Reviewerly/exHarmony huggingface dataset:
Subjective assessment of the quality of static and video images from mobile phones

The fast progress of mobile shooting technologies stimulates development of the methods for reliable assessment of image quality. In each case, successful comparison or evaluation requires a proper choice of method. The paper contains a brief tentative reference source for such investigations. We consider the most commonly used subjective methods for assessing and comparing static and video images: ACR – absolute category rating, ACR-HR – absolute category rating with hidden reference, SSCQE – single stimulus continuous quality estimation, DCR – degradation category rating, DSCQR – double stimulus continuous quality rating, PC – pair comparison, PSJ – pairwise similarity judgment, and SDSCE – simultaneous double stimulus for continuous evaluation.
Pengembangan Media Pembelajaran Mesin Menggunakan Teknologi Augmented Reality

Learning media are all things that can be used to channel messages and stimulate the learning process for students. Learning machine of two-wheeled vehicles in SMK YPT 2 Purbalingga is still using Ms. Powerpoint as a learning medium. In one of the subjects that discussed the partitioning machine parts, how to work a motorcycle engine and troubleshooting the machine parts as well as how to repair or replace spare parts, students felt the use of Ms. media. Powerpoint is less interesting and difficult to understand the material. Educators also see students tend to get bored easily when learning so that they need other alternatives as a learning medium. For that reason, the writer applies a markerless augmented reality technology as a medium for learning two-wheeled vehicles to help as well as learning media for students, the method used is MDLC (Multimedia Development Life Cycle). This research produces an augmented reality application that helps visualize motorcycle engines in the form of 3D models for vocational students.
Penerapan Hidden Markov Model (HMM) dan Mel-Frequency Cesptral Coefficients (MFCC) pada E-Learning Bahasa Madura untuk Anak Usia Dini

Bahasa Madura is a regional language used in Madura island. This language has many variations of pronunciation and dialect that makes it not easy to learn, even by the local people especially children. There hasn’t been any interesting learning media to learn Bahasa Madura so far. In fact, a fun learning activity is needed to help children to enhance their ability in pronouncing animals’ names, numbers, fruits and things in Bahasa Madura. Thus, it’s considered important to create Bahasa Madura e-learning by implementing the recognition of voice patterns in order to make it easier for the children to learn Bahasa Madura which has several variations of pronunciation only for one single object. This Bahasa Madura e-learning application for young learners is used to introduce Bahasa Madura vocabularies by recognizing the voice pattern recordings which have been processed through MFCC technique as the extracted voice features and HMM as the learning techniques. The implementation of MFCC and HMM as the learning tool to introduce the pronunciation of regional language vocabularies especially Bahasa Madura has never been done before. Therefore, this research is expected to help the young learners to be able to pronounce Bahasa Madura vocabularies properly. In this study, a number of young learners’ voices were recorded and were set as the trial data. Only the proper voice data that were used—voice data that were considered to be pronounced correctly. The trial method was done through one-single model and multi-model. After doing several simultaneous trials, the result showed the accuracy level. The average accuracy level for one-single model system was 73% (with the highest accuracy reached 75%) and the average accuracy level for multi-model system was 80% (with the highest accuracy reached 81%).
Multi Parameter Design in AIML Framework for Balinese Calendar Knowledge Access

Balinese calendar is defined as a unique calendar system for combining solar-based and lunar-based system and assuming local system.It is considered as guidance of Balinese societies' activities management, starting from meeting arrangement, wedding ceremony, to religious ceremonies.Practically, it has developed in the form of printed Balinese calendar and electronic Balinese calendar, either web or mobile application.The core of the function is to find out the day with its various characteristics in the Balinese Calendar.In general, society usually asks the religious leader to find out the day in detail.The technology of NLP combined with models of pattern discoveries supports the arrangement of the interaction model in searching the good day in Balinese Calendar to equip the conventional searching system in the previous applications.This study will design a dialog model with AIML method in multi-parameter basis; therefore, the users will be dynamically able to use the searching content in various ways by chatting in similar with consulting to a religious leader.This model will be applied in a chatbot basis service in telegram machine.The addition of the context recognition section into 4 paterns has been successfully improve the ability of AIML to recognize input patterns with many criteria.Based on the testing with 50 random input patterns obtained a success rate of 92.5%.
Web Service Classification using Stacking

