Reviewerly/exHarmony huggingface dataset:
Airplane Object Detection in Satellite Images Based on Attention Mechanism and Multi-scale Feature Fusion

The order of magnitude of object detection instances in satellite images is larger than that in conventional images, and many small object instances are clustered together in satellite images. Most objects in conventional object detection datasets are perpendicular to the ground, while objects in satellite images are parallel to the ground and their orientation varies greatly. Conventional detection with horizontal bounding box, a horizontal bounding box may contain multiple dense instances and may contain a lot of background information, resulting in a disproportionate proportion of the background in the detection box. The oriented bounding box helps to locate the object more accurately and obtain the azimuth information of the object more easily. Therefore, in this work, we used oriented bounding boxes to detect airplane objects in satellite images. In order to target the detection of airplane objects, we produced a high-resolution dataset containing only airplane objects and more small instances. We use ResNet as backbone and FPN as Neck. By adding an SE Block module after each stage of ResNet to pay attention to important features, and connecting a pyramid convolution (PConv) module after FPN to enhance feature fusion. Cropping the input image to 1024*1024 using a sliding window allowed detection accuracy improved on DOTA v1.0(90.53 mAP) and our own dataset Satellite-Airplane2309(83.48 mAP) on the GTX TITAN X.
A Play of Letters, Words, and Images: On One Line by Mayakovsky and Its Visualization (The Experience of Decoding the Cover of Rodchenko’s NO.S)

The problem of the book cover has gained little attention from researchers (philologists, art historians, literary historians, designers). However, what is in plain sight in a book may paradoxically remain invisible, both to contemporaries and to posterity. In other words, the reader/viewer/researcher may not even realize that he is dealing with a kind of “cipher,” “code,” “secret,” “rebus,” “secret writing.” The article demonstrates the cryptographic nature of one of these covers, created by Alexander Rodchenko for Vladimir Mayakovsky’s collection of poems NO. S (Moscow, 1928). Any reader should be immediately intrigued by the very obvious “weirdness” of both the cover and the title of this book. On the title page this weirdness is partially cleared up, for here the title is subtitled: NO. S: New Poems. However, such an author’s “transcription” is deliberately deceitful and provocative, due to a deliberately illiterate abbreviation of the adjective. It is noteworthy that this book opens with a poem with the program title Incomprehensible for the Masses. We can, with equal reason, assume that the occasion for the cover could equally serve as a verbal pun, as well as a visual one. That is, the question could be posed as follows: what exactly determined the letter composition of the cover? It could be some kind of visual artifact that became the source for mastering in Rodchenko’s work, in which case the graphics of the cover itself are not random, but strictly constructed and possess an implicit program. Or, on the contrary, Rodchenko’s recognizable constructivist style bears in this case only a secondary and incidental plastic decorative function, and all the unobvious meaning for the public is concentrated only in the title, reduced to three mysterious letters. The deciphering of the cover of this book is undertaken for the first time, 94 years after its publication.
Short Paper: An Initial Investigation of the Correlations Between the Quality of Engineering Assignments and Task-Independent Features

Abstract The potential development of automated grading brings us the opportunity to change the way of teaching. In this paper, we present our pilot study of the correlations between the scores of engineering assignments and several task-independent features. This work aims to identify features that can subsequently be used in a machine learning framework to support automated grading. We also identified some interesting patterns in this dataset. Our result shows that length features such as word count may indicate a highly structured assignment’s quality, and the number of grammar errors has the potential to be part of the evaluation if we use a carefully designed grammar checker. The present study is expected to contribute to our understanding of automated grading of mechanical engineering technical reports and provide insights into rubric design for assignments.
An optimized Bitsliced Masked Adder for ARM Thumb-2 Controllers

