Reviewerly/exHarmony huggingface dataset:
Deep and shallow fast embedded capsule networks: going faster with capsules

Abstract Capsule Networks (CapsNets) is a great approach for understanding data in the field of computer vision. CapsNets allow a deeper understanding of images compared to the traditional Convolutional Neural Networks. The first test for CapsNet was in digits recognition on the ‘MNIST’ dataset, where it successfully achieved high accuracy. CapsNets are reliable at deciphering overlapping digits. Deep Capsule Networks achieved state-of-the-art accuracy in CIFAR10 which isn’t achieved by shallow capsule networks. Despite all these accomplishments, Deep Capsule Networks are very slow due to the ‘Dynamic Routing’ algorithm. In this paper, Fast Embedded Capsule Network and Deep Fast Embedded Capsule Network are introduced, representing novel capsule network architectures that uses 1D convolution based dynamic routing with a fast element-wise multiplication transformation process. These architectures not only compete with the state-of-the-art methods in terms of accuracy in the capsule domain, but also excels in terms of speed, and reduced complexity. This is shown by the 58% reduction in the number of trainable parameters and 64% reduction in the average epoch time in the training process. Experimental results shows excellent and verified properties.
Streamlining User Experiences with ScienceDirect Prepaid Articles

Two librarians from the James E. Walker Library at Middle Tennessee State University describe the implementation of prepaid article access to ScienceDirect content. An overview of the initiative is provided along with adjustments that were made to the implementation. Also included is a description on how the use of various tools streamlined the user experience. The authors describe the challenges of determining the levels of mediation that worked for the library and its users. Although the program will be discontinued due to costs and limited customization options, useful information was gathered about article use indicating the need for scholarly resources and document delivery services. This article is based on the lightning talk, Streamlining User Experiences with ScienceDirect Prepaid Articles, presented at the 2022 North Carolina Serials Conference.
CULTURAL CONTENT ANALYSIS IN TWO EFL TEXTBOOKS USED BY BOARDING SCHOOLS IN BANTEN: A MULTIMODAL ANALYSIS

Learning a language also contains a cultural learning component. Teaching a foreign language in a country can help to promote the learner’s local culture. English is the most significant language for cross-cultural communication amongst people all over the world in these global Englishes. English is included in the education curriculum in Indonesia and has been learned as a foreign language since the elementary school level. This study aims to find out the cultural content in EFL Textbooks used by Boarding Schools in Banten as well as how the representation of culture in the textbooks. Kachru’s Three Concentric Circle of English (1984) and Moran’s Five Dimension of Culture (2001) were used as the main theory in this study. Content analysis qualitative research was used in this study. This research is a multimodal analysis because the data is not only in the form of words but also from pictures and audio. The subjects of this analysis are two textbooks used by SMA Islam Nurul Fikri Serang and SMAN CMBBS Pandeglang with the textbooks title are “Pathway to English” Grade X and “Symphony 1” Grade X. Mile and Huberman’s theory about qualitative data analysis method (2014) i.e. Data Condensation, Data display, and Conclusion drawing used in this study for analyzing the data. The data analysis on the two textbooks reveals that first, Inner circle culture, Outer Circle Culture, Expanding Circle Culture, and Local culture were identified in the textbook with the most dominant type is inner circle culture; second, the cultural content in the two textbooks were represented by product, practice, perspective, community, and person with the most dominant occurrence was products. This study concludes that the cultural content in the two textbooks still orients to and promotes the inner circle culture and accommodating local culture, expanding circle culture and outer circle culture.
Elis: A Virtual Chatbot

Abstract: A Chatbot is Artificial Intelligence computer software that can act as a conversation either through text or audio method. The core analyses a customer’s data using the artificial intelligence which integrates the response with them. Different tasks can be replaced with AI bots as they are much more powerful and can perform multiple tasks simultaneously. Machine Learning techniques are basically used for getting signals and responding to that. Natural language processing allows a bot to have a conversation as naturally as possible. The ideal interaction between user and chatbot is a balanced mix of Innovative technology and human Intervention.
PENGARUH JARAK PENYINARAN TERHADAP NILAI DERAJAT KONVERSI RESIN KOMPOSIT BIOAKTIF

