Reviewerly/exHarmony huggingface dataset:
MENGEMBANGKAN KECERDASAN LOGIS MATEMATIK PADA ANAK USIA DINI MELALUI METODE CERITA BERGAMBAR MODEL POP UP KELOMPOK B

This research was conducted to find out the differences from the learning methods of ordinary pictorial stories with the pop up models of the more unique and different pop up models, but also through this research it is hoped to provide new experiences for children, bearing in mind that learning is still focused on writing, reading and counting (calistung). This study uses the experimental method because there is a comparison between the control class and the experimental class. The subject and location of the study were group B students. The study population was the B-Saturn group and the B-Uranus group with a sample students, with a total of 28 students. Data collection techniques using pretest and posttest. Pretest technique using ordinary picture stories while in the posttest technique using picture models pop up. Results of Research The average value (mean) in the control class is BB (1.21), MB (0.21), BSB (0.42) and BSH (0.14) while in the experimental class the average value is BB (0.29), MB (0.21) , BSB (0.5) and BSH (0.14). Then it can be concluded that "Hypothesis is accepted", meaning that there is a difference between student learning outcomes to develop mathematical logical intelligence in the pretest and post test. So it can be concluded that there is an influence in "Developing mathematical logical intelligence in early childhood through the method of picture story pop up models in group B"This research was conducted to find out the differences from the learning methods of ordinary pictorial stories with the pop up models of the more unique and different pop up models, but also through this research it is hoped to provide new experiences for children, bearing in mind that learning is still focused on writing, reading and counting (calistung). This study uses the experimental method because there is a comparison between the control class and the experimental class. The subject and location of the study were group B students. The study population was the B-Saturn group and the B-Uranus group with a sample students, with a total of 28 students. Data collection techniques using pretest and posttest. Pretest technique using ordinary picture stories while in the posttest technique using picture models pop up. Results of Research The average value (mean) in the control class is BB (1.21), MB (0.21), BSB (0.42) and BSH (0.14) while in the experimental class the average value is BB (0.29), MB (0.21) , BSB (0.5) and BSH (0.14). Then it can be concluded that "Hypothesis is accepted", meaning that there is a difference between student learning outcomes to develop mathematical logical intelligence in the pretest and post test. So that it can be concluded mathematical logical intelligence by using the pop up model pictorial story method is better than groups that use ordinary learning.
Blockchain Governance for Technologists

As blockchain applications become more pervasive and visible, it becomes increasingly important to consider their non-technical as well as their technical aspects. This paper provides a brief tutorial-style introduction to institutional economics, which is one of the important frameworks for thinking about the economic aspects of blockchain systems.
An Efficient Word Lookup System by using Improved Trie Algorithm

Efficiently word storing and searching is an important task in computer science. An application space complexity, time complexity, and overall performance depend on this string data. Many word searching data structures and algorithms exist in the current world but few of them have space compress ability. Trie is a popular data structure for word searching for its linear searching capability. It is the basic and important part of various computer applications such as information retrieval, natural language processing, database system, compiler, and computer network. But currently, the available version of trie tree cannot be used widely because of its high memory requirement. This paper proposes a new Radix trie based data structure for word storing and searching which can share not only just prefix but also infix and suffix and thus reduces memory requirement. We propose a new emptiness property to Radix trie. Proposed trie has character cell reduction capability and it can dramatically reduce any application runtime memory size. Using it as data tank to an operating system the overall main memory requirement of a device can be reduced to a large extent.
A Framework for Affective & Sustainable Learning

