Reviewerly/exHarmony huggingface dataset:
Level of Priority based Leader-Following Behavior using Reciprocal Velocity Obstacles in Multi-Agents Navigation

Leader-following behavior is a behavior in which a number of follower agents are required to go after the leader. The leader agent is tasked to lead the group to reach their goal. This leader holds a significant role for a group of leader-following agents to reach their shared destination since the leader has full information of the whole area of navigation. Due to its importance, leader movement supplicate hindrance-free navigation. Considering the follower agents have minimal information regarding path information, they tend to stick with their leader. These followers&#x2019; actions may affect leader movement thus creating a disturbance that drives the group into navigation failure such as deadlock. This research utilized leader-following behavior with levels of priority between the leader and follower agents in the avoidance process. We employ Reciprocal Velocity Obstacles(RVO) to handle the avoidance process. Levels of priority enforced difference weight in avoidance effort, thus creating an absolute necessity for the followers to fully accomplish avoidance on their own against their respective leader. We conduct a series of experiments to reveal the problem that caused by followers which hinders the leader&#x2019;s navigation. We also exemplify that our method can successfully provide necessary action to satisfy leader navigation. From the results of the experiments we conduct, the leader&#x2019;s movement is safe from deadlocks caused by followers blocking the leader agent movement.
Hubungan Kemandirian Belajar dengan Motivasi Belajar Siswa Kelas Tinggi di Sekolah Dasar

This research is a descriptive quantitative research with correlational type which aims to determine whether there is a positive relationship between learning independence and student motivation at SDN 220 Cinnong, Sibulue District, Bone Regency. The population in this study were all students in grades IV, V and VI of SDN 220 Cinnong, Sibulue District, Bone Regency, which collected 41 students. The sampling technique in this study is non-probability sampling. Then based on the results of inferential statistical analysis obtained t count of 2.1404 and t table with a significance of 5%. of 1.684888 so that t count t table. It can be said that there is a positive relationship between learning independence and student motivation at SDN 220 Cinnong, Sibulue District, Bone Regency.
Mining Frequent Spatial Patterns in Image Databases with 17D-SPA Representation

In this paper, we propose a new algorithm for mining frequent patterns in image databases. Our method mines patterns with more accuracy than a previously known algorithm and can be beneficial, where small differences in object locations can change the pattern. In this regard, we generate larger patterns from smaller ones and check whether the support for each candidate is less than a user-specified amount.
An Exploration of the Information Processing Mode of Chinese Wushu’s Intrapersonal Communication

Based on the research methods of literature, text analysis and the theories of philosophy, communication and sports, this paper rationally discusses the information processing process of Chinese Wushu&rsquo;s intrapersonal communication. It is believed that the individual body of the wushu practitioner has the general characteristics of the general information dissemination system and can actively reflect the wushu dissemination information provided by the external world. The intrapersonal communication of Chinese wushu is influenced by the distinct characteristics of individual wushu practitioners&rsquo; sociality and interactivity, which forces the individual wushu practitioners to reconstruct the significance of their own social practice of wushu communication and aggregate it into a new impetus to promote the healthy inheritance and development of Chinese wushu. In the age of digital media, the cognitive schema in the individual brain of wushu practitioners is exposed to the relevant dissemination information of wushu, which can show strong cognitive needs and have the ability to carry out in-depth cognition.
A Gentle Introduction to Stream Processing

Learning to tackle and optimize data engineering problems can be challenging due to the many dimensions each problem can take on. At the outset of each new problem, you must think about data discovery, wrangling, ingestion, transformation, and data accountability, which is an umbrella relating to data contracts (strictly defined data definitions), as well as the need to optimize the data ingestion footprint (since data at scale can easily eat into operation costs). There are additional concerns relating to data access, lineage, and governance that need to be back of mind as well. Understanding how to use your collective knowledge to create quick plans of data attack is a skill that will get you far as a modern data engineer.
Epistemic uncertainty in fault geometry effects earthquake rupture behavior