ABSTRACTBackground: The improper irradiation process causes imperfect polymerization, so that the hardness of the composite resin, material strength, and color stability of the resulting composite resin are not optimal and water absorption increases. The long irradiation distance will result in the intensity of the light obtained getting smaller because the light can not reach the composite resin optimally and the degree of perfection of the polymerization of the composite resin will decrease. Objectives: The purpose of this study was to determine the difference between the irradiation distance and the degree of conversion of the bioactive composite resin and to analyze the ratio of the irradiation distance of 0 mm, 1 mm, and 5 mm to the value of the degree of conversion of the bioactive composite resin. Methods: This research uses a true experimental method with a post-test only design with a control group design with a simple random sampling technique. Results: The results showed that the highest degree of conversion of bioactive composite resins was at a 0 mm irradiation distance of 38.57%, 1 mm irradiation of 36.02% and the lowest was at a 5 mm irradiation distance of 31.90%. Conclusion: The highest degree of conversion of bioactive composite resin is at a 0 mm irradiation distance. Keywords: Beam distance, Composite resin, Degree of conversion, Light intensityABSTRAKLatar belakang: Proses penyinaran yang kurang tepat menyebabkan polimerisasi tidak sempurna, sehingga kekerasan dari resin komposit, kekuatan bahan, stabilitas warna dari resin komposit yang dihasilkan tidak maksimal serta penyerapan air meningkat. Jarak penyinaran yang jauh akan mengakibatkan intensitas sinar yang didapat semakin kecil karena sinar tidak dapat mencapai resin komposit secara optimal dan derajat kesempurnaan polimerisasi resin komposit akan berkurang. Tujuan: Tujuan penelitian adalah untuk mengetahui perbedaan jarak penyinaran terhadap nilai derajat konversi resin komposit bioaktif serta menganalisis perbandingan jarak penyinaran 0 mm, 1 mm, dan 5 mm terhadap nilai derajat konversi resin komposit bioaktif. Metode: penelitan ini menggunakan metode eksperimental murni (true experimental) dengan rancangan post-test only with control group design dengan teknik pengambilan sampel simple random sampling. Hasil: Hasil penelitian menunjukkan nilai derajat konversi resin komposit bioaktif tertinggi berada pada jarak penyinaran 0 mm sebesar 38.57%, penyinaran 1 mm sebesar 36.02% dan terendah berada pada jarak penyinaran 5 mm sebesar 31.90%. Kesimpulan: Nilai derajat konversi resin komposit bioaktif tertinggi berada pada jarak penyinaran 0 mm. Kata Kunci: Derajat konversi, Intensitas sinar, Jarak sinar, Resin komposit
What is Multimodal?

Our experience of the world is multimodal: we see objects, hear sounds, feel texture, smell odors, and taste flavors. In recent years, a broad and impactful body of research emerged in artificial intelligence under the umbrella of multimodal, characterized by multiple modalities. As we formalize a long-term research vision for multimodal research, it is important to reflect on its foundational principles and core technical challenges. What is multimodal? Answering this question is complicated by the multi-disciplinary nature of the problem, spread across many domains and research fields. This talk is based on a recent review of 700+ research papers, to study computational and theoretical foundations for multimodal research, with a focus on multimodal machine learning. Two key principles have driven many multimodal innovations: heterogeneity and interconnections from multiple modalities. Historical and recent progress will be synthesized in a research-oriented taxonomy, centered around 6 core technical challenges: representation, alignment, reasoning, generation, transference, and quantification. The talk will conclude with open questions and unsolved challenges essential for a long-term research vision in multimodal research.
Fast Violence Recognition in Video Surveillance by Integrating Object Detection and Conv-LSTM

Video surveillance involves petabytes of data storage requiring expensive hardware, which might also be time-inefficient. The aim of this article is, therefore, to develop an intelligent system capable of analyzing long sequences of videos captured from CCTV, helping to mitigate catastrophe and mitigate the violent threats faced by citizens every day, economically and efficiently. Existing models have achieved high accuracy on available datasets, the primary focus is to improve speed (time-efficient) of violence detection and use very little storage (economical) such that the system can be used in real-time. The paper presents an end-to-end hybrid solution for detecting violence in real-time video frames incorporating both human and weapon detection algorithms applied in a synchronized way. The focus of this article is to propose a generic HWVd (Human Weapon Violence detection) model to detect all kinds of public violence. HWVd is a three-tier ensemble model to detect violence in videos. The first tier is human detection, which uses a LightTrack framework. In the second tier, a Fast Region-based Convolutional Neural Network (F-RCNN) to detect any weapon in videos is used. The third tier uses a pre-trained VGG 19 (a pre-trained model of CNN) for spatial feature extraction and Long Short Term Memory (LSTM) to detect violent activity. Lastly, the output of this framework is sent to the Support Vector Machine to classify the activity as (i) violence not involving weapon, (ii) violence involving weapon and (iii) non-violent. The accuracy obtained using the proposed model is 98%.
Panoramic Viewport Prediction Relying on Emotional Attention Map

