Reviewerly/exHarmony huggingface dataset:
RETRACTED CHAPTER: Non-peaked Discriminant Analysis for Image Representation

The L1-norm has been used as the distance metric in robust discriminant analysis. However, it is not sufficiently robust and thus we propose the use of cutting L1-norm. Since this norm is helpful for eliminating outliers in learning models, the proposed non-peaked discriminant analysis is better able to perform feature extraction tasks for image classification. We also show that cutting L1-norm can be equivalently computed using the difference of two special convex functions and present an efficient iterative algorithm for the optimization of proposed objective. The theoretical insights and effectiveness of the proposed algorithm are verified by experimental results on images from three datasets.
A New Interactive Mathematical Modeling -- Artificial Neural Network Method for the Problems with a Limited Learning Data Set

One of the most common and universal problems in science is to investigate a function. The prediction can be made by an Artificial Neural Network (ANN) or a mathematical model. Both approaches have their advantages and disadvantages. Mathematical models were sought as more trustworthy as their prediction is based on the laws of physics expressed in the form of mathematical equations. However, the majority of existing mathematical models include different empirical parameters, and both approaches inherit inevitable experimental errors. At the same time, the approximation of neural networks can reproduce the solution extremely well if fed with a sufficient amount of data. The difference is that an ANN requires big data to build its accurate approximation whereas a typical mathematical model needs just several data points to estimate an empirical constant. Therefore, the common problem that developer meet is the inaccuracy of mathematical models and artificial neural network. An another common challenge is the computational complexity of the mathematical models, or lack of data for a sufficient precision of the Artificial Neural Networks. In the presented paper those problems are addressed using the integration of a mathematical model with an artificial neural network. In the presented analysis, an ANN predicts just a part of the mathematical model and its weights and biases are adjusted based on the output of the mathematical model. The performance of Integrated Mathematical modeling - Artificial Neural Network (IMANN) is compared to a Dense Neural Network (DNN) with the use of the benchmarking functions. The obtained calculation results indicate that such an approach could lead to an increase of precision as well as limiting the data-set required for learning.
Local Coordinate Exhaustive Search Hybridization Enhancing Big Bang-Big Crunch and Particle Swarm Optimization Algorithms

In general, all of the hybridized evolutionary optimization algorithms use “first diversification and then intensification” routine approach. In other words, these hybridized methods all begin with a global search mode using a highly random initial search population and then switch to intense local search mode at some stage. The population initialization is still a crucial point in the hybridized evolutionary optimization algorithms since it can affect the speed of convergence and the quality of the final solution. In this study, we introduce a new approach by creating a paradigm shift that reverses the “diversification” and then “intensification” routines. Here, instead of starting from a random initial population, we firstly find a unique starting point by conducting an initial exhaustive search based on the coordinate exhaustive search local optimization algorithm only for single step iteration in order to collect a rough but some meaningful knowledge about the nature of the problem. Thus, our main assertion is that this approach will ameliorate convergence rate of any evolutionary optimization algorithms. In this study, we illustrate how one can use this unique starting point in the initialization of two evolutionary optimization algorithms, including but not limited to Big Bang-Big Crunch optimization and Particle Swarm Optimization. Experiments on a commonly used benchmark test suite, which consist of mainly rotated and shifted functions, show that the proposed initialization procedure leads to great improvement for the above-mentioned two evolutionary optimization algorithms.
On Designs and Implementations of Service Request Composition Systems Using a Cooperative Multi-agent Approach

Though much attention has been paid on composing new web services, a closely related but distinct problem of composing requests to existing services has been relatively unexplored. Using existing geo-spatial web services, we illustrated that the problem has become complex that demands support systems of their own kind. We first formalized such systems as logic program, abstracting away from specific implementation languages. We then developed a communication protocol to combine them into a cooperative multi-agent service environment for composing service requests. Advantages that future web service composition could take from our approach was discussed also.
Design And Develop Academic Tutor Online Application System For FCSHD

This report is about the develop and design of academic tutor online application system . The main objective of this research is to simplifies the recruitment process. In the meanwhile, the specific objectives of the online application system provides lecturer to recruit academic tutor and evaluate the candidates online. Besides, students can view the job list and apply for the labtutor job position through the online system. Before the development process of this online application system was conducted, the existing online e-recruitment system that is related to this application are reviewed to gather the features and, functionalities that are suitable andpracticable. After that, the requirements has been analyzed and. fr-om the requirement gathered the system has been designed to make sure that the development process carry out systematically. In brief the academic tutor online application system is to simplify therecruitment process by reducing the time consumed and brings convenience for lecturers and students.
Question Formulation and Question Answering for Knowledge Graph Completion.