&amp;lt;p&amp;gt;It is well established in the seismology community that geometric complexity plays an important role for a fault&amp;amp;#8217;s seismotectonic behavior. It affects the initiation, propagation and termination of an earthquake as well as influencing the stress-slip relationship, the size of fault segments, and the probability of multi-segment rupture. Consequently, fault geometric complexity is studied intensively and increasingly incorporated into computational earthquake rupture simulations. These efforts reveal a problem: While we may be able to constrain a natural fault&amp;amp;#8217;s geometry with a high level of detail at the surface (i.e., the fault trace), we cannot do the same for the buried portion of the fault -where most of the rupture takes place. How much does a fault&amp;amp;#8217;s seismotectonic behavior vary as a result of this epistemic uncertainty?&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;We address this question computationally with a physics-based multi-cycle earthquake rupture simulator (MCQsim), enabling us to investigate how (for example) earthquake recurrence, slip accumulation, magnitude-frequency distribution, and fault segmentation vary (looking at the entire fault as well as individual locations on the fault) as function of our insufficient knowledge about the fault&amp;amp;#8217;s geometric complexity. To simulate fault geometric complexity, we generate 2-D random fields, using the &amp;amp;#8220;random midpoint displacement&amp;amp;#8221; method (RMD), representing the fault&amp;amp;#8217;s non-planar, self-similar geometry. The advantage of using RMD is that it allows us to create a 2-D random field while also keeping one or more of the field&amp;amp;#8217;s edges at a prescribed value. Hence, this approach allows us to generate a random field to represent fault roughness while also allowing us to incorporate what is known about the fault geometry (i.e., the fault surface trace, representing one of the random field&amp;amp;#8217;s edges). In doing so, we can investigate how the aforementioned seismo-tectonic parameters vary as a function of fault roughness uncertainty.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;For this purpose, we create 5000-year long earthquake catalogs for a 150x18km large strike slip fault that is parameterized by more than 40k fault cells (average cell size 0.07km^2), containing earthquakes with 3.5 &amp;lt; M &amp;lt; 7.8. We create these catalogs for 100 roughness realizations while keeping the simulated fault&amp;amp;#8217;s surface trace constant for all realizations. The results of these simulations will be presented in our presentation.&amp;lt;/p&amp;gt;
SISTEM PEMELIHARAAN MENARA BTS (BASE TRANSCEIVER STATION) BERBASIS MOBILE

The development of mobile device technology, especially Android applications, is growing very significantly. The focus of this research is how to build a mobile-based BTS (Base Transceiver Station) tower maintenance system. This system was built to simplify and speed up the documentation and reporting process for BTS tower maintenance, thereby minimizing loss and duplication of documentation files when performing maintenance. This system is built using the Java programming language with a Firebase database. The system development method used is Extreme Programming. System testing using ISO 25010 testing using three testing aspects, with the results: 100% functionality aspect, 89.00% usability, and 5.4% CPU usage performance efficiency. Tests were carried out on 5 Android Mobile devices with different specifications. From the results of testing on respondents using a Likert measurement scale, it was obtained an average of 94.5%. Based on this, it can be concluded that the system is very good/very feasible to use and provides solutions to the problems faced.
Evaluating of EFL Online Learning on Islamic Higher Education During Pandemic Era

The outbreak of Covid-19 brings a new paradigm of conducting the teaching-learning process literally. There is a shifting learning activity from traditional into the recent one. Online learning becomes common sense while doing all the activities supporting the learning process. This recent case study aimed to explore the EFL adult learners’ perceptions and experiences while in online learning classes during the pandemic era. This recent qualitative case study examined the perceptions and experiences of EFL adult learners during their two-year participation in online classes. This qualitative case study was based on Maslow’s theoretical framework. There were a hundred students of EFL at UIN Walisongo Semarang as the participants of this study. They were asked to respond to their perceptions and experiences while conducting online learning via Google form. Questionnaires and semi-structured interviews were used to collect data, and template analysis was used to document the students' experiences taking part in the research. The researchers employed SPSS 21 to analyze the data taken from the questionnaire. It shows that 6% of participants disagreed with implementing online learning. On the other hand, 10.5% of participants strongly agreed with online learning conducted during the pandemic era. At last, there were 34.3% who responded that they neither agreed nor disagreed in online learning classes.
English Writing Anxiety among College Non-English Majors in Jiangxi University of Engineering

College English writing is a very important part of college English class, but for non-English majors, it is inevitable to have anxiety when facing English writing.Therefore, this study adopted a mixed-method to investigate the current situation and analyze the causes of writing anxiety to put forward some suggestions that can alleviate writing anxiety and effectively affect the teaching of second-language writing.The sampling method used in the research is random sampling.
Portable laparoscopy 3D measurement system by using Raspberry Pi

Minimally invasive techniques have become the standard for a variety of surgeries in all surgeries. Specially، there has been a recent move to integrate low-cost and more efficient technology into standard laparoscopy and endoscopy. Surgery to design portable laparoscopy device and improve visual field stability using, a low cost laparoscopic camera, the portable device differ from conventional in equipment (number, size, Wight, ..). The scope of the control room of the inserted laparoscopic platform system receives increasing attention from researchers, surgeons, and also patients. Although many prototype by using Raspberry pi embedded system laparoscopes have been introduced with a built-in platform smart touch screen system, few of them eliminate the blocked cable. It is suggested to Hardware architecture for integrated system Endoscopic camera design fully modern dynamic platform, facilitating installation without fully connected cables laparoscopic surgical robotic camera with adequate in-vivo motility. Modular design and preliminary test on board.
Introduction to This Book

