Reviewerly/exHarmony huggingface dataset:
Parametric Design, Manufacturing and Simulation of On-Demand Fixed Wing UAVs

As the market for Unmanned Aerial Vehicles (UAVs) continues to expand, an unfulfilled need has been identified for tailor-made solutions leveraging an end-to-end process for the design and manufacture of the vehicle.The use of computer aided design combined with new manufacturing techniques allows small UAVs to be parametrically sized and quickly prototyped and deployed.This parametrization technique can be used throughout the entire design process to create optimized, attritable, on-demand solutions that can be adapted to evolving customer requirements.High-level requirements are mapped to quantitative design constraints and an automated process uses these constraints to design and manufacture a vehicle within a specified amount of time.The proposed framework is demonstrated with the generation of a fixed wing UAV solution for the detection and tracking of wildlife in remote areas.National Parks seek to prevent illegal poaching but often lack either the resources to monitor endangered animals, or the budget to purchase UAVs specially designed for wildlife tracking.First, mission requirements are identified and define a design space from which an optimal design point is selected.This design point sizes a UAV model, which is then optimized to minimize manufacturing time with the objective to yield a ready-to-fly solution within 48 hours.A flight simulation of the mission is then performed to ensure that the vehicle will fly as designed.Structural limitations of the UAV are accounted for and linked to parameters of the flight control algorithm to ensure that the UAV can safely fly its mission.
Explorative Probabilistic Planning with Unknown Target Locations

Motion planning in an unknown environment demands synthesis of an optimal control policy that balances between exploration and exploitation. In this paper, we present the environment as a labeled graph where the labels of states are initially unknown, and consider a motion planning objective to fulfill a generalized reach-avoid specification given on these labels in minimum time. By describing the record of visited labels as an automaton, we translate our problem to a Canadian traveler problem on an adapted state space. We propose a strategy that enables the agent to perform its task by exploiting possible a priori knowledge about the labels and the environment and incrementally revealing the environment online. Namely, the agent plans, follows, and replans the optimal path by assigning edge weights that balance between exploration and exploitation, given the current knowledge of the environment. We illustrate our strategy on the setting of an agent operating on a two-dimensional grid environment.
EMZD: Equal Means Z-Test Concept Drift Detector

Algorithms for extracting information from data streams must learn online, as the data distribution may change with time, a phenomenon usually known as concept drift. Drift detectors are programs that approximate the positions of the drifts to replace the base learner with the aim of increasing accuracy. EDDM is a simple and traditional drift detector but its performance is often weak. This paper proposes EMZD, which is rooted in EDDM and uses the z-test for equal means in the detection of concept drift. Experiments using artificial dataset generators, with abrupt and gradual concept drift versions plus real-world datasets, run in MOA, show that EMZD improves the accuracy and the detections of EDDM and other detectors in many situations.
New Iterated RC4 Key Correlations and their Application to Plaintext Recovery on WPA-TKIP

This paper presents new key correlations of the keystream bytes generated from RC4 and their application to plaintext recovery on WPA-TKIP. We first observe new key correlations between two bytes of the RC4 key pairs and a keystream byte in each round, and provide their proofs. We refer to these correlations as iterated RC4 key correlations since two bytes of the RC4 key pairs are iterated every 16 rounds. We then extend the existing attacks by Isobe et al. at FSE 2013 and AlFardan et al. at USENIX Security 2013, 0and finally propose an efficient attack on WPA-TKIP. We refer to the proposed attack as chosen plaintext recovery attack (CPRA) since it chooses the best approach for each byte from a variety of the existing attacks. In order to recover the first 257 bytes of a plaintext on WPA-TKIP with success probability of at least 90%, CPRA requires approximately 230 ciphertexts, which are approximately half the number of ciphertexts for the existing attack by Paterson et al. at FSE 2014.
Early Analysis and Detection of Compressed Traffic

The amount of compressed data in network traffic is gradually increasing. Such traffic effectively reduces the transmission time and improves the data transmission efficiency in the network, but it poses a challenge to the existing network traffic identification mechanism. At present, the identification method used for the compression traffic is often used to recover the complete compressed data for content identification. However, this method takes a lot of time to restore the complete compressed data and subsequent content matching.
Smart Glasses to Assist Monocular Vision to Estimate Depth

Smart technology is being used in every possible field to make our life easier. To connect humans with the virtual world, computing devices like Smart Glasses are vital. Smart Glasses are very useful in medical, entertainment, education, and many other fields. We proposed smart glasses to assist a person with a Monocular vision in carrying out his day-to-day activities. Understanding depth is the challenge faced by such a person. To overcome this problem, we designed glasses using the Convolution Neural Network and YOLOv3. Recording videos and AR are one of the most important features of Wearable smart glasses. Our glasses assist in measuring the depth of objects (Distance between camera and objects) using a camera module and providing real-time support. It will be useful while judging the distance between approaching barriers. In congested or crowded areas, these glasses help individuals to collect the surrounding information by measuring the distance between different objects.
Statutory Interpretation as Problem Solving

