Reviewerly/exHarmony huggingface dataset:
Dual Axis Solar Tracking System with Data Logger

Solar photoelectric technology is one of the most eminence resources of sustainable energy. However, the contemporary solar photoelectric system has consequential hindrance, such as high cost compared to fossil fuel energy resources, intermittency and low efficiency.  Apprehending maximal energy from the sun by using photoelectric system is formidable. Various aspects that influence the energy yield of such system comprises of photoelectric material, geographical position of solar illumination, angle of sun prevalence, weather and ambient temperature, orientation of the panel. Photovoltaic panels are used to convert the sun’s radiation to electrical energy, but since these cells are placed at a fixed angle, the efficiency is low so has to overcome this, we go with the tracking system. In this paper, dual axis solar tracking system with data logger is been implemented. Hardware part includes solar panel, LDR’s, two geared DC motors, resistors, transistor, relays etc, and  the software part has an Arduino programming used for tracking system and  for logging the voltage and current column.
Protection of the Result of Intellectual Activity in the Form of a Visual Work, Industrial Image, Design: Legislation and Practice of its Application

The article discusses the features of protection of such objects as a artwork, industrial design and design. The author notes that in the form of these objects, the same result of intellectual activity can be protected for which the connection of the content of the result with its expression in a materialized form is inseparable. The same result can be protected by copyright and patent law if there are certain conditions: the ability to characterize the result with «individualizing characteristics». Analyzing the legislation and judicial practice, the author found that the «individualizing characteristics» of the work, which the court establishes in the case of a dispute, are a manifestation of the form of the work. Copyright protects the form of the artwork. In the case of protection of such a artwork as an industrial design, «individualizing characteristics» are called essential features of an industrial design and characterize its content, since an industrial design is a solution of appearance, which is subject to protection. The author of the article comes to the conclusion that there is no sufficiently unambiguous definition of the result of intellectual activity and the elements that characterize it as an object of law: content and form.
Olympiad potential for identifying mathematical giftedness in elementary schoolers

The purpose of this article is to demonstrate the possibilities of identifying the mathematical giftedness in elementary schoolers with the help of Olympiad problems. For this, the authors clarify the concept of “mathematical giftedness”, show the relationship between the concepts of “mathematical giftedness” and “mathematical abilities”, and indicate the most significant abilities of elementary schoolers from the set of mathematical giftedness. The role of mathematical Olympiads in identifying mathematically gifted elementary schoolers is substantiated. This role consists in creating situations where the participants of the Olympiad are forced to make mental efforts to perform the following actions: analysis of a problem situation to identify essential relationships, modeling a new way of action to solve the proposed problem, combining available methods of action to apply in a new situation in limited time. The criteria for compiling Olympiad tasks for identifying mathematically gifted students are formulated, the most important of which is the clear focus of each task on demonstrating a mathematical ability of a certain type, as well as the selection of the mathematical content of the Olympiad problems strictly from the elementary course of mathematics. The problems of one Olympiad should be based on the content of different sections of the elementary mathematics course. The examples of the Olympiad problems based on the content of the elementary mathematics course are provided and the substantiation of their role in demonstrating the mathematical abilities of the Olympiad participant in solving them is given. The results of observing the educational achievements of students (during their entire stay at school) who showed mathematical abilities at the Olympiads are provided as well as the prospects and certain difficulties of further research on ways to solve the problem.
A Survey on Automatic Recognition of Fake Indian Currency Note

The Currency Recognition System was developed for the purpose of fraud detection in paper currency, so this system is u sed worldwide. The uses of this framework can be recognized in banking frameworks, cash observing gadgets, cash trade frameworks. This paper proposes an automatic paper currency recognition system through an application developed using Machine learning Algorithms. The algorithm implemented is simple, robust and efficient.
3D reconstruction from coded plenoptic sampling: 3D reconstruction from coded plenoptic sampling: Three-dimensional reconstruction from coded plenoptic sampling

