Reviewerly/exHarmony huggingface dataset:
Language Ability of Mild Intellectually Disabled (MID) Children: Case Study of Dina MaraMida in SLB Negeri 1 Padang

This study is a case study of mild intellectually disabled children. The purpose of this study is to describe the language skills of Dina Maradina as children with mild intellectual disability (MID). This research is expected to contribute educatively to actions that can be given to intellectually disabled children, especially mild intellectual disability to encourage increased language skills. At the stage of providing data, used the refer and proficient method. The basic technique used in this method is Teknik Sadap, followed by Teknik Simak Libat Cakap (SLC), Teknik Simak Bebas Libat Cakap (SBLC), Teknik Catat and Teknik Rekam as advanced techniques. Data analysis was carried out qualitatively in the form of a description of aspects of language disorders experienced by the subject of the research by describing various symptoms and language skills owned by the subject. The results showed that subjects with mild intellectual disability has good language skills. It has several disadvantages, such as the ability of subject in emotional control, the ability in focus and concentration control and the ability in language production in terms of writing production. The results showed the subject did not have a significant language disorder. The subject is able to communicate smoothly with the other person. This can be seen from the subject's ability to issue sentences that fit the context of the conversation. The subject is also able to show gestures, facial expressions, and usual expressions in accordance with the communication she does.&#x0D; &#x0D; Keywords: Language ability, intellectual disability, neurolinguistics&#x0D;
Emerging Technologies in the C-Suite

As I have said in the past, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Life in the C-Suite</i> is complicated. It is part political and part financial; part operational and part strategic; quiet and chaotic; and fun and tragic. It is not for the faint of heart: introverts need not apply. C-level executives also have stakeholders. Some are internal—like Boards of Directors—and some are external, like supply chain partners, vendors, and ultimately customers. Some stakeholders are aggregates, which we call brands. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Life in the C-Suite</i> is also tenuous: Some executives survive for a while and some for years. Certain skills, competencies, relationships, financial realities, and experience all determine how long the lease on the C-suite runs. Many of them are well beyond the control of the residents.
DARIAH-EU and ARTEC: Adding a unique feature to the profile of NTNU

Presentation given at UiT Digital Humanities Conference 2017
Electronic Forensics Deposit Model Based on Block Chain

Block chain has the characteristics of decentralization, openness, autonomy; information cannot be altered forged and so on. It is superior to centralized database in data security and data sharing. Many industries have actively carried out the application research of block chain. The judicial departments have very high requirements for data sharing and data security. The application of block chain is also feasible. This paper studies and analyzes the principle, types and development trend of block chain technology, and puts forward the value of block chain application in the management of judicial evidence data. Taking the case investigation evidence information management as an example, we constructed a "coalition chain" structure of evidence storage, consensus mechanism and block data structure, so as to realize the data sharing and security management within the coalition.
Good Choices for Deep Convolutional Feature Encoding

Deep convolutional neural networks can be used to produce discriminative image level features. However, when they are used as the feature extractor in a feature encoding pipeline, there are many design choices that are need to be made. In this work, we conduct a comprehensive study on deep convolutional feature encoding, by paying a special attention on its feature extraction aspect. We mainly evaluated the choices of the encoding methods; the choices of the base DCNN models; and the choices of the data augmentation methods. We not only quantitatively confirmed some known and previously unknown good choices for deep convolutional feature encoding, but also found out that some known good choices tune out to be bad. Base on the observations in the experiments, we present a very simple deep feature encoding pipeline, and confirmed its state-of-the-art performances on multiple image recognition datasets.
Extended hybrid approach for detecting spammers on Twitter

One of the biggest social networks is Twitter for providing message posting and use direct message services via “tweets”.366 million currently active users on Twitter, Is the second largest space to share common news or message post. These features are also used by spammers on Twitter, spammers are not new on Twitter. spammers must be detected in improving the quality of Twitter message services. In this spammer detected by using metadata, content, interaction, and community-based features methods. Tweet meta information extracted and analyzed based on user-id, tweets,tweet-time and tweet-type. Content Features are extracted based on user posting content with URL, Mention-tags and hash-tags. Interaction and community-based features are analyzed by following and follower information. The proposed approach to introducing network-based features for spammer ratio detection by using unique IP address based user classification. Spammers can be detected by analyzing their tweets based on the extended hybrid approach by using the random forest, decision tree, and Bayesian network on the Twitter dataset that has benign users and spammers.
Interactive Environment for Testing SfM Image Capture Configurations

