Reviewerly/exHarmony huggingface dataset:
Assessing Impact of PV Systems on Centralised Generation

In response to climate change concerns, most of the industrialized countries have committed in recent years to increase their share of Renewable Energy Sources (RES), in order to reduce greenhouse gas emissions. Therefore, the rapid deployment of small-scale photovoltaic (PV) systems, mainly in residential applications, is starting to represent a considerable portion of the available electrical power generation and, for this reason the stochastic and intermittent nature of these systems is impacting on the operation of centralized resources. Network operators are constantly changing their approach to both short-term and long-term forecasting activities due to the higher complexity of the scenario in which more and more stakeholders have active roles in the network. The scope of this paper is to create a model to evaluate the impact of generation from aggregated rooftop PV systems along with a model to simulate future contributions. The model is developed in MATLAB and the methodology used is based on statistical assumptions concerning the available details about PV systems installed.
Burst-Mode Optical-Clock-Pulse Generator with Enhanced Sensitivity

The feasibility of a burst-mode optical-clock-pulse generator that demands of peak input optical power for setting the timing of generated clock pulse is shown and error-free label recognition is demonstrated with it.
Comparative Analysis of Gaudy Booch and Ivar Jacobson Methods in Mercu Buana Mobile Application Database Design

Abstract Attendance, presence, or attendance recording is very important for every lecture, office or other organizational activities. Currently, recording student attendance activities at Mercu Buana University is by calling one by one the students by the lecturer, then the lecturer signs attendance on the special application form for lecturers that have been provided. For this reason, it is necessary to design a database to create the database. The analysis used is SWOT to compare between Gaudy Booch and Ivan Jacobson methods. This comparison is used to find out which method is appropriate in implementing a better database. Based on the database design that is made to further facilitate archiving of attendance, increase data efficiency. From the results of the research with class diagram description objects, the class diagram and database model that we use is from Ivar Jacobson, because it shows how actors from class diagrams point to Object-Oriented Software Engineering that has advantages that are easy to learn and have notation simpler.
Validity and Reliability of the Problem-Based High School Teaching Materials of Physics using Android

Abstract The very rapid development of information and communication technology has such a broad influence including education. Educators as the main actors in formal education are required to be able to utilize the development of information and communication technology to support the learning process undertaken. The learning model with classical media applied by the teacher so far has not broadly developed a high level of thinking. This classical model results in the ability of students to evaluate whose capability to develop is unsatisfactory. Starting from this consideration, this research was conducted with the aim of knowing the validity and reliability of problem-based high school teaching materials of physics using Android and of improving the ability of students to evaluate such teaching materials. This development research was carried out by adopting the ADDIE (Analysis, Design, Development, Implementation, and Evaluation) model. Data collection was done using validation sheets, observation sheets, questionnaires, and tests. The results showed that problem-based high school teaching materials of physics using Android were valid with a total average score of 3.44 and with the percentage agreement (PA) level of 89.52%. The teaching materials are also able to improve the ability of students in evaluating in the improvement category medium with an N- gain value of 0.359.
Boosting Correlation Filter Based Tracking Using Multi Convolutional Features

Correlation filter based tracking algorithms have been commonly used in object tracking community. Recently, hand-craft features are replaced by deep convolutional features pre-trained on lager scale image datasets. The low level features with high resolution can locate the position of targets more accurate while the high level features contain more semantic information. In this paper, we construct several single conv-feature correlation filters as weak classifiers. Then, we apply boosting learning method to train a multi conv-features tracker for combining both high resolution features and semantic features. The boosting learner assigns adaptive weights for weak classifiers and the position of target is estimated by the adaptive weighted response map. Experimental results on comprehensive dataset OTB2013 demonstrate that our tracking algorithm can achieve accurate and robust performance compared with baselines and other state-of-art trackers.
Streaming Machine Learning For Real-Time Gas Concentration Prediction

The monitoring data of the gas in coal mines are characterized by the streaming big data, because of the development of the Internet of Things. To accurately and dynamically predict the gas concentration, and improve the accuracy of the risk prediction of gas outburst, first, we established a model based on the streaming data to predict the gas concentration, using the streaming machine learning algorithm. This model was proposed based on the principal component analysis and the streaming linear regression method. In addition, we proposed a prototype system which supports iterative prediction model refreshment for live data streams for the real-time prediction of gas concentration, using the Spark Streaming. Moreover, the experimental results show that the update cycle of the model was 45s. Therefore, this system, based on the streaming machine learning can properly predict the real-time gas concentration.
Mobile Application Development of Food Additive Calculation for Meat Products