For many readers the paradigm of argumentation in a legal setting is that of the trial, an instance of the type of dialogue called the persuasion dialogue or critical discussion in the argumentation literature (van Eemeren and Grootendorst, 1992; Walton, 1999; Prakken, 2009). This setting is an adversarial one. For example, in a criminal case the prosecution’s role is not only to support its claim that the defendant committed the crime by bringing forward evidence, but also to attack the arguments of the other side, defend its own arguments against these attacks, and prove its own claim to the standard required, that of beyond reasonable doubt in the common law system. With this paradigm in mind, it is easy to jump to the generalization that legal argumentation is a kind of persuasion dialogue in which each side is trying to persuade the trier of fact to accept its view of the matter (Feteris, 1999, 171–174; Kloosterhuis, 2013).
Recovering Human 3D Model from Monocular 2d Imaged for Detecting Postures Deformilities

Human 3D pose estimation is one of the most talked-about or the hottest in recent years and even in the future. Most of the present algorithm can only get us the 3D skeletons from the pose which we have detected. There can be cases wherein because of lack of knowledge and data which we have obtained from the human shape, angles and textures, the accuracy of many various algorithms is not enough for high development level artificial intelligence and image processing tasks. In our paper, we purposed an algorithm and develop a project which will recover a 3D model of the human skeleton from the images which are captured by the camera to detect postural deformities and sitting postures. The algorithm proposed is very sturdy, dynamic and can help us for implementation of high development level image processing and computer vision tasks which also including shapes and textures. It also briefs us about many important techniques and important information from the implementation of the algorithm.
The development of cluster technology of educational programs of culture and art

The use of natural science research methods in the form of cluster analysis in the field of humanities on the example of the education system of culture and art gives an innovative direction to the development of the entire field of culture. The main significance of this development has an applied character, what contributes to the forming of the innovative potential of the territory and the attractiveness of the region. As a result of the proposed research, a method of cluster analysis of the education system of culture and art is developed, an algorithm for implementing the cognitive-hermeneutical methodology of teaching and approving the principles of self-development of students, as well as the realization of the role of globalization processes are proposed. The method of factor analysis in the application for the cultural sphere was tested. Recommendations, key indicators and author’s methods of development of the higher education system of culture and art are formed, taking into account the specifics of music education.
Adversarial Robustness of Open-Set Recognition: Face Recognition and Person Re-identification

Recent studies show that DNNs are vulnerable to adversarial attacks, in which carefully chosen imperceptible modifications to the inputs lead to incorrect predictions. However most existing attacks focus on closed-set classification, and adversarial attack of open-set recognition has been less investigated. In this paper, we systematically investigate the adversarial robustness of widely used open-set recognition models, namely person re-identification (ReID) and face recognition (FR) models. Specifically, we compare two categories of black-box attacks: transfer-based extensions of standard closed-set attacks and several direct random-search based attacks proposed here. Extensive experiments demonstrate that ReID and FR models are also vulnerable to adversarial attack, and highlight a potential AI trustworthiness problem for these socially important applications.
Privacy-Preserving Warning Management for an Identity Leakage Warning Network

Identity leakage is the public disclosure of user accounts that were stolen from an online service provider, e.g. email adresses and passwords. Identity leakage is an emerging threat to the security of user accounts because the number of online identities grows notably faster than the amount of used email adresses and passwords.
Blockchain-Based Implementation for Integration of DNA Profiles Information Systems

Blockchain has been a new technology that involves an emergent evolution of many areas, particularly in finance, healthcare and supply chain. Due to its remarkable features including immutability, decentralization, peer-to-peer networking and capability to corporate with data protection and privacy, it is attractive to system integration. In traditional system integration architecture, a central mediator with a silo to store transactions stands in the center of integration to provide trust and transparency for participated systems. Hence existing central mediator could become a possible target of Distributed Denial of Service (DDoS) cyberattack and single point of failure. This paper presents a blockchain-base system architecture and its implementation for system integration which doesn't need a central mediator. The blockchain-based system has been implemented using Ethereum Blockchain in compliance with the General Data Protection Regulation (GDPR) standard to support the integration of DNA profiles information systems.
RETRACTED: Simulation of basketball motion image resolution based on FPGA and gaussian mixture model