The plenoptic function describes a scene in terms of light rays, it is a 7-dimensional function with spectral, directional, spatial, and temporal variation. Traditional plenoptic sampling is acquired either by employing a standard plenoptic camera or a camera array, andthe spatial-angular sampling can be potentially used to model 3D surface. ☐ In this dissertation, I present three coded plenoptic sampling schemes, i.e., the rotational cross-slit (R-XSlit) plenoptic sampling, the wavelength coded plenoptic sampling, and the polarimetric plenoptic sampling. The additional coded sampling information, suchas non-centric sampling, spectral sampling, and polarization sampling, are conducive to 3D reconstruction. Therefore, I also develop the corresponding 3D reconstruction framework for each of them. ☐ First, I introduce the R-XSlit plenoptic sampling scheme by exploiting a special noncentric camera called the crossed-slit or XSlit camera. An XSlit camera acquires rays that simultaneously pass through two oblique slits. I show that instead of translating the cameraas in the pinhole case, we can effectively sample the 4D plenoptic sampling by rotating individual or both slits while keeping the camera fixed, which makes the plenoptic sampling coded in the spatial-angular domain. The theoretical analysis shows that it provides denser spatial-angular sampling, which is beneficial for scene reconstruction and rendering. I develop a volumetric reconstruction scheme for scene reconstruction. ☐ Second, I present two wavelength coded plenoptic sampling schemes in the visible and infrared spectrum respectively. I firstly design a compact system with lights and cameras arranged on concentric circles to acquire a concentric wavelength coded plenoptic samplingin the visible spectrum, the cameras on each ring capture images in a unique spectrum. I employ the Phong dichromatic model onto its plenoptic function for 3D reconstruction and spectral reflectance map estimation. Experiments show that our technique can achieve high accuracy and robustness in geometry recovery. Moreover, I present an infrared wavelength coded plenoptic sampling and develop a hybrid sensing framework to efficiently achieve pose estimation and face reconstruction by exploiting the captured reflected infrared raysfrom human eyes. ☐ Finally, I present a polarimetric plenoptic sampling framework for recovering 3D surfaces, the polarization of light is included in its plenoptic function. I employ a new analysis analogous to the optical flow to correlate the polarization radiance function with both surface normal and depth. The proposed framework effectively resolves the azimuth-zenith ambiguity by forming an over-determined system. Extensive experiments on both synthetic and real data demonstrate that the technique is capable of recovering extremely challenging glossy and textureless objects.
A Master-slave Multi-chain Hierarchical Cross-chain Model Based on Credit Voting Consensus

This paper proposes a consensus algorithm based on the credit voting mechanism, which introduces the voting mechanism to decide the ownership of the accounting privilege, avoids the competition of the computation power among nodes, and makes all nodes in the system get the accounting privilege fairly. By assigning credit value to nodes, the influence of equity on the system can be reduced. Meanwhile, quantitative evaluation on the behavior of nodes can better prevent nodes conducting malicious behaviors. Based on PoVT, we propose a master-slave multi-chain layered cross-chain model, and conduct experiments to evaluate the performance. The results show that the efficiency of the system is improved, and the system has a certain defense capability against attack methods such as double spending attack, selfish mining, nothing-at-stake attack.
Open Problem: Are all VC classes learnable with computable learners?

The independence from set theory of learnability results ([Ben-David et al. 2017, 2019]), motivated us to consider learnability by algorithms with computable output predictors (both learners and predictors are then representable as finite objects). In [Agrawal et al 2020] we introduced the notion of CPAC learnability, by adding some basic computability requirements into a PAC learning framework. As a first step we have shown there that, in contrast with the well studied case of learnability without such restrictions, in this framework proper learnability of hypothesis classes is not implied by the finiteness of their VC-dimension. A major remaining open question is whether a similar result holds even for improper learning. Namely, does there exist a computable concept class of finite VC-dimension (of computable classifiers) such that no computable learner can PAC learn it (even if the learner is not restricted tooutput a hypothesis that is a member of the class)?
Applying Human Interaction to Human-Computer Interface Design

This paper examines interactional data drawn from human-computer interface that was developed by computer engineers. A total of 1,860 cases of conversational exchanges were collected from 62 participants who interacted with service bots in three domains (Schedule, Contact and Weather). The research followed the principle of conversation analysis (CA) by tracing line-by-line progression of interactional exchanges. The analysis produced 19 different categories of codes through a qualitative research from which three most common problems emerged. The finding offers a useful insight into some notable challenges in developing dialog systems that are to interact with human participants. Since the findings are drawn from methodological approaches in social sciences, they provide somewhat different solutions to engineering problems in human-computer interface. The manuscript also includes introductory descriptions of the four papers that are published in this special volumes on human-computer interaction.
SECURE AND ENERGY AWARE TASK SCHEDULING IN CLOUD USING DEEP LEARNING AND CRYPTOGRAPHIC TECHNIQUES