Knowledge graphs contain only a subset of what is true. Following recent success of Question Answering systems in outperforming humans, we employ the developed tools to complete knowledge graph. To create the questions automatically, we explore domain-specific lexicalization patterns. We outline the overall procedure and discuss preliminary results.
On an attempt to Explore the Possible Challenges Faced by Upcoming and Established Photographers in India and Studying the Interrelationships using ISM Methodology

Present research paper makes an exploratory study about the various challenges faced by different category of photographers such as professional photographers, landscape photography and freelance photographers.
On the use of Silhouette for cost based clustering

Clustering plays a fundamental role in Machine Learning. With clustering we refer to the problem of finding coherent groups in a dataset of elements. There are several algorithms to perform clustering that have been proposed in the literature, considering different costs for the optimization problems they consider. In this thesis we study the problem of clustering when the cost function is the silhouette coefficient, an index traditionally used for the internal validation of the results.
Exploring the Diffusion of the ISMS Standard ISO/IEC 27001

We presented and discussed the applicability of Web Mining to explore the Diffusion of Management System Standards, in particular in regards to Information Security
태국 중등학교 한국어 수업의 제(諸) 문제 - 태국 중등학교 교사 및 학습자의 설문조사를 중심으로 -

This study considers the future trajectory of Korean language education in Thailand by analyzing the present condition, status, and problems of Korean language education among the middle class against a backdrop of changes in the education system and the college admission system in Thailand. Korean language education is expected to be revitalized after its adoption in foreign-language selection courses of the PAT (Professional and Academic Aptitude Test), a college entrance examination, in 2018. This study examines the present condition and perception of Korean language education through a survey of Korean language teachers and students in secondary schools in Thailand. I found the actual condition of Korean language teachers'' class, students'' satisfaction and demand for the class, and teachers'' satisfaction and the demand for their ability as a Korean language teacher. I discovered that Korean teachers lacked confidence in their abilities and expressed a desire to learn more about the Korean language (grammar, vocabulary, phonology, pragmatics, etc.), its functions (speaking, listening, reading, writing) and methods of teaching, and developing and using textbooks through teacher training. In addition, the survey of Korean learners found that they have a favorable impression of Korea and Korean culture. In particular, they showed a strong interest in Korean dramas and K-pop, wanting to use them for Korean language learning. Besides, it was confirmed that the Korean Wave could have a positive effect on their career decisions such as choice of major in university, studying in Korea, and employment.The survey suggests that systematic curriculum, competent teachers, and good textbooks are needed for quality education. With respect to curriculum, a systematic curriculum considering the linkage between middle school, high school, and university is needed. In order to train high-quality Korean teachers, systematic support such as quality teacher-training programs should be provided and there should be research on teacher reorientation. Lastly, with respect to textbooks, it is necessary to develop secondary school textbooks for the middle class, Korean education textbooks published by the KEC, and teaching guides and other materials for teachers. Thus, this study provides perspectives on the present condition and development trajectory of Korean education among the middle class in Thailand, and the possibility of overseas Korean education.
Data Pattern Of Computer Maintenance Management System With Eclat Algorithm

Decision support system, basically used to help choosing some solution for stakeholde to take the best decision in manufacturer. In manufacturer company using Enterprise Resource System (ERP) that has Work Oder (WO) modul as request maintenance from user. But many of data from WO still didn’t use to help decision making and only as warehouse data about infrastructure maintenance from last time. Because that, author use that data to help technician to take decision making by using association rule as pattern processing. This is because WO has unique pattern that has problem (p), symptom (s), and root cause (r). Previous research (Sukmana, Rozi, 2017) was proved if association rule can use to help people to take decison making, it is just involved two variable, that is symptom (s), root cause (r) and using apriori algorithm as association rule. And focussing in this research is using that three variable and eclat algorithm as association rule methode. Result of this research has purpose to take the best pattern when using eclat algorithm.
The study of blockchain technology in election system

This paper studied the blockchain technology for an election system. The study was done in the laboratory scope, which took several advantages of blockchain technology. The system was capable of detecting the eavesdropper and the error automatically. It emerged if the initial data was different from the final data. Therefore, this technology could provide a secure, transparent and decentralization data in the election system.
Geomorphology of the Great Australian Bight and Offshore Seamounts and Canyons