Social, Emotional and Affective Factors [SEA] are critical to academic and career success [1]. Affective Education helps children better understand their feelings and respond to challenging situations. Although the importance of affect on learning and cognition is widely accepted in Education Research, the research so far has treated affect and cognition on two separate dimensions - loosely coupled. Recent findings, scattered across various disciplines, have shown their relationship to be more tightly coupled than what the previous theories have posited. Also, with the advent of online education, students are on their own to overcome the challenges that arise in the course of learning without the guidance of a human teacher. Therefore, it is imperative that machines detect and respond to affect effectively. In this paper, we propose a unified & scalable framework that brings together findings from multiple disciplines (Decision-making, Affective research, Chess studies, Education, Mindfulness studies), highlighting some of the challenges encountered in detecting/responding to affect and propose ways to address them. We then validate our framework through a Pilot Experiment (Chess puzzles) by examining the effectiveness of response strategies in mitigating the influence of incidental affect on performance. The results from the experiment, 80 chess amateurs solving chess puzzles, reveal that introducing time-delay between tasks & being aware of their state, can minimize the impact of incidental affect. We are hopeful that the learning from these experiments can be incorporated into cognitive-affective agents making learning - effective, sustainable and enjoyable.
Activity Recognition System Optimisation Using Triaxial Accelerometers

Activity recognition is required in various applications such as motion analysis and health care. The accelerometer is a small, economical, easily deployed and high-performance sensor, which can continuously provide acceleration data from the body part it is worn. Previously, the human activity recognition system researches utilising triaxial accelerometer have mainly focused on one placement of the sensor, and rarely states the reason for the choice of sensor placement. This paper presents an optimisation method utilising a triaxial accelerometer when the sensor is placed on different body parts. The statistical characteristics-based algorithms use data from a motion-captured database to classify six classes of daily living activities. Feature selection is performed using the principal component analysis (PCA) from a range of features. Robust and sensitive features that highly contribute to the classification performance are selected. Activity classification is performed using the support vector machine (SVM) and K-nearest neighbour (K-NN) and the results are compared. Based on the HDM05 Mocap database with six activity types (overall 89 motions) collected from five subjects, the best place for wearable accelerometers is the waist, followed by chest, head, left wrist, right wrist, humerus and femur. Based on the preliminary results, multi-accelerometers and data fusion methods are utilised for further increasing the accuracy of classification, where the accuracy increases by 6.69% for SVM and 7.99% for KNN. For two sensors, the best placements for sensors are the waist with the left wrist, followed by the waist with the right wrist, waist with chest, waist with the humerus, waist with head and waist with femur. The result provides a guideline for sensor placement when developing an activity recognition system.
UNO: Uncertainty-aware Noisy-Or Multimodal Fusion for Unanticipated Input Degradation

The fusion of multiple sensor modalities, especially through deep learning architectures, has been an active area of study. However, an under-explored aspect of such work is whether the methods can be robust to degradations across their input modalities, especially when they must generalize to degradations not seen during training. In this work, we propose an uncertainty-aware fusion scheme to effectively fuse inputs that might suffer from a range of known and unknown degradations. Specifically, we analyze a number of uncertainty measures, each of which captures a different aspect of uncertainty, and we propose a novel way to fuse degraded inputs by scaling modality-specific output softmax probabilities. We additionally propose a novel data-dependent spatial temperature scaling method to complement these existing uncertainty measures. Finally, we integrate the uncertainty-scaled output from each modality using a probabilistic noisy-or fusion method. In a photo-realistic simulation environment (AirSim), we show that our method achieves significantly better results on a semantic segmentation task, compared to state-of-art fusion architectures, on a range of degradations (e.g. fog, snow, frost, and various other types of noise), some of which are unknown during training. We specifically improve upon the state-of-art[1] by 28% in mean IoU on various degradations. [1] Abhinav Valada, Rohit Mohan, and Wolfram Burgard. Self-Supervised Model Adaptation for Multimodal Semantic Segmentation. In: arXiv e-prints, arXiv:1808.03833 (Aug. 2018), arXiv:1808.03833. arXiv: 1808.03833 [cs.CV].
Balance Rule in Artificial Intelligence

