Reviewerly/exHarmony huggingface dataset:
Time-optimal of fixed wing UAV aircraft with input and output constraints

&lt;p style='text-indent:20px;'&gt;The route prediction of unmanned aerial vehicles (UAVs) according to their missions is a strategic issue in the aviation field. In some particular missions, the UAV tasks are to start a movement from a defined point to a target reign in the shortest time. This paper proposes a practical method to find the guidance law of the fixed-wing UAV to achieve time-optimal considering the ambient wind. The unique features of this paper are that the environment includes the moving and fixed obstacles as the route constraints, and the fixed-wing UAVs have to keep a given distance from these obstacles. Also, we consider the specific kinematic equation of the fixed-wing UAV and limitations on the flight-path angle and bank-angles as other constraints. We suggest a method for controlling a fixed-wing UAV to get time-optimal using the re-scaling and parameterization techniques. These techniques are useful and effective in maximizing the performance of the gradient-based methods as a sequential quadratic programming method (&lt;inline-formula&gt;&lt;tex-math id="M1"&gt;\begin{document}$ SQP $\end{document}&lt;/tex-math&gt;&lt;/inline-formula&gt;) for numerical solutions. Then, all constraints of the time-optimal control problem are converted to a constraint using an exact penalty function. Due to being exact, finding the control variables and switching times is more accurate and faster. Finally, some numerical examples are simulated to explore the effectiveness of our proposed study in reality.&lt;/p&gt;
Regular Model Checking with Regular Relations.

Regular model checking is an exploration technique for infinite state systems where state spaces are represented as regular languages and transition relations are expressed using rational relations over infinite (or finite) strings. We extend the regular model checking paradigm to permit the use of more powerful transition relations: the class of regular relations, of which the rational relations are a strict subset. We use the language of monadic second-order logic on infinite strings to specify such relations and adopt streaming string transducers (SSTs) as a suitable computational model. We introduce nondeterministic SSTs over infinite strings and show that they precisely capture the relations definable in MSO. We further explore theoretical properties of omega-NSSTs required to effectively carry out regular model checking. In particular, we establish that the regular type checking problem for omega-NSSTs is decidable in PSPACE. Since the post-image of a regular language under a regular relation may not be regular (or even context-free), approaches that iteratively compute the image can not be effectively carried out in this setting. Instead, we utilize the fact that regular relations are closed under composition, which, together with our decidability result, provides a foundation for regular model checking with regular relations.
AiroIdent &amp;#x2013; User identification based on analyzing WPA2 encrypted traffic containing search engine interactions

Most search engines provide search suggestions and autocompletion mechanisms based on the partially typed search string. In order to implement such functionality, frequent requests are being sent to the search engine provider. Recent publications show that there is a risk that the user can be identified by observing the TLS encrypted traffic and analyzing the unencrypted meta data. In this paper we extend this approach to the observation of widely used encrypted WiFi networks in order to estimate the potential privacy impact. Without having access to Layer 3 and 4 meta data, the main challenge of this approach is the identification of potential requests being sent to the search engine. We use a linear regression-based approach to identify candidate packet sequences for the feature extraction. The evaluation is done in an optimal environment (reduced WiFi-traffic) to determine a first tendency and performed using three search engines. In total four different user identification/verification approaches are utilized: M1 identification using a neural network, M2 identification using Manhattan distance, M3 identification using Euclidean distance and M4 verification using a one-class support vector machine (SVM). Our results show a classification performance for 10 different test subjects is ranging from 13.2% using the one-class SVM (M4) to 64.1% using the neural network (M1) for the identical search engine. In comparison to a group of five test subjects it can be seen that M1 provides more scalability in comparison to M2, M3 and M4. In addition to that, we present potential countermeasures which could help to increase the privacy of the users of a search engine.
Application of the Task Centered System Design (TCSD) Method for UI / UX Design Analysis in E-Learning at SMAN 1 Sidoarjo

SMAN 1 Sidoarjo which is one of the favourite schools in the district. When implementing online learning, SMAN 1 Sidoarjo has not used an e-learning platform so it uses many existing platforms such as google classrooms, so students and teachers need to open many platforms, and the UI design e-learning on platforms does not motivate students, causing bored. Because the design user interface in e-learning is an important element for creating virtual-based learning so it is necessary to have a design analysis before building e-learning. The TCSD method is used for the design analysis stage, so that the results are in prototype accordance with the process task and the display results are in accordance with the results of the user persona. Usability heuristic is used to test whether the results prototype are running according to the task with a display that is acceptable to the user. The prototype has been compiled and evaluated, using the evaluation heuristic the SR value for each aspect is obtained with an average of 0.822 rounded to 1, so that the result is in the category cosmetic which means there is a problem but no improvement is needed unless there is still time for processing.
जी. एस.टी. एन. पालनाचे तंत्रज्ञान वस्तू व सेवा कर नेटवर जीएसटी लाभ आणि समस्या (G. S.T. N. - A Compliance Technology and it's Benefits and Problems on Goods and Services.)

