Reviewerly/exHarmony huggingface dataset:
Y-net: Biomedical Image Segmentation and Clustering

We propose a deep clustering architecture alongside image segmentation for medical image analysis. The main idea is based on unsupervised learning to cluster images on severity of the disease in the subject's sample, and this image is then segmented to highlight and outline regions of interest. We start with training an autoencoder on the images for segmentation. The encoder part from the autoencoder branches out to a clustering node and segmentation node. Deep clustering using Kmeans clustering is performed at the clustering branch and a lightweight model is used for segmentation. Each of the branches use extracted features from the autoencoder. We demonstrate our results on ISIC 2018 Skin Lesion Analysis Towards Melanoma Detection and Cityscapes datasets for segmentation and clustering. The proposed architecture beats UNet and DeepLab results on the two datasets, and has less than half the number of parameters. We use the deep clustering branch for clustering images into four clusters. Our approach can be applied to work with high complexity datasets of medical imaging for analyzing survival prediction for severe diseases or customizing treatment based on how far the disease has propagated. Clustering patients can help understand how binning should be done on real valued features to reduce feature sparsity and improve accuracy on classification tasks. The proposed architecture can provide an early diagnosis and reduce human intervention on labeling as it can become quite costly as the datasets grow larger. The main idea is to propose a one shot approach to segmentation with deep clustering.
Artistic and methodical culture of a teacher of artistic disciplines: the essence, the principles of self-development

The author’s interpretation of the concept «artistic and methodical culture of the teacher of artistic disciplines» is presented in the article, its essence, content, structure and criteria of formation is substantiated. The basic principles of self-development are determined. The importance of the artistic and methodological culture of high school teachers in the improvement and modernization of professional artistic education is revealed
Feature Pyramid SSD: Outdoor Object Detection Algorithm for Blind People

To benefit the blind by using advanced deep learning techniques, we establish a new outdoor object detection dataset, BLIND. Different from PASCAL VOC, the scales of objects in our dataset are quite various because of different distances between objects and the camera. The characteristic of the BLIND dataset requires a high ability of scale invariance for the object detector, which classical SSD isn't adequate. We propose a novel object detector named Feature Pyramid SSD (FPSSD) focusing on BLIND, applying feature fusion strategies to classical SSD. FPSSD achieves 75.4% mean Average Precision (mAP) on BLIND, surpassing classical SSD by 1.7%. Extensive experimental results and analyses demonstrate the necessity to establish the BLIND dataset and validate the effectiveness of the proposed FPSSD object detection algorithm for the blind people.
Teachers’ Teaching Reading Strategies at Public Elementary Schools in Haripur District

The growing importance of English as an international language globally demands the students in Pakistan to be proficient in English especially reading skills.Thus, the objective of the study was to identify which reading strategies were taught by the English teachers to elementary pupils.In order to achieve the research objective, quantitative research design was employed in this study.Data were collected through random sampling of 100 teachers from 50 public schools which offer English as a subject using a set of questionnaires.The data were analysed using SPSS.The data are presented in percentages and frequency.The major findings indicate that the majority of the teachers have many problems in teaching English reading strategies to elementary students.It is hoped that the findings could help the education department officers in developing a suitable module to conduct training for elementary English teachers.Such measure is vital in order to improve the teaching capabilities of the English teachers in teaching reading strategies as to enhance the pupils' reading comprehension.
An Attention Model of Customer Expectation to Improve Review Helpfulness Prediction

Many people browse reviews online before making purchasing decisions. It is essential to identify the subset of helpful reviews from the large number of reviews of varying quality. This paper aims to build a model to predict review helpfulness automatically. Our work is inspired by the observation that a customer's expectation of a review can be greatly affected by review sentiment and the degree to which the customer is aware of pertinent product information. Consequently, a customer may pay more attention to that specific content of a review which contributes more to its helpfulness from their perspective. To model such customer expectations and capture important information from a review text, we propose a novel neural network which leverages review sentiment and product information. Specifically, we encode the sentiment of a review through an attention module, to get sentiment-driven information from review text. We also introduce a product attention layer that fuses information from both the target product and related products, in order to capture the product related information from review text. Our experimental results show an AUC improvement of 5.4% and 1.5% over the previous state of the art model on Amazon and Yelp data sets, respectively.
Bibliometrical analysis of requests to RNPLS&amp;T’s e-catalog: What the users search for