Deep learning embodied some essence of artificial intelligence, but it relied on data set and lacked migration learning ability. We should build general theorem to explain artificial intelligence from nature or human. We can treat each static data as a variable like wave-particle duality, then we can adopt idea from convolutional neural network or other machine learning algorithms to extract features from little data. This method can open up a new theory to accomplish migration learning and artificial intelligence. The theory will be supported by balance rule: everything has a gradient and tends to remain a zero gradient state, and we can connect different feature spaces by gradients.
ADMINISTRATION SYSTEM DEVELOPMENT OF EDUCATION IN IMPROVING SERVICE QUALITY

The purpose of this study was to find out the development of a technologybased administration system in improving the quality of services in Higher Education.The data analysis technique uses the plomp method.This study uses a research development approach.The research subjects were three students for one on one test and twenty students for large group trials.The results showed that: based on the Likert scale 1-5, the average score of the expert system for the display aspect was 3.67 and the programming aspect was 3.85.So that the attractiveness of the system developed and the attractiveness of the product on the criteria are "very interesting", while fourteen students show the attractiveness of the product on the "Attractive" criteria.
Instance Segmentation as Image Segmentation Annotation

The instance segmentation problem intends to precisely detect and delineate objects in images. Most of the current solutions rely on deep convolutional neural networks but despite this fact proposed solutions are very diverse. Some solutions approach the problem as a network problem, where they use several networks or specialize a single network to solve several tasks. A different approach tries to solve the problem as an annotation problem, where the instance information is encoded in a mathematical representation. This work proposes a solution based in the DCME technique to solve the instance segmentation with a single segmentation network. Different from others, the segmentation network decoder is not specialized in a multi-task network. Instead, the network encoder is repurposed to classify image objects, reducing the computational cost of the solution.
Developing a Framework of Media-Aided Descending-Ascending Repetition of Vocabulary Learning

Foreign language basic vocabulary learning for teenagers mostly belongs to verbal information learning, involving a lot of memorization and thus, necessary repetition. However, EFL teachers, particularly in the school observed, fail to pay attention to vocabulary learning at this stage due to limited time, which has resulted in low learning achievement. This action research was focused on developing a framework of media-aided fading repetition of vocabulary learning for purposes of mastery improvement. The research participants were two English language teachers, one teacher educator, and 32 students in a state junior secondary school of a medium ranking and size in Sleman District, Yogyakarta Special Territory, Indonesia. This school was selected considering the transferability of the findings. The study was conducted from January-May 2017 in three planning-action-observation-reflection cycles of repeating the learning of the target vocabulary in the process of developing an appropriate framework of media-aided fading repetition in the existing curriculum implementation. Data were collected through observation and testing. The results were of two types: (1) the intended framework, and (2) improvement in the following aspects: the increasing classroom atmosphere liveliness, students’ greater participation, students’ increasing scores, and the teacher’s awareness of the importance of repetition and variations of activities in vocabulary learning. Keywords: vocabulary, EFL, media-aided descending-ascending repetition
Créer un raccourci de son application à partir de l'application elle-même. – PatCatNat's

Access 97 | Compatible | Access 2003 | Non teste | Fonction d'un module : Public Sub Raccourci() Dim WshShell As Object Dim strdesktop As String Dim oshellLink As Object Set WshShell =…
Role of Usability on using Biometrics for Cybersecurity

ABSTRACT &#x0D; Biometrics are traits that allow individuals to be identified. Popular biometrics include fingerprints, faces, and irides. A common use of biometric systems is for authentication of users desiring access to a system or resource. However, the use of biometrics presents challenges and opportunities unique to other authentication methods, such as passwords and tokens. Biometric systems are also vulnerable to poor usability. Such systems must be engineered with wide user accessibility and acceptability in mind, but must still provide robust security as well. As lack of usability causes systems' failures, and enhancing systems' usability reduces such failures. This article first presents an overview of biometric systems employed today, including their usage and security merits. We then consider the specific role usability plays on both the development and long-term utility of biometric systems used for Cybersecurity.
Prediksi Harga Terendah Dan Harga Tertinggi Dengan Menggunakan Metode Anfis Untuk Analisa Teknikal Pada Forex Market