The problem of web service selection is an important problem from engineering perspective. Quality of Service (QoS) based selection of web services is a popular technique. However, the QoS based selection techniques have their own limitations. Therefore, the Classification of web services before selection can be useful. Two datasets are used for analyzing and obtaining the results. In this paper, we have compared various web service classification techniques and found that stacking is most suitable technique to be applied for classification of web services. The accuracy of stacking is found to be 86.53.
Mixing Preshared Keys in IKEv2 for Post-quantum Security

The possibility of quantum computers poses a serious challenge tocryptographic algorithms deployed widely today. IKEv2 is one exampleof a cryptosystem that could be broken; someone storing VPNcommunications today could decrypt them at a later time when a quantumcomputer is available. It is anticipated that IKEv2 will be extendedto support quantum-secure key exchange algorithms; however that is notlikely to happen in the near term. To address this problem beforethen, this document describes an extension of IKEv2 to allow it to beresistant to a quantum computer, by using preshared keys.
COBRA: COllaborative Bot with multi-Rotor Actuation

Wheeled robots operating in the field are faced with mobility challenges such as drop-offs, slippery slopes, and cluttered environments. In these situations, it is desirable to have agile and highly mobile platforms. This paper explores the utilization of multiple rotors to enhance the mobility of ground vehicles. A strategy based on downward thrust generation is developed to increase traction and surmount otherwise non-traversable slippery inclines. Both simulation and experimental results are presented to show the efficacy of the proposed solution.
A-EXP4: Online Social Policy Learning for Adaptive Robot-Pedestrian Interaction

We study self-supervised adaptation of a robot's policy for social interaction, i.e., a policy for active communication with surrounding pedestrians through audio or visual signals. Inspired by the observation that humans continually adapt their behavior when interacting under varying social context, we propose Adaptive EXP4 (A-EXP4), a novel online learning algorithm for adapting the robot-pedestrian interaction policy. To address limitations of bandit algorithms in adaptation to unseen and highly dynamic scenarios, we employ a mixture model over the policy parameter space. Specifically, a Dirichlet Process Gaussian Mixture Model (DPMM) is used to cluster the parameters of sampled policies and maintain a mixture model over the clusters, hence effectively discovering policies that are suitable to the current environmental context in an unsupervised manner. Our simulated and real-world experiments demonstrate the feasibility of A-EXP4 in accommodating interaction with different types of pedestrians while jointly minimizing social disruption through the adaptation process. While the A-EXP4 formulation is kept general for application in a variety of domains requiring continual adaptation of a robot's policy, we specifically evaluate the performance of our algorithm using a suitcase-inspired assistive robotic platform. In this concrete assistive scenario, the algorithm observes how audio signals produced by the navigational system affect the behavior of pedestrians and adapts accordingly. Consequently, we find A-EXP4 to effectively adapt the interaction policy for gently clearing a navigation path in crowded settings, resulting in significant reduction in empirical regret compared to the EXP4 baseline.
Real Time Data Plotting Tool using Open Source Platform like Raspberry Pi and Python

Various solar PV panel parameters like temperature, voltage, current, power, etc. vary with time and this variation should be recorded so that a control/precautionary action can take place at a defined point of time or in real time. This paper presents work on an embedded platform which can have for a sensor network interface and the real time display of the senor readings. The developed real time data plotting system presented in this paper comprises of Arduino and Raspberry Pi, both available as open source platform. The embedded platform developed for real time data plotting senses and display the variations in the parameters of interest (like temperature, voltage, current etc.) based on connected sensor type at the input of the system. The system also stores the data in comma separated values (CSV) file format which can be used for comparison with real time data in display interface or for future analysis.
Bayanno-Net: Bangla Handwritten Digit Recognition using Convolutional Neural Networks