This contract research project has developed quantitative methods to standardise the classification ofgeomorphic features on targeted surveys across the Great Australian Bight (GAB) and additionaloffshore surveys in the Tasmania region. The deliverables include spatial products and spatialderivatives for the survey regions to be used in the preparation of scientific manuscripts and reports2019/2020.
Additive Compositionality of Word Vectors

Additive compositionality of word embedding models has been studied from empirical and theoretical perspectives.Existing research on justifying additive compositionality of existing word embedding models requires a rather strong assumption of uniform word distribution.In this paper, we relax that assumption and propose more realistic conditions for proving additive compositionality, and we develop a novel word and sub-word embedding model that satisfies additive compositionality under those conditions.We then empirically show our model's improved semantic representation performance on word similarity and noisy sentence similarity.
Bi-Directional LSTM Networkを用いた発話に伴うジェスチャの自動生成手法

We present a novel framework for automatic speech-driven natural gesture motion generation. The proposed method consists of two steps. First, based on Bi-Directional LSTM Network, our deep network learns speech-gesture relationships with both forward and backward consistencies for a long period of time. The network regresses full 3D skeletal pose of a human from perceptual features extracted from the input audio in each time step. Second, we apply combined temporal filters to smooth out generated pose sequences. We utilize a speech-gesture dataset recorded with a headset and a marker-based motion capture to train our network. We evaluate different acoustic features, network architectures, and temporal filters in order to validate the effectiveness of the proposed approach. We also conduct a subjective evaluation and compare our approach against real human gestures. The subjective evaluation result shows that our generated gestures are comparable to “original” human gestures and are significantly better than “mismatched” human gestures taken from a different utterance in the scale of naturalness.
A Study on the Space Design Method based on Space Planning Direction and Public Library Policy in the UK

Today, Korea’s public library faces various problems, and the UK public library has sought ways to respond to these problems. The purpose of this study is to analyze and consider the policies, strategies, and directions that are corresponded to the aspects of the operation and spatial design of UK public libraries. Therefore, this study is meaningful at the point of exploring spatial planning countermeasures to solve Korea’s public library challenges. To this end, Chapter 2 presents the public library’s role and aim by researching and analyzing the UK government’s public library policy report in 2013-17. In chapter 3, the public library’s role and aim presented in chapter 2 and the relationship between the design principles of ‘21st-century library design’, ‘accessibility’, ‘connectivity’ and ‘flexibility’, are derived in the direction of spatial planning. The results are summarized as follows. ‘Accessibility’: 1) emphasizing the concept of place to open and connect shared spaces, 2) diversifying approach to provide specialized services for local communities, 3) realizing user-friendly spaces to provide casual and enjoyable experience services. ‘Connectivity’: 1) provides a function in the middle area for the Utilization of Shared Space, 2) provides a vertically open space for direct spatial information perception, 3) provides a digital device and face-to-face service space to provide user-customized information. ‘Flexibility’: 1) zoning space by age group and division for space corresponding to the user’s purpose, 2) future-oriented space applying digital technology, flexible to time-based behavior for Flexible Activity Programs. The design method of the UK public library space plan reflecting the policy can be used as the basic data to show the direction for Korea’s public library space plan.
COMPARATIVE ANALYSIS OF EXTRAPOLATION METHODS OF LABORATORY DATA TO THE ECOSYSTEM LEVEL IN AQUATIC ECOTOXICOLOGY

In order to assess the environmental effects during risk assessment, in practice it is impossible to conduct laboratory and field studies for all types of organisms in the biocenosis, as well as accurately reproduce in a laboratory experiment all combinations of conditions and factors of influence. That is why it is necessary to find the most precise model of data extrapolation from laboratory toxicological experiments - bioassays - to the level of aquatic ecosystem. Regardless of the calculation method, all such models are based on determining the predicted no-effect concentration of the pollutant for living organisms that populate the reservoir. Different methods of extrapolation of laboratory toxicity data to ecosystem level are compared by the example of determining the toxicity of phenol to water bodies. Calculation is based on bioassay results and carried out by methods of safety factors and empirical statistical models (Kooijman's method and method of Van Straalen and Denneman). The method of safety factor is the simplest and fastest, but its outcome strongly depends on the quantity and quality of the toxicity profile data and does not include the probability estimation. The safe concentration value, calculated by the method of Van Straalen and Denneman, is the highest. The error occurring during estimation of NOEC on the basis of LС(EС)50 values affects on the calculation in this case. Instead, the Kooijjman method is very precise. The safe concentration calculated according to this method is significantly understated in comparison with the results of other methods, because it strongly depends on the number of species inhabiting the aquatic ecosystem and the number of investigated test objects. It has been found that when using the Kooijman's method too high backward LС(EС)50 values of the least sensitive test objects significantly reduce the safe concentration of a pollutant. These may cause difficulties in decision-making process. In order to obtain the most reliable results, it is recommended not to consider too backward LС(EС)50 values using Kooijman's method for calculation of safe concentration of the pollutant and to take into consideration all values from LС(EС)50 calculation line using the method of Van Straalen and Denneman.
Monads in Haskell and Category Theory

