Reviewerly/exHarmony huggingface dataset:
Machine-scored syntax (Roberts et al., 2020)

Purpose: The results of automatic machine scoring of the Index of Productive Syntax from the Computerized Language ANalysis (CLAN) tools of the Child Language Data Exchange System of TalkBank (MacWhinney, 2000) were compared to manual scoring to determine the accuracy of the machine-scored method.Method: Twenty transcripts of 10 children from archival data of the Weismer Corpus from the Child Language Data Exchange System at 30 and 42 months were examined. Measures of absolute point difference and point-to-point accuracy were compared, as well as points erroneously given and missed. Two new measures for evaluating automatic scoring of the Index of Productive Syntax were introduced: Machine Item Accuracy (MIA) and Cascade Failure Rate— these measures further analyze points erroneously given and missed. Differences in total scores, subscale scores, and individual structures were also reported.Results: Mean absolute point difference between machine and hand scoring was 3.65, point-to-point agreement was 72.6%, and MIA was 74.9%. There were large differences in subscales, with Noun Phrase and Verb Phrase subscales generally providing greater accuracy and agreement than Question/Negation and Sentence Structures subscales. There were significantly more erroneous than missed items in machine scoring, attributed to problems of mistagging of elements, imprecise search patterns, and other errors. Cascade failure resulted in an average of 4.65 points lost per transcript.Conclusions: The CLAN program showed relatively inaccurate outcomes in comparison to manual scoring on both traditional and new measures of accuracy. Recommendations for improvement of the program include accounting for second exemplar violations and applying cascaded credit, among other suggestions. It was proposed that research on machine-scored syntax routinely report accuracy measures detailing erroneous and missed scores, including MIA, so that researchers and clinicians are aware of the limitations of a machine-scoring program.Supplemental Material S1. Sample Index of Productive Syntax (IPSyn) output.Supplemental Material S2. CLAN sample transcript. Supplemental Material S3. IPSyn manual scores (based on Scarborough, 1990).Roberts, J. A., Altenberg, E. P., & Hunter, M. (2020). Machine-scored syntax: Comparison of the CLAN automatic scoring program to manual scoring. Language, Speech, and Hearing Services in Schools. Advance online publication. https://doi.org/10.1044/2019_LSHSS-19-00056
A Critical Overview of Desicion Making Support Systems for Complex Dynamic Systems

This paper analyses briefly the nature and state in modelling and controlling Complex dynamic systems (CDS) and of Intelligent Systems (IS) been related to Decision Support Systems (DSS) theories, research and applications. A brief historical review of DSS and how Artificial Intelligence (AI) has been embedded into the DSS and how this generated the interesting scientific area of Intelligent Decision Support Systems (IDSS). The challenge and absolute need for “Making Decisions” is briefly outlined. The challenge now is to make sense of DSS in ‘’Decision Making’’ by planning it in understanding context and by searching new ways to utilize other advanced methodologies to the challenging issues of CDS in the future. The possibility of using, Fuzzy Cognitive Maps (FCM) and Intelligent Systems (IS) in DSS is reviewed and analyzed. Some drawbacks and deficiencies of FCM are briefly presented and discussed. Open issues for future research of DSS and FCMs are outlined and briefly discussed.
On the Teaching Mode of the Integration of General Communication Technology and Command Specialty Based on TRIZ Theory

On the basis of combing the disadvantages of traditional teaching mode of general communication technology and command specialty, this paper innovatively uses TRIZ tool in integrated training teaching, and realizes the optimization of training mode through the reconstruction of teaching content, teaching mode, teaching means and assessment mode.
Outsourcing Computations to a Cloud That You Don't Trust

In many application scenarios, data need to be collected, stored and processed. Often sensitive data are collected from IoT devices, which are constrained regarding their resources, and, thus, remote, untrusted cloud servers are required to perform the computations. However, cloud computing raises many security and privacy concerns since cloud providers cannot be fully trustworthy. Data owners want their sensitive information to remain private and expect confidentiality guarantees; while users want to utilize the computations' results and desire correctness guarantees. Furthermore, in some cases, standard cryptographic primitives are not sufficient to ensure that there is no leakage of information. In this work, we focus on the problem of outsourcing joint computations from joint sensitive inputs to multiple untrusted servers, while at the same time achieving public verifiability (i.e., everyone can verify the correctness of the computed result). Additionally, we investigate how to avoid any leakage of information by providing differential privacy guarantees on the outsourced computation. More precisely, we introduce the notion of verifiable homomorphic secret sharing (VHSS) which allows multiple clients to outsource joint computations on multiple servers providing also the capability to verify the correctness of the computed result. We propose a concrete instantiation of VHSS for the function that computes the product of n secret inputs. Besides, we suggest three instantiations of computing the sum of n secret inputs by employing homomorphic collision-resistant hash functions, linearly homomorphic signatures, and a threshold signature scheme, respectively. Moreover, we design a protocol that provides both differential privacy and verifiable computation guarantees for outsourced computations.
Hardware realisation of an intelligent medical image watermarking

Digital intelligence features the competence to transmit data at a swifter measure with a substantially superior computing relaxation. Hindrance to this is the up rise of copyright transgression problems. In digital watermarking, novel consumer embeds a distinguishable imprint in the digital medium for eschewing franchise breach. A tunnelled version of the aforementioned methodology is medical image watermarking which primarily focuses on embedding of the watermark in a concerned medical pictorial. The writers have concerned on the realm of intelligent medical image watermarking. Medicative images like USG, CT scan, MRI and X-rays are utilised. An inkling of shovelling a masked image in juxtaposition to the novel medical paradigm has been insinuated. The binary mask used is primarily sectioned according to a fixed ratio and in accordance with a predefined intelligent schematic, the watermark bits are hidden in only a part of the sections to prevent distortion of the information pixels in the medical image. The entrenchment and excerpting epistemologies have been operationalised utilising FPGA. The image testing parameter outcomes are discernibly persistent. Furthermore, an analogy of the proposed approach against few germane methods ensures the supremacy of the technique put forward.
Jazz Arranging for Beginners – Part 1 [Tecniche di Arrangiamento Jazz per Principianti – Prima Parte]