Basketball shooting thrown assumes an essential function in the Free-Basketball. A serious problem to play any of the tosses to the right, untimely to prepare all of the accounts. And prepared to not regularly excessively to tenacious. The point of this article is to change the free bio-feedback control. Elements of the elbow and the shoulder will be determined by the frame preparation strategy with a video acquisition. The learning control arrangement naming framework presented herein can be evaluated and given phonetic gradually, as described above, the input boundary. Method respects the identification and control of learning and the right of shooting performance. Test results show that the free toss and shooting style upgrades, including location shooting pocket and bolts. Video preparation circuit and framework to deal with top record successive frames are the keys these days. The circuit proposed in the article, improvement of open memory library, focused on the strong identification of the basis of the target stream of balls moving the details of the calculation of the Gaussian Mixture Model (GMM). According to the present invention, facility layout, detailed GMM conditions, reduce the use of dual multipliers, and pressure method reduce the device's complexity and allow the expansion of capacity. The proposed circuit is proposed to enable a high-speed and reasonable asset to defeat the implementation. It is planned to have a business, Filed Programmable Gate Array (FPGA) gadgets as a target.
Some classes of permutation polynomials with the form (xk + x) s + x 2 n −2

Abstract For a prime 2, let n be a positive integer, and F 2 n be the finite field with 2 n elements. In this paper, we propose several classes of permutation polynomials with the form ( x k + x ) s + x 2 n −2 over finite fields F 2 n which have the highest degree of algebra.
WITHDRAWN: An efficient multi-authentication system for cloud storage

Distributed computing, is one of the key half breeds of Internet-put together registering that permits with respect to request sharing of assets, including handling and information stockpiling to worldwide isolated machines and other savvy electronic gadgets. This rational model backings pervasive, on-request admittance to a common pool of configurable processing assets. Gathering confirmation, in its array offers certain indispensable pain points which incorporate successful access control, secure record access/move among bunch member(s), expansion/repudiation of gathering member(s) without rehashed age of new keys and conservation of gathering/information classification in a unique cloud-based situation. Due to the previously mentioned requirements, bunch confirmation actually stays a field not completely investigated and subsequently, presents a considerable exploration issue to build up a gathering verification protocol (we call it as GAP) in a powerful cloud condition. This makes the framework autonomous of encryption/unscrambling keys. Besides, the client isn't bothered in recollecting difficult gathering confirmation subtleties. The login cycle, thus, depends on the everyday movement of each gathering part inside the gathering.
Optimization of Filter and Operational Amplifier Based on Evolutionary Strategy

Abstract Optimization of analog circuits relies on engineers’ experience and intuition to find suitable parameters to satisfy circuit specifications. This job is highly labor-intensive, highly repetitive, and time-consuming, but the optimized circuit is sub-optimal. In this paper, the evolutionary strategy is proposed to optimize analog circuit design strategy. The filter designed by engineers and operational amplifier with random generated instances’ parameters are included, and the S parameters of the filter and the gain and dynamic power consumption of the operational amplifier are optimized respectively. The simulation results show that the filter and operational amplifier can be further optimized by using the evolutionary strategy. This method can greatly reduce the workload of analog circuit designers, improve the performance of analog circuits and shorten the design cycle.
Selective Image Watermarking through Normalized Principal Components

Image watermarking is one among the preferred solutions to deal with copyright and ownership problems. This paper suggests a watermarking method in the selective blocks of the cover image using covariance analysis. To accomplish watermarking, the cover image blocks and the watermark (WM) scrambles are selected with the same spatial resolution. The Pearson correlation is calculated between each block of the cover image and the WM scrambles obtained using Arnold transform. Five pairs of cover image block and WM scramble with maximum correlation are selected for watermark embedding process. During the extraction steps, five different scrambles of the watermark are extracted from five embedded blocks of the cover image. Watermark embedding is implemented using normalized principal components based discrete wavelet transform-singular value decomposition watermarking scheme and the Arnold transform is used to obtain the scrambles of the WM. The performance of the proposed watermarking technique is analysed by the metrics evaluated on embedding and extraction.
Iteration Strategy and its Effect Towards the Performance of Population Based Metaheuristics

Metaheuristics algorithms solve optimization problems by repeating a set of procedures. The algorithms can be categorized based on number of agents, either single agent algorithms which are also known as single solution metaheuristics or multi agents algorithms, also known as population-based metaheuristics. In single solution based algorithms, the steps are executed one by one by the single search agent. However, the sequence of the procedures execution with respect to members of a population becomes an issue in population-based algorithms. This issue is governed by iteration strategy, which affects the flow of information within the population. The effect of iteration strategy is studied here. This is an important issue to be considered when designing a new population- based metaheuristic. Three parent algorithms, namely, particle swarm optimization (PSO), gravitational search algorithm (GSA), and simulated Kalman filter (SKF) are used in this work to find a general pattern of the effect of iteration strategy towards the performance of population-based algorithms. Here, the effect of iteration strategy is studied using the CEC2014's benchmark functions. The finding shows that iteration strategy can influence the performance of an algorithm and the best iteration strategy is unique to its parent algorithm. A researcher developing a new population-based algorithm need to identify the best strategy so that the performance of the algorithm proposed is maximized.
Religious Entrepreneurs and Corporate R&amp;D Investment