Handwritten digit recognition is one of the most novel topics from last few years. The complexity of recognition handwriting are differ in languages because of their shapes, character numbers and streak. Albeit Bangla is the 7th most popular language in order to the number of first language speakers. Remaining approaches use discrete feature expulsion methods and algorithms to recognize handwritten digits. Recently, Deep learning and convolutional neural network is used to solve the classification problem, it gives better accuracy for image classification with its distinct features. In this paper, we have proposed a Convolutional Neural Network referred as “ByannoNet”, to identify Bangla hand-written digits. We worked with the richest and popular dataset called NumtaDB generated and published by the Bengali.ai community. Our proposed model has achieved 97 percent accuracy with a very low cross-entropy rate.
A Morphological Study of Affixes Used by Major and Minor Characters in the Novel Through the Looking Glass

This research is entitled A Morphological Study of Affixes Used by Major and Minor Characters in the Novel Through the Looking Glass. The objectives of this research are to identify the affixes, to find out the derivation and inflection changes used by characters in the novel Through the Looking Glass and to find out the most dominant affixes. The method of this research is qualitative research. The results of this research are: (1) affixes found at major characters are suffix, prefix, and confix. Afterward, affixes found at minor characters are suffix and prefix, (2) this research found 40 derivations and 85 inflection used by major characters. Besides, this research found six derivations and 17 inflections used by minor characters, and (3) the most dominant affix found at characters are suffix. In total of suffixes used by major character, there were 31 –ing, 10 –ly, 42 –s, 3 –y, 3 –able, 2 –ation, - -d, 15 –ed, 4 –er, 3 –es, 1-est, 2 –ful, 1 –ination, 1 –ish, 3 –ment, 1 –ness, 1 –or, 1 –ous, 1 –t, and 1 -th. Afterward, suffix found at minor characters there were 1 –ance, 4 –ing, 2 –es, 10 –s, 1 –ly, and 1 –ed.
Intelligent assistants in language learning: friends or foes?

We have entered the age of everyday encounters with artificial intelligence. Intelligent assistants (IAs) are increasingly available when educational activities are carried out using a portable or wearable device. These developments have special implications for language learners, many of whom now have access to immediate assistance, to artificial conversational partners, as well as to a large repertoire of smart tools and services to help them with specific challenges in communication and language learning. The rise of IAs can be seen against a backdrop of increasing opportunities for technology-supported and informal learning both inside and outside the classroom. This emerging learning landscape confronts language teachers with some difficult questions around adaptation of pedagogical methods and teachers’ changing roles, that need to be better understood. IAs might be used to support learning or they might be misused. Are they friends or foes? The paper discusses the significance of IAs available to many learners on their smartphones and looks towards a future when they will be available even more widely and when intelligent robots will be used; it considers some of the capabilities of IAs in relation to challenges in language learning as well as the concerns they raise. Finally, the mobile learning community is urged to direct more research efforts towards this complex topic.
Analysis of Core Concepts and Achievement Standards in 'Home Life' in Practical Arts Curriculum For the Connection and Convergence Lesson Plan of Practical Subjects