Marathi Abstract: वसत व सवा कर भारतात 1 जल 2017 पासन वसत व सवा कर एकच अपरतयकष कर लाग करणयात आला. सपरण दशभरात एकसमान करपरणाली असावी कदर सरकार व राजय सरकारचा मखय उददश होता. यासाठी भारताचया राजय सघटनत दरसती करन नवीन कायद करणयात आल. वसत व सवा कराचया अमलबजावणीसाठी माहिती ततरजञानाच जाळ पसरविणयासाठी वाहन महणन वसत व सवा करायच जीएसटीएन नावाची सकलपना साकारणयात आली जीएसटीएन कडन कदर व राजय सरकारला माहिती-ततरजञानाचया पायाभत सविधा आणि सवा परविणयात आल आहत. परत जीएसटीएन च काही लाभ असल तरी तयात काही समसयाना करदातयाना समोर जाव लागत आह. सरकार आणि वयवसाय दोनहीचया दषटिकोनातन ततरजञानाची भमिका अमलबजावणी मोलाची आह. महणन सशोधनासाठी जीएसटी पालनाच ततरजञान वसत व सवा कर नटवरक लाभ आणि समसया हा विषय निवडला आह.English Abstract: Goods and Services Tax (GST) is the only indirect tax from 1 July 2017 in India. The main objective of the Central and State Government was to have a uniform tax system throughout the country. For this, new laws were enacted in the State Organization of India.The concept of GSTN was introduced as a vehicle for disseminating information technology as a network for implementation of Goods and Services Tax (GSTN). GSTN has provided information technology infrastructure and services to the Central and State Government. But despite the benefits of GSTN, there are some issues that tax payers face. The role of technology in both government and business perspectives is crucial to GSTN implementation.Therefore, the topic of research is G. S.T. N. - A Compliance Technology and it's Benefits and Problems on Goods and Services.
PENERAPAN TEKNOLOGI AUGMENTED REALITY PADA APLIKASI MEDIA PEMBELAJARAN MIKROKONTROLER BERBASIS ANDROID DENGAN PLATFORM ARCORE

Augmented Reality (AR) is an interactive technology that combines the real and digital world in two-dimensional and three-dimensional forms and projected in a real environment at the same time. Attractive and effective learning media is needed to improve students’s understanding of material, especially if the material requires access to physical objects such as microcontroller learning. By utilizing AR technology, physical objects can be replaced with interactive three-dimensional models.&#x0D; The Mobile based AR application that has been developed in this study as microcontroller learning media was built using the latest AR platform from Google ARCore, that utilizes smartphone cameras to detect flat surfaces, then the selected three-dimensional microcontroller models will appear on the surface without the need to use markers. The developed AR application also has an interactivity feature between users and a three-dimensional model, by generating information of the user selected microcontroller components.
Camera Positioning and Vision-based Fall Detection

Elderly care residences often have falling incidents, sometimes with dire consequences. This project aims to implement a method for detecting when people fall, an issue that has seen much research and practical implementations already. In contrast to other work, this project aims to create a non-intrusive, non-wearable solution through the use of cameras. It extends an existing patient monitoring system developed by Eya Solutions, a start-up in the medical field. Their system monitors patients and is composed of embedded systems (clients), a back-end with a database, and a web-based dashboard (the front-end) for administrators, caretakers and users. Our client wants to extend their system by introducing: (i) a video processing component which performs face recognition, (ii) functionality for indoor positioning of people, (iii) functionality to automatically determine near-optimal placement of cameras, and (iv) automatic detection of fall incidents. To understand the relevant research, we survey the field investigating five key research topics: (i) object detection, (ii) fall detection, (iii) facial recognition, (iv) floor plan modelling, and (v) camera placement optimisation. The first part of the project is detecting fall incidents in video footage. By means of image processing (in particular, subsequent frame subtraction), our system detects objects in the foreground and tracks these between frames. Based on the properties of such objects, namely size and shape, we detect fall incidents. The second part of the project is the floor plan editor. This editor is integrated into the existing dashboard, where administrators can model the building. Eya Solutions wishes to provide the product to customers as a complete package, including (i) showing where fall incidents have occurred, and (ii) how and where to place cameras. Our system allows administrators to edit the floor while allowing caretakers to see the modelled floor and see where falls are detected. Considering (ii), it is desirable to generate a configuration where the number of cameras is low while the view coverage is high. Our contribution includes a genetic algorithm which can generate automatically a suitable configuration. Alternatively, cameras can be placed manually by the administrator.
Premier League 2020 Player Data Clustering with the DBSCAN Algorithm

