Reviewerly/exHarmony huggingface dataset:
The Use of Gridded Model Output Statistics (GMOS) in Energy Forecasting of a Solar Car

For many years, primary weather forecasting services (Global Forecast System (GFS) and the European Centre for Medium-Range Weather Forecasts (ECMWF)) have been made available to the public through global Numerical Weather Prediction (NWP) models estimating a multitude of general weather variables in a variety of resolutions. Secondary services such as weather experts Meteomatics AG use data and improve the forecasts through various methods. They tailor for the specific needs of customers in the wind and solar power generation sector as well as data scientists, analysts, and meteorologists in all areas of business. These auxiliary services have improved performance and provide reliable data. However, this work extended these auxiliary services to so-called tertiary services in which the weather forecasts were further conditioned for the very niche application environment of mobile solar technology in solar car energy management. The Gridded Model Output Statistics (GMOS) Global Horizontal Irradiance (GHI) model developed in this work utilizes historical data from various ground station locations in South Africa to reduce the mean forecast error of the GHI component. An average Root Mean Square Error (RMSE) improvement of 11.28% was shown across all locations and weather conditions. It was also shown how the incorporation of the GMOS model could have increased the accuracy in regard to the State of Charge (SoC) energy simulation of a solar car during the Sasol Solar Challenge 2018 and the possible range benefits thereof.
The Implementation of Contextual Teaching and Learning on English Grammar Competence

The research was aimed to the effectiveness of Contextual Teaching and Learning (CTL) in teaching grammar. Experimental study of pretest-posttest was used in this research. Non-randomize sampling was used as sampling technique. The validity test was calculated using point biserial correlation, and reliability test was 0.848 which was calculated by using K-R 21 formula. In analyzing the data, researcher used ANCOVA. The result shows that average score of pretest was 60,95 for experimental group and 60,00 for control group. The average score of posttest was 85,95 for experimental group and 78,9 for control group. The calculation of ANCOVA found that the value of F is 8.7 and F critical with df 76 at 0.01 level of significance 6.96. it means that F value was higher the F critical. From the result of data analysis showed that Contextual Teaching and Learning (CTL) gave effect on teaching grammar for 7th grade students of junior high school.
Oversampling for Imbalanced Time Series Data

Many important real-world applications involve time-series data with skeweddistribution. Compared to conventional imbalance learning problems, theclassification of imbalanced time-series data is more challenging due to highdimensionality and high inter-variable correlation. This paper proposes astructure preserving Oversampling method to combat the High-dimensionalImbalanced Time-series classification (OHIT). OHIT first leverages adensity-ratio based shared nearest neighbor clustering algorithm to capture themodes of minority class in high-dimensional space. It then for each modeapplies the shrinkage technique of large-dimensional covariance matrix toobtain accurate and reliable covariance structure. Finally, OHIT generates thestructure-preserving synthetic samples based on multivariate Gaussiandistribution by using the estimated covariance matrices. Experimental resultson several publicly available time-series datasets (including unimodal andmultimodal) demonstrate the superiority of OHIT against the state-of-the-artoversampling algorithms in terms of F1, G-mean, and AUC. The code of OHIT isavailable at github.com/zhutuanfei/OHIT.
Inducing a Target Association between Ordinal Variables by Using a Parametric Copula Family

The need for building and generating statistically dependent random variables arises in various fields of study where simulation has proven to be a useful tool.In this work, we present an approach for constructing ordinal variables with arbitrarily assigned marginal distributions and value of association or correlation, expressed in terms of either Goodman and Kruskal's gamma or Pearson's linear correlation. The approach first constructs a class of bivariate copula-based distributions matching the assigned margins, and then, within this class, identifies the distribution matching the assigned association or correlation, by calibrating the copula parameter. A numerical example and a possible application are illustrated.
A new approach for content-based image retrieval for medical applications using low-level image descriptors

&lt;p&gt;Content based image retrieval (CBIR) has become an important factor in medical imaging research and is obtaining a great success. More applications still need to be developed to get more powerful systems for better image similarity matching, and as a result getting better image retrieval systems. This research focuses on implementing low-level descriptors to maximize the quality of the retrieval of medical images. Such a research is supposed to set a better result in terms of image similarity matching. In this research a system that uses low-level descriptors is introduced. Three descriptors have been developed and applied in an attempt to increase the accuracy of image matching. The final results showed a qualified system in medical images retrieval specially that the low-level image descriptors have not been used yet in the image similarity matching in the medical field.&lt;/p&gt;
Localization of Cyber-Physical Systems: Privacy, Security and Efficiency