이 연구는 실과에서 연계·융합교육을 계획할 때 수업 설계의 방향에 도움을 주고자 2015개정 실과 교육과정 ‘가정생활’ 분야의 핵심개념과 성취기준을 분석한 것이다. 구체적으로 ‘가정생활’ 분야의 6개의 핵심개념의 교육적 의의를 살펴보고, 성취기준의 키워드를 추출하였다. 추출된 43개의 키워드와 타 교과의 성취기준 키워드와 비교하여 7개의 공통된 키워드를 제시하였다. 이 중 동일하거나 유사하게 나타나고 있는 공통 키워드는 ‘가족, 가족 역할, 배려와 돌 봄, 안전사고, 안전, 환경, 시간관리방법’ 이었다. 공통 키워드를 제시하고 있는 교과는 주로 도덕과, 사회과, 체육과, 과학과였다. 실과에서 타 교과와의 연계·융합수업을 계획할 때는 공통된 성취기준 키워드를 중심으로 전개될 때 그 타당성과 효율성이 확보될 수 있다. 이 때 해당 성취기준의 난이도와 범주를 고려해야 하고, 성취기준의 지향에 따라 수업의 방향이 달라질 수 있으므로, 실과 본래의 내재적 목표를 달성할 수 있도록 계획하여야 한다. 이를 위하여 성취기준이 포함된 실과 핵심개념의 교육적 의의를 의식할 수 있어야 할 것이다. 또한 실과의 연계·융합교육이 효과적으로 이루어지기 위해서는 다양한 교수학습방법과 평가방법이 동시에 모색되어야 할 것이다.The purpose of this study is to analyze the key concepts and achievement criteria in the Revised Life section of the 2015 revised curriculum in order to propose the direction of instructional design when planning connected and converged education in the classroom. Specifically, we examined the educational significance of six key concepts in the field of family life and extracted keywords of achievement criteria. Seven common keywords were presented in comparison with the extracted 43 keywords and the achievement criteria keywords of other subjects. Among these, the same or similar common keywords were family, family role, consideration and care, safety accident, safety, environment, and time management method . The subjects suggesting common keywords were moral, social, physical and scientific. In the lesson, when planning linking and fusion classes with other subjects, the feasibility and efficiency can be secured when they were developed around the common achievement criteria keywords. In this case, the difficulty and category of the achievement standard should be considered, and the direction of the class can be changed according to the orientation of the achievement standard. To this end, it is necessary to be able to be aware of the educational significance of the core concepts and the facts that include achievement standards. In addition, various teaching and learning methods and evaluation methods should be simultaneously searched for effective connection and convergence education.
MOBILE ASSISTED LANGUAGE LEARNING: INCREASING STUDENTS’ READING INTEREST TROUGH E-BOOK

The purpose of this article is to review theories and previous studies about the potential offered by e-Book to increase students’ interest in reading. In Indonesian context, where English serves as a foreign language, the problem is the students tend to have low reading habits. According to PISA, by the level of literacy in Indonesia ranks the second lowest from 61 countries. Another fact shows that Indonesia is the country with the fourth largest active smartphone users in the world after China, India and America.one of the alternative ways to deal with this problem is that students must be directed to read text on the screen through online application like e-Books. This article then will discuss deeper about the theory of reading and e-Book, the reason why using e-Book as media of learning reading and how to use e-Book in reading class. Some previous research highlighting the effect of e-Book on the students’ reading interest and how e-Book can increase students’ reading interest will be the next discussion. This paper finally presents conclusion and pedagogical implication as the closing remarks.
Automated Extraction of Parasite in the Microscopic Images by Distance Regularized Level Set Evolution initialized with Hough Transform

The analysis of biomedical microscopic images is carried out manually in medical laboratories.The manual analysis of clinical images lets to both repetitive tasks and management of huge amounts of data.This is tedious and times consuming for laboratory technicians.Inevitably, it is also prone to human errors.Our objective in this work is to contribute to the automation of the analysis of microscopic images of stools using Distance Regularized Level Set Evolution (DRLSE) automatically initialized by Hough transform.We firstly converted the microscopic images to edge maps using canny algorithm.Next, we located the parasite through circular Hough transform and draw circles around them.Those circles stand as initial contours of DRLSE.The contours evolve until they fit the boundaries of the parasites.The final extraction is performed using a complementary method based on the signed distance character of the level set function.The Distance Regularized Level Set Evolution (DRLSE) has been automatically initialized.We applied our method to the detection of intestinal parasites in microscopic images.Experimental results show accurate, efficient and less time consuming of our scheme compared to others recently proposed in the literature.This is a notable contribution to the automation of stools examination in the medical laboratories.In forthcoming works, we plan to include this segmentation process in an expert system of parasitic diseases diagnosis.
Noetic end-to-end response selection with supervised neural network based classifiers and unsupervised similarity models

