Reviewerly/exHarmony huggingface dataset:
Target Chase, Wall Building, and Fire Fighting: Autonomous UAVs of Team NimbRo at MBZIRC 2020

The Mohamed Bin Zayed International Robotics Challenge (MBZIRC) 2020 posed diverse challenges for unmanned aerial vehicles (UAVs). We present our four tailored UAVs, specifically developed for individual aerial-robot tasks of MBZIRC, including custom hardwareand software components. In Challenge 1, a target UAV is pursued using a high-efficiency, onboard object detection pipeline to capture a ball from the target UAV. A second UAV uses a similar detection method to find and pop balloons scattered throughout the arena. For Challenge 2, we demonstrate a larger UAV capable of autonomous aerial manipulation: Bricks are found and tracked from camera images. Subsequently, they are approached, picked, transported, and placed on a wall. Finally, in Challenge 3, our UAV autonomously finds fires using LiDAR and thermal cameras. It extinguishes the fires with an onboard fire extinguisher. While every robot features task-specific subsystems, all UAVs rely on a standard software stack developed for this particular and future competitions. We present our mostly open-source software solutions, including tools for system configuration, monitoring, robust wireless communication, highlevel control, and agile trajectory generation. For solving the MBZIRC 2020 tasks, we advanced the state of the art in multiple research areas like machine vision and trajectory generation. We present our scientific contributions that constitute the foundation for our algorithms and systems and analyze the results from the MBZIRC competition 2020 in Abu Dhabi, where our systems reached second place in the Grand Challenge. Furthermore, we discuss lessons learned from our participation in this complex robotic challenge.
GPN: A Joint Structural Learning Framework for Graph Neural Networks

Graph neural networks (GNNs) have been applied into a variety of graph tasks. Most existing work of GNNs is based on the assumption that the given graph data is optimal, while it is inevitable that there exists missing or incomplete edges in the graph data for training, leading to degraded performance. In this paper, we propose Generative Predictive Network (GPN), a GNN-based joint learning framework that simultaneously learns the graph structure and the downstream task. Specifically, we develop a bilevel optimization framework for this joint learning task, in which the upper optimization (generator) and the lower optimization (predictor) are both instantiated with GNNs. To the best of our knowledge, our method is the first GNN-based bilevel optimization framework for resolving this task. Through extensive experiments, our method outperforms a wide range of baselines using benchmark datasets.
Tinjauan Kebutuhan Rak Penyimpanan Rekam Medis di RSUD Bangka Selatan

Medical record is a collection of facts or evidence of the patient's condition, past and current medical history and treatment written by the health professional who provides services to the patient. Medical records require sufficient storage shelves and storage space is needed to maintain confidentiality, avoid damage and make it easier for officers to retrieve and return medical records in the long term. If the medical record storage is adequate and meets the standards to support maximum patient care, it is necessary to adjust the need for medical record storage racks at the South Bangka Hospital. The purpose of this study was to determine the need for medical record storage racks for the next 5 years at RSUD South Bangka. This type of research uses a descriptive method with a quantitative approach. Data collection techniques used are observation and interviews. The results of this study are the number of medical record storage racks in the South Bangka Hospital currently amounts to 17 shelves and the South Bangka Hospital currently has a medical record storage area of 25m². It is recommended that the South Bangka Hospital need to provide 49 storage shelves for the next 5 (five) years so that the shelf needs can be met and can accommodate all medical records and it is hoped that the hospital will add an area of medical record room with an additional area of 11.96m² to adjust the addition of medical record racks.
CORWA: A Citation-Oriented Related Work Annotation Dataset

Academic research is an exploratory activity to discover new solutions to problems.By this nature, academic research works perform literature reviews to distinguish their novelties from prior work.In natural language processing, this literature review is usually conducted under the "Related Work" section.The task of related work generation aims to automatically generate the related work section given the rest of the research paper and a list of papers to cite.Prior work on this task has focused on the sentence as the basic unit of generation, neglecting the fact that related work sections consist of variable length text fragments derived from different information sources.As a first step toward a linguistically-motivated related work generation framework, we present a Citation Oriented Related Work Annotation (CORWA) dataset that labels different types of citation text fragments from different information sources.We train a strong baseline model that automatically tags the CORWA labels on massive unlabeled related work section texts.We further suggest a novel framework for human-in-the-loop, iterative, abstractive related work generation.
Application and research of computer modeling technology in smart window home product design