Cloud Computing is one amid emerging technology greatly necessitated aiding computing on demand services by letting users for subsequent pay-per-use-on-demand scheme. The service cloud providers have non insignificant impacts on ideal resources exploitation and cost benefit in case of Energy aware task scheduling in cloud. Presently Minimum Migration Time (MMT) policy was employed for Virtual Machines migration and offering an energy proficient cloud service. Nonetheless prevailing methodologies never concentrated on any security for cloud. The confidential data protection is highly demanded now-a-days due to increasing users for cloud computing. Hence robust security system for cloud computing is greatly demanded by various cloud researchers. An enhanced approach is presented for mitigating these concerns in which Artificial Bee Colony Optimization (ABC) is deployed for queuing all incoming tasks into multi-level. Shortest-Job-First (SJF) buffering and Min-Min Best Fit (MMBF) scheduling algorithms are checked initially. The SJF buffering and Extreme Learning Machine (ELM)-based scheduling algorithms integration is done for evading job starva¬tion probability in SJF-MMBF. The over utilized host detection is achieved through Adaptive Neuro Fuzzy Inference System (ANFIS) and Virtual Machines (VMs) migration is attained via Minimum Migration Time (MMT) policy from over-utilized hosts to other hosts for energy consumption reduction. Also, security in cloud is greatly achieved by presenting a novel cryptographic technique. There are several advantages such as sharing hardware, software and losing data fear deficiency and due to which current demand for cloud computing is greatly necessitated. The significant information on cloud is maintained by business person, hence data security is vital concern as there is hacking and unauthorized access probability. Here cloud data encryption is attained through elliptic curve cryptography, hence successful and secure storage on cloud is accomplished thereby. The authorized user might access cloud data via key in the suggested system.
SPAM: Electronic Advertisement Tool in Information Sector

Usually, e-mails spammers search for economic income by promoting services and products. Performing mail bombing is neither difficult nor expensive. If appropriately used, internet advertising can be appealing to consumers and cost-effective to advertisers. The purpose of most spam e-mail messages distributed over the Internet today is to entice the recipients into visiting World-Wide sites advertised through spam. E-mail spamming is a campaign that broadcasts in the Information sector at a massive scale and a minimum cost for the advertisers and those advertised.The characteristics of spam-advertised websites, however, have not been widely examined. This paper will explore the properties of URL dissemination through spam e-mail and how the spammer in the information sector received the e-mail addresses and sends this advertisement to the user. Ultimately, dealing with Internet advertising is like dealing with any other type of advertising is discussed.
Users’ Responses to a Non-processing Message by a Dialogue System: HCI

The present research examines users’ various and sequential understanding of a non-processing message “There is no schedule that meets the condition” by a voice dialogue system. While prior HCI research on Korean voice dialogue systems focuses on recognizing users’ intentions better but pays little attention to how users understand system’s messages sequentially. The lopsided take results from a deficient orientation to user-repairs for a communication breaks down. Therefore, the paper tries to add an interpretative value on different and sequential user-repair according to their understanding of the non-processing message. The finding of 7 dialogues between the system and users shows that the users interpret its negative response differently and sequentially from non-repairable to repairable. The different interpretations result from attributing its communicative failure to a system’s poor recognition of users’ whole speech or of their certain word or phrase. These attributions are utilized through users’ distinctive and contingent choices of user-repair, leading to their employment of different strategies such as “recipient design.” The present study aims to appeal for a need of conversation analysis as a tool for analyzing human-computer interaction.
Subject Review: Image Encryption Techniques based on Chaotic Systems

The interchange of information over the internet and networks has grown fast.The Digital images occupy an important role in multimedia communications.Images are utilized in a variety of discipline, including biometric authentication, military, medical science; hence, their security become a major concern.The best solution for securing the data (in any form) is encryption.The recent encryption trend is chaos-based encryption.Image encryption approaches based on chaos have essential merits l.This paper surveys various aspects and approaches of chaos maps image encryption like PWLCM (piecewise linear chaotic map), logistic map, skew tent map.Considering security measurements like correlation analysis and keyspace when comparing image encryption techniques that use different chaotic maps.
Optimization of Data Security System Control with CRC (Cyclic Redundancy Check) Algorithm

Authenticity is one of the critical factors in data communication; moreover, making a program implementation design tasked with data security is one solution to determine the authenticity of the data. This application system is designed using Microsoft Visual Studio 2010, WampServer 5.0, ODBC Connector 5.3. This application system is built using the CRC (Cyclic Redundancy Check) algorithm to determine the file's checksum. Thus, the author hopes that the user can find out whether the received file has been modified in the transmission process. to avoid access by unauthorized parties. The method of sending data often has the risk of unwanted changes to the data.
k-Nearest Neighbors by Means of Sequence to Sequence Deep Neural Networks and Memory Networks