Panoramic video is considered to be an attractive video format since it provides the viewers with an immersive experience. However, only the viewers’ focused region of a panoramic video, viewport, is shown on the screen. Numerous applications may benefit from the future viewport prediction, such as the adaptive viewport delivery. Two aspects may be considered for predicting the viewports. Firstly, the viewport trajectory within a time interval is highly correlated, hence the historical viewport trajectory should be utilized. Secondly, the panoramic video content within the viewport highly correlates with human visual attention. In this paper, we propose the Emotional Attention map aided panoramic Viewport Estimation (EAVE) model for predicting the future viewport trajectory. In this model, the historical viewport trajectory and the emotional attention map are jointly exploited by a Long Short-Term Memory (LSTM) network. Our experiments show that the proposed method outperforms several baseline methods in terms of prediction accuracy on a panoramic dataset containing viewing trajectory data from 50 viewers for watching 75 panoramic videos.
FL0C: Fast L0 Cut Pursuit for Estimation of Piecewise Constant Functions

Partitioning of images is a fundamental image processing task, which is closely related to various problems and applications in computer vision. Due to the hard nature of the underlying problem, existing algorithms are very compute intense. In this work we present a stochastic algorithm to efficiently approximate solutions of the image partitioning problem. Our contributions lie in the novel convex reformulation of the underlying graph cut problem, along with the application of a stochastic solver. These changes allow a faster convergence compared to other graph cut based methods, which is confirmed by our experiments.
Non-Smooth Energy Dissipating Networks

Over the past decade, deep neural networks have been shown to perform extremely well on a variety of image reconstruction tasks. Such networks do, however, fail to provide guarantees about these predictions, making them difficult to use in safety-critical applications. Recent works addressed this problem by combining model-and learning-based approaches, e.g., by forcing networks to iteratively minimize a model-based cost function via the prediction of suitable descent directions. While previous approaches were limited to continuously differentiable cost functions, this paper discusses a way to remove the restriction of differentiability. We propose to use the Moreau-Yosida regularization of such costs to make the framework of energy dissipating networks applicable. We demonstrate our framework on two exemplary applications, i.e., safeguarding energy dissipating denoising networks to the expected distribution of the noise as well as enforcing binary constraints on bar-code deblurring networks to improve their respective performances.
Discriminate Clearer To Rank Better: Image Cropping By Amplifying View-Wise Differences

Image cropping aims to enhance the aesthetic quality of a given image by searching for the good cropping views. One common routine is to score and rank the candidate views by the neural network. The network is expected to discriminate the subtle view-wise differences. However, the image-wise differences and the ambiguity in the annotations render difficulties in discriminating the view-wise differences. To focus on the view-wise differences, we propose a feature spliter to build image-wise and view-wise feature and evaluate the candidate views only based on the view-wise feature. Then, we propose the ranking gain loss that alleviates the ambiguity in annotations to amplify the view-wise differences. The remarkable improvement compared with prior arts on public benchmarks illustrates that the view-wise differences matter in cropping view recommendation.
The Effectiveness of the Demonstration Method to Improve Student Learning Outcomes

This research is motivated by the fact that most students find it difficult to learn science so they don't like it. From the results of preliminary observations, obtained several things that are not in accordance with the fulfillment of quality learning for grade 6 students at SD Negeri 1 Cikeris Purwakarta Regency, namely: (1) The learning activities carried out have not provided a learning experience for students who require excessive challenges to optimize the development of thinking skills, creativity, problem solving skills, experimentation, innovation, discovery, development of interests, talents and skills. (2) In the delivery of learning, the teacher does not attract the attention of students. Among them are not using learning methods that are less precise and less varied, as well as the lack of utilization of media and learning resources from the environment, resulting in low student learning outcomes.
Analysis of the Current Situation of English Writing Teaching Research in China

By searching and analyzing the research literature on English writing teaching published in major foreign language core journals in China in the past five years (2018-2022), this paper summarizes the research status of English writing teaching in China in recent years. In view of the existing problems, the solutions are put forward, and the future development trend of English writing teaching research is discussed.
Meningkatkan Kemampuan Berhitung Melalui Media Kartu Angka Interaktif Pada Kelompok Usia 5-6 Tahun Taman Kanak – Kanak Taman Hijau, Kota Batam