The modular addition is used as a non-linear operation in ARX ciphers because it achieves the requirement of introducing non-linearity in a cryptographic primitive while only taking one clock cycle to execute on most modern architectures. This makes ARX ciphers especially fast in software implementations, but comes at the cost of making it harder to protect against side-channel information leakages using Boolean masking: the best known 2-shares masked adder for ARM Thumb micro-controllers takes 83 instructions to add two 32-bit numbers together. Our approach is to operate in bitsliced mode, performing 32 additions in parallel on a 32-bit microcontroller. We show that, even after taking into account the cost of bitslicing before and after the encryption, it is possible to achieve a higher throughput on the tested ciphers (CRAX and ChaCha20) when operating in bitsliced mode. Furthermore, we prove that no first-order information leakage is happening in either simulated power traces and power traces acquired from real hardware, after sufficient countermeasures are put into place to guard against pipeline leakages.
Automated Image Captioning Using Machine Learning

The study of machine learning algorithms and processes is suited for each image and language process. The use of existing packages in implementing machine learning algorithms. Implementation of an Associate in Nursing algorithmic programme takes a photograph and explains it in full phrases. A list of domain experience and prospective models was developed after the demand analysis. Following that, a study of the available technologies that may aid with the creation of the appliance was conducted, and the look, the solution’s implementation and validation began. A deep convolutional neural network is used to extract features, and transfer learning is combined with a repeating neural network for description generation in this study. The implementation is done with Keras with a TensorFlow backend. It was possible to obtain photo exploitation language is described by a trained model.
Analysis on Characteristics and Innovation of Physical Education Teaching Reform in Higher Vocational Colleges

With the promotion and development of quality education, the new curriculum reform has carried out new interpretation and Reform on the content and concept of education.Higher vocational schools are different from other ordinary schools.The teaching goal of higher vocational schools is to train practical talents.In the process of teaching, we should be student-oriented and focus on students' actual employment and skills practice as the main objective, so as to lay a foundation for students to better adapt to society in the future and cultivate more professional and technical talents for the society.Under such a background, higher vocational schools pay more and more attention to physical education teaching, which is not only conducive to the development of physical education teaching quality in China, but also provides more sports skilled talents for the society.Therefore, in the teaching process of higher vocational schools, consciously reforming and innovating physical education teaching is not only the actual requirement for improving students' physical quality, but also the necessary condition and important foundation for students to complete their studies and participate in work in the future.
LF electronic Architecture—Saving cost and adding acoustic flexibility in the construction of multi-purpose performing arts facilities

Over the course of many years, we have successfully integrated LF components into full range electronic architecture installations. These components are typically utilized when programming includes acoustic instruments such as pipe organ, or a large orchestra (or both)—or when electronic sources producing LF energy (such as effects mapping or film screening) need to be considered. However, we have also installed LF only EA systems in several concert halls in order to optimize LF performance without the high cost associated with brick and mortar construction methods. Electronic Architecture provides the added benefit of variability necessary for multi-purpose performing arts venues.
Estimating the Physical Parameters of Human Arm Motion from Video using Fixed-Point PCA Transform and Nonlinear Least-Squares Method

In this paper, we propose a simulation of human arm movement relying on parameters extracted from video. Fixed-Point based PCA is introduced in order to perform hand tracking in video. An arm model based on nonlinear least squares which contains physical parameters, i.e. shoulder and elbow joint angles, is minimized by Gauss-Newton algorithm. The estimated parameters can generate an efficient neural-numerical simulator for human arm motion.
The Implementation and Impact of Gamification on User Engagement and Acceptance of Mobile Personal Health Record Application

Health issues is still a serious problem in the world, including in Indonesia. One of the leading causes of death in Indonesia are related to health problems. To reduce the risk of health issue is to adopt a healthy lifestyle; however, the currently Indonesian people have a low health awareness. This study aims to develop a mobile personal health record (mPHR) application by applying gamification concept. The requirements for mPHR are taken from the Ministry of Health's Healthy Community Movement program. The application was tested on 64 respondents over three days: 32 of the respondents used gamification applications and 32 used non-gamification applications. After three days, the user was given a questionnaire regarding user engagement and acceptance. The mPHR application implements 10 use cases that can monitor users' healthy lifestyles and implement gamification elements, such as points, progress bars, feedback, leader boards, and badges. The analysis of the questionnaire showed that respondents who participated in this study had engaged with and accepted the mPHR application. This study can be used as a guide for governments and mobile health application developers in developing adequate mPHR to promote healthy living.
Overcoming Covid19 Effect to Implement NAAC: Mind Mapping

Abstract :The sudden impact of Covid19 in India coincided with the NAAC assessment submission decision at Sreyas Institute of Engineering &amp; Technology at Hyderabad, India. Institute decided to document the upgraded National Assessment and Accreditation Council (NAAC) version and submit it to the NAAC board during February 2020; Covid19 started spreading in India. By March first week, a total lockdown started, and all educational institutions were closed. Along with quickly adapting to online classes, online examinations for the benefit of student's the staff also adopted the online media to complete the NAAC documentation as per the new standards laid by NAAC. To motivate the staff, who were technically knowledgeable, a lateral thinking approach was adopted. The criteria aspects were mapped to the socio, spiritual, scientific, and management aspects to bring the group together to focus on achieving their common goal for the institute of achieving the assessment and approval of the upgraded NAAC procedures and standards. Within the Covid locked down period of about five months, the required five years of data of all aspects of all criteria were collected with co-operation among the staff, and the submission was completed in September of 2020. This report is to focus on the mind mapping used initially to bring the faculty team together forpreparing the NAAC Document. All seven criteria of the NAAC system were mapped to socio, scientific and spiritual practices through which all humans were brought up. The relationship is communicated via zoom meetings to all staff and the criteria in charge. Commitment improved as they related the known imbibed knowledge they possessed. Keywords: Covid19; Mind Mapping; NAAC; Baghavad Gita; Engineering Institute; Pedagogy
ResNet50+Transformer: kazakh offline handwritten text recognition

Nowadays, due to the transition to digital data storage, there is a need to implement handwritten text recognition (HTR), which is an automatic translation of handwritten characters into a machine format. Handwriting recognition is complicated by the fact that there are many languages and it is possible to write the same character in different ways. In this regard, we conducted a study of a machine learning model for recognizing handwritten characters using databases of the Kazakh language. We trained the ResNet50 + Transformer deep learning model using two published databases of the Kazakh language: KOHTD and HKR. In the course of the study, these databases were studied on the component and qualitative sides with a comparison of the results of validation of the trained model. As a result, the KOHTD database showed results in the form of CER-9.46% and WER-20.18%, while the HKR database showed results in the form of CER-6.08% and WER-15.51%.
STUDENT PORTFOLIO AS A TOOL FOR POSITIONING EXPERTISE

The article discusses the main approaches to the definition of expertise and the formation of a student portfolio as a tool for its positioning. An author’s approach to creating a portfolio is proposed based on the analysis of domestic and foreign practices and taking into account the experience of implementing this approach in educational activities and project work.
Scholarship Monitoring Information System at Ar-Raniry Islamic University

The aim of this research is; 1) Able to design an information system for monitoring bidikmisi scholarships at Ar-Raniry State Islamic University Banda Aceh, and 2) Knowing the quality of the information system monitoring bidikmisi scholarships at Ar-Raniry State Islamic University Banda Aceh in providing information about bidikmisi scholarships based on ISO 9126 on functionality aspects, usability, efficiency, reliability, maintainability and portability. The design of an information system for processing scholarship monitoring data at the Ar-Raniry State Islamic University based on a website that the author designed consists of several stages, namely input design, output design, process design, control design, labor design, and cost design, while the application development uses a model prototyping. Based on the results of research and testing of the student monitoring information system at UIN Ar-Raniry Banda Aceh that has been carried out by the author, several conclusions can be drawn, namely; 1) This study succeeded in creating a student monitoring information system at UIN Ar-Raniry Banda Aceh, and 2) This research succeeded in collecting and reporting data on scholarships and orphaned students.
SPGNet: Spatial Projection Guided 3D Human Pose Estimation in Low Dimensional Space

