Reviewerly/exHarmony huggingface dataset:
Evaluation of rule-based learning and feature selection approaches for classification

Feature selection is typically employed before or in conjunction with classification algorithms to reduce the feature dimensionality and improve the classification performance, as well as reduce processing time. While particular approaches have been developed for feature selection, such as filter and wrapper approaches, some algorithms perform feature selection through their learning strategy. In this paper, we are investigating the effect of the implicit feature selection of the PRISM algorithm, which is rule-based, when compared with the wrapper feature selection approach employing four popular algorithms: decision trees, na'ive bayes, k-nearest neighbors and support vector machine. Moreover, we investigate the performance of the algorithms on target classes, i.e. where the aim is to identify one or more phenomena and distinguish them from their absence (i.e. non-target classes), such as when identifying benign and malign cancer (two target classes) vs. non-cancer (the non-target class).
PEMBUATAN PERMAINAN LINK COLOUR BERBASIS ANDROID

Casual Game Is a genre of the game which has same pattern and short level. For the example of the casual game is Catch Dot. Catch Dot is a game which has genre Casual Whom the player must match the color of the dot Which coming to circle in the center of the screen. Game will be over if the player can not match the color of the dot. At first, Catch Dot is very attractive, however, because of the lackof some features and variation, this game is rarely played right now. Then, an opportunities arise to make a similar game with Catch Dot which is named Link Colour. Link Colour has some features dan variation which is never exist in Catch Dot. Some features will be added in the Link Colour are online multiplayer, pause button, tutorial, levelling, power up. Power up which will be used are power up to increase the player’s health, slowing the rotation of the enemy wheel, reverse the direction of the enemy wheel. Theaddition ofthis feature are expected to make the Link Colour game can be more exciting thanthe CatchDot game and can be sought bymany people. Link Colour game uses Android Operating System. The development of Link Colour Game uses the Unity Game Engine and utilizing C# Programming Language. After implementation and some test run, obtained a result for Link Colour game. Link Colour game is exciting and easy to be played.
Collaboration

In 1953–1954, the WDR composers began building sounds with additive synthesis, a process of layering and recording sine tones using generators and magnetic tape. The young composers, including Stockhausen, Goeyvaerts, Koenig, Gredinger, and Pousseur, believed that this meticulous work, carried out in accordance with their own serial, proportional schemes, would yield complete sonic control. Much to their disappointment, the sounds they produced were unsophisticated. Moreover, the process was tedious and time consuming. They turned to each other to voice these frustrations, discussing their perceived failures and collaborating on experimental solutions. Eventually, the composers relinquished total control, and instead found technical shortcuts based on the scientist Meyer-Eppler’s teachings on psychoacoustics, or perception of sound. The composers’ initial additive synthesis compositions were in some ways aesthetic failures, but useful ones nevertheless. Through trial-and-error, composers learned more about both the studio machinery and human perception. Their successes and failures also reached far beyond the studio, as composers such as Ligeti translated electronic inspirations into compelling orchestral music.
A monocular camera based person-specific fall detection system exploiting deep neural network aided unsupervised

In this paper, we propose a novel fall detection system based on a monocular camera. A single camera covering the living area is used for video recordings of an elderly person’s daily activities. From the video recordings, the human silhouette regions in every frame are extracted from the background, with related low-dimensionality representative features being automatically extracted by a convolutional neural network based autoencoder (CNN-AE). Extracted features together with the silhouette position information are combined together to construct an one class support vector machine (OCSVM) model for fall detection. From the comprehensive experimental evaluations in a real home environment,it is shown that the proposed fall detection method can detect different types of falls (falls in different orientations, falls with occlusions in a home environment) with high accuracy while achieving better performance than hand-crafted features based ones.
The Role of Implicit and Explicit Knowledge Sharing in Improving Financial and Executive Performance: Mediating Role of Innovation Speed and Quality

This study tended to investigate the effect of implicit and explicit knowledge sharing on financial and executive performance considering the mediating role of innovation speed and quality. To this end, 150 successful ceramic and tile manufacturers in Iran were selected as samples. The results of path analysis showed that explicit knowledge has a direct positive and significant effect on innovation speed, innovation quality and financial performance; however, its direct effect is not significant on executive performance. Implicit knowledge has a direct positive and significant effect on innovation speed, innovation quality, executive performance and financial performance. Explicit knowledge has an indirect significant effect on financial and executive performance through innovation speed and innovation quality. Moreover, implicit knowledge has an indirect significant effect on financial and executive performance through innovation speed and innovation quality. Innovation speed and quality has a direct positive and significant effect on financial and executive performance.
How to protect your practice from ransomware

Advanced attacks are using a variety of methods to steal data. Here’s how to keep your practice up to date.
Deep One-Class Classification Using Data Splitting.