A design scheme of smart window based on STM32 is proposed. This paper puts forward the following innovations for the smart window: automatically close the window when it rains, automatically close the window when strong wind comes, automatically open the window when combustible gas exceeds the standard, automatically lock the window when children approach, automatically open the window when indoor harmful gas exceeds the threshold, automatically clean the window when it rains, remote video monitoring and infrared remote control. The design optimizes the size of the window through the research of ergonomics. Let intelligence enter the family and bring convenience to people. While integrating intelligence, redesign the appearance and size of the product. In this study, computer software assistance, ergonomics and other methods are used.And through the research of ergonomics, the size of the window is optimized. Let intelligence enter the family and bring convenience to people. While integrating intelligence, redesign the appearance and size of the product. In this study, computer software assistance, ergonomics and other methods are used.
Evolution of the Internet from Web 1.0 to Metaverse: The Good, The Bad and The Ugly

&lt;div&gt;The World Wide Web as the largest global information media through which user can share, read, and writes data through computers connected with internet. In last few years, internet has had much progress from web1.0 to web 3.0. The first iteration of the web or web 1.0, also known as the Classic Web, arrived in 1991. Web1.0 was all about connecting and getting information on the net. Then came web 2.0, enabling users to read as well as create and deliver content. Due to the read and write functionalities of web 2.0, there was an immense growth in the on the internet, specially in social media alongside Ecommerce. Web3.0 is generally regarded as the emergence of the semantic web, where computer will generating and thinking new information rather than humans. Using artificial intelligence and machine learning technologies, users will be able to interact with data. The Metaverse is the future iteration of the internet. It will combines multiple different virtual spaces that provides access to a diverse variety of entertainment and projects utilizing the full range of augmented reality.&lt;/div&gt;
Pragmatic Analysis of Speech Acts in Short Dialogue of Listening Comprehension Test

Listening comprehension is regarded as one of the most challenging tasks for students and the majority of students struggle to grasp the proposed meaning in TOEFL short dialogue of listening comprehension test items. The utterances in TOEFL short dialogue test can be analyzed using pragmatic through speech act classification by J. Searle. This study aims to investigate the kind sand the dominant type of speech act in TOEFL short dialogue of listening comprehension test. The study uses a qualitative descriptive approach with a content analysis research design to reach the objectives of this research. The objects were taken through 30 short dialogues in TOEFL listening test items. The results of the study show the distribution of each classification found as the following: 44% for directive, 42% for assertive, 11,5% for expressive, and 1% for commisive. It can be seen that the most dominant type is directive and commissive is less found. The study concludes that test takers must be familiar with the context of the speech to comprehend the proposed meaning of the TOEFL listening items. It is recommended for students to evaluate the meaning of the utterances using the speech acts theories to assist the students in identifying the different sorts of utterances and understanding the proposed meaning of the utterances.
Static Analysis for AWS Best Practices in Python Code

Amazon Web Services (AWS) is a comprehensive and broadly adopted cloud provider, offering over 200 fully featured services, including compute, database, storage, networking and content delivery, machine learning, Internet of Things and many others. AWS SDKs provide access to AWS services through API endpoints. However, incorrect use of these APIs can lead to code defects, crashes, performance issues, and other problems. This paper presents automated static analysis rules, developed in the context of a commercial service for detection of code defects and security vulnerabilities, to identify deviations from AWS best practices in Python applications that use the AWS SDK. Such applications use the AWS SDK for Python, called "Boto3", to access AWS cloud services. However, precise static analysis of Python applications that use cloud SDKs requires robust type inference for inferring the types of cloud service clients. The dynamic style of Boto3 APIs poses unique challenges for type resolution, as does the interprocedural style in which service clients are used in practice. In support of our best-practices goal, we present a layered strategy for type inference that combines multiple type-resolution and tracking strategies in a staged manner. From our experiments across >3,000 popular Python GitHub repos that make use of the AWS SDK, our layered type inference system achieves 85% precision and 100% recall in inferring Boto3 clients in Python client code. Additionally, we present a representative sample of eight AWS best-practice rules that detect a wide range of issues including pagination, polling, and batch operations. We have assessed the efficacy of these rules based on real-world developer feedback. Developers have accepted more than 85% of the recommendations made by five out of eight Python rules, and almost 83% of all recommendations.
ANALYTICAL FORWARD-PROJECTION AND SYSTEM CALIBRATION FOR IMAGING THROUGH REFRACTIVE WINDSHIELDS IN AUTOMOTIVE APPLICATIONS