Food additives are used in meat products for food safety, shelf life and food technology reasons. The types and levels of food additives used in processed meats must comply with the state regulations in order to process safe foods for human consumption. Food additive calculator which is a web-based version, provided by The Thai Food and Drug Administration to help the producers in calculating maximum use level of food additives for all kinds of foods including meats, is found too complicated for small entrepreneurs with inadequate knowledge. Web-based version is also not responsive design and display to users view and is not mobile user oriented. Therefore, this research was aimed to develop a user friendly and convenient mobile application on Android Mobile Operating System for calculating maximum permitted level of food additives used for meat products. This mobile application is designed for calculating four kinds of food additives widely used in ten different favorite meat products. The application gives a correct results of maximum level of each food additives based on the type and weight of meat products. Therefore, this application may be beneficial to reduce the health risk from food additive abuse in meat products.
A Real-Time Precise Vision Measurement Method for Thin Material Tensile Tests at Full Strain-Rates

Vision measurement has extensive potential applications in the thin material stress-strain tests. The traditional single vision measurement methods of sub-pixel location based on feature extraction (FE) or digital image correlation (DIC) are defective in their full strain-rate ranges. FE exhibits a satisfactory stability at dynamic strain-rates, but yields a low accuracy because of the imprecise artificial mark, especially for materials with a rough surface texture. DIC, on the other hand, requires time-consuming computation, and exhibits an unstable accuracy at a high strain-rate because an increasing deformation can decrease the correlation of pixel subsets. To address these issues, a real-time precise measurement method combining DIC and FE is presented for thin material tensile tests, which can satisfy the test requirements region-by-region in the full strain-rate ranges. To reduce the effect of imaging distortion, a projection model based on the local sub-plane mapping was designed. Real experiments and analyses were performed to evaluate the performance the proposed method. The results showed that this method yields an improved performance at dynamic strain-rates.
Statistical inference for Functional data: two sample Behrens-Fisher problem

With modern technology development, functional data analysis (FDA) has received considerable recent attention in many scientific fields. The estimation of mean in FDA is of interest, because it is not only important by itself but it is a prelude to other issues such as dimension reduction and modeling of functional dataIn this paper we construct a two-sample Behrens-Fisher problem when data are functions and obtain the asymptotic properties of the test statistic as data dimension increases with the sample size. The power of the proposed test is also investigated.The proposed test used for inference about the differences in the mean temperature functions of the Western and the South-western weather stations of Iran.
Performance Prediction of Multichannel Coherence Detector for Sonar Imagery

This paper addresses the problem of performance prediction and estimation for a multichannel coherence detector. The saddlepoint approximation is employed to approximate the empirical null distribution of the test statistics for the purpose of predicting the false alarm performance. The ability of the proposed method to achieve a prescribed false alarm rate is then examined for different background conditions using a Synthetic Aperture Sonar (SAS) imagery dataset.
Statistical Analysis in System Evaluation of ilearning Media With Mccall’s Quality Model

Abstract Evaluation of the system regarding user participation and satisfaction will affect the success of the system implementation, where user participation can improve information system performance. In practice of evaluation, there must be a survey through statistical analysis of the system so that in its application can be known system deficiencies and user satisfaction in using information system services. The application of the business intelligence concept in this iLearning class is very felt in the decision support process and it can be felt directly by students without any further guidance from educators. This research aims to determine the results of the evaluation of the system implementation that has been running in order to know the validity and reliability test. The method used in this research is the statistical analysis approach with McCall’s quality model. The data retrieval process by distributing questionnaires to the class which is used as a sampling of the total population of classes in SMK Al Fattah. This research aims to find out empirical data about the implementation of the iLearning Media system at the vocational high school level with the approach of McCall’s quality model.
De-noising of medical images using iterated hybrid filters

The medical images like ultrasound, CT scan and MRI are captured by different medical devices which contain Gaussian noise. These Gaussian noises reduce the image quality and information. This paper proposes a de-noising algorithm, iterated hybrid filtering techniques, for the removal of speckle noise from medical images. The performance of the proposed algorithm is compared with quantitative measures such as RMSE and PSNR values.
Non-linear Observer Design for Ship Based on Covariance fitting for square-root cubature Kalman Filter