This paper introduces a generic method which enables to use conventional deep neural networks as end-to-end one-class classifiers. The method is based on splitting given data from one class into two subsets. In one-class classification, only samples of one normal class are available for training. During inference, a closed and tight decision boundary around the training samples is sought which conventional binary or multi-class neural networks are not able to provide. By splitting data into typical and atypical normal subsets, the proposed method can use a binary loss and defines an auxiliary subnetwork for distance constraints in the latent space. Various experiments on three well-known image datasets showed the effectiveness of the proposed method which outperformed seven baselines and had a better or comparable performance to the state-of-the-art.
3D Visualization For Augmented Reality In ‘Jajanan Pasar’ Puzzles

Jajanan Pasar is a term for Indonesian traditional snacks, a part of Indonesian culture that has been forgotten by the young generation. Three-dimensional (3D) animation and Augmented Reality (AR) can be used as a medium for introducing this culture to children aged 4 to 6. Because, in AR, visual between real and digital world can be altered, so the visual of 3D models can be enjoyed from various sides. This study focuses on 3D visualization for AR that packaged in 5 set of puzzles. Each piece has an illustration of the ingredients for making 5 kinds of Jajanan Pasar, after all, puzzle pieces of each set get arranged, a new 3D model of traditional snacks will be appeared. The data was collected using literature and existing studies method. The purpose of this study is to create an optimal 3D visualization for AR that will be applicated for mobile devices. Conclusion from this project are the polygon count and target marker’s quality, affect the appearance of the 3D model in AR form.
Design and Implementation of the Middle School Students' Composition Grading System Based on SVM

Now the traditional composition score required a large number of manpower material resources. And the marking quality is greatly influenced by subjective factors. Combined with the present popular technology-Machine Learning and the Text Classification, studied the middle school essay grading system based on support vector machine (SVM). The software system use the crawler to climb a scale middle school students' composition as the training set and the test set from the website, then participle, segmentation sentences and extract the features, use the support vector machine algorithm train the grading model and build a classifier by features, then we use the classification model to predict the test sample or Judge an unknown level article. The experiment results show that this method has a bit feasibility and effectiveness.
Modelling and simulation of atmospheric conditions impact on photovoltaic production in Saint Louis area

In this study, we worked on the modelling and the simulation of atmospheric conditions impact on photovoltaic production in Saint Louis area.Using Ineichen's model based on the disorder factor of Link, an assessment of sunshine in the study area was made.A characterization of the irradiation is elaborated by modelling the radiation and by simulating outputs of a photovoltaic power plant.We can estimate aerosols impact on photovoltaic production in the river area thanks to results obtained.We evaluated the sunshine rate of this area by using the modelling process.We chose an irradiation model to estimate the outputs of a photovoltaic power plant subjected to an atmosphere disturbed by aerosols.This work enabled us to set up a system of alerts and specific warnings for populations benefiting from this type of resource.
PERFORMANCE OF STEGANOGRAPHY USING MULTIRESOLUTION ANALYSIS APPLIED TO DIGITAL IMAGES

This paper will allow us to know and understand what is the art of steganography with the support of a digital image. The main objective of the steganography is to transmit a message without anyone knowing the existence of the latter and also to keep a high transparency against the statistical and visual attacks. Our work consists of transforming the image into four sub-bands using the discrete wavelet transform, and then inserting the message into the 3 sub-detail spaces with insignificant coefficients. The algorithm will allow us to design a steganographic diagram respecting a good transparency and imperceptibility compared to other existing algorithms.
NOVEL ALISYA KARYA MUHAMMAD MAKHDLORI: SEBUAH TELAAH STRUKTURAL

The purpose of this study is to describe the intrinsic elements of Alisya novel by Muhammad Makhdloril. The problem that will be examined and studied is how to describe the intrinsic elements that are the base of a literary work, among other things, the existence of themes, and mandates, figures and characterizations, plots, and settings that become the structure of Muhammad Makhdori's Alisya novel? The method used is descriptive method. The advantages of research is that it can reveal the structure of a novel that can be used as a material for studying learning to deal with life problems. The source used in this research is Alisya novel by Muhammad Makhdlori. The results obtained in this study indicate that the Alisya novel by Muhammad Makhdori has the theme of poverty can make people go berserk and invites immorality. Life needs to struggle and work hard.
Study and Practice on Primary School Mathematical Modeling

The mathematical modeling is one of the ten core concepts proposed by the Ministry of Education's â€œCompulsory Education Mathematics Curriculum Standardsâ€. The cultivation of mathematical modeling ideas and methods can help students get clear mathematical thinking and gradually form a scientific method to understand the world to improve students' basic mathematical literacy and interest in learning. This paper expounds the connotation and the significance of elementary school mathematical modeling. Through the abstraction and simplification of practical problems, two cases of teaching modeling are given.
Implementing Industry Applications

In this chapter, we are going to implement end-to-end solutions for a few of the Industry applications around NLP.
Efficacy of long-term treatment with lurasidone in children and adolescents with bipolar depression: Interim analysis of a 2-year open-label study

To improve segmentation of normal/abnormal livers in contrast-enhanced/non-contrast CT image using the Active Shape Model (ASM) algorithm; we introduce a generalized profile model. We also intend to accurately detect boundary of liver where it touches nearby organs with similar intensities.Initial boundary of a liver in a CT slice is found using an intensity-based technique and it is then represented by a set of points. The profile of a boundary point is represented by a generalized edge model and the parameters of the model are obtained using a non-linear fitting scheme. The estimated parameters are used to classify boundary points into genuine and dubious groups. The genuine points are located as the true border of the liver and the locations of dubious points are refined using smoothed spline interpolation of genuine landmarks. Finally, the liver shape is kept inside the “Allowable Shape Domain” using a Statistical Shape Model.We applied the proposed method on four sets of CT volumes including low/high-contrast, normal/abnormal and public datasets. We also compared the proposed algorithm to conventional and state-of-the-art liver segmentation methods. We obtained competitive segmentation accuracy with respect to recent researches including enhanced versions of the ASM. Concerning conventional Active Shape and Active Contour models, the proposed method improved Dice measure by at least 0.05 and 0.08 respectively. Regarding the MICCAI dataset, we promoted our score from 68.5 to 72.1.The proposed method alleviates segmentation problems of conventional ASM including inaccurate point correspondences, generalization ability of the model and sensitivity to initialization. The proposed method is also robust against leakage to nearby organs with similar intensities.
Stages of Notational Development

This chapter examines the research on invented music-notation systems, comparing the music notations generated by children with invented spellings, as well as describing the role that music training plays in shaping children’s notations of their own compositions. It also explores the role of developing notations in a creative community of practice. Further, the chapter outlines five developmental stages, beginning with the child who creates notations with no sound-symbol correspondence and moving through to notations showing the musical units, notations depicting limited rhythm and pitch information, and regulated but nonstandardized notations and ending with standardized music notation. The chapter is filled with examples from children to show how notations are developed, including a case study of a single child progressing through all of the developmental phases.
LibGuides: Topics in Business, Industry, and Marketing Research: Market and Industry Research

Recommended resources for business, industry, and marketing research by RCAD faculty and librarians.
Incognitus: Privacy-Preserving User Interests in Online Social Networks

Online Social Networks have changed the way we reach news and information. An increasing number of people use social networks not only for communicating with friends and colleagues but also for their daily information needs. Apart from providing the users with personalized information in a timely manner, this functionality may also raise significant privacy concerns. The service provider is able to observe both the Pages a user is subscribed to and her inter- actions with them. The collected data can form a detailed user profile, which can later be used for several purposes; usually beyond the control of the user. To ad- dress these privacy concerns, we propose Incognitus: an approach to allow users browse Pages of OSNs without disclosing their interests or activity to the service provider. Our approach provides (i) a incognito mode of operation when browsing privacy-sensitive content. In this isolated, offline mode no tracking mechanisms can monitor the users behavior and no information can be leaked to the provider. At the same time, (ii) by using an obfuscation-based mechanism, Incognitus reduces the accuracy of the service provider when monitoring the interests of a user. Early results show that Incognitus has minimal bandwidth requirements and imposes reasonable latency to the users browsing experience.
Listwise vs Pagewise