We estimate the location of a given target while guaranteeing the privacy of locations and measurements of the observers. Then, we propose three different algorithms to jointly solve time synchronization and localization problems in a distributed fashion. Next, An event-triggered diffusion Kalman filter is proposed. Then, reachability analysis is utilized to establish a security layer providing secure estimate shares for the distributed Kalman filter. Finally, we propose a pointing approach for interacting with devices as an application for accurate localization.
ANALYSIS ON HAND GESTURE RECOGNITION USING ARTIFICIAL NEURAL NETWORK

The main goal of gesture recognition research is to create a system that can recognize specific human gestures and use it to transmit information or to control the device.Human-computer interaction needs to use various methods, such as location, voice, gestures, lip development, facial joints, etc., and coordinate them to provide an increasingly vivid customer experience.The visual interpretation of gestures can be used to complete the natural human-computer interaction.In this article, we propose a method for recognizing gestures.We have designed a system that can recognize specific gestures and use them to transmit information.We have used backward propagation and training algorithms based on supervised feeding neural networks to classify gestures.A neural network program was developed in MATLAB, which can recognize the number of fingers and achieve correct results of 95.4% testing accuracy.An effective and effective gesture recognition method is proposed.The hand area is detected by background subtraction.Then spread your palm and fingers apart to identify your fingers.After recognizing fingers, you can classify gestures with a simple ANN classifier.
Empty nominalization over antonymous juxtaposition/coordination and the emergence of a new syntactic construction

In Japanese, direct combination of verbs or adjectives by coordination (with to 'and') or juxtaposition (with its empty counterpart) can form a NP, if the conjuncts are antonymous to each other; the coordinator to 'and' can combine only NPs elsewhere. We claim that this is because there is a phonetically empty nominalizer that can nominalize each conjunct, and that the new nominal construction has been gradually developing in the history of Japanese. An acceptability-rating experiment targeting 400 participants shows that the younger speakers were likely to judge this construction more acceptable than the older ones, that this tendency is slightly weaker in the Nominative condition than in the Genitive condition, and that the coordination condition was significantly worse than the juxtaposition condition. Dieser Beitrag ist ursprünglich im Peter-Lang-Verlag erschienen (https://www.ingentaconnect.com/contentone/plg/jwf/2020/00000004/00000002/art00002)
Make a Match Learning for English Conversation Skills of Students with Intellectual Disabilities

Background:This research aimed to discover the effectiveness of Make-A-Match model in improving the English conversation skills of students with intellectual disabilities. The participants of this research were 7th-grade students in Class C of SMPLB (Junior High School for Special Needs) JambiMethodology:The data in this applied action research were obtained by using observation, interviews, and notes. This research was conducted in 3 cycles using four steps: planning, acting, observing, and reflecting in each cycle.Findings:The result showed that using the contextual approach to Make-A-Match model was sufficient to improve English conversation skills of students with intellectual disabilities. The students were more active, enthusiastic, and confident in uttering expressions without being anxious about making mistakes because the classroom atmosphere was relaxing and fun. This model also made students worked well together.Conclusion:through this model, the teacher succeeds in encouraging students to apply English in their daily conversation.
An Optimized Cepstral Feature Selection method for Dysfluencies Classification using Tamil Speech Dataset

Speech is the most important and indispensable mode of communication between humans. In communication, the continuous flow of speech gets affected due to the interruption of emotional, panic and psychological factors that cause syllable or word repetition, prolongation and interjection. Speech dysfluency is a primary challenge for speech pathologist to isolate the normal speech from the stuttered speech. The primary objective of this paper is to propose a novel approach through optimized cepstral features selection that improves the classifiers accuracy. In this paper, Particle Swarm Optimization (PSO) and Synergistic Fibroblast Optimization (SFO) were introduced to select optimal features from conventional MFCC (Mel-Frequency Cepstrum Coefficients). The optimized cepstral features from PSO and SFO of pre-processed Tamil speech data is used to discriminate among different categories of speech signals like Normal, Moderate and Sever stutter through machine learning classification methods such as Support Vector Machine (SVM) and Naive Bayes (NB). From the experimental results, the optimal selection of cepstral features using SFO algorithm has achieved high accuracy of 96.08% employed with NB which outperforms well to the feature selection of PSO and classical MFCC. The evaluation of the proposed methodology is done by using performance metrics like sensitivity, specificity, precision, f-score and accuracy.
The comparison of erythrocyte sedimentation rate (ESR) modify Westergren Caretium Xc-A30 and Westergren Manual in Clinical Pathology Laboratory, Sanglah General Hospital, Denpasar, Bali

Â Background: The erythrocyte sedimentation rate (ESR) test is one of the most widely performed laboratory test to assess acute phase of inflammation, infection, autoimmune or malignancy. The reference method for ESR measurement was introduced by Westergren. This method is generally easy, un-expensive, yet, time consuming. Automatic instrument has been introduced to decrease the measurement time. Caretium XC-A30 is automatic instrument to measure ESR; it is used in Sanglah General Hospital Denpasar without previous research. Aim of this study was to assess comparison, correlation and agreement of Caretium XC- A30 to the reference method.Methods: A total of 35 samples in consecutive sampling were taken during August 2018 at Sanglah General Hospital, Denpasar. The samples were examined for ESR with Caretium XC-A30 and manual Westergren. Comparison, correlation and agreement were tested for both methods used.Results: The Westergren method was the reference method and Caretium XC-A30 was the tested method. Wilcoxon signed rank test showed no difference between two methods (p= 0.439). There was a very strong correlation and excellent agreement showed by Spearman coefficient correlation r= 0.989 and kappa coefficient 0.942. Conclusion: This study showed no difference between Caretium XC-A30 and Westergren as the reference method for ESR measurement, with very strong correlation and excellent agreement. Thus, Caretium XC-A30 has a potential use in performing ESR measurement with high throughput and lesser time than manual Westergren method.
An efficient implementation of the Chinese Remainder Theorem in minimally redundant Residue Number System

The Chinese Remainder Theorem (CRT) widely used in many modern computer applications. This paper presents an efficient approach to the calculation of the rank of a number, a principal positional characteristic used in the Residue Number System (RNS). The proposed method does not use large modulo addition operations compared to a straightforward implementation of the CRT algorithm. The rank of a number is equal to a sum of an inexact rank and a two-valued correction factor that only takes on the values 0 or 1. We propose a minimally redundant RNS, which provides low computational complexity of the rank calculation. The effectiveness of the novel method is analyzed concerning conventional non-redundant RNS. Owing to the extension of the residue code, by adding the extra residue modulo 2, the complexity of rank calculation goes down from \(O(k^2)\) to \(O(k)\), where \(k\) equals the number of residues in non-redundant RNS.
Regulatory Issues of Digital Currencies

With the rapid development of the Internet and electronic payment, digital currencies with blockchain as the underlying technology have gradually entered people's horizons and have also received the attention of governments around the world. Due to the convenience and decentralization of digital currency transactions that are not limited by time and region, it has a significant impact on traditional commercial systems around the world, and its core block chain technology may trigger changes in many areas. At present, different countries have different views on the legal status of bitcoin digital currencies, but digital currencies circulate across borders and regions. Once problems arise, it is difficult to have a unified regulatory measure to deal with them.
The Mediating Role of Knowledge Sharing Behavior on the Effect of Person-Organization Fit on Innovative Work Behavior

This study aims to determine the effect of person-organization on fit on innovative work behavior mediated by knowledge sharing behavior. The population in this study were all employees of Ebiz Corporation. The sample size, determined through Slovin formula, and 74 samples were obtained. The sampling technique is convenience sampling. The data analysis method used in this study is path analysis using analytical tools from Preacher – Hayes, The Simple Mediator Model. From the research findings, the knowledge sharing behavior is proven to mediate the effect of person-organization fit on innovative work behavior.
Deep learning based moving object detection for oblique images without future frames

Moving object detection from UAV/aerial images is one of the essential tasks in surveillance systems. However, most of the works did not take account of the characteristics of oblique images. Also, many methods use future frames to detect moving objects in the current frame, which causes delayed detection. In this paper, we propose a deep learning based moving object detection method for oblique images without using future frames. Our network has a CNN (Convolutional Neural Network) architecture with the first and second layer containing sublayers with different kernel sizes. These sublayers play a role in detecting objects with different sizes or speeds, which is very important because objects that are closer to the camera look bigger and faster in oblique images. Our network takes the past five frames registered with respect to the last frame and produces a heatmap prediction for moving objects. Finally, we process a threshold processing to distinguish between object pixels and non-object pixels. We present the experimental results on our dataset. It contains about 15,000 images for training and about 6,000 images for testing with ground truth annotations for moving objects. We demonstrate that our method shows a better performance than some previous works.
Modelling of Twin Rotor MIMO System using Differential Evolution with Success-based Parameter Adaptation