Children begin to enter the preschool period in the age range of 5-6 years, this age is a period of preparation to enter formal education actually in elementary school. Cognitive development is one aspect of development that must always be given stimulation. The ability to count is part of the aspect of cognitive development. The purpose of this study in general is "Improving the ability to count through the medium of interactive number cards in the age group of 5-6 Taman Kanak – Kanak Taman Hijau, Batam City". To determine the achievement of children in the learning development activities carried out, an assessment is carried out by means of Class Action Research through the medium of interactive number cards. This study uses Class Action Research of Kemmis and Mc Taggrat cycle models with four stages, namely: planning, implementation, observation and reflection. The data of this study comes from the results of action observations and evaluation results. The study was conducted in two cycles. Each cycle is based on the stages of activity planning, execution of actions , observation and post-analysis reflection. Before the step of cycle 1, 4 students were able to do numeracy activities with worksheet media. After cycle 1 there was the addition of 3 more children who showed better counting skills. By the end of the 2nd cycle, 11 children were able to develop very well and 2 children developed as expected. This shows that the use of interactive number card media has a positive impact and can improve students' ability to do numeracy.Meningkatkan kemampuan berhitung
Rebuilding our community networks post-COVID-19

Background. Communities of Practice (CoP) have long been discussed for their abilities to support individuals in decision making, knowledge sharing, and collegiate support[1]. Individuals who are actively involved in CoP can also act as agents for change within an institution[2]. The University of St Andrews Open Access team have developed strong links to School administrators and established ‘deposit hubs’ in Schools whereby researchers can get local support from the ‘hubbers' for creating new research output records in the University’s Current Research Information System (CRIS), as well as support for uploading open access versions and input based on specialist local knowledge such as linking research grants. Aims. To assess the impact of COVID-19 on the CRIS activity of our ‘hubbers’, to determine whether more could be done to improve resilience in the face of time-constraining factors. We also sought to determine what measures might be taken to improve communication channel within the University and how a network might develop and grow. Methods. A quantitative assessment of the impact of COVID on the CRIS activity of hubbers and administrators whom we have developed links with. Through qualitative assessment and dialogue with administrators we wanted to ascertain other issues that result in delays or non-deposit. Results. There was a correlation between the uptick in CRIS record creation and manuscript deposit activity by the Open Access team, and a decrease in activity by ‘hubbers'. Feedback received also suggested there was inertia due to common queries arising, and further inactivity due to inadequacies with communication channels. It was also clear that the uptick in administrative effort from the OA team needed to be addressed. Conclusion. Determining a correlative effect of a discrete set of administrative tasks based on quantitative indicators is prone to error. However, the Open Access team is confident that such Communities of Practice do add value to research culture, both in quantitative measurable results, and in terms of qualitative cultural effects. But more is needed to be done to enhance resilience, transparency, and confidence. It was decided therefore that a frictionless communication channel was required using Microsoft Teams, to bring together ‘hubbers’ and limit wasted effort by sharing best practice, a set of resources, and guides to ensure common standards and consistency, as well as an FAQ section.
Designing Ar-Fhat Bakery Toast Packaging Using The Quality Function Deployment (QFD) Method

The determining factor for the success of a product lies with the consumer, therefore a design that is strictly adapted to the needs and desires of the consumer is needed. In a situation of intense competition, in order to increase sales volumes and market mastery, it is increasingly realized the need for a marketing strategy that is not only based on the needs of consumers, but also competitors who target the same target consumers , by therefore, companies need to anticipate various opportunities and obstacles in the marketing process. Packaging products with an elegant and unique look from competing products will provide their own selling value to the products produced. If done correctly, the company will understand consumer needs and translate them into product designs that are not only effective but also have a good image in the eyes of consumers. From the results of the analysis using the method QFD on Ar-Fath Bakery can it is known the packaging material to be used, the variety of models, the length of the packaging, the width of the packaging and also the height of the packaging where for the main material , namely ivory paper and for printing design drawings using digital printing materials. For the mo del variation used is an attractive and safe packaging design during delivery by adding full attributes to the packaging of Ar Fhat Bakery toast. For the length of the packaging using a size of 20 cm, the width of the packaging is 10 cm and the height of the packaging uses a size of 6 cm.
User requirements and interface design for collaboration research applications using user experience design process

In conducting collaborative research involving more than one researcher, a system is needed that can improve the performance of researchers in various ways. This study captures the challenges faced by researchers in collaborative research and defines the requirements for collaborative research systems needed to address these challenges. From the analysis of the needs obtained, the researchers designed a collaboration application interface. Collaboration applications are needed to facilitate communication between researchers, search for articles, share publications, and other applications. The distribution of questionnaires and interviews were conducted to obtain the requirements needed for the development of a collaboration system. This research informs system developers to support the development of collaborative systems. In this study, the level of need for a research collaboration system in the university environment will be analyzed along with an analysis of its needs and the design of the user interface.