In this introductory paper we discuss some simple 2 and 3-part arranging techniques, particularly suitable for jazz musicians.By exploiting the Diatonic Parallelism, we provide an explicit writing of the 2 and 3-part harmonization of 21 fundamental scales (or modes).The 2-part harmonization is carried out by using third and sixth intervals.The 3-part harmonization is carried out by resorting to triads (in root position, first and second inversion), in close and open (DROP2) form.In order to harmonize the so-called approach notes, we herein exclusively resort to the Chromatic Parallelism.josha.org
Interactive Data Visualization of Fuzzy Membership Functions and Fuzzy Clustering

Since the volume of currently available data is growing from day to day, it is necessary to design and implement tools for a fast and comprehensive gain of knowledge from datasets created with this data. We can use the visualization of data as one of these methods - it is human and easy to understand. The presented paper aims to design and implement web application, which can be used for interactive visualization of data gained from fuzzification algorithms and fuzzy clustering. In this application, the user can interact with the visualization system and change form of input data, parameters, and visualization method.
Invited Speaker 1: Navigation without GPS for Unmanned Aerial Vehicles

In recent years, research and development of unmanned aerial vehicles (UAVs) have gained much attention in the academic and industrial communities worldwide. Extensive research and development have been done for UAVs to operate in complex and unknown environments, especially in GPS-denied environments. Consideration of a wide range of factors needs to be observed in such environments. Control systems for the unmanned vehicles are required to integrate, not only the basic input-output control laws but also the high-level functionalities for perception, decision making and task scheduling. Software systems for unmanned vehicles are required to perform tasks from hardware driving to the management of device operations, and from traditional input-output control law implementation to sensing, task scheduling and event management. In this talk, in-depth research in the advanced autonomous systems on UAVs is presented, involving automate flight process in GPS-denied environments, such as below the forest canopy or indoor environments, in which a board range of sensing and navigation technologies have been used. The sensors and algorithms plan the drones' flight paths, make sense of where they are, and to ensure that they do not collide with obstacles. All these are done automatically with no human intervention. The proposed systems have been successfully tested in both simulations and real flight experiments. Several related applications of the autonomous systems on UAVs will also be presented.
PENGEMBANGAN BAHAN AJAR BERBASIS KOMIK UNTUK MENINGKATKAN PEMAHAMAN KONSEP PADA SUB TEMA 2 LINGKUNGAN SEKITAR RUMAHKU

Abstract: The development of thematic teaching materials for comic-based picture stories is one of the tools to help students understand learning. Facts in the field indicate that the learning process has not proceeded as desired, this is because the teacher and students only hold on the textbooks (student books and teacher books) provided by the teacher without being accompanied by supporting media when the teaching and learning process takes place so that children feel bored, unhappy, sleepy and lazy because there are no exciting media to support thematic learning in which there are several subjects. The purpose of this development is to produce products in the form of fun comic-based teaching materials making it easier for students to deepen the understanding of the environment around my home. The kind of research used by researchers is descriptive with qualitative and quantitative data analysis. This type of research is Research and Development, which refers to the Dick and Carrey model. The results of the research development of thematic teaching materials based on pictorial stories meet interesting criteria with the results of the content expert tests reaching 86% eligibility level, design experts reaching 92.5%, linguists reaching 80%, learning practitioners reaching 86%, and the results of field trials reaching 93 %, student learning outcomes on average post-test scores 72.68 and pre-test scores 97. From the explanation above, there are significant differences in student learning outcomes using thematic materials based on comic-based pictorial stories and those who do not use thematic-based thematic teaching materials pictorial. This shows that the product being developed has appropriateness of qualification because the concepts are in accordance with the characteristics of the child. Hence, the teaching material is suitable for use in learning.
A TSK Fuzzy System Based on the Rate of Change of Moving Average for Time Series Prediction

It is very difficult for nonstationary or nonlinear time series to establish a proper prediction model. In this paper, we propose a TSK FPS that uses the rate of change of MA of data as the predictor input. The LPF property of the MA stabilizes statistical characteristics of time series and the rate of change of them removes the monotonic increasing/decreasing tendency of the data, thereby overcoming the rule bias of the data. For the fuzzy partitioning of input space, CBKM using the correlation coefficient as the similarity index is applied. As a result, more appropriate rules to the attribute of data can be obtained. In order to verify the validity of the proposed method, simulations were performed on representative cases of nonstationary and nonlinear time series, respectively. The result of the simulation shows excellent performance and effectiveness of the proposed method.
Research Guides: Librarian Resources for Supporting Covid19 Remote Learning: Start

This guide is meant as a hub for tools and tips to help librarians and public service staff provide remote support to faculty and students during the Covid19 crisis.
An Image Inpainting Method Based on Adaptive Fuzzy Switching Median

Image inpainting is an important problem of image processing that has many applications. The goal of the image inpainting problem is to restore or fill the corrupted or missing regions of image. In this paper, we propose an image inpainting method based on the adaptive fuzzy switching median. The adaptive fuzzy switching median is to provide an accurate estimation for the values of corrupted pixels when there are many corrupted pixels on image. In the experiments, we implement the proposed method on an open dataset of real natural images. We utilize standard image quality assessment metrics such as the peak signal-to-noise ratio metric and the structured similarity metric to compare the inpainting result of the proposed method with other similar inpainