Reviewerly/exHarmony huggingface dataset:
THE EFFECT OF ANAGRAM GAMES ON SECONDARY LEVEL STUDENTS’ READING ACHIEVEMENT

The study employed a quantitative approach with Two-Group Design. The population consisted of six classes. We took a sample of two classes, VII-C as the experimental group and VII-D as the control group. Samples were determined using cluster sampling techniques. Based on the writer’s observation, some teachers in Junior High School Tegal still used the conventional technique in teaching especially in teaching reading, in fact, reading is very difficult to teach in Junior High School because a lack of vocabulary made the students’ motivation declined in reading. The result of the study revealed the use of Anagram was effective in teaching and learning reading. It happened since in Anagram implementation the students as the participants and the teacher as the facilitator. This situation was suited to the curriculum 2013 in which it concerned students oriented. Besides the students had fun and enjoyed reading because they teach each other, it easy to known students’ lack and need by Anagram Games, students trained to dare to ask and give their opinion especially in leaning reading which has many words and paragraphs. This method is easier, useful and flexible for the teacher to apply because of no need for a lot of time, media, realia and place. So, this study gives recommendations for teachers and students to implement this method.
3-DOF measurement method for non-diffracting Moiré fringes based on CGH

Aiming at the motion errors of the linear stage, a measurement method for the determination of three-degree-of-freedom (3-DOF) error motions is proposed based on non-diffracting Moire fringes produced by computer-generated holograms (CGHs). A liquid crystal spatial light modulator (SLM) is used to generate non-diffracting beams, and two non-diffracting beams form Moire fringes. A 3-DOF measuring optical path of non-diffracting Moire fringes is designed. Meanwhile, a 3-DOF mathematical model of motion errors is established, and three kinds of motion errors (yaw angle, roll angle and pitch angle) are separated by geometric analysis method. A rotary table is used to simulate the 3-DOF motion errors on different conditions. The NDB and non-diffracting Moire fringe patterns are obtained by CCD1 and CCD2 respectively. Experimental results show that the motion errors calculated by the positions of the central points agree well with the theoretical value with the error less than 0.0104°, which can verify the feasibility and correctness of the 3-DOF measurement system for non-diffracting Moire fringes.
Identification of Factors Causing Breast Cancer using Factor Analysis

Factor analysis is a data reduction technique that is used to reduce a number of observed variables from large data to a lesser number of latent variables.These latent variables are called factors.These factors are hypothetical variables used to explain the correlation between the variables.Factor analysis is found to be a useful tool to relationships among the variables and to classify them.In breast cancer diagnosis, pathologists examine FNA (Fine Needle Aspirate) tissue samples.In these samples, certain characteristics are considered to determine whether the tissue is malignant or benign.So here the Factor analysis is carried out for breast cancer dataset to find out the factors which is more prominent in detecting the breast cancer.Maximum likelihood estimation is used in extracting the factor and Varimax rotation is done to rotate the obtained factors.It is used to simplify the description of a specific sub-space in terms of a few major factors.Finally the factors used in the detection of breast cancer has been reduced to just twoappearance and nature of the cell.Factor analysis has been carried out using R tool.
LibGuides: Open Journal System: Home

This guide aims to familiarize faculty, student, and staff users to the open journal system (OJS) through a series of tutorials, videos, and links to helpful information on the Web.
Simulation with Multi Agent Flood Prediction Based on Rain Intensity Using Particle Swarm Otimization

Flood is one of the natural disasters that still often occurs in Indonesia. The lack of an adequate warning system is considered as the cause of the flood disaster. At present the flood detection sensor is only around the river which measures the water level, the lack of flood detection around the road bodies causes flooding caused by the high intensity of rain. Simulation model uses a multi agent that is used to detect the point of flooding based on the high intensity of rain, this simulation uses the Multi Agent approach by utilizing intelligent agents. Each agent is simulated using NetLogo at the time of rain by placing the agent into points that have the potential for flooding. This simulation test by placing several agents who have been inserted intelligence to detect locations that have the potential to flood based on the intensity of rain. Each testing agent will move to find the source of rain with the parameters of each agent that has been determined, then the results will be searched for an average value to measure how large the area has considerable potential.
SecuredDW: A Homomorphic Schema to Securely Hosting Data Warehouse in the Cloud

Currently, cloud computing has become the most popular technologies in the area of IT enterprise.It has many advantages such as computing power, storage, network and software as a service.Moreover, many other benefits have made it attractive.In fact, it is easy to deploy, its technical infrastructure is adaptable to the volume of business activity and its cost is relative to consumption.Whereas building a data warehouse typically necessitates an important initial investment, with the cloud pay-as-you-go paradigm, BI system can benefit from this new technology.However, cloud computing brings its own risks in terms of security.For this purpose, before outsourcing sensitive data to the cloud, the owner must encrypt his data to keep secure.In the particular context of cloud data warehouse, privacy is of critical importance because it contains sensitive data.Cloud provider proposes traditional security solutions to ensure the confidentiality of outsourced data.Unfortunately, those solutions are not practical in the case of data warehouse anymore because they induce a heavy overhead in terms of data storage and query performance.So, a new solution must be proposed for outsourcing data warehouse to the cloud that respects its specification and swings performance and security.In this paper, we propose (SecuredDW) a new sharing schema for securing and querying a data warehouse hosted in the cloud based in a homomorphic algorithm.The integrity of data is also addressed in this paper by proposing two new signatures to verify the correctness of data sent and received from the cloud.Theoretical results show the efficiency of Secured DW in terms of privacy and performance with respect to other solutions.
Purifying Real Images with an Attention-guided Style Transfer Network for Gaze Estimation

Recently, the progress of learning-by-synthesis has proposed a training model for synthetic images, which can effectively reduce the cost of human and material resources. However, due to the different distribution of synthetic images compared to real images, the desired performance cannot be achieved. Real images consist of multiple forms of light orientation, while synthetic images consist of a uniform light orientation. These features are considered to be characteristic of outdoor and indoor scenes, respectively. To solve this problem, the previous method learned a model to improve the realism of the synthetic image. Different from the previous methods, this paper try to purify real image by extracting discriminative and robust features to convert outdoor real images to indoor synthetic images. In this paper, we first introduce the segmentation masks to construct RGB-mask pairs as inputs, then we design a attention-guided style transfer network to learn style features separately from the attention and bkgd(background) region , learn content features from full and attention region. Moreover, we propose a novel region-level task-guided loss to restrain the features learnt from style and content. Experiments were performed using mixed studies (qualitative and quantitative) methods to demonstrate the possibility of purifying real images in complex directions. We evaluate the proposed method on three public datasets, including LPW, COCO and MPIIGaze. Extensive experimental results show that the proposed method is effective and achieves the state-of-the-art results.
Development of a communication policy for the formation of the image of the General education organization

In the article, the author considers and implements the mechanism of communication policy, which contributes to the formation of the image of the organization of General education
SUSTAINING INTERACTION THROUGH GROUP WORK IN ENGLISH FOREIGN LANGUAGE CLASSROOM

The purpose of teaching and learning English as a foreign language in Indonesia is to enable the learners to use English for communication in various contexts. To promote communication in teaching and learning activities, the teachers should be able to initiate interaction. To initiate interaction, the teachers may use questions, by which the teachers should consider the appropriate types of question that match with the students. In addition, the teachers should be able to maintain or sustain the interaction in their teaching and learning context. One of the activities which are effective to sustain interaction in the process of teaching and learning is group work. By using group work, the learners are encouraged to interact in English communicatively. Besides, this method increases students' motivation in learning. This is as the effect of learning climate which offers freedom for the students to express their ideas, feeling or criticism freely in front of their group's members. In addition, group work promotes students' learning responsibility and autonomy. Each member of the groups must be responsible to achieve their common goal. Considering those ideas, group work can be one of the effective methods to sustain interaction in the EFL classroom.
Histology of Watersnake (<i>Enhydris enhydris</i>) Lung

Rainbow watersnake is a snake that can be found in ponds, has a relatively medium body, a maximum length of 80 cm, generally between 50-60 cm, small-headed, a rather large belly, and short-tailed. The aim of this study is to determine the structure of the histology of the lungs of watersnake ( Enhydris enhydris ). This study used a sample of 3 watersnakes ( Enhydris enhydris ) with a body length of ± 50 cm. This study conducted a micro technical method with hematoxylin-eosin (HE) staining. Data obtained from the results of this study were analyzed descriptively and presented in the form of images. Macroscopic observations of the warp in snakes are long, most of the trachea attaches to the warp, and there are water sacs or swimming pouches at the tip of the warp, as well as the histological features of the snakes' warp, alveolar ducts, alveolar sac and alveoli, the histological structure of the lungs in watersnakes ( Enhydris enhydris ) consist of type 1 alveoli epithelial cells, type 2 alveoli cells, muscle bundles, connective tissue, capillary vessels, and macrophage cells. Based on the results of the study, it can be concluded that the histological structure of the watersnake ( Enhydris enhydris ) lung is different from the histological structure of the reptile function in general. In the lungs of watersnakes ( Enhydris enhydris ) only consists of alveolar ducts, alveolar sacs, alveoli, and the presence of water sacs at the ends of the lungs.
A Hybrid Approach for Sarcasm Detection