Forex Market Is a type of currency trading of the country that handles the world currency market within 24 hours agreed, foreign exchange trading has become an alternative for investors to save more trades in general and traders are required to support good technical analysis of good fundamentals so that able to reap huge profits. Technical analysis is an analysis used to estimate prices will fall at the lower price threshold (support) and the upper price threshold (resistance). Fibonacci Retracement is a method often used for technical analysis of rising prices or rising prices. The data used in this study was downloaded from the FBS Forex Market server which consists of open, high, low, close, and volume data. The next step is grouping data as a preprocessing method with the k-means method to normalize the data before the data is processed in the proposed method, the k-means method is a method of grouping data based on the nearest cluster object. One of the advantages of the k-means method is simple, efficient and easy to apply. In this study, artificial neural network and fuzzy inference system (ANFIS) and Fibonacci Retracement methods are used to predict support and resistance levels. Testing is done using training data and test data with different time intervals. This data produces the highest level of testing based on data from 3 January 2015 - December 2017 and 1 month test data for the period January 2018 100% weekly real data ,. While the value of the accuracy of the trial data period 1 to 2 years and 1 month test data for the period January 2018 daily real data, which is 40%. The average value of the experiment using training data and test data with different time intervals was 52.61%.
An explorative case study on the key issues in the public opinion formation process concerning education policy decision-making

민주주의 사회의 교육정책 결정 과정은 다양한 집단의 이해관계가 논의·반영되는 정치적인 과정임에도 불구하고 그간 한국사회 교육정책 결정은 소수의 정책 선도가들에 의해 이루어진 경우가 많았다. 이 연구는 교육정책 결정 과정의 민주성과 공공성을 제고하기 위한 대안으로 부상하고 있는 교육정책 공론화 제도의 도입과 운영 과정에서의 고려사항에 대한 다중사례연구이다. 이를 위해 선행연구 분석을 통해 공론화 과정에서 중점적으로 고려해야 할 다섯 가지 영역을 도출하였다. 이를 분석틀로 삼아 대입제도개편 공론화와 ‘편안한 교복’ 공론화 사례를 살펴보았다. 연구 결과는 다음과 같다. 첫째, 교육정책 공론화 주제는 다수 시민에게 영향을 미치는 것으로, 구체성의 수준에 대한 고려가 필요하다. 둘째, 공론화 주관 기구는 정부로부터 자율적이고 독립적이어야 한다. 셋째, 공론화 절차에 있어 가장 중요한 것은 학습·토론에서의 숙의성이며, 참여자들이 성장과 배움을 경험하는 전환적 과정이 되어야 한다. 넷째, 공론화 참여자는 대표성과 평등성을 고려하여 구성해야하며, 특히 학생들의 참여를 보장해야한다. 다섯째, 교육정책 공론화 결과가 민주적 의사결정 과정이 되기 위해서는 그 결과가 정책에 구체적으로 반영될 수 있는 기획이 필요하다.In a democratic society, diverse interest groups are to engage in education policy making processes. However, education policies in South Korean society have been predominantly decided by a few policy leaders. Meanwhile, a public opinion formation is recognised as an alternative way to enhance democracy and public concerns in education policy formation. Therefore, this study explores some major issues relevant with public opinion formation process concerning education policy decision-making. From literature review, five main issues were identified. Adopting these as an analytical framework, this study examines two cases of public opinion formation, a reform of college entrance system and a ‘comfortable school uniform’. The implication of this study are as follows: Firstly, as to the topics of public opinion formation, we should select issues that affect a majority of citizens. A level of specificity about the topic should be also considered. Secondly, a supervision body should be autonomous and independent from the government. Thirdly, a priority in the procedure is a deliberation in the learning process, which is to be transformative for participants. Fourthly, representativeness and equity should be guaranteed in selecting participants. Especially, the participation of students should be considered. Fifthly, a systematic mechanism is to be prepared to ensure that education policy reflects the outcomes of public opinion formation in a specific way.
Saving the World One Block at a Time