This chapter investigates the influence of an entrepreneur’s religious belief on R&D investment and further examines the moderating effect of political connections, extending previous literature about the association between religiosity and the risk-averse tendency of entrepreneurs. This chapter provides strong and consistent evidence to show that: (1) an entrepreneur’s religious belief is significantly negatively associated with corporate R&D investment, validating that religious entrepreneurs are inclined to be risk-averse; (2) the inhibiting effect of an entrepreneur’s religious belief on corporate R&D investment is more pronounced for Western religions than for Eastern religions; (3) political connections attenuate the negative association between an entrepreneur’s religious belief and corporate R&D investment, and further the moderating effect only stands for Eastern religious belief, not for Western religious belief. In addition, the conclusions are still valid after using the propensity score-matching approach to mitigate the potential endogeneity between religious belief and R&D.
Device-Independent Quantum Cryptography

The Chapter is organized as follows. In Sect. 7.1 we introduce the concept of non-local correlations and show how they can be witnessed through a Bell inequality violation. We formalize the definitions of different kinds of correlations in Sect. 7.2. In Sect. 7.3 we link the observation of a Bell violation to the security proof of device-independent (DI) protocols. In Sect. 7.4 we describe the bipartite DIQKD protocol based on the Clauser-Horne-Shimony-Holt (CHSH) inequality and prove its security in Sect. 7.5. In Sect. 7.6 we generalize the security proof technique to a whole class of multiparty DI protocols. We conclude by discussing the suitability of full-correlator Bell inequalities for DICKA and present a multipartite Bell inequality specifically built for the task of DICKA (Sect. 7.7). In the Appendix of this Chapter (Sects. 7.8 and 7.9) we provide additional details on the security proof of the CHSH-based DIQKD protocol.
Space Visualization of Rotating Magnetic Field Using Lissajous Curves

This document depicts Space Visualization of Rotating Magnetic Field using Lissajous Curves. Conducting magnetic measurements usually is cumbersome and tiring. These difficulties in conducting magnetic measurements can be overcome by designing an analogy between Magnetic Field and Electric Field and exploiting it since Electric Field can be measured easily. We have proposed a method by which we can visualize the Rotating Magnetic Field (RMF) produced in an induction motor on the screen of a 2-channel CRO using Lissajous Patterns, by exploiting the fact that magnetic fields and the current producing them have a definite relationship.
Viewpoint-agnostic Image Rendering

Rendering an any-viewpoint image is extremely difficult for Generative Adversarial Networks. This is because conventional GANs do not understand 3D information under-lying a given viewpoint image such as an object shape and relationship between viewpoint and objects in 3D space. In this paper, we present how to perform a Viewpoint-Agnostic Image Rendering (VAIR), equipping a conditional GAN with a mechanism to reconstruct 3D information of the input view. VAIR realizes any-viewpoint image generation by manipulating a viewpoint in 3D space where the reconstructed instance shape is arranged. In addition, we convert the reconstructed 3D shape into a 2D representation for image-based conditional GAN, while preserving detail 3D information. The representation consists of a depth image and 2D semantic keypoint images, which are obtained by rendering the shape from a viewpoint. In the experiment, we evaluate using a CUB-200-2011 dataset, which contains few-samples biased a viewpoint such that covers only part of the target appearance. As a result, our VAIR clearly renders an any-viewpoint image.
Heuristic Algorithm for Cooperative Motion Planning &amp; Controlling of Unmanned Surface Vehicles

Abstract From the past decades autonomous technology is growing significantly in all applications. In Marine applications, Unmanned Surface Vehicles (USV’s) is emerging research technology. For this research mobile robotics motion, path planning technologies are adopted and extended. The objective of this paper finds out the shortest route and Collision free path between the two points at the dynamic environment in moving time using the proposed modified A* algorithm. The simulation of the proposed algorithm is using python - OpenCV.
Computation of Solar Reflections from Photovoltaic Arrays

As photovoltaic (PV) arrays near transportation pathways and installations in urban areas continue to grow, concern arises about how solar reflections may distract people with potentially dangerous consequences. We demonstrate a method to calculate sunlight reflections as a function of date, time, and location dependent solar positions, and given PV module orientation. Mathematical methods have been used to study reflections, with numerous methods available to calculate reflections under various circumstances. Here, tools within the pvlib-python package were used to generate angles for the Sun's path, in order to calculate reflections in terms of elevation and azimuth angles, common measurements to the field of PV array design and analysis.