There is an excessive growth in user generated textual data due to increment in internet and social media users which includes enormous amount of sarcastic words, emoji, sentences. Sarcasm is a nuanced form of communication where individual states opposite of what is implied which is done in order to insult someone, to show irritation, or to be funny. Sarcasm is considered as one of the most difficult problems in sentiment analysis due to its ambiguous nature. Recognizing sarcasm in the texts can promote many sentiment analysis and text summarization applications. So for addressing the problem of sarcasm many steps have been adopted for sarcasm detection. Different preprocessing techniques such as Hypertext markup language removal, stop words removal, etc. have been done. Similarly, conversion of the emoji and smileys into their textual equivalent has been performed. Most frequent features has been selected and a hybrid cascade and hybrid weighted average approaches which are the combinations of the algorithms random forest, naïve Bayes and support vector machine have been used for sarcasm detection. The comparison of these two approaches on different basis has been done which has shown cascade outperformed weighted approach. Moreover, comparison of cascade approaches in terms of the algorithm placement has also been performed in which random forest has proved to be the best.
Abstract rewriting internalized

In traditional rewriting theory, one studies a set of terms up to a set of rewriting relations. In algebraic rewriting, one instead studies a vector space of terms, up to a vector space of relations. Strikingly, although both theories are very similar, most results (such as Newman's Lemma) require different proofs in these two settings. In this paper, we develop rewriting theory internally to a category $\mathcal C$ satisfying some mild properties. In this general setting, we define the notions of termination, local confluence and confluence using the notion of reduction strategy, and prove an analogue of Newman's Lemma. In the case of $\mathcal C= \operatorname{Set}$ or $\mathcal C = \operatorname{Vect}$ we recover classical results of abstract and algebraic rewriting in a slightly more general form, closer to von Oostrom's notion of decreasing diagrams.
A Study on the Sentiment Analysis of Netizen's Response to Subjects

This study proposes a sentiment analysis system to explore the response and the preference of netizens on special social network subjects. Our proposed system consists of 4 procedures: (1) crawls a large amount of network articles and messages for data collection; (2) proposes a vocabulary encoding model based on semantic text encoding method (word embedding) for text processing; (3) develops an emotional learning classification model based on word2vec and support vector machine to classify articles into three emotions; (4) implements sentiment analysis based on emotional learning classification model to obtain the preference of the subjects. Our system can effectively classify the messages of different subjects into different emotional categories to observe the netizens' response to the subject, and further understand the subject's attention and preference. Moreover, our system also focuses on the comparison of preferences between multiple subjects to understand whether a subject is more popular with netizens than other subjects. Then, we can clearly observe and grasp the influence of these subjects.
SOFTWARE PROCESS MODELS : A SURVEY

A eld of software engineering which is related to development of software product, needs systematic development for large software. This paper specify study of various process models from which systematic development of large software can be developed. Study of various paper and paper review of software process model is explained.
Vocabulary for Foods and Everyday Living Words Written by Chinese Characters Found in Banchandeungsok

This study explores food vocabulary and everyday living words found in ‘Ban-chan-deung-sok’, which was written about 100 years ago. The book consists of three parts: recipes written in ‘Hangeul’, Korean alphabet, explanation of Korean vocabulary using Chinese characters, and explanation of Chinese idiomatic phrases. Among these three parts, this research investigates the second part, Korean vocabulary written in Chinese characters quoted with either their meanings or pronunciations and Sino-Korean words. Korean vocabulary written in Chinese characters found in the book ‘Ban-chan-deung-sok’ has variety of words including food vocabulary, such as words about titles, designations, gadgets for daily lives, clothes, jewelries, laundries, and architecture etc. There are three types of Korean vocabulary written in Chinese characters: (i) Sino-Korean words, pure Korean words written in Chinese characters (ii) quoted by their pronunciation, and (iii) quoted by their meaning. Writing Korean vocabulary using either pronunciation or meaning of Chinese characters is one of the ways of writing by adopting Chinese characters.
ЕXPERIENCE OF DEVELOPING DUAL TRAINING SYSTEM FOR THE SPECIALISTS IN CULTURAL, LEISURE AND RECREATIONAL ACTIVITIES: ORGANIZATIONAL AND METHODOLOGICAL ASPECTS