We propose a method SPGNet for 3D human pose estimation that mixes multi-dimensional re-projection into supervised learning. In this method, the 2D-to-3D-lifting network predicts the global position and coordinates of the 3D human pose. Then, we re-project the estimated 3D pose back to the 2D key points along with spatial adjustments. The loss functions compare the estimated 3D pose with the 3D pose ground truth, and re-projected 2D pose with the input 2D pose. In addition, we propose a kinematic constraint to restrict the predicted target with constant human bone length. Based on the estimation results for the dataset Human3.6M, our approach outperforms many state-of-the-art methods both qualitatively and quantitatively.
Semantic Information Discovery and Complex-Valued Deep Architectures for SAR Data Processing

In the first year of my PhD project, as the fifteenth Early Stage Researcher (ESR) of the MENELAOS-NT project, I have focused on two objectives of my thesis. In the first objective, I have exploited semantic data mining techniques for latent information discovery from various Earth Observation images. In the second goal and as the continuity of the first aspect, I have studied complex-valued deep architectures for Synthetic Aperture Radar (SAR) data processing in order to utilize both the amplitude and phase information in SAR images.
Performance Analysis and Implementation of Pre-trained Model Using Transfer Learning on Bangla Document Clustering

Natural Language Processing has ushered in a revolutionary improvement in making intelligent systems for various purposes using machine learning techniques to process human language. NLP tasks like machine translation, summarization, sentiment analysis, etc. have helped make these applications possible. The techniques and algorithms behind these tasks are changing fast with each improvement. Furthermore, scholars from all over the world use cutting-edge methodologies and approaches in a variety of languages. In this research, we explore the state-of-the-art NLP framework BERT that has been pre-trained in several languages including Bangla. We demonstrate the importance of contextual language representation in Bangla, analyze performance and implement the state-of-the-art BERT pre-trained language model on the Bangla Document Clustering task accompanied by a web app to demonstrate the aforementioned implementation.
A Study on the C-E Translation of Hydropower Engineering Texts Under the Guidance of Systemic Functional Linguistics

With the development of basic social undertakings, the exchange and cooperation between China and other countries in water conservancy and hydropower engineering technologies are getting closer and closer.Not only that, hydropower engineering text involves multiple contents related to various fields, such as building, geology, ecology, etc., featuring professionalism, practicality, and communicative nature, so more attention should be given to the translation of hydropower engineering texts.Therefore, under the theoretical framework of systemic functional linguistics proposed by Halliday(1976), this paper first analyzes the characteristics of general hydropower engineering texts from the perspective of the register and then aims to seek the equivalences of three metafunctions, including ideational, interpersonal, and textual metafunctions between the source text(ST) and the target text(TT), thus exploring some applicable translation methods for C-E translation of hydropower engineering texts.Hopefully, this study can provide some inspiration for translators engaged in hydropower engineering text translations.
The Approach to Building a Context-Dependent Sentiment Dictionary

The rapid development of the Internet has led to a fast increase in the number of news sites and social networks that describe various events in the world and society. Today, authorities consider social networks as a channel of communication with civil society, which allows you to quickly report on the work done and form an actual agenda. Social networks provide an opportunity to regulate the involvement of citizens in the conduct of public affairs, discussion of legal norms, bills, public services, and the activities of public authorities. News posts and comments of a different nature of statements are divided into categories of positive, negative, and neutral assessment. Thus, the problem arises of accurately determining whether these categories of sentiment belong to these categories. Currently, various approaches are implemented to automatically determine the sentiment of texts and sentences: the use of sentiment dictionaries and machine learning algorithms. This article discusses the construction of a more sophisticated sentiment dictionary based on textual data labelled by experts on the content category and sentiment.
Development of E-book “FLASHBACK SEJARAH SASTRA” as a Supporting Source of Literaturgeschichte Course of German Literature Universitas Negeri Malang