The author reviews the results of the extended bibliometrical analysis of the requests to the RNPLS&T's e-catalogs in 2018 and the first half of 2019. This analysis enables to obtain popular requests rating for various sources – the Internet search engines and individual users. The author concludes that the search engines more often search for full texts on the Internet. However, individual users mostly search for bibliographic records of theses abstracts' in RNPLS&T's e-catalog. The printed publications by the authors with the highest rating in the Library's collection would enable potential users to access these publications if the owner removes the digital copy. The publications which texts are available for uploading are recommended to be made accessible free through the National Electronic Library.
The Density-Aware Estimation Network for Vehicle Counting in Traffic Surveillance System

In a surveillance system, the performance of vehicle counting is typically sensitive to the different patterns of traffic density. To address this issue, we proposed the estimation network utilizing intermediate layers for mapping between the appearance of the input image and its density map, where each layer corresponds to different traffic density. The backward connection is introduced by extracting feature maps from a deeper layer to combine with a shallower layer. Taking advantage of the high-level feature from deep layers, more informative features are extracted in the shallow layers, where the performance in an earlier stage can be improved. The experimental results show that the proposed method provides more stable performance in various traffic density than traditional approaches, where the difference between the maximum and the minimum errors in various density is about 5, evaluated by mean absolute error.
Research on Text Representation Method Based on Improved TF-IDF

Abstract According to the different importance degree between feature and text, this paper proposes a method of improved traditional TF-IDF algorithm according to the position information of the words and the ability to distinguish the texts, and proposes a text representation method based on improved TF-IDF and the corresponding word vector calculation method. Finally, the effectiveness of the method is proved by experiments.
Connecting Robust Shuffle Privacy and Pan-Privacy

In the \emph{shuffle model} of differential privacy, data-holding users send randomized messages to a secure shuffler, the shuffler permutes the messages, and the resulting collection of messages must be differentially private with regard to user data. In the \emph{pan-private} model, an algorithm processes a stream of data while maintaining an internal state that is differentially private with regard to the stream data. We give evidence connecting these two apparently different models. Our results focus on \emph{robustly} shuffle private protocols, whose privacy guarantees are not greatly affected by malicious users. First, we give robustly shuffle private protocols and upper bounds for counting distinct elements and uniformity testing. Second, we use pan-private lower bounds to prove robustly shuffle private lower bounds for both problems. Focusing on the dependence on the domain size $k$, we find that robust approximate shuffle privacy and approximate pan-privacy have additive error $\Theta(\sqrt{k})$ for counting distinct elements. For uniformity testing, we give a robust approximate shuffle private protocol with sample complexity $\tilde O(k^{2/3})$ and show that an $\Omega(k^{2/3})$ dependence is necessary for any robust pure shuffle private tester. Finally, we show that this connection is useful in both directions: we give a pan-private adaptation of recent work on shuffle private histograms and use it to recover further separations between pan-privacy and interactive local privacy.
Development of Low-Cost Vision-based Eye Tracking Algorithm for Information Augmented Interactive System

Deep Learning has become the most important technology in the field of artificial intelligence machine learning, with its high performance overwhelming existing methods in various applications.In this paper, an interactive window service based on object recognition technology is proposed.The main goal is to implement an object recognition technology using this deep learning technology to remove the existing eye tracking technology, which requires users to wear eye tracking devices themselves, and to implement an eye tracking technology that uses only usual cameras to track users' eye.We design an interactive system based on efficient eye detection and pupil tracking method that can verify the user's eye movement.To estimate the view-direction of user's eye, we initialize to make the reference (origin) coordinate.Then the view direction is estimated from the extracted eye pupils from the origin coordinate.Also, we propose a blink detection technique based on the eye apply ratio (EAR).With the extracted view direction and eye action, we provide some augmented information of interest without the existing complex and expensive eye-tracking systems with various service topics and situations.For verification, the user guiding service is implemented as a proto-type model with the school map to inform the location information of the desired location or building.
Market Quality Approach to IoT Data on Blockchain Big Data

The Internet of things (IoT) Internet of Things (IoT) is considered a key driving force of what the JapaneseJapan government refers to as Society 5.0Society5.0, the image of an ideal future society that the JapaneseJapan government currently advocates. Society 5.0Society5.0 is defined as “a human-centered society that balances economic advancement with the resolution of social problems by a system that integrates cyberspace and physical spacePhysical space.” According to the government, “In Society 5.0Society5.0, a huge amount of information from sensorsSensors in physical spacePhysical space is accumulated in cyberspace.
The concept of responsibility as the modern outlook of the designer