The increasing requirements in the modern labor market for the qualification of specialists in different fields dictate the need for the implementation of efficient forms of practiceoriented organization of the educational process in higher educational institutions, among which the dual education is of particular interest nowadays. The authors of the article believe that the development of program targets and the justification of the complex of normative-documentary, scientific-theoretical, organizational and technological prerequisites for the project implementation on introducing the elements of dual education system into the professional training process of the specialists in cultural, leisure and recreational activities can promote the integration of science, education and production peculiarities of the multidirectional cultural and leisure pedagogical process, activate students’ motivation for obtaining the highlevel qualification and successful employment opportunities, increase their professional mobility and competitiveness in the labor market, and help future specialists adapt to the changing conditions of the modern-day cultural and recreational environment.
A Novel Circular Flexible Multiscale Geometric Analysis Method

Image representation is an essential problem in image processing. The most effective image representation method is multiscale geometric analysis (MGA). However, the current representative MGA method has some shortcomings, such as the fixed division of the scale spectrum and the direction spectrum, which cannot achieve well the sparsest representation of the image; the lack of rotation invariance and translation invariance make it impossible to achieve better results in the application. In this paper, a new circular flexible MGA method is proposed to solve this problem. First, the McClellan method was used to design a circular flexible multiscale decomposition, which had translation invariance and rotation invariance due to the circular spectral shape. Moreover, the spectral division of the new multiscale decomposition method could be flexibly changed according to the image, rather than being fixed at π/2 in the traditional manner. Second, new linear phase directional filter banks were proposed to divide the direction flexibly, which had selectivity in any direction. Finally, the two steps above were combined to construct a new MGA method, which maintained translation invariance, low redundancy, and flexibility in both scale and direction, resulting in better frequency localization and more sparse representation. The results of our denoising experiment show that the method proposed in this paper not only achieves a perfect reconstruction, but also performs well in image denoising compared to other state-of-the-art MGA methods.
Personality Prediction from Social Media Images: A Content Driven Approach

“If you want to discover the true character of a person, you have only to observe what they are passionate about”. Automatic evaluation of personality traits from the posts posted on various social media platforms is an interesting field of research. The interests of a person are reflected in the content of images which users post to their social media accounts. Popular personality prediction systems classify the personality of a person on the basis of five broad personality traits Openness, Conscientiousness, Extraversion, Agreeableness and neuroticism (also known as the Big Five Personality Traits). This paper proposes a novel approach of predicting a person’s personality reflected by his/her interests. The project detects significant features in each image posted by the user in his/her social media profile and then maps the features detected in the image to a predefined class which is based on the frequent interest domains normally observed in social media. For example, a person inclined towards adventure might post a higher number of photos related to adventurous activities like trekking, surfing, etc. The classes, for instance, can be; animal lover, foodie, adventurous etc. The significant features in an image posted by, for example, an animal lover might be a dog, a cat, or any other animal. Normally, a person is more likely to make friends with other person if they share similar interests. This project helps to connect an individual to other people sharing similar interests with him/her and make social media more “familiar” to the user.
Learning by Augmented Reality: Cluster Analysis Approach

Because the use of augmented reality (AR) is increasing, it is important to study its possibilities within both formal and informal learning contexts. We clustered 146 sixth graders using AR at a science center based on their reasoning, motivation, and science learning results using the self-organizing maps method (SOM) to identify AR-using subgroups. The aim was to consider reasons why the AR method could be of more beneficial for some students than others. The clustering results complemented earlier findings on AR gains in learning, as an unexpected response to intervention was discovered using this nonlinear analysis. The previous results had indicated that after the AR experience, science test results generally improved and particularly among students with the lowest achievement. The SOM-clustering results showed a majority group of boys, especially those interested in science learning both at school and at the science center using AR. Despite low school achievement, their high motivation led to good science learning results. The prior results, according to which girls closed the science knowledge gap between boys after using AR, became more relative, as two girl-dominated subgroups were identified. The reasons for the results were considered on the basis of motivation, multimedia learning theory, and concept formation theories.
Formal specification of the semantics of grasping using the Web Ontology Language (OWL) and integration into a robot programming GUI

In this thesis the semantics of grasping get developed first conceptually, then modelled ontologically and finally implemented in fortiss’ Robot Instruction Framework. The ad- vantage of doing this on a symbolic level compared to classical grasp planning approaches is that it saves a lot of computational effort and allows semantically meaningful reasoning about grasp modes. By logically guaranteeing incompabilities, the remaining search space for subsymbolic methods shrinks considerably. The basic idea is to compare the grasping capabilities of a gripper with the geometric conditions of the object to grasp, in order to find matching candidates - the applicable grasp modes. Basic sanity checks like values within ranges are performed and feasiblity scores per grasp mode allow ranking the re- sulting list of matches.