As heterogeneous verticals account for more and more in search engines, users' preference of search results is largely affected by their presentations. Apart from texts, multimedia information such as images and videos has been widely adopted as it makes the search engine result pages (SERPs) more informative and attractive. It is more proper to regard the SERP as an information union, not separate search results because they interact with each other. Considering these changes in search engines, we plan to better exploit the contents of search results displayed on SERPs through deep neural networks and formulate the pagewise optimization of SERPs as a reinforcement learning problem.
Improving generalization in reinforcement learning on Atari 2600 games

Deep Reinforcement Learning (DRL) is poised to revolutionize the field of artificial intelligence (AI) and represents a crucial step towards building autonomous systems with a higher-level understanding of the world around them. In particular, deep reinforcement learning has changed the landscape of autonomous agents by achieving superhuman performance on board game Go, a significant milestone in AI research. In this project, we attempt to train a Deep RL network on Demon Attack – an Atari 2600 game and test the model on different game environments to investigate the feasibility of applying Transfer Learning on environments with same action space but slightly different state space. We further extend the project to use established Reinforcement Learning techniques such as DQN, Dueling DQN, and SARSA to examine whether RL agents can be generalized on unfamiliar environments by fine-tuning the hyperparameters. Finally, we borrow classic regularization techniques like 2 regularization and dropout from the world of supervised learning and probe whether these techniques which have received very limited attention in the domain of reinforcement learning are effective in reducing overfitting of Deep RL networks. Deep Networks are expensive to train and complex models take weeks to train using expensive GPUs. We find that the use of the above techniques prevents the network from overfitting on the current environment and gives satisfactory results when tested on slightly different environments thus enabling substantial savings in training time & resources.
STUDY ON THE MOVE TO <i>MAIKO</i>, PRODUCTION OF THE BRICK, THE COMPANY BADGE AND RELATIONS THE HUNTER & CO. OF THE <i>KANSAI-RENGA-KAISYA</i>

This article reconsidered the Maiko bricks that J. Condor made to "AN ARCHITECT'S NOTES ON THE GREAT EARTHQUAKE OF OCTOBER, 1891." after the field investigation of the disaster area of the Nobi earthquake, and the Kansai Bricklay Co., which made the bricks. The following points became clarified. Initially, Kansai-renga-seisakuzyo was founded in 1886 at Ozone of Osaka by Simeirou, and Wada Hanbee participated in the capital in October 1887. The reason why the Kasai-renga-seisakuzyo moved to Maiko of Hyogo at early time was that Wada thought about the move of the factory. According to the document, the foundation of the Kansai-Renga-Kaisya was in January 1888, the company's authorization was June 16, 1888, but the completion of the factory was at the end of January 1889. According to the newspaper report, the company started manufacturing bricks in February 1889, the company produced 30,000 bricks every day. I thought that the company invited the engineer from British as for the Maiko brick having been slightly large with the front article, however, the reason was that the company manufactured the Maiko bricks with brick making machines imported from the UK via the Hunter & Co.. In addition, the Hunter & Co. participated in the management of the company. The company exported more than half of the bricks to Canada as the ballast of foreign ship. The Maiko bricks were rather large size, I thought in the previous manuscript because the company invited British engineers. However, the reason was that the company imported brick making instruments from the UK through the Hunter & Co. produced bricks. The company's mark of Kansai-Renga-Kabusikigaisya decides to combine three rectangles into a triangle by the company's advertisement. This stamp can also be confirmed on the brick used at the former the Hunter's mansion. And the Hunter & Co. was a stockholder of Kansai-Renga-Kabusikigaisya.
Making Instruments—Sound and Symbol

When one makes one’s own instruments, many opportunities arise for understanding how sound is created. This chapter describes not only how students made instruments but also how they explored sound using simple materials like string and straws, learning how pitch is changed through, for example, the length of the string, the tension, and the thickness. The discussion is integrated with anecdotes of how this instrument making was reflected in the children’s compositions and performances. Finally, the chapter considers how the instruments made and/or chosen by students, and the ensembles they create, have an influence on notation—and vice versa. There is also discussion of how performance and careful listening can help students understand Western harmonic structures and develop their sense of form.
Causes of the Imbalance Between Exploration and Exploitation in Evolutionary Computation

Evolutionary algorithms have been used in more and more research fields. However, it is very usual that an optimal of nontrivial problems cannot be found by an evolutionary algorithm. In fact, only if the balance between exploration and exploitation is achieved in runs, good solutions can be obtained. In this paper, we observe the changing trend of genotype diversity in runs, which cannot obtain the optimal, of different EAs. Then, we illustrate the main cause of the imbalance between exploration and exploitation in different situations.