Reviewerly/exHarmony huggingface dataset:
Curve Adjustment Method: Deriving a Formula from a Graph

Audio Engineering, and others technical fields, need more mathematical-based methodologies. There are procedures in studio or live recordings that have not been tabulated yet and depend entirely on human experience and appreciation. Audio engineers whether at studios or live-music settings need tools that allow them to translate their daily personal annotations, rules of thumb, live-music and/or empirical experiments into mathematical expressions or formulas that can benefit the practitioners to get rid of the dependency on the personal and individual appreciation. In this paper, the authors attempt to describe a general procedure to convert any group of into a graph.
Robust robotic visual servoing for uncertain systems

The control of robotic manipulators in unstructured environments is a challenging task. Exploiting the camera images for that purpose, known as visual servoing, offers an interesting solution to the problem. Classic visual servoing techniques were the first attempts towards this goal. However, these methods suffered from system’s shortcomings such as ones imposed by the limited camera’s field of view and the robot’s reachability. Numerous approaches were proposed to overcome these limitations. Nevertheless, most of these techniques assumed full knowledge about the system and did not account for uncertainties. Uncertainties in visual servoing systems are introduced by multiple sources such as camera image noise and robot parameters. The lack of knowledge about system’s parameters may lead to reduced accuracy or even total failure. Adaptive techniques were introduced previously to cope with this matter. However, those techniques were usually useful for deterministic uncertainties (e.g., camera calibration errors). Alternately, robust methods were employed to improve the performance of the system under uncertainties. Yet, those methods were usually conservative and more concerned with the stability of the system, rather than its accuracy. This work proposes three steps towards robust and accurate visual servoing. First, the pose estimation algorithm, used in many visual servoing systems, is revised by introducing novel sensor fusion techniques. Multiple fusion algorithms at different levels of estimation are introduced to enhance the accuracy and robustness of the estimation against system uncertainties. Second, a novel uncertainty estimation technique is presented to approximate the level of uncertainties induced by image noise at different levels of the system. A general approach is used for that matter which has applicability over a wide range of controllers. Finally, multiple constraint-aware and robust controllers with improved stability and numerical feasibility are proposed to enhance the performance of the visual servoing systems in presence of uncertainties. The developed uncertainty model is exploited in robust control design. The effectiveness of each proposed technique is verified through numerous simulations and experiments. As it is expected, the proposed methods are capable of handling the uncertainties and enhancing the accuracy, while accounting for system constraints.
GAN-based Data Mapping for Model Adaptation

Although Machine Learning algorithms are solving tasks of ever-increasing complexity, gathering data and building training sets remains an error prone, costly, and difficult problem. However, reusing knowledge from related previously-solved tasks enables reducing the amount of data required to learn a new task. We here propose a method for learning a mapping model that maps data from a source task with labeled data to a related target task with only unlabeled data. We perform an empirical evaluation showing that our method achieves performance comparable to a model learned directly in the target task.
IoT enable Low-Cost Implementation of Data Center Infrastructure Management System

For any Data Center, environment and equipment monitoring for power and cooling in Data Center is very important.Thus, all Data Center need monitoring systems to help operators in their works.Currently, each type of equipment has their own monitoring system, provided by that equipment carrier.So, to monitoring whole devices in Data Center, people have to use many separated systems.To solve this issue, we apply IoT technique for connecting all devices into one real-time monitoring system, which help to save server resource and more convenience for operator.
Performance Exploration on Various Document Clustering Techniques with K-Means Family

Clustering performs a important position in numerous fields which include Computer science &amp; packages, facts, pattern reputation, system studying technique and find out dating among the files. Clustering focuses on document clustering, and other related area. Increase within the extent of statistics saved in virtual form (text, photograph, audio) has improved the need for requirement of an automated tool, that allows people to find and manage the records in an efficient way. Usually clustering refer to document clustering technique investigates the documents and find its relation. This paper center of attention on the a range of clustering methods and evaluation its overall performance. This paper also categories the document clustering techniques as three major groups, namely Group K-means, Expectation Maximization and Semantic-based techniques (Hybrid method). Several experiments were conducted to analyse the performance accuracy and Speed.
Modifikasi Kunci Kontak Menggunakan Perintah Suara (Arduino Uno R3) Pada Sepeda Motor