k-Nearest Neighbors is one of the most fundamental but effective classification models. In this paper, we propose two families of models built on a sequence to sequence model and a memory network model to mimic the k-Nearest Neighbors model, which generate a sequence of labels, a sequence of out-of-sample feature vectors and a final label for classification, and thus they could also function as oversamplers. We also propose 'out-of-core' versions of our models which assume that only a small portion of data can be loaded into memory. Computational experiments show that our models on structured datasets outperform k-Nearest Neighbors, a feed-forward neural network, XGBoost, lightGBM, random forest and a memory network, due to the fact that our models must produce additional output and not just the label. On image and text datasets, the performance of our model is close to many state-of-the-art deep models. As an oversampler on imbalanced datasets, the sequence to sequence kNN model often outperforms Synthetic Minority Over-sampling Technique and Adaptive Synthetic Sampling.
Rapid Assessment of Building Collapse based on Sequential Dynamic Fusion of Multi-source Disaster Information from News Media

Abstract News media provides time and data guarantee for rapid post-disaster assessment. However, disaster information from news media often suffers from semantic ambiguity and conflicting content, and disaster information changes over time. These characteristics of disaster information seriously affect its application in disaster assessment. How to obtain timely reasonable quantitative disaster assessment results based on this kind of disaster information is the key to making full use of media information, but existing studies rarely have addressed the issue. This paper proposes a novel method to assess the percentage of buildings collapse by leveraging timely disaster information with geographical positions. The method includes four parts. First, based on preprocessing of disaster information, the cloud model is used to quantitatively express fuzzy disaster information and construct basic probability assignments (BPAs) for different ranges of buildings collapse. Second, the conflict and ambiguity of each item of disaster information is analyzed, and its credibility is measured. Based on this, the BPAs are modified to reduce conflicting disaster information. Third, multiple items of disaster information are fused by using Dempster–Shafer theory to obtain buildings damage assessment results. Finally, the assessment results of the previous stage are dynamically updated with new information. The method is applied to Ya'an earthquake on April 20, 2013 and Yi'bin earthquake on June 17, 2019. The assessment results are analyzed and compared with those obtained by other methods, and it is found that the method can obtain reliable results in a short time. This study can provide a reference for timely emergency decision-making.
Durable banknotes strategies and their ability to resist soiling and Dirtiness

Banknotes are widely exchanged for goods and services worldwide. During its circulation, it can get contaminated by money counting machines, atmosphere, dust, soil, storage process or during usage. soiling level is considered the most predominant reason for classifying notes as defective, so soiling reduction should be the first aim of developing more durable banknotes. Many countries begin to apply clean note policy, because it represents the country’s development level in the economy and the culture.This study has performed to compare between Anti – Soiling Banknotes Paper strategy ( Egyptian 10 pounds ), Banknotes Varnishes strategy ( 5 Euro ), Polymer Banknotes strategy ( 10 sterling pounds ) against contaminates. This study recommended that substrate alternative solutions are needed and the Egyptian banknotes substrate has to be converted to one of the strategies that resist, oil, sweat and light, such as polymer banknotes, or it also can be post coated by varnish (conventional – antibacterial) in order to reduce contamination and increase its lifetime
An Experimental Approach for Encryption and Decryption of Image using Canonical Transforms & Scrambling Technique

Data security is a prime objective of various researchers & organizations. Because we have to send the data from one end to another end so it is very much important for the sender that the information will reach to the authorized receiver & with minimum loss in the original data. Data security is required in various fields like banking, defense, medical etc. So our objective here is that how to secure the data. This study is performed on MATLAB R2016b with standard databasegrey scale images like Barbara, Cameraman and Lenna or by using the personalize images in standard format. First of all, the images are scrambled and then the generation of a new complex image took place. Initially phase mask is applied on the complex image by using RPM 1, and then the complex image is encrypted by using LCT of first order. Again the phase mask RPM 2 is applied on the encrypted image followed by the LCT of second order to get the encrypted image finally. Reverse process is applied to get the original image. Various parameters are calculated which shows various aspects. Like Change in the value of MSE with change in order of transform tells the quality of encrypted image. Correlation coefficient of encrypted and decrypted image also shows the difference between the encrypted and decrypted image. The original image is then reconstructed and histogram of all these images analyzed. Robustness and imperceptibility of images increases by the proposed method.
Load Data Lake Storage Gen2 Files into a Synapse Analytics Dedicated SQL Pool

Chapter 4 showed you how to create a dynamic, parameterized, and metadata-driven process to fully load data from an on-premises SQL Server to Azure Data Lake Storage Gen2. This chapter will demonstrate how to fully load all of the snappy compressed parquet data files from ADLS Gen2 into an Azure dedicated SQL pool.