In recent years 3D reconstruction has become an important part of the manufacturing industry, product design, digital cultural heritage preservation, etc. Structure from Motion (SfM) is widely adopted, since it does not require specialized hardware and easily scales with the size of the scanned object.However, one of the drawbacks of SfM is the initial time and resource investment required for setting up a proper scanning environment and equipment, such as proper lighting and camera, number of images, the need of green screen, etc, as well as to determine if an object can be scanned successfully.This is why we propose a simple solution for approximating the whole capturing process.This way users can test fast and effortlessly different capturing setups.We introduce a visual indicator on how much of the scanned object is captured with each image in our environment, giving users a better idea of how many images would be needed.We compare the 3D reconstruction created from images from our solution, with ones created from rendered images using Autodesk Maya and V-Ray.We demonstrate that we provide comparable reconstruction accuracy at a fraction of the time.
Image to Image Search using K-means Clustering

With the increase in the amount of information on the World Wide Web, it has become a difficult task of finding relevant information.More often, textual based search engines were used but there were very few search engines using which similar images can be searched all over the internet with an image as input.This method of finding information is called Content-Based Image Retrieval (CBIR).Commonly used engines for CBIR like Google Images, Yahoo!Images are based on textual annotation of Images.The images that form the result have to be previously tagged in order to appear as result.In this research, K-means clustering for segmentation of images into clusters have been studied and applied, thereby finding similar images without the need of labelling or tagging images in the database.
Model Training Task Scheduling Algorithm Based on Greedy-Genetic Algorithm for Big-Data Mining

With the coming of the big data age, data mining attracts more and more attention from all trades and professions. Due to the vast computation cost of data mining, the public service platform for big data mining has become the urgent needs, especially for the model training tasks. In this way, how to perform this kind of task scheduling becomes critical. This paper focuses on the assignment of tasks on multiple computing resources to optimize the total operation time. Firstly, a task scheduling algorithm based on the greedy and genetic algorithm is proposed to set the computation resource requirement for each task. Moreover, a greedy strategy is used to decide the task operation order and the assignment mapping between the tasks and the computation resources. Finally, the proposed algorithm proves to be efficient by several experiments.
INVESTIGATION OF LEADERSHIP AND CREATIVITY FEATURES OF TEACHER CANDIDATES

The purpose of this study was to investigate of leadership and creativity features of teacher candidates.The descriptive method was used in the study.Totally 787 teacher
Critical Security Mechanism Designed for Data Transmission in Wireless Sensor Networks using Hierarchical Cloud Server

The rapid advancement of pervasive computing, IoT and wearable systems, given rise to low-power internet-based systems in elimination of distance complications by application of Wireless Sensor Networks, which consists of sensor, server and Cloud servers to sense various environmental readings and monitor the condition based on the data. Due to the association of vital data, and transferring it over an insecure and public communication channel, there is a critical prerequisite for sensor authentication, data integrity and data privacy. In this context many researchers had proposed various schemes for user authentication and secure data transmission over Cloud server. In this paper we proposed a three-factor user authentication and key agreement protocol for cloud server and claimed that the proposed protocol is efficient, secure and lightweight. The experimental analysis shows that the proposed scheme is resistance to well-known cryptographic attacks. Though the proposed scheme resists major cryptographic attacks, after in-depth analysis, we demonstrate that the scheme overcome many security pitfalls such as failure to resist replay attack, known session-specific temporary information attack, and failure to resist stolen-verifier attack.
Editing Operators for Cross-Sectional Data-Sets

This paper describes an innovative methodology which automatically creates a 2D-axisymmetric finite element (FE) model of a quasi-axisymmetric component from its 3D CAD model.The process has been implemented as a script and uses the API to a commercial FE package.The calculation of a volume shape coefficients to be applied in the non-axisymmetric regions of the FE model, to account for the fact the region is not fully axisymmetric, is also described.In the paper, the methodology is demonstrated for a rotating blade of tapered profile analyzing and comparing both stresses and displacement.Excellent results are shown.
INTERACTIVE MULTIMEDIA ON LOCAL LANGUAGE LEARNING OF ELEMENTARY SCHOOL IN SURAKARTA CITY