This paper describes a solution for the Noetic End-to-End Response Selection challenge – one of the tasks of the 7th Dialog System Technology Challenge. The goal of the task is to select the most appropriate continuation of a dialogue from a given set of responses. We approach this problem by building an ensemble of supervised neural network based classifiers and unsupervised similarity models. The dialogue continuation is selected according to a score that aggregates the rankings of candidate responses determined by the models in the ensemble.
$2$-Neighbour-Transitive Codes with Small Blocks of Imprimitivity

A code $C$ in the Hamming graph $\varGamma=H(m,q)$ is $2$-neighbour-transitive if ${\rm Aut}(C)$ acts transitively on each of $C=C_0$, $C_1$ and $C_2$, the first three parts of the distance partition of $V\varGamma$ with respect to $C$. Previous classifications of families of $2$-neighbour-transitive codes leave only those with an affine action on the alphabet to be investigated. Here, $2$-neighbour-transitive codes with minimum distance at least $5$ and that contain ``small'' subcodes as blocks of imprimitivity are classified. When considering codes with minimum distance at least $5$, completely transitive codes are a proper subclass of $2$-neighbour-transitive codes. This leads, as a corollary of the main result, to a solution of a problem posed by Giudici in 1998 on completely transitive codes.
Graph Compression Storage Based on Spatial Cluster Entity Optimization

Graph storage technology is confronted with an enormous challenge as far as the compact and complex graph-structure data. This phenomenon is derived from social networks with spatially intensive data. Since a hot event can cause the generation of a network cluster, which consists of a massive duplicate associated entities in the social networks, the space utilization and processing speed of graph data is obstructed. Therefore, it is necessary to design a graph storage mechanism specifically for the above data. In this paper, we propose a Graph compression Storage engine based on spatial Cluster entity Optimization (GSCO), which improves the native graph storage model through the proposed the many-to-one mapping structure and a Heat Evolution Elimination algorithm (H2E). Firstly, we define the spatial cluster entity formally and confirm the compressed storage objects. Then, we introduce the many-to-one relationship to transfer the mapping structure between the node and property. It compresses the data to raise the space utilization of the graph database. Finally, we propose the H2E algorithm that allows the representative nodes to be anchored an extended period in memory according to the heat evolution acceleration. It increases the hit rate and throughput and reduces the I/O operation by deleting the redundancy of data. Extensive experiments results show that the proposed GSCO storage model is better than Neo4j for reading and writing data in spatial clustering entity. It significantly promotes the effectiveness of graph operation, including the data loading, the common queries, and the clustering test.
Senior Scientists &amp; Valuable Data

Why is it important that Senior Scientists engage themselves in Open Science and particularly Open Data? Lars Figenschou, biologist and Academic Librarian at the University Library at UIT - The Arctic University in Norway, explains why. In addition, he gives us some good tips on how to create a program at the University that secures valuable data. The host of this episode is Erik Lieungh.&#x0D; This episode was first published 1 October 2018.
A k-Nearest Neighbor Algorithm Based on Homomorphic Encryption

Protection of privacy has become an essential problem in cloud platform security. In many cases, data is shared with the third party for the analysis purpose. However, the sharing of data for analysis is not safe. Fully homomorphic encryption (FHE) is very promising to deal with ciphertext without decryption, FHE has become one of the key technologies to improve the security of user sensitive information. In this paper, we solve the problem of privacy preserving k-Nearest neighbor classification (K-NN), which forms the basis of many data analysis applications. We propose a scheme FK-NN, which is based on homomorphic encryption and numerical comparator. In our scheme, the homomorphic subtraction operation is designed and implemented firstly. Then, the cloud calculates the nearest neighbors of a given data point while the data point as well as the data points in the training set are in encrypted form. We can obtain classification results which are in encrypted form. The correctness of the scheme has been shown over cardiac disease dataset. The results show the efficiency of the proposed scheme satisfy the requirements of the system and accurately classify data which is in encrypted form.