A square-roots Kalman filter nonlinear observer in view of covariance fitting is proposed for the data adaptive problem of square-roots Kalman filter. Based on the Kalman filter, the covariance fitting for square-roots cubature Kalman filter and the square-roots cubature Kalman filter is introduced. In addition, this algorithm is applied to the non-linear observer of ship's dynamic positioning system. The analysis of simulation result prove the validity of the covariance fitting for square-root cubature Kalman filter.
Intelligent Control of an Exoskeleton for Rehabilitation Purposes Using a ROS-Based Software Architecture

This paper describes an open-source software architecture that allows an exoskeleton to be remotely used for rehabilitation purposes. The exoskeleton can be controlled through a Natural User Interface (NUI), which directly records the therapist’s legs motion, from which, the input references that should be sent to the exoskeleton are calculated. The proposed architecture consists of a set of interconnected components, running independently, which use a middleware for transparently sharing information. In particular, a set of software components, executed as ROS nodes, solve the problems related to hardware issues and control strategies. An early prototype of the system has been tested and results are shown in this paper, together with a discussion about the advantages and disadvantages of the system.
Visual Tracking Via Siamese Network With Global Similarity

Visual tracking is a very important and challenging problem in the field of computer vision. In recent years, Siamese networks have been widely used for visual tracking due to their fast tracking speed, but many trackers based on Siamese network train their networks by utilizing either pairwise loss or triplet loss, which easily leads to over-fitting. In addition, it is difficult to distinguish some hard samples in the training samples. In this paper, we propose a novel global similarity loss to train the network. Specifically, we utilize two Gaussian distributions to simulate and optimize the distribution of positive and negative samples in the train set and add constraint on the hard samples. In experiments, without any other modification, we apply the proposed method to the Siamese network. And the results on several popular tracking benchmarks show our method achieves superior tracking performance than the baseline.
Gicoface: Global Information-Based Cosine Optimal Loss for Deep Face Recognition

Loss function plays an important role in CNNs. However, the recent loss functions either do not apply weight and feature normalisation or do not explicitly follow the two targets of improving discriminative ability: minimising intra-class variance and maximising inter-class variance. Besides, all of them consider only the feedback information from the current mini-batch instead of the distribution information from the whole training set. In this paper, we propose a novel loss function - Global Information-based Cosine Optimal loss (Gico loss). Gico loss is applied with weight and feature normalisation, designed explicitly following the aforementioned two targets of improving discriminative ability, and is guided by the distribution information from the whole training set. Extensive experiments are conducted on multiple public datasets, which confirms the effectiveness of the proposed Gico loss and shows that we achieve state-of-the-art performance.
Toward Creative Convergence

In South Korea, the recently revised national curriculum is not irrelevant to the trend of global education reform, which focuses on competency-based education, creative convergence, and free learning semester system. In this light, the purpose of this study is to present a convergence education model by integrating STEAM, and creative problem solving (CPS) approach as a learning method, which is coined CPS-based STEAM. Following the principles and process of the creative convergence model, a series of the instructional module was developed and applied to a 7th-grade classroom of free learning semester in a middle school, South Korea. After completing 15 units of CPS-base STEAM class, students' reflection journals were analyzed with Atlas.Ti. Results show that while participating 'making an ecological map of our schoolyard' project students were able to cultivate consilience thinking by converging knowledge, attitude, and skill of science, technology, engineering, arts, and mathematics. Also, they were able to actively explore and solve problems in the real world.
Passage of fractal signals via circuit with a ferroelectric capacitor with a negative capacitance

In the report presented, the results of synthesis of two of the newest scientific areas, namely integrated ferroelectrics and fractal radio systems, have been shown on the simplest example. For this goal, the numerically analytical method for an approximate solution of the equation for the electric charge value on a ferroelectric capacitor with negative capacitance connected to a fractal voltage source through a series resistor has been developed. This method combines the regularisation of the input fractal signal (voltage), decomposition of obtained fractal voltage by means of Haar wavelets using the Mallat algorithm, and matching of analytical expressions for charge at the constant input voltage. The accuracy of the method proposed and change of the fractal dimension of voltage before and after schemes mentioned have been discussed.
Referenceless Quality Assessment for Contrast Distorted Image Using Hybrid Features