This research about the use of interactive multimedia in Local Language Learning in the Elementary School in Surakarta region aimed to find out the effectiveness of the use interactive multimedia in the Wayang Purwa and Javanese script topics. This research applied research and development (R&amp;D) method with one-group pretest-posttest experimental design. The data were collected using tests. The validity test comprised of instrument and content validation. The results of the treatment to the third-grade students of SD Negeri Karangasem III Surakarta in the topic of Wayang Purwa showed that the average score in the pre-cycle, first cycle, and second cycle always increased. In the pre-cycle, the students' average score was 54.9 with the completeness percentage of 31.2 %. The average score after the treatment in the first cycle was 72.34 with the completeness percentage of 71.88 and in the second cycle was 81.27 with the completeness percentage of 90.63 %. The same results were also obtained in the topic of Javanese script in the second-grade students of SD Tunggulsari II Surakarta indicating that the average score of pre-cycle, first cycle, and second cycle always increased. The classical completeness percentage in the pre-cycle of 6.25 % increased to 56.25 % in the first cycle and 93.75 in the second cycle. The conclusion is that the used of interactive multimedia can improve the skills of Wayang Purwa storytelling and Javanese-script writing.
Idyllic and Apocalyptic in the Drama Composition of the Concert «The Garden of Divine Song» by I. Karabyts

The purpose of the article is to determine the essence of interaction between idyllic and apocalyptic in drama composition of the concert “The Garden of Divine Songs” by I. Karabyts (1971).The research methodology is based on the system of philosophical, general scientific as well as specially scientific methods. In particular, the reliance on the method of hermeneutic analysis is determined by fulfilling the tasks of decoding the philosophical and artistic contents of the Concert by I. Karabyts, created on the basis of the outstanding literary work of the Ukrainian Baroque — “The Garden of Divine Songs” by G. Skovoroda; the analysis method of the musical drama of the work is intended to establish the intonational symbols of the idyllic and apocalyptic in the artistic concept of the Concert for choir.Results оf the study lie in the determination of the artistic concept of the Concert as a confrontation between the idyllic and apocalyptic principles that enter the struggle for mastering the soul of the lyrical character; the establishment of intonational and poetic symbols of the idyllic and apocalyptic in the context of the choral work. Novelty of the study consists of the introduction of a scientific interpretation of the artistic concept in the Concert for I. Karabyts choir as a contest of symbols of the idyllic and apocalyptic for the soul of the lyrical character in the context of the latest rethinking of the Baroque picture of the world.The practical significance of the study is based on the possibility of using its results in such training courses as «History of Ukrainian Music», «History of Choral Performance», «Reading of Choral Parts», as well as in the process of preparing the Concert by I. Karabyts «The Garden of Divine Songs» for concert performance.Кeywords: idyll, apocalypse, concert, “Garden of Divine Songs”, composer’s interpretation, dramaturgy, musical and poetic symbolism.
Exploring task-agnostic, ShapeNet-based object recognition for mobile robots

This position paper presents an attempt to improve the scalability of existing object recognition methods, which largely rely on supervision and imply a huge availability of manually-labelled data points. Moreover, in the context of mobile robotics, data sets and experimental settings are often handcrafted based on the specific task the object recognition is aimed at, e.g. object grasping. In this work, we argue instead that publicly available open data such as ShapeNet can be used for object classification first, and then to link objects to their related concepts, leading to task-agnostic knowledge acquisition practices. To this aim, we evaluated five pipelines for object recognition, where target classes were all entities collected from ShapeNet and matching was based on: (i) shape-only features, (ii) RGB histogram comparison, (iii) a combination of shape and colour matching, (iv) image feature descriptors, and (v) inexact, normalised cross-correlation, resembling the Deep, Siamese-like NN architecture of Submariam et al. (2016). We discussed the relative impact of shape-derived and colour-derived features, as well as suitability of all tested solutions for future application to real-life use cases.
HYBRID MORTALITY PREDICTION USING MULTIPLE SOURCE SYSTEMS

The use of artificial intelligence in clinical care to improve decision support systems is increasing.This is not surprising since by its very nature, the practice of medicine consists of making decisions based on observations from different systems both inside and outside the human body.In this paper, we combine three general systems (ICU, diabetes, and comorbidities) and use them to make patient clinical predictions.We use an artificial intelligence approach to show that we can improve mortality prediction of hospitalized diabetic patients.We do this by utilizing a machine learning approach to select clinical input features that are more likely to predict mortality.We then use these features to create a hybrid mortality prediction model and compare our results to non artificial intelligence models.For simplicity, we limit our input features to patient comorbidities and features derived from a well-known mortality measure, the Sequential Organ Failure Assessment (SOFA).
Modeling Dynamics of Video Request Routing in Mobile Networks using Adaptive Scheme