he monad is a mathematical concept, used by Haskell to describe — among other things — Input/Output. Many are intimidated by it since it stems from abstract mathematics — namely Category Theory. Ho ...
Feature-based association rules for the evaluation of the English network considering non-metric multidimensional scale

With the continuous development of foreign language testing, more and more scholars have begun to pay attention to the ability of language to communicate in communication. At the beginning of the self-intellectual test, language proficiency has always been one of the key test subjects, and most of the intelligence tests also need to be tested by language and writing skills. Testing of English language proficiency is inseparable from the real language environment, but testing in a real environment is time-consuming and laborious. In response to this problem, this paper proposes a test method for rapid evaluation of English networks considering non-metric multidimensional scaling. This study aims to improve the platform test system of the current English network test by analyzing the algorithm characteristics of non-metric multidimensional scale and to optimize the existing English network fast test. At the same time, in order to test the applicability of the English network evaluation project under the algorithm characteristics of the non-metric multidimensional scale, some college students were selected for the test. The results of comparative analysis show that the rapid evaluation of English network based on non-metric multidimensional scale has good reliability and validity, which can effectively distinguish the merits of the assessors, and also can well test the students’ level.
Doc2Vec 단어 임베딩 언어 모델을 활용한 텍스트 장르 구분

According to Biber (1993) and Biber and Conrad (2009), multiple dimensional approach on several bi-polar features can classify genres founds in texts. Problem is that the process between feature extraction and statistical model building is exhaustively applicable when the machine learning system is dependent on frequency based language models. Following the machine learning approach of Kanaris and Stmatatos (2007), nearly 8,000 frequency-based models are used to induce genre distinction. If their whole process is not successful, they have to exhaustively redo the classification process. Upon such problem, we used a word embedding language model in order to deal feature extraction and model building at the same time. Among several word embedding models, our research is based on Doc2Vec model which captures paragraph feature of texts. We used the genre distinctions from the Project Gutenberg, dividing text databases into three parts in revealing distributional characteristics of linguistic features. Our method for detecting text genre is convenient in process as well as accurate in capturing feature distribution of text genre.
The Noisy Jackal: Measurement and analysis of the coloured noise on the longitudinal, lateral and rotational velocities and identifcation of its characteristics due to the unmodeled dynamics of a skid steer mobile robot during a steady-state turning manoeuvre

This research focuses on proving the presence of coloured noise on the longitudinal, lateral and rotational velocity in steady-state cornering of a skid steer mobile robot. Furthermore, it also focuses on the creation of a Gaussian filter which is able to recreate the characteristics of the measured coloured noise. This is done to determine the characteristics of the Gaussian filter based on real-life experimental values, which defines the Gaussian filter that creates coloured process noise in the Active Inference algorithm. To accomplish the main research goal, the following is done: - Create a linear dynamical model of the jackal robot and optimize the model in such a way that its velocity states resemble the experimental values of the velocities for the given experimental inputs. - Show the presence of coloured noise in the dynamical behaviour of the jackal robot. - Create a Gaussian filter and determine its characteristics, which can recreate the coloured noise found in the velocity states of the jackal robot in steady state turning. To accomplish this, experiments are done capturing the linear acceleration, rotational ve- locities, position and heading of the skid steer mobile robot using both the internal sensors of the robot as well as an external motion capturing system. A linear model of the jackal robot is constructed and discretised as the noise is a function of the difference between the experimental value for the next step state [k + 1]exp and the prediction of the next step state [k + 1]est. The prediction is made by inputting the experimental values for step [k] into the discretised linear model together with the model input. The difference between [k + 1]exp and [k+1]est is the noise on the velocities during the steady-state cornering experiments. Optimal values for Gaussian filter are found by fitting the autocorrelations of coloured noise which is made by filtering white noise with a range of Gaussian filters on the autocorrelation of the measured coloured noise. The result of this research is proof of the presence of coloured noise in skid steer mobile robots which in turn indicates that using Active Inference on these types of robots is a worthwhile approach to control and state estimation.