Premiere League is prestigious event that is in demand by many people. And player goals are very important in this regard. Research on the number of players based on this age can be done. One of which is by clustering. Clustering is a method for grouping objects according to their similarities. And the algorithm used DBSCAN. This algorithm can solve complex problems and has the right density so that it can help to get clustering data on this theme.
CREATIVITY OF A PERSONALITY AS A FACTOR OF DIGITAL ECONOMY DEVELOPMENT

The annual International Scientific and Practical Conference “Development of Personality Creativity in a Modern Multicultural Space” was held at Bunin Yelets State University on April 15, 2021. The situation in the country and the world determined the online format of the event, more than two hundred researchers, teachers, cultural workers, young researchers from Russia, Bulgaria, Italy, Saudi Arabia discussed issues of international scientific cooperation in a constantly changing world; prospects for the development of science in accordance with the requirement of personalization of education; systematization of the fundamental problems of the development of creativity as a segment of the digital competence profile and the basis of efficiency in a situation of uncertainty. Speeches dedicated to the development of creativity in the educational process of schools and universities have become traditional, making it possible to understand the modern picture of the world, its internationality in informational and artistic aspects. The problem of personality creativity development in the modern multicultural digital space is relevant and promising.
UCF Research Guides: Referrals to UCF Libraries Resources: Triage for Success Coaches: FAQ

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PEMBELAJARAN MENULIS TEKS PERSUASI MENGGUNAKAN METODE CONTEXTUAL TEACHING AND LEARNING

This research was conducted to examine learning to write persuasion texts which generally still raises various problems, namely the difficulty of students in starting to write, difficulties in expressing ideas, and difficulty of students in finding writing ideas that are invitations and persuasions to be put into writing. This research was conducted on students of class VIII MTS Darul Ma'arif with research subjects totaling 20 students. The formulation of the problems faced in this study is how difficult are students in learning to write persuasion texts? This study aims to answer the problem formulation regarding students' difficulties in writing persuasion texts and to find out an increase in the results of the initial and final test scores in learning persuasion writing. This research method uses descriptive qualitative which aims to describe the learning outcomes of writing persuasion texts using the contexrual teaching and learning method. The data collection technique in this study was a writing skill test. Based on the results of writing tests carried out in learning activities, the students' initial test got an average score of 50, and the final test got an average score of 78. These results prove that there is a difference between the mean score of the initial test and the final test, which is a difference of 28. With Thus, learning to write persuasion texts using the contextual teaching and learning method can be declared effective and able to become a new innovation in learning activities to write persuasion texts.
Methodology for predictive socio-cultural design

This article examines the main methodological provisions for the theory and practice of predictive socio-cultural design. The article examines the main problems, which the developers of projects in the socio-cultural sphere are facing; emphasizes the communicative content and project activities focus; analyses the achievements of the Russian school of predictive social design initiated by T.M. Dridze and their significance for modern design practice. The theoretical and activity-related, as well as systematic and situational analyses of project activity in terms of the social interaction paradigm are considered to be the initial methodological requirements. The social levels of this interaction and the corresponding strategies for project activities are of particular attention. The leading role of the cultural content and the cultural context of predictive socio-cultural design is highlighted in the critical analysis of the project experience accumulated during the autonomous sociological approach and social engineering, which remain insufficiently effective in their development and implementation.
A case study on the perceptions of I.T. professionals during the transition from a traditional to an agile process model

This paper aims to identify and analyze which individual perceptions are more frequent in the transition process between traditional and agile methods in the context of software development in a large company. The motivation for this work is due to the observation of the growing adoption of agile work models by large companies and the human aspects involved in this scenario. Thus, the particularity of this research is to offer a perspective focused on the individual aspect of each person involved in the process. This objective is achieved through the qualitative analysis of the speech of four professionals in the I.T. area of a large company concerning their perceptions about a transition from a traditional development model to an agile development model. To survey the interview questions, we used GQM. An analysis of the collected data was carried out according to procedures of the Grounded Theory, aiming to identify emerging topics among the views exposed by the interviewees. Thus, the following topics were highlighted in the context of the transition: perceived benefits for the team, difficulties faced and solutions to these difficulties.
Implementation Of Vlan Networks On The Website In The Polda Jabar Profession And Security Unit (Propam)