3G and 4G equipment development has melodramatically increasing the mobile internet in the recent years. The devices like laptops, cellular mobiles and tablets using the mobile broadband internet like rise steeply. The most popular mobile presentation is the video streaming in the application of hypermedia. In a cost effective way, the big challenge is the quality to make obtainable these services to users. The above task is achievable by means of emerging the LTE (Long Term Evolution) in the world of mobile. With low latency and high data rates in the applications of multimedia the effective services is provided by the LTE equipment features. In this paper, we study and analyze the Quality of Experience (QoE) at the end user for Video on Demand (VoD) over the LTE network. To achieve this, we streamed High Definition (HD) videos based on H.264/AVC and these videos are delivered from foundation to destination using Transport Control Protocol (TCP) and User Datagram Protocol (UDP). Specifically, our study is about QoEassessment in terms of delay variation, packet loss metrics and provides performance assessment to characterize the impact of conveyance layer protocol in video streaming over radio systems like LTE.
Vocational college students’ common errors in EFL speaking performance

This research aims to find out the common errors made by students studying at one of the vocational colleges in Banda Aceh, Indonesia. The students’ opinions on their experiences of learning English, particularly in speaking, were also explored. This qualitative-quantitative research design was conducted by collecting some recordings of the students’ speaking performance, and distributing questionnaires on the process of teaching and learning EFL to be filled in by the participants. In the analysis, the data from the recordings were coded, transcribed, described and displayed in accordance with the students’ error items. Meanwhile, the analysis of the questionnaire employed a simple percentage calculation. From the speaking performance, the students in the speaking class produced two types of common errors, i.e. pronunciation and grammar errors. The common errors in their English pronunciation vary between the vowel and the consonant. The errors in vowel production were produced the most. Meanwhile, 70% of the students made errors in grammar on language tense and some on plural morphemes. From the questionnaire, it was revealed that even though the students tried to speak English well, all of them were aware and agreed that they made grammatical errors when speaking English.
Application of Intelligent Communication Power Operating System in Nuclear Power Plant

Communication power is often referred to as the heart of communication equipment, and the communication equipment also affects the stable operation of the power transmission and transformation, and even about nuclear safety in nuclear power plant. This paper introduces an intelligent communication power supply operation system, modularization of power systems. It has the characteristics of high reliability and convenient maintenance, comprehensive monitoring function; it can provide a more intelligent and reliable communication power supply system for nuclear power plants.
Speeding Up of the Complex Discrete Wavelet Transform by Using Lifting Scheme

It is well known that the Lifting Scheme (LS) allows us to design the fast calculation method of the Discrete Wavelet Transform (DWT).However, unfortunately, the LS can be only adopted for the wavelets having a compact support.For example, Meyer wavelet, which is a famous orthonormal wavelet basis, has no compact support.Additionally, the Complex Discrete Wavelet Transform (CDWT) is steady and useful for many signal processing applications, however, its imaginary part is constructed from the wavelets having no compact support.Therefore, we cannot adopt the LS for these analyses.In this study, we propose the design method of the LS filters for all the orthonormal wavelet bases without relation to having a compact support or not.We adopt our proposed method for the CDWTs using Meyer wavelet and Daubechies 6 wavelet, and confirm their steady analyses and fast calculation speeds.
An Emerging Role of Chatbot in Businesses as a Novel Interactive Tool

Chatbot enables the business people to reach their target customers using popular messenger apps like Facebook, Whatsapp etc. Chatbots are not handled by humans directly. Nowadays, Chatbots are becoming very popular especially in business sector by reducing the human efforts and automated customer service. It is a software which interacts with user using natural language processing, Machine Language and Artificial Intelligence. They allow users to simply ask questions which would simulate interaction with the humans. The popular and well known chatbots are Alex and Siri. This paper focus on review of chatbot, history of chatbot and its implementation along with applications.
Implementasi Algoritma Genetika Pada Perancangan Aplikasi Android Untuk Memprediksi Buta Warna

Color blindness is one of the decreasing diseases which is very difficult to determine its deterioration, whether a family member will suffer from color blindness or not, especially with the prediction of color blindness which has been using manual methods by calculating the inheritance formula. Genetic Algorithms have advantages over other traditional optimization algorithms. To implement a computerized method in predicting color blindness that can be used by many people, it is necessary to have a user-friendly operating system like the Android operating system. The test results show that the implementation of genetic algorithms in applications to predict color blindness produces more optimal predictions and their application to Android makes the application a user friendly application. Keywords: Heredity, Color Blindness, Genetic Algorithms, Android Application, Color Blindness Predictions