Abstract Blockchain is often associated with high energy usage, writes Matt Lucas from IBM’s blockchain team. But, is the environmental impact of this much-hyped technology as bad as we’ve been led to believe?
Widening Access to the Glasgow School of Art Library Artists’ Book Collection

Discusses a project to digitise select pages from the collection of c.2000 artists' books at Glasgow School of Art Library.
Towards a Model-Driven Framework for Data and Application Portability in PaaS Clouds

Cloud computing paradigm has gained momentum during last decade owing to the numerous benefits (Cost, Scalability, etc.) it offers. Several developers and organizations have steadily got interested in PaaS (Platform as a Service) clouds since it allows deploying applications without any requirement for a consecrate infrastructure, installations of dependencies or server configurations. However, there still exist some issues that need to be resolved to make Cloud computing and PaaS widely adopted. Portability of applications along with the portability of databases (DBs) among heterogeneous cloud platforms is one of the issues. To address this, a middleware platform has been proposed in this paper in which the application layer and the DB layer of that application shave been decoupled from each other. Both the layers can be ported from one platform (PaaS) to another PaaS independent of each other. Model-Driven Engineering (MDE) approach has been leveraged to make the middleware flexible, further making application layer and DB layer portable, productive and reusable. MDE has been proved to be a better alternative to standardization in the literature.
The translation of Youth Language: Strategies Applied on the German Translation of Marko Vidojković’s Novel Ples sitnih demona

New technologies have pervaded many aspects of modern life and influenced human communication, emotions and language. This close interaction between people and computers is reflected in language, in the use of computing terms applied to human emotions, relationships and everyday activities. Metaphor plays an important role in the language of information technology and it is widely used in creating new vocabulary. This paper explores conceptual metaphors in order to determine their usage in the information technology research papers, through describing similarities and differences in the conceptualisation of these metaphors within two languages. The aim of the paper is to quantitatively and qualitatively present conceptual metaphors, regarding computers and the Internet, found in ten research papers written in English and in Serbian. These expressions are compared with respect to their frequency in the papers and the degree to which metaphorical vocabulary is present in analysed research papers. The results indicate that all authors have used conceptual metaphors, although papers in Serbian include a slightly larger number of expressions than papers in English. Apart from differences and diversities, the analysis also identifies a remarkably similar structure of the mapping in both languages.
Interface on User's Back of the Hand Using ToF Sensor Array on the Curved Surface

Smartwatch is one of useful wearable devices. However, the display of smartwatch is small, and the operability is low. A technique of around device interaction (ADI) has attracted attention. In this paper, we propose ToF sensor array on the curved surface to operate a smartwatch using user's back of the hand. The ToF sensor array detect the finger motion on the wide range of user's back of the hand because the sensor is on the curved surface. In addition, the sensor detects the multi-touch and palm motion. Thus, ToF sensor array on curved surface will be useful interface for smartwatch.
Social creativity of personality of students of "social work" direction as a necessary condition of their professional competency

The article explores social creativity as a significant component of the social worker's professional competency. The concepts of creativity and social creativity are defined. Social creativity is considered as a complex multi-component education, in which the personality characteristics are fused in a special way with some characteristics of personal cognitive needs and cognitive activity. The main components of social creativity are indicated. The article presents the results of an empirical study of the level of social creativity of students in "social work" direction. It was revealed that for most of the "social work" direction students, social creativity is developed at a sufficiently high level that meets the requirements of the specialist's professional competency in this field of activity. Attention was also paid to active learning methods as the main tool for students' social creativity development. The ways of activating the individual innovation potential are considered.