Motorcycles are the most in demand vehicles in Indonesia. The number of users of these two-wheeled vehicles continues to increase every year. However, the increasing number of motor vehicles is also accompanied by increasing crimes against motorcycle users. To solve the problem, it is designed a security tool on motorcycles that can turn motorcycles on and off using voice commands based on arduino uno r3 connected to bluetooth on smartphones. It aims to tackle and reduce the number of crimes against motorcycle users.
REIMAGINING RELATIVITY Transitioning the physical body into a virtual inhabitant

This paper explores the ideas and mechanics through a case study which generated a reimagined means of inhabiting a speculative immersive environment. Currently, many users reside within virtual environments for their own leisure, work, or any other reason desired from short amounts of time to extreme lengths. This paper shows the generation directly relative to the inhabitant, where gravity, orientation, scale, and locomotion is completely dynamic. Details within this paper experiment with the laws and bounds of the virtual space within a real-time game engine where reimagining the way one inhabits space compared to current norms of real-world inhabitation is possible with creativity and applied knowledge. Escher’s lithograph of Relativity is the driving concept explored within this paper beginning with creating gravitational pulls in multiple directions within the immersive virtual reality environment to accommodate various sources of gravity. The result of the case study demonstrated the generation of new virtual relativity laws reimagining how the virtual space is inhabited, in short, omnidirectional flying, gravitation defined by the inhabitant to geometry relationship, controlled local scaling, and populating space with multiple inhabitants in a unique manner.
Examination and Assessment of Different Cryptographic Technique Based On a Variety of Features

Cloud computing provides an administrations such as programming bundle stockpiling, internetwork and equipment these assortments of administrations are given to client. Cloud storage is certainly get to wherever whenever of the information because of cloud is figure in remote area. It utilizes the capacity administration given by the cloud provider. Data isn't verify inside the cloud because of the unapproved client will endeavor to utilization of the non-open information. Along these lines, giving the information security it utilizes the various encryption strategies to protect the information. so inside the anticipated investigation it utilizes the development encryption rule. Inside the development encryption it consolidates 2 very surprising calculations for giving the higher security.
Fault Tolerant - Optimal Resource Allocator for Cloud

Cloud Computing is mainly attracted by people for its unlimited storage space and worldwide accessibility from anywhere and anytime. The data that is stored in the cloud has to be retrieved in a faster manner as well as without any faults. Content Delivery Networks dominates Cyberspace traffic heavily due to its increasing demand. Resource allocation plays a vital role in determining the performance of the cloud. Over allocation leads to wastage which can be used for instances that are running short of resources. This work proposes an optimal resource allocation through Genetic algorithm. They help in increasing the download speed which in turn would be helpful in controlling traffic to greater extent. Recently cloud downloading Services have been emerged, in which cloud storage hoards the user interested content and updates the cloud cache. This process takes place in two modes, server mode and the helper mode. The proposed Resource Allocation Policy can well support the server mode of processing by the way it can increment the download speed with dynamic load balancing and fault tolerance.
Ordinary network systems

Knowing how to manage the losses from water supply networks and how to get to the next level in bettering your system is a major problem and one that is most common in the majority of water companies worldwide. Sometimes water companies set their sights too high and cannot deliver due to non-realistic targets setting. Of course this is considered or seen as a failure within the company or country when it is really just exceeding expectations of what can be delivered.The aim of Improving Water Supply Networks is to assist water companies to identify where they are on the ‘water loss ladder’ and what is required to move to the next level. The book will provide an understanding of what the water companies need to achieve and where they should be aiming for in their efforts to reduce water losses. The book provides useful and practical information on non-revenue water (NRW) issues and solutions enriched with relevant case studies.ISBN: 9781780409191 (paperback)ISBN: 9781780409207 (eBook)
Towards Improving Exploratory Faceted Search Results

Finding information on the web, containing billions of documents, is becoming a serious issue.Search engines (SE) help users find handy information such as videos, text or pictures.For open-ended results, users need to perform queries in order to find enough information about their topic of interest.This can be difficult when huge numbers of relevant and irrelevant results are returned from the queries causing information overload.Certain SEs incorporating visualization allow easy understanding of the documents and often reduce the Information overload issues.Sorting of more relevant results from the less relevant ones is difficult since the former is insufficient.This is obvious when the Web grows and the information therein increases to become larger data repositories.The query and response (lookup) processes are often used by most current SEs.Exploratory Search (ES) can provide open ended search.Therefore, the overall search can be improved by applying the Faceted search (FS), which is one of the features of ES.Studies have mentioned that the overloaded data can be reduced when traditional SEs are replaced with the ES, through their features.The prototype design we are working on is based on the idea of ES engine that can be used to visualize the information when exploring the Web.This concept is aimed at supporting more active means of finding information through coordinated visualizations and reducing large amount of search efforts required per query.The prototype system was evaluated for performance and compared with CloudMining SE.The results show that our prototype gives average improvement of 20% relevant results when compared with CloudMining SE.
PERSEPSI MAHASISWA PERPUSTAKAAN DAN SAINS INFORMASI UNIVERSITAS PENDIDIKAN INDONESIA ANGKATAN 2019 TERHADAP IMPLEMENTASI KODE ETIK PUSTAKAWAN