Abstract. We study in this paper models to mitigate effect of a windshield-related refraction on imaging systems. The literature shows that the distortions introduced by this curved surface are non-linear in their effect and reduce the performance of image-based analyses and depth estiamtion algorithms. We show that using geometric optics and local approximation of the windshield’s surface to a spherical one, a direct analytical refractive forward projection (RFP) form of a 3-space point onto the image plane can be derived. However, an exact form requires solving a 22-degree polynomial which may become numerically unstable. To stabilize the solution, we demonstrate how the introduction of valid local assumptions on the interface allows reducing the polynomial degree down to 8 and 4. Utilizing these forms we then show that the RFP can be used to jointly estimate the camera pose and the windshield’s surface parameters through minimization of the reprojection error. The proposed models are tested on simulated data and validated on real-world observations. Results show stability and a sub-millimeter level of reconstruction accurecy, alluding to the validity and quality of our representations.
Speech Recognition by using Optimization Method

In this paper we discuss the importance of speech recognition as well as we show how speech recognition evolved in last few years. Speech Recognition is a challenging domain, which made it an important research topic. In its early stage or at the time of invention it was not an as effective as it now, therefore many researchers worked on this domain and made it an exceptional one. This paper also shows the technological perspective and the progress in the field of speech communication. We also discuss how the speech recognition changed the way the world as it is now with the help of ASR (Automatics speech recognition) system work. Speech Recognition is based on the voice of research object. It allows the machine to turn speech signal into text as command. The speech recognition technology is gradually becoming the key technology of the IT man machine interface. The paper describes the development of speech recognition technology and its basic principles, methods, reviewed the classification of speech recognition systems and voice recognition technology. This paper gives you the complete idea about speech recognition.
Cybersecurity and Interoperability of Aviation Safety Service Ecosystem

As the largest high speed mobile network system, the aviation safety service integrated network provides air-to-ground communication to various operators, Air Navigation Service Providers (ANSPs) and airlines across multiple continents. Maintaining such a large network and mobile nodes comes with challenges. Seamless interoperability underpinned by cybersecurity is essential to successful safety service communication. By ensuring that technologies work together across platforms and geographic locations, we better protect the data that flows throughout our aviation systems. And when data is secure, we&#x2019;re able to confidently extend secure communication to reach aircraft, ANSPs, content providers, airline operation centers, and many more no matter where they receive and send messages across multiple endpoints within an aviation ecosystem across the globe. To provide aviation partners with cutting-edge equipment and to ensure that connected devices and systems meet or surpass security standards, the aviation community needs to be committed to ensuring technologies meet needed security specifications including security standards, the Risk Management Framework (RMF), and compliance to the contemporary security protocols and processes. By performing to these specifications, the aviation community can better enable the system-wide availability and cybersecurity of aviation data, thereby facilitating more timely and effective secure communication. This will require an extensive set of external compliance certifications, attestations to objective evidence of compliance to security regulations (examples include ISO 13485, ISO 14971, ISO 27001/18, SOC2) and product cybersecurity testing certification. This also requires combined cybersecurity testing elements of the established standard for software cybersecurity for network-connectable products, as well as security principles from international standards. This paper discusses the critical components of seamless interoperability underpinned by cybersecurity and related issues for secure data exchanges that ensures the continuum of Internet Protocol Suite (IPS) based safety service communication networks to the aviation safety service ecosystem.
Integration of Python Modules in a MATLAB-Based Predictive Analytics Toolset for Healthcare

Python and MATLAB both are common tools used for predictive modelling applications, not only in healthcare. In our predictive modelling group, both tools are widely used. None of the two tools is optimal for all tasks along the value chain of predictive modelling in healthcare.The aim of this study was to explore different ways to extend our MATLAB-based toolset with Python functions.Pre-existing interfaces between MATLAB and Python have been evaluated and more comprehensive interfaces have been designed to exchange even complex data formats such as MATLAB tables.The interfaces have successfully been implemented and they were validated in a Natural Language Processing scenario based on free-text notes from a telehealth services for heart failure patients.Integration of Python modules in our MATLAB toolset is possible. Further improvements especially in terms of performance, are required if large datasets need to be exchanged. A big advantage of our concept is that tabular data can be exchanged between MATLAB and Python without loss and the Python functions are called dynamically via the interface.
Research on dynamic scheduling method of railway transportation based on pre-classification