This research and development aim to test the validity of the feasibility of the e-book "Flashback Sejarah Sastra" so that it can be used as a source of supporting learning in the Literaturgeschichte course. The research and development model used is the ADDIE development model. The ADDIE development model is divided into five stages, namely: 1) analyze, 2) design, 3) develop, 4) implement, and 5) evaluate. The results obtained from this research and development are that students who have taken the Literaturgeschichte course find the e-book “Flashback Sejarah Sastra" interesting and can support learning.
The Parallel Reversible Pebbling Game: Analyzing the Post-quantum Security of iMHFs

The classical (parallel) black pebbling game is a useful abstraction which allows us to analyze the resources (space, space-time, cumulative space) necessary to evaluate a function f with a static data-dependency graph G. Of particular interest in the field of cryptography are data-independent memory-hard functions $$f_{G,H}$$ which are defined by a directed acyclic graph (DAG) G and a cryptographic hash function H. The pebbling complexity of the graph G characterizes the amortized cost of evaluating $$f_{G,H}$$ multiple times as well as the total cost to run a brute-force preimage attack over a fixed domain $$\mathcal {X}$$ , i.e., given $$y \in \{0,1\}^*$$ find $$x \in \mathcal {X}$$ such that $$f_{G,H}(x)=y$$ . While a classical attacker will need to evaluate the function $$f_{G,H}$$ at least $$m=|\mathcal {X}|$$ times a quantum attacker running Grover’s algorithm only requires $$\mathcal {O}\left( \sqrt{m}\right) $$ blackbox calls to a quantum circuit $$C_{G,H}$$ evaluating the function $$f_{G,H}$$ . Thus, to analyze the cost of a quantum attack it is crucial to understand the space-time cost (equivalently width times depth) of the quantum circuit $$C_{G,H}$$ . We first observe that a legal black pebbling strategy for the graph G does not necessarily imply the existence of a quantum circuit with comparable complexity—in contrast to the classical setting where any efficient pebbling strategy for G corresponds to an algorithm with comparable complexity for evaluating $$f_{G,H}$$ . Motivated by this observation we introduce a new parallel reversible pebbling game which captures additional restrictions imposed by the No-Deletion Theorem in Quantum Computing. We apply our new reversible pebbling game to analyze the reversible space-time complexity of several important graphs: Line Graphs, Argon2i-A, Argon2i-B, and DRSample. Specifically, (1) we show that a line graph of size N has reversible space-time complexity at most $$\mathcal {O}\left( N^{1+\frac{2}{\sqrt{\log N}}}\right) $$ . (2) We show that any (e, d)-reducible DAG has reversible space-time complexity at most $$\mathcal {O}\left( Ne+dN2^d\right) $$ . In particular, this implies that the reversible space-time complexity of Argon2i-A and Argon2i-B are at most $$\mathcal {O}\left( N^2 \log \log N/\sqrt{\log N}\right) $$ and $$\mathcal {O}\left( N^2/\root 3 \of {\log N}\right) $$ , respectively. (3) We show that the reversible space-time complexity of DRSample is at most $$\mathcal {O}\left( N^2 \log \log N/\log N\right) $$ . We also study the cumulative pebbling cost of reversible pebblings extending a (non-reversible) pebbling attack of Alwen and Blocki on depth-reducible graphs.
An Integrated Fuzzy Logic and K-Means Clustering Adaptive Learning System

E-learning is gaining fame in assisting both instructors and students while reducing spatial or temporal boundaries. Despite these clear benefits, such platforms need to be measured apropos the degree of students’ commitment, the delivery of course materials, and teaching approach. This information is of paramount importance for evaluating teaching quality and adjusting the teaching […]