The article analyzes the modern concept of responsible design, its components and main provisions. The main components of responsible design are the systems of universal and unpleasant design, the history of the origin and development of these components, as well as their modern extended understanding. The basic principles and areas of application of universal and unpleasant design are given. Features of formation of responsible approach to design as a basis of world view of future designers as exemplified by training students specializing in "Design" and "Technology for the decorative processing of materials", both at the level of bachelors and at the level of masters are shown. A set of knowledge, skills abilities necessary for the designer to understand the concept of responsible design ensure such a design process is determined. The arising problems are considered, and the approaches to their solution on the basis of modern competence approach are offered. The authors formulated tasks and exercises that help the teacher to form the responsibility of the designer, as well as test questions and topics of tasks, up to the final state certification, allowing to check and consolidate the understanding and application of the concept of responsible design. Examples of developments made by students using the concept of responsible design are given.
Kemampuan Menganalisis Kesalahan Berbahasa Mahasiswa Program Studi Pendidikan Bahasa dan Sastra Indonesia Universitas Islam Riau

Learning outcomes of language error analysis courses are students mastering linguistic theories, types of language analysis, and language error analysis techniques and are able to apply theories of language error analysis at each level of linguistics. But unfortunately, the learning achievement is difficult to achieve because based on the phenomenon that the writer found as lecturer in the course of language error analysis, many students could not reach the determined target and did not have the criteria set by the lecturer or university lecturer. Based on this problem, the formulation of the problem of this research is how to analyze the errors of grammar study program of Indonesian Language and Literature in Riau Islamic University. The study used a descriptive method with a research population of all sixth semester students of the Indonesian Language and Literature Education Study Program at the Riau Islamic University and used random sampling as a research sample. Research Results The ability to analyze language errors in the level of phonology of Indonesian Language and Literature Education Study Program at Islamic University with an average score of 47.32 with a very poor category. Meanwhile, the ability to analyze language errors at the level of morphology of Indonesian Language and Literature Education Study Program Students at Islamic University with an average score of 33.13 with the category of failure.&#x0D;
Design of Autonomous Obstacle Avoidance Unmanned Boat System for Wetland Monitoring

Abstract In view of the drastic reduction of wetland area, serious pollution, low efficiency of prior art and many factors, this paper proposes an autonomous obstacle avoidance unmanned boat system design for wetland monitoring. The system adopts D* algorithm and improved LOS guidance law to realize unmanned ship track control and global path planning, and combines Yolov3 algorithm for target recognition and partial data acquisition during navigation to achieve autonomous obstacle avoidance navigation. The sensor is used to collect the wetland environment information and upload it to the shore monitoring centre to complete the automatic data collection and monitoring of the wetland. The system can improve the efficiency and quality of wetland monitoring, reduce labor costs, and can be widely used in wetland monitoring automation, marine environment monitoring, and cloud service platforms.
Local-Global Video-Text Interactions for Temporal Grounding

This paper addresses the problem of text-to-video temporal grounding, which aims to identify the time interval in a video semantically relevant to a text query. We tackle this problem using a novel regression-based model that learns to extract a collection of mid-level features for semantic phrases in a text query, which corresponds to important semantic entities described in the query (e.g., actors, objects, and actions), and reflect bi-modal interactions between the linguistic features of the query and the visual features of the video in multiple levels. The proposed method effectively predicts the target time interval by exploiting contextual information from local to global during bi-modal interactions. Through in-depth ablation studies, we find out that incorporating both local and global context in video and text interactions is crucial to the accurate grounding. Our experiment shows that the proposed method outperforms the state of the arts on Charades-STA and ActivityNet Captions datasets by large margins, 7.44\% and 4.61\% points at Recall@tIoU=0.5 metric, respectively. Code is available in https://github.com/JonghwanMun/LGI4temporalgrounding.
Flood Vulnerability Mapping Using Geographic Information System (GIS) in Gajah Wong Sub Watershed, Yogyakarta County Province