Starting in 1988, the Indonesian government has authorized the librarian profession to become a functional position. Functional positions are regulated gradually, and finally with the decision of KEMENPAN RB 132/KEP/M.PAN/12/2002 concerning Functional Librarians. As a profession that the state has recognized, librarians must be responsible for all actions both of fellow librarian professions, organizations, and to themselves. Each member of the Indonesian Librarian Association is responsible for implementing the code of ethics in the highest standards for the needs of users, professions, libraries, professional organizations, and the community. Librarians must not only know about the librarian’s code of ethics, but librarians must also implement it. The purpose of this study is to determine the perception of students class of the 2019 library and information science study program on the importance of implementing the librarian code of ethics. Later, it can provide knowledge to libraries, especially in Indonesia about the importance of implementing a librarian code of ethics. The method used in this study is descriptive with a quantitative approach. The results showed that students of library and information science study program class of 2019 Indonesian Educational University strongly agreed to implement the librarian code of ethics according to IPI with results above 85%. The implementation of the code of ethics will impact the library and the librarian for the achievement of the shared goals of the library.
Secure Multiparty Equality Check Based on Homomorphic Cryptosystem

There exist many scenarios where multiple parties jointly work on some common project but these parties are not interested to show actual value of data to each other. Here we propose an algorithm where multiple cooperating but distrustful parties can compare their data for equality without disclosing it to one another. This is an improvement over two party comparison algorithm devised earlier by other researchers. The proposed work is suitable for semi honest adversaries who respect rules of the protocol but somehow try to know private values with other parties.
Edgar Allan Poe Simulators

dgar Allan Poe is one of the few canonical literary authors to have a signifi cant presence in video games.The list of titles inspired by Poe spans three decades of graphic adventure games, from the live-action-based Phantasmagoria (Sierra On-Line, 1995) to Dark Tales: Edgar Allan Poe's Murders in the Rue Morgue (ERS G-Studio, 2009), a puzzle game for mobile platforms.This success is a sign of Poe's enduring popularity within and without the United States; it refl ects the capacity of his work to speak to a broad audience.Mark Neimeyer has explained this popularity by highlighting Poe's "ambiguous position between highbrow and lowbrow culture," which makes "him especially appealing to the general public." 1 Poe himself famously remarked that "The Raven" (1845) was intended to be a poem which would "suit at once the popular and the critical taste." 2 This chapter will approach Poe's work from a different, but complementary, angle.Rather than exploring the extent of Poe's contribution to popular culture, as other scholars have done, 3 I will consider one of the reasons for his lasting appeal and suggest that Poe's short stories, and particularly his classic horror tales, are so effective because they are-to borrow Emily Troscianko's term-"cognitively realistic." 4Troscianko introduces this concept in a book-length study of Kafka's fi ction in which she argues that Kafka's major works recreate
REKAYASA PERANGKAT LUNAK PENGARSIPAN DIGITAL DOKUMEN ACCOUNTING FINANCIAL DENGAN PENDEKAN METODE MVC

In the activities of document interception has an important role in the processing of document archiving in an agency or company and is used in supporting administrative processes or other activities. If the archiving of documents owned is not well managed can lead to difficulty finding the information that has been stored and ultimately can hinder the next stage of the work process. In the practice of paper-based records management, many problems are faced, thus giving space to electronic media as an alternative in archiving management. In archival terminology, electronic media is grouped as a new media archive, one form of storage of new media archives is digital media. Digital media usually requires tools in the form of computers, because it cannot be read directly, can be processed in computer programs and stored in digital data storage media. In This research discussed how to design, implement the system and maintenance and security of documents so as to avoid damage. This Software Engineering was created with MVC approach by using Framwork Codeigniter with the aim of archiving this digital document done to help and prevent a very long process in the storage and search of a document needed in a fast, precise and detailed time
Face Image Super-resolution Based On Relative Average Generative Adversarial Networks

