strategies in e-commerce, manufacturers decide how to improve their products, or people adjust behavior in their lives. In this paper, we propose a deep network model to classify the reviewed product in Vietnamese. Specifically, we develop a new deep learning model called the Residual Attention Bidirectional-Long Short Term Memory (ReAt-Bi-LSTM) model. First, the residual technique is used in multiple layers Bidirectional Long Short Term Memory (Bi-LSTM), to enhance the model’s capability in learning high-level features from input documents. Second, the attention mechanism is integrated after the last Bi-LSTM layer to assess each word’s contribution to the context vector to the document’s label. Last, the document’s final representation is the combination of the context vector and output of Bi-LSTM. This representation captures both context information from the context vector and sequence information from the Bi- LSTM network. We conducted extensive experiments on four common Vietnamese sentiment datasets. The results show that our proposed model improves the accuracy compared with some baseline methods and one state of the art model for the sentiment classification problem.
ANALISA PENGARUH SUDUT DATANG SINAR MATAHARI TERHADAP KINERJA SOLAR CELL 50 Wp

Indonesia is a country located on the equator which has a relatively high average daily solar irradiation rate in the world.And that the world is currently experiencing a crisis in the production of fossil fuels to be converted into electricity.Therefore, there are things that underlie the use of solar energy as a source of Solar Power Generation (PLTS).Solar cells as a technology application of renewable energy sources have an insufficient output power constraint and are highly dependent on natural conditions.However, here we will review a Solar Cell to see how it works at rest and changes according to changes in the angle of the sun.From the testing the results at the highest irradiation level of each test, namely for a stationary solar panel on the third day of 552.7 W / m 2 , the efficiency of the tool was equal to that for the state of the panel following changes in the angle of the sun which was 579.1 W / m 2 .With efficiencies of 22.01% and 21.01, respectively.
Dataset Augmentation Using Back-Translation to Improve Early Stage Dialog Systems

As dialog systems are increasingly used, a major challenge for building new ones is the lack of annotated training data.The necessary data collection and annotation efforts are laborious and time-consuming.A potential solution is to augment initial seed data by automatically paraphrasing existing samples.In this paper, we propose a novel dataefficient approach towards this goal.Our method can kick-start a dialog system with minimum human effort while delivering a performance strong enough to allow real-world usage.We ran experiments using Neural Machine Translation on two open corpora.On both of them, the proposed approach improved the generalization capabilities of the model.Our results suggest that paraphrase generation techniques could be used as-is to provide a boost in performance to dialog systems in an early phase.
IEEE Journal of Selected Topics in Quantum Electronics Information for Authors

Journal of Selected Topics in Quantum Electronics fall within the broad field of science and technology of quantum electronics of a device, subsystem, or system-oriented nature.Each issue is devoted to a specific topic within this broad spectrum.Announcements of the topical areas planned for future issues, along with deadlines for receipt of manuscripts, are published in this Journal and in the IEEE Journal of Quantum Electronics.Generally, the scope of manuscripts appropriate to this Journal is the same as that for the IEEE Journal of Quantum Electronics.Manuscripts are published that report original theoretical and/or experimental research results that advance the scientific and technological base of quantum electronics devices, systems, or applications.The Journal is dedicated toward publishing research results that advance the state of the art or add to the understanding of the generation, amplification, modulation, detection, waveguiding, or propagation characteristics of coherent electromagnetic radiation having sub-millimeter and shorter wavelengths.In order to be suitable for publication in this Journal, the content of manuscripts concerned with subject-related research must have a potential impact on advancing the technological base of quantum electronic devices, systems, and/or applications.Potential authors of subject-related research have the responsibility of pointing out this potential impact.System-oriented manuscripts must be concerned with systems that perform a function previously unavailable or that outperform previously established systems that did not use quantum electronic components or concepts.Tutorial and review papers are by invitation only.