When the current method is used to schedule railway transportation, the scheduling takes a long time, and the difference between the obtained scheduling result and the expected one is large, and there is a problem of low scheduling efficiency and poor validity. A dynamic scheduling method based on pre-classification is proposed, which pre-classifies railway transportation resources, improves the utilization rate of railway transportation resources, and shortens the time required for scheduling. The execution time is taken as the optimization target, and the railway transportation dynamic scheduling model is constructed based on the pre-classification results. The genetic algorithm is used to solve the dynamic scheduling model of railway transportation, and the dynamic scheduling of railway transportation is realized. The experimental results show that the proposed method takes less time for railway transportation scheduling, and requires less time to perform tasks after scheduling. The proposed method has high scheduling efficiency and good effectiveness.
The Relationship between Indonesian Language Learning and the Environment

In learning especially Indonesian, the environment can affect the quality of student learning. The environment is an influential component in the implementation of teaching and learning activities. The environment can also support the course of teaching and learning activities in schools. Schools with a clean environment will make students learn comfortably and vice versa. Environmental-based Indonesian language learning is known to reduce the boredom experienced by students when teaching and learning activities are carried out. When students experience this, educators or teachers can invite students to take advantage of the surrounding environment as a fun learning medium. This can help students in rethinking the relationship between humans and the environment as well as being aware of and considering problems in the surrounding environment.
SCHOOLS AS INFORMATION CHANNEL TO REDUCE ALCOHOL USAGE HABITS AMONG ADOLESCENTS

The purchase of alcohol and the use of such substances among adolescence is prohibited in Latvia by the legal system of rights. Despite the legal ban alcohol consumption is widespread among Latvian adolescence and starts at very early age. Recent studies show that most of 15-year-olds have consumed alcohol in Latvia. In order to proactively inform and reduce alcohol consumption among young people, a number of information and education programmes have been implemented, mainly in the school environment. Most of these programmes lack an assessment. Consequently, there is a lack of data on the programme effectivity and the link of programme with young people’s knowledge and confidence in their alcohol consumption-related behaviour. The purpose of the study is to identify information channels where adolescence are most frequently gain information, to assess the level of knowledge of grade 9 pupils and its relevance to potential action in alcohol consumption situations. The empirical data of this study is based on a survey with grade 9 pupils. The results of the study show that the school environment is important information channel, but it is essential to offer a diverse information content, involving a number of experts to provide information. High levels of knowledge have a positive impact on young people’s confidence in alcohol consumption-related situations, but do not have a significant impact on alcohol trying rates.
Operating Fiber Networks in the Quantum Limit

We consider all-optical network evolution from a quantum perspective. We show that a use of optimal quantum receivers allows an estimated $55\%$ decrease in energy consumption of all-optical amplifiers in network configurations that are typical today. We then compare data transmission capacities of quantum receivers with today's technology operating within the boundaries set by Shannon. We find that quantum receiver technology allows for a logarithmic scaling of the system capacity with the baud-rate, while Shannon-type systems are limited by the transmit power. Thus a natural quantum limit of classical data transmission emerges. Based on the above findings we argue for a new approach to optical communication network design, wherein in-line amplifiers are replaced by novel fiber supporting high spectral bandwidth to allow for noiseless data transmission in the quantum limit.
Pemanfaatan Aplikasi e-office dalam Manajemen Arsip di Madrasah Aliyah Negeri 4 Kota Pekanbaru

The rapid development of technology in the industrial revolution 4.0 is marked by the presence of electronic devices that humans can utilize as users in various work activities. Facing this phenomenon, e-office as records management needs serious attention. In addition to time efficiency, the use of technology can also reduce costs and other resources such as paper, ink, etc. Unfortunately, users sometimes lack the skills to use existing electronic systems. Therefore, this article aims to explain the use of e-office in MAN 4 Kota Pekanbaru and the opportunities, challenges, and obstacles faced. This article was written with a case study approach, namely by explaining the facts in the field using a qualitative descriptive method. The study's conclusion shows that archive management at MAN 4 Kota Pekanbaru is currently carried out using manual and online systems. However, there were several challenges and obstacles encountered during the study, so it is recommended to conduct training so that HR skills can be adequately improved and e-office applications can be implemented optimally.