The use of computer network technology as a data communication medium is increasing. The need for simultaneous use of existing resources in the network both software and hardware has resulted in various technological developments on the network itself, Along with the increasing level number of network users who want  to provide maximum results both in terms of efficiency and increased network security especially to support the staffing system of a company,  based on these desires various parties continue to make improvements by utilizing various techniques, especially subnetting techniques and better use of hardware (including switches), so the concept of Virtual Local Area Network (VLAN) has emerged apply by IT(Information Tecnology)  PROPAM POLDA of West Java to maintain its network system and to support its staffing system and official vehicle loan systems because VLAN  provide management flexibility in making separate Virtual LANs into segments or subnets that can be used to define separate locations or networks network of departments in the PROPAM POLDA JABAR environment.
A Study of the Futuristic Indicators with respect to Crypto currency

The Crypto Research Report has predicted that Bit coin will be worth $397,000 in 2030. A major Tesla investor’s prediction is that Bit coin could be worth more than $1 Trillion by 2031. Satoshi Nakamoto, the person who created Bit coin is currently the Top Richest Bit coin owner. After registering the domain name for Bit coin as bitcoin.org, the Bit coin network was introduced to the market on January 3rd, 2009. For this digital asset to work as a medium of exchange is definitely a ‘Wait and Watch’ Policy. After a lot of rumblings about crypto currency, the global regime has definitely unleashed a new perspective of crypto currency within India. In April 2018 the Reserve Bank of India had prohibited Financial Institutions from engaging with individuals or businesses dealing in virtual currency.  However, the Supreme Court gave the verdict that the RBI ban was unconstitutional and gave permission to banks to handle crypto currency transactions from traders and exchanges. A Government panel was then set up and went on to recommend a ban on crypto currencies and also penal action and jail terms for anyone dealing with crypto currencies. The 2021 Budget session of Parliament considered prohibiting all private crypto currencies and to provide for an official digital currency to be issued by the RBI. The new law was supposedly to be based on China’s model, wherein trading and usage of crypto currency has been banned and the Government is working to issue its own virtual currency. Crypto currency prices in India fell by 30% as a result of this impending proposed bill.  The scenario underwent a complete transformation with Tesla’s announcement in Feb 2021 to purchase Bit coin worth $1.5 billion and the statement that Tesla would accept Bit coin as a payment option.
An Archetype of Cognitive Innovation as Support for the Development of Cognitive Solutions in Smart Cities

This chapter presents a Cognitive Innovation Model that formalizes the basic components and the interactions between them for the establishment of a Cognitive Architecture (CA). The convenience of walking in the sense of achieving an archetype as support for the implementation of innovative intelligent solutions in Smart Cities and having the client as a means of convenient validation of the representation and processing of the knowledge expressed in the CA in comparison with those executed by humans in their daily activities.
Applications of Deep Learning into Computer Visions

The Deep learning has recently turn out to be one of the most famous sub-fields of device mastering as a result of its distributed information illustration with more than one tiers of abstraction. A numerous variety of deep gaining knowledge of algorithms is being employed to solve traditional synthetic intelligence issues. Deep neural network (DNN) are a successful into computer vision task. Though, the much accurate DNN requires million of the parameter & the operation, making energy to them, computations & the memory intensive. Impedes deployment for large DNN in lower-power device alongwith limited computing resource. Recent researches improved DNNs model from reducing memory requirements, energy consumptions & some of the operation without significantly decrease in the accuracy. The paper addresses the numerous methods of deep learning algorithms, followed by way of a description in their applications in image classifications, object identifications, face recognitions, images graph extractions and semantic segmentations inside the presence of noise. This assessment gives a review of a number of the maximum significantly deep learning scheme used into computer visions which, Convolution ally Neural Network, Deep’s Boltzmann Machine & Deep Beliefs Network, & the Stacked Denoised Autoencoder.
Multi-Object Tracking in Drone Videos

In this report, three popular methods for multi-pedestrian tracking are extended to a multi-category setting and tested on a large drone-based dataset. A thorough comparison of the algorithms is presented and a common shortcoming is identified. Building on this, a new tracking-by-detection based approach is developed that outperforms the other methods by a large margin. In addition, a state-of-the-art object detection model is adapted for the drone imagery, since no public detections are available for the dataset.
RESIDENCIA, JUEGOS Y PANDEMIA

Being student and teacher at the same time are the roles that a resident teacher must assume in his or her internships. This year, because of the social isolation, preventive and mandatory due to the COVID-19 had to add a new challenge, that of being resident in pandemic, which involved not only valuing the knowledge and strategies acquired in the training journey, but also skills in technology. The proposal presented is part of the educational intervention carried out by an advanced student of the Faculty of Chemistry of the UNS, within the framework of the Professional Internship of Higher Level. The resources and methodological strategies proposed to the class group through asynchronous and synchronous activities are detailed, as well as reflections on the experience. The results encourage rethinking residency under potential new educational scenarios.