An efficient evolutionary optimization technique has been employed for modelling of a twin rotor MIMO (multi-input-multi-output) system, using black box system identification approach. The modelling problem has been framed as an optimization problem by formulating suitable objective functions. The optimization algorithm aims at determining the optimal set of model parameters by minimizing the deviation between experimental and model data. A comparative analysis has been carried out duly supported by extensive experimentation and simulation results.
Comparison of Pixel-based Position Input and Direct Acceleration Input for Virtual Stick Balancing Tests

A virtual stick balancing environment is developed using a computer mouse as input device. The development process is presented both on the hardware and software level. Two possible concepts are suggested to obtain the acceleration of the input device: discrete differentiation of the cursor position measured in pixels on the screen and by direct measurements via an Inertial Measurement Unit (IMU). The comparison of the inputs is carried out with test measurements using a crank mechanism. The measured signals are compared to the prescribed motion of the mechanism and it is shown that the IMU-based input signal fits better to the prescribed motion than the pixel-based input signal. The pixel-based input can also be applied after additional filtering, but this presents an extra computational delay in the feedback loop.
Structural differences between reaction wood and opposite wood with different drying temperatures

Reaction wood is characterized by having different anatomical and chemical features than normal wood. The different composition of cell walls, the higher quantitative proportion of thick-wall fiber cells, diameter, and the abundance of vessels have remarkable effects on reaction wood’s physical and mechanical properties. Reaction wood has fewer vascular cells. In addition, it has a smaller lumen diameter, which results in reduced permeability. Therefore, reaction wood is more difficult to dry at a certain moisture content. The differences in the drying times of the reaction wood and the normal wood were largest at a temperature of 60 °C and durations greater than 30 h, and the reaction wood dried more slowly. At a temperature of 120 °C, the differences in drying time were minimalized, and drying end times were almost identical. The expected negative effect of higher temperature on the morphology of reaction wood and opposition wood was not confirmed.
Effective Integration of Automatic Word Spacing and Morphological Analysis in Korean

In general, morphological analysis in Korean is performed on a sentence in which word spaces are correctly inserted. To process a sentence that is not correctly spaced, automatic word spacing model should be performed in advance. many previous studies have adopted a pipeline architecture in which results of word spacing are used as inputs of morphological analysis. However, under this kind of pipeline architecture, word spacing errors lead to dismissed performances of morphological analysis models. To resolve this problem, we propose an integrated neural network model that performs word spacing and morphological analysis at the same time. The proposed model consists of two layers of bidirectional gated recurrent unit models with conditional random field layers: a lower layer for word spacing and an upper layer for morphological analysis. In the experiments, the proposed model outperformed both an independent word spacing model and independent morphological analysis model. It also showed better performances than the previous integrated models.
A LLS operator based S‐I WT de‐noising algorithm applied in EDXRF

An improved shift‐invariant wavelet (S‐I WT) de‐noising algorithm based on LLS operator is proposed for high‐resolution energy dispersive X‐ray fluorescence. Sym8 is chosen as the wavelet basis function and performed noise reduction on the analog signal. Comparison of the de‐noising effect of S‐I WT, improved WT and LLS S‐I WT (where LLS is the log square root operator) method are quantitatively evaluated by using evaluation criteria signal‐to‐noise‐ratio (SNR), root mean square error and Pearson correlation coefficient. Meanwhile, a new evaluation criterion of de‐noising effect, called peak area relative difference, is also proposed to evaluate the counting deviation. The results show that the LLS‐SI WT is simple and reliable, can effectively reduce pseudo‐Gibbs artificial signals and statistical fluctuation. Besides, this method simplifies the calculation, reduces the running time and improves the running efficiency. The LLS‐SI WT is also applied to reduce the noise after adding strong noise to the signal, the SNR has been improved from 14.0040 to 14.7552, and most of the characteristic peak information retains to the greatest extent.
Automatic generation of quizzes for Java programming language

Java is an objected oriented language that is platform independent. That is why it is widely used for Internet programming. A beginner that starts to study Java language has firstly to learn how an object is instantiated based on its constructor, how a public method is called from another class based on its signature and on class constructor, how a public and static method is called, based on its signature and on class name, how a public instance variable can be used in a method defined in a different class and how to access a constant defined in class in another class. In this paper it is presented an automatic way of generating random questions concerning these basic issues. These questions are presented to the student and he has to edit his answers. The paper also presents an automatic way of verifying the correctitude of the answers.
Artificial intelligence technologies in higher education institutions: a model of adaptive education

Planning and Teaching Engineering Staff for the Industrial and Economic Complex of the Region 2019: Proceedings of 2019 XVIII Russian Scientific and Practical Conference on Planning and Teaching Engineering Staff for the Industrial and Economic Complex of the Region (PTES)