Contrast distortion has a significant influence on the perceptual quality of an image, which may be generated in various image processing procedures. In this paper, we propose a no-reference image quality assessment (IQA) algorithm for contrast-distorted images based on hybrid features from information and appearance attributes. From information attribute aspect, we utilize the basic information feature to quantify the information of the visible part and the extended information feature further containing the invisible part of an image. From the appearance aspect, we propose an efficient perceptual contrast and colorfulness index to capture the direct visual changes. With the hybrid information attribute and appearance attribute features, support vector regression (SVR) is utilized to learn an IQA model to predict the quality of contrast distorted images. Extensive experimental results on CCID2014 and TID2013 databases further demonstrate the superior performance and robustness of the proposed method.
Object-Oriented Programming Robot Refactoring and Its Effectiveness Estimation

Robots are controlled by programs including object-oriented. Time-to-time object-oriented programs need to be refactored in different ways. For example, the use of the switch statement is not good practice in programming, since it complicates program maintenance. It is therefore necessary to discover better alternative to it and how to refactor it to the alternative. Alternatives are the if statement and Java enum. The known approaches are not scientifically justified and do not estimate effectiveness. It introduces the criteria of comparison and metrics, measuring proximity to this one. It measures common modification actions with the switch statement and its alternatives by metrics and compare. These actions are to add new the switch statement with the same set of values, to add and to delete a case and a value of the switch statement. Actions for switch consist basically in changing methods with the switch statement. Actions for Java enum consist of adding methods, but not in changing them. So, it estimates the effectiveness of switch refactoring and concludes Java enum is a better alternative to the switch statement.
Experiencing Materialized Reading: Individuals’ Encounters with Books

Abstract In the past few years, the materials of which objects are made of have increasingly gained attention, particularly in relation to the design and usage of computational objects. Different kinds of materialities have been investigated, discussed, and attentively designed. In order to contribute knowledge on how the materiality of things influences how individuals experience (im-)material artefacts, this paper presents an inquiry into two independent debates on Twitter about whether or not consuming alternative material representations of books (audiobooks or ebooks) “count as” reading. Our findings indicate that experiential aspects of the material instantiations of books are of high relevance and that individuals show strong emotional and reflective responses about them. We discuss several aspects of materialized reading and conclude by detailing how the findings may influence (research on) the design of future books.
Diverse Demands Estimation and Ranking Based on User Behaviors

In the big data era, users can get massive information from the Internet, but the value density is very low. In order to help users find the information they need more quickly, this paper presents the mechanism of diverse demands estimation and ranking based on user behaviors. Firstly, a definition of classification system for users query intent is proposed. Secondly, in order to mine the documents on the websites of specific classification, LDA model is used to cluster and annotate the websites. To speed up the inference process of LDA, we take advantage of MPI and OpenMP hybrid parallelism techniques to reduce both internode and intra-node communication cost. Lastly, according to the historical behaviors of users and the search engine return results, we rank the classifications on Map-Reduce platform and present the top-ranking ones to users
Opportunities and Challenges of E-Book Readers and Mobile Devices in Libraries

There is a common saying that “books are the windows to the world.” Despite the fact that in this digital age the leading role is taken by the internet, books still play their part as openings to the vast knowledge. It is no longer news that changes have been brought to the book world due to the development in modern technology. As we have printed contents, so also are digital version of books or e-books which can be read on any digital devices with e-book reader applications installed. This development enables people to have a library in their pockets. This chapter examines the experience of Nigeria and the utilization of mobile devices, libraries, e-book readers, and mobile devices for reading. This chapter will also discuss the future potential of mobile applications in libraries and opportunities associated with e-book readers and mobile devices. This chapter also identifies the challenges associated with the use of e-book readers and mobile devices and the way forward towards promoting the use of e-book readers and mobile devices for reading in Nigeria.
Creation of a Distributed NoSQL Database with Distributed Hash Tables

Databases are an essential tool in the real world. Traditionally, the relational model and centralized architectures have been used mostly. However, with the growth of the Internet in recent decades, both in the number of users and in the amount of information, the use of decentralized architectures and alternative database models to the relational model has been extended, which receive the name of NoSQL (Not only Structured Query Language) databases. With the present end of degree work, the development of a distributed NoSQL database is proposed, which will try to achieve high availability and high scalability through a decentralized architecture based on DHT (Distributed Hash Tables).
Cloud Service Brokerage

The objective of this chapter is to introduce the reader to the basics of cloud service brokerageCloud Service Brokerage (CSB) (CSB). By the end of this chapter the reader should have a fair understanding of CSB, the reasons enterprises need CSB, its typical capabilities, and architecture.