This introduction presents an overview of the key concepts discussed in the subsequent chapters of this book. The book describes the regulatory requirements on governance and risk management that provide the framework around which most organisations construct their risk management systems. It shows the transition into a discussion of risk management practice rather than theory, and so also includes brief snapshots of risk events and their impact across a wide range of large and small organisations. The book reviews the concept of technology risk and makes clear the important distinction between the broader technology risk and the more specific term cyber risk. It integrates the lessons learned from case studies and translates these into a list of factors influencing the effectiveness of risk management systems in practice. The book concludes that the ideal scenario of an organisation where everybody is continuously aware of and talks about risk and the risk of surprise is minimised is extraordinarily difficult to achieve.
Energy-Efficient Multi-agent Cooperative Search Control Based on Deep Reinforcement Learning on Uneven Terrains

Anti-flocking algorithm for multi-agent to search a given area of interest(AOI) has been relatively mature. Multi-agent is basically used to search for uneven terrain, but the most existing anti-flocking algorithms are designed for flat terrain, so agents often use the shortest path to move between navigation targets. Using the shortest path to move in uneven terrain will consume more energy. At present, agents basically use portable energy to provide power, so we should try to reduce energy consumption. This brief proposes an energy-efficient multi-agent cooperative search control based on deep reinforcement learning on uneven terrains. The proposed algorithm selects the navigation target points through deep reinforcement learning, and encourages the agent to move between the navigation target points along the contour line. Simulation results show that the proposed control protocol is a promising energy-efficient solution for multi-agent operating on uneven terrains.
PENERAPAN APLIKASI WEB UNTUK ADMINSTRASI DI DESA SIDOSARI LAMPUNG SELATAN

Correspondence services and civil registration of the population are very important in village administration. In this case, Sidosari village provides services including correspondence services and population registration for the Sidosari village community. Based on interviews with representatives of village staff that have been carried out at the Sidosari village office, they said that there are several shortcomings in the service section at the Sidosari village office, one of which is the correspondence service and population registration which is done manually. In this case the correspondence service is done manually causing data and letters that have been made difficult to find and frequent data loss occurs. This website is expected to be a tool for employees in carrying out their duties to serve and record population in Sidosari village, South Lampung. Keywords: Administration, Village, Website.
Scientific Imaging Problems

Connecting theory with practice, this systematic and rigorous introduction covers the fundamental principles, algorithms and applications of key mathematical models for high-dimensional data analysis. Comprehensive in its approach, it provides unified coverage of many different low-dimensional models and analytical techniques, including sparse and low-rank models, and both convex and non-convex formulations. Readers will learn how to develop efficient and scalable algorithms for solving real-world problems, supported by numerous examples and exercises throughout, and how to use the computational tools learnt in several application contexts. Applications presented include scientific imaging, communication, face recognition, 3D vision, and deep networks for classification. With code available online, this is an ideal textbook for senior and graduate students in computer science, data science, and electrical engineering, as well as for those taking courses on sparsity, low-dimensional structures, and high-dimensional data. Foreword by Emmanuel Candès.
Evaluation and Promotion of a Multidimensional Information Intelligent Speech System in Dialect Teaching

Due to the wide scale of learners, large individual differences and scattered distribution, dialect teaching is difficult to carry out effectively by traditional school education. In order to improve the teaching level of dialect, taking Cantonese as an example, this paper constructs a teaching evaluation system based on multidimensional information. Through the questionnaire and investigation of large Cantonese training institutions in Guangdong Province, the data set is formed, the CMA-ES algorithm with efficient optimization ability is selected to optimize the SVM, and the model is compared with ACO and SVM without optimization algorithm. Experimental results show that the average accuracy of CMA-ES algorithm is 95.85% and the average running time is 21.0 ms on 8 data sets, which has obvious advantages relatively. Based on the evaluation model, the basis for teaching optimization is found through sensitivity analysis, and student’s language expression is the most important index. And with the help of the intelligent voice system, the improvement measures for Cantonese teaching are proposed from the aspects of scene, oral, and scoring.
Blind denoising using dense hybrid convolutional network