Face image plays an important role in visual perception and various computer vision tasks. However, due to the influence factors of equipment and environment, the image often has the problem of low resolution. In order to relieve this problem, this paper proposes a face image super-resolution reconstruction algorithm based on Relative average Generative Adversarial Networks. Different from the standard discriminator D in Generative Adversarial Networks(GAN), which estimates the probability that one input image is real and natural, a relativistic average discriminator tries to predict on average the probability that a real image is relatively more realistic than a fake one. At the same time, the loss function used to measure the spatial similarity of image pixels is combined with the perceptual loss function used to measure the similarity of image feature spaces, so that the network pays attention to the reconstruction of image pixel information while taking into account the feature information of the image. Experimental results demonstrate the effectiveness of the proposed method in multi-scale face image super-resolution, and the evaluation indicators (PSNR and SSIM) tested on common test sets are better than those of the contrast algorithm, it also has better visual perception and more detailed information.
Big Data Clustering And Its Applications Examination

Clustering is a type of mining process where the data set is categorized into various sub classes. Clustering process is very much essential in classification, grouping, and exploratory pattern of analysis, image segmentation and decision making. And we can explain about the big data as very large data sets which are examined computationally to show techniques and associations and also which is associated to the human behavior and their interactions. Big data is very essential for several organisations but in few cases very complex to store and it is also time saving. Hence one of the ways of overcoming these issues is to develop the many clustering methods, moreover it suffers from the large complexity. Data mining is a type of technique where the useful information is extracted, but the data mining models cannot utilized for the big data because of inherent complexity. The main scope here is to introducing a overview of data clustering divisions for the big data And also explains here few of the related work for it. This survey concentrates on the research of several clustering algorithms which are working basically on the elements of big data. And also the short overview of clustering algorithms which are grouped under partitioning, hierarchical, grid based and model based are seenClustering is major data mining and it is used for analyzing the big data.the problems for applying clustering patterns to big data and also we phase new issues come up with big data
Improving bug report quality by predicting correct component in bug reports

Bugs reported in bug tracking systems contain important information in the form of standard and mandatory fields like version, operating system, product, component and type of the bug, etc. Unfortunately, the information provided in these fields is sometimes missing and inaccurate. Inaccurate information makes the program understanding difficult and inflicts delay in the process of bug fixing. Many times, these fields are reassigned during the bug fixing time even more than ones. This study explores the automatic identification of correct component field in a bug report. This study proposes using fuzzy similarity-based approach for identifying the correct component as well as predicting the possibility of component reassignment. Experimentation is done using bug reports of three open source projects from eclipse. The experimental results show that fuzzy similarity approach performs better as compared to state of art approaches on two out of three datasets in terms of precision score.
Data Mining Algorithm To Predict The Factors for Agricultural Development using Stochastic Model

Data mining is a route of extract patterns from data and it is used to transforms unprocessed collections of data into information. In this paper proposes an efficient factor of agriculture development using different type of agriculture related datasets by adopting stochastic modeling and data mining approaches. Firstly, the novel model and algorithm is proposed to predict the growth of agriculture based on primary and secondary data using stochastic modeling approach. Numerical illustrations and various expected estimations also prove the proposed system approach.
Data Analytics in Health Management System

Large information, a quickly creating theme, has begun to have a crucial influence in the production of medical care exploration and practices. It has enabled people to assemble, put together, examine, or ingest monstrous volumes of heterogeneous, coordinated, and unstructured information made by the present wellbeing frameworks. Large information investigation has as of late been utilized to help with the conveyance of care and infection research. In any case, a few major hardships innate in the huge information worldview keep on preventing acknowledgment and examination extension in this field. We address a portion of these crucial difficulties in this paper, with an emphasis on three arising and entrancing disciplines of clinical science: picture, sign, and age sequencing investigation. The utilization of huge volumes of clinical information while consolidating multimodal information from numerous sources is investigated considering current discoveries. Potential examination subjects in this space that can impact medical care arrangement are likewise assessed.
Cosine Transformation of Image Coordinates for Reduction of Image Loss due to Compression and Decompression

Discrete Cosine Transformation (DCT) is a popular image compression technique, but it is lossy compression because of image losses found after decompression.In order to reduce the loss, a new algorithm with model of Cosine Transformation of Image Coordinates (CTIC) has been proposed.The earlier method with Matlab standard built in function and proposed modelboth have been implemented over 100 Google images.It has been found that CTIC method has much less loss than in the existing DCT method's Matlab built in functions dct2(.)and idct2(.).Also PSNR and Energy Compaction Ratio have been calculated for both the image transformation techniques.