Gajah Wong Sub Watersheds frequently hit by floods which are potentially damaging. Therefore, a study on a flood vulnerability of the area is deemed necessary. This study aims to map floods vulnerability, to know the level and its spread in Gajah Wong Sub Watershed of Yogyakarta County Province by using Geographic Information System (GIS). The methods implemented in this study was weighing and scoring analysis and overlay of parameter attributes data of flood vulnerability framer, consisting of land use, slope of mountain, rainfall, soil type, geology, height of location and river buffer. Each parameter of flood vulnerability framer is classified based on the magnitude of effect towards flood vulnerability. The results of this study indicate that there were three levels of flood vulnerability in Gajah Wong Sub Watershed, i.e. low flood vulnerability of 338.34 Ha (6.86%), medium flood vulnerability level of 4,595.62 Ha (93.13%) and high flood vulnerability level of 0.76 Ha (0.02%). Low flood vulnerability level is ditributed randomly to all areas of Gajah Wong Sub Watershed cover of Ngaglik Sub-district, Depok Sub-district, small part of Pleret Sub-district and was predominantly in Banguntapan Sub-district, an area with rainfall. Medium flood vulnerability areas dominated Gajah Wong Watershed. Meanwhile, high flood vulnerability level occupied small portion of the area and spread in the southern part of Pleret Sub-district which was taken as the area of River Buffer analysis.&#x0D; Keywords: GIS; Gajah Wong; Sub Watershed; Yogyakarta.&#x0D; &#x0D; Copyright (c) 2020 Geosfera Indonesia Journal and Department of Geography Education, University of Jember&#x0D; This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License
Experimental quantum probing measurements with no knowledge of the system-probe interaction

In any natural science, measurements are the essential link between theory and observable reality. Is it possible to obtain accurate and relevant information via measurement whose action on the probed system is unknown? In other words, can one be convinced to know something about the nature without knowing in detail how the information was obtained? In this paper, we show that the answer is surprisingly, yes. We construct and experimentally implement a quantum optical probing measurement where measurements on the probes, the photons' polarization states, are used to extract information on the systems, the frequency spectra of the same photons. Unlike the pre-existing probing protocols, our measurement does not require any knowledge of the interaction between the probe and the system.
AR and VR Based Child Education in Context of Bangladesh

Now day's children are more likely to use smartphones.They would like to use smartphones more than a textbook.They use smartphones for playing various games and watch the cartoon as well as funny videos and movies also.The addiction to using smartphones through children is increasing day by day.Maximum parents now want to teach their children via smartphones.In that case, they try to find various learning apps and games.From that sense, we decide to make a child learning apps by using Augmented Reality & Virtual Reality.AR & VR is the most powerful way of interaction nowadays.On AR apps we design an alphabets book for the children according to our survey report and we make an android app using unity 3D.When a child opens the apps, then the phone camera will open.And if the child holds the camera in any picture of the book, then the smartphone will tell the name of the alphabet and also tell a word with that particular word and will show a 3D visual model of the object on the mobile display.And on the VR apps, we design some 3d environments according to our survey.Inside the environment, there will some alphabets in some fixed placed according to sequence and the child has to collect them by walking inside the environment.When he/she pick any alphabet than the apps will tell the name of the alphabet.
Low Quantum Cost Realization of Reversible Binary-Coded-Decimal Adder

The ability of reversible design to reduce power consumption in designing digital circuits compared to the traditional logic design has been gaining much attention in recent decades. Also, because of the attention gained by the decimal arithmetic in the application of commercial, internet-based systems, etc, an approach to design the reversible binary-coded-decimal adder is proposed and carried out in this paper. Proper selection and arrangements of the gates with parallel implementation have been able the proposed design to show improvements in the reversible performance parameters. The proposed design shows the most efficient design with at least 10% improvements of quantum cost compared with existing counterparts found in the literature. Furthermore, the proposed design is mapped into the quantum equivalent circuit using RCViewer+ tool.
Local low-rank matrix recovery for hyperspectral image denoising with ℓ0 gradient constraint

Hyperspectral image (HSI) acquisition often suffers from the mixed noise, which greatly limits its subsequent applications. This paper proposes a novel HSI denoising method by using local low-rank matrix recovery and ℓ0 gradient, which can simultaneously identify the low-rank structures of the clean HSI and the sparse components of the mixed noise. Specifically, the HSI is modeled locally and a scheme of rank-fixed low-rank matrix recovery is employed to separate the latent clean HSI patches from the noisy counterpart. Meanwhile, the ℓ0 gradient constraint mechanism is utilized to characterize the piecewise smooth structure along both the spectral and spatial dimensions of the reconstructed image from the patches. Moreover, the ℓ1 norm regularization is adopted to suppress the sparse noise, such as stripes, deadlines, impulse noise, and so on. Also, an efficient iterative schema is developed based on an augmented Lagrange algorithm. The corresponding closed-form solutions of the subproblems are derived for calculating an approximate result of the nonconvex optimization problem. Extensive experiments on both simulated and real HSIs prove that the ℓ0 gradient constraint can preserve the edge details well and the proposed method can yield better performance than the state-of-the-art methods for HSI denoising.