The performance of existing deep convolutional networks is limited when encountering images with different noise levels. In this study, a denoising method with state-of-the-art performance that combines a deep convolutional network with the traditional nonlocal mean denoising method is proposed. The noisy image is first denoised using the nonlocal mean method. Then, the denoised image is input into the proposed dense hybrid convolutional network to be trained, producing a clean image with clear details. The dense hybrid convolutional network comprises three parts: a feature-extracting noise-suppressing module that extracts abstract features from denoised images and suppresses the residual noise by interval convolution; a feature-learning module used for training blurred edges and textures; and a magnifying module that uses deconvolution to restore the feature maps to the original size and reduce the noise again. In contrast to existing denoising algorithms, the method has two desirable properties: 1) it can restore edges and textures clearly while removing the noise; 2) it effectively deals with noise of unknown levels (i.e. blind denoising) with a single network model. The conducted experiments show that the proposed method achieves superior performance compared to those of state-of-the-art denoising methods.
Prediction of Rupiah Currency Value Against Dollar with ARIMA Model

&lt;p&gt;The currency of each country is different, resulting in difficulties in transacting between one country and another. So it takes a currency exchange process to facilitate a transaction process between countries called the Exchange Rate. However, exchange rate volatility can threaten the economy of a country. Therefore, a prediction of the exchange rate is needed so that investors or the public can determine strategies or plans for future economic policies. Therefore, this study aims to find the ARIMA model that has the best performance in predicting the rupiah exchange rate against the dollar. So that this model can be a reference for investors and the public in investing in shares with other countries. The results of this study obtained the best model, namely the ARIMA model (0, 1, 1) to predict the exchange rate for the next 20 periods with the help of &lt;em&gt;eviews9 software&lt;/em&gt;.&lt;/p&gt;
Introduction to the Minitrack on Security and Privacy Challenges for Healthcare

This year, the minitrack has grown from the traditional patient-centric view into a more multifaceted phenomenon.These three accepted research in the Security and Privacy Challenges for Healthcare minitrack is a testament of how the minitrack continues to be the place for acknowledging, addressing, and asserting the importance of security and privacy in healthcare.
Sign Language Recognition using Deep Learning

Abstract: Millions of people with speech and hearing impairments communicate with sign languages every day. For hearingimpaired people, gesture recognition is a natural way of communicating, much like voice recognition is for most people. In this study, we look at the issue of translating/converting sign language to text and propose a better solution based on machine learning techniques. We want to establish a system that hearing-impaired people may utilise in their everyday lives to promote communication and collaboration between hearing-impaired people and people who aren't trained in American Sign Language (ASL). To develop a deep learning model for the ASL dataset, we'll use a technique called Transfer Learning in combination with Data Augmentation. Keywords: Sign language, machine leaning, Transfer learning, ASL, Inception v3
Discovery of scattered subvolcanic complexes that feeded the volcanism in the area of Etna

&amp;lt;p&amp;gt;In this work we present a new tomographic inversion of the velocity structure and hypocenter parameters at Mt. Etna, carried out by the larger seismic dataset never used than to the previous tomographies. The result of tomographic inversion, including the 3D distributions of P and S velocities, Vp/Vs ratio, and accurate source locations, has been obtained based on the integration of active seismic data (151.403 P-phases from 4.112 shots) acquired during the 2014 TOMO-ETNA experiment (EC-FP7 MED-SUV and EUROFLEET2 MED-SUV.ISES projects) and 10.955 selected local earthquakes data (218.473 P-phases and 39.073 S-phases), recorded by a total number of 262 stations of the INGV permanent seismic network and from the onland and OBS temporary network. For the inversion we used the tomoDDPS algorithm [Zhang et al., 2009] and the input velocity model previously obtained with the PARTOS code (Moreno et al. 2016), considering a total number of 1.580.343 P and 228.663 S differential times.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Based on our data selection and inversion strategy, we obtain a strongly improved 3-D high-resolution Vp, Vs and Vp/Vs models both onland and offshore the volcano, discovering for the first time, in the peripherical part of the edifice: i) on-land, the presence of two subvolcanic complexes in the south-eastern and southern flanks, west to Acicastello-Acitrezza and Patern&amp;amp;#242; and Motta, respectively, where the Etna&amp;amp;#8217;s ancient volcanisms (500 to 110 ka) manifested and ii) the presence of a ca. N-S oriented high velocity anomaly (5.0-6.5 km/s) located offshore southeast of Etna area, suggesting a clear interplay between submarine volcanic manifestations and tectonic setting. This body extending from about the sea level to ca. 8 km b.s.l. confirms the observation of a large and intense magnetic positive anomaly (&amp;gt;700 nT) related to deep sources (Cavallaro et al., 2016), evidenced by the magnetic survey carried out during TOMO-ETNA.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;amp;#160;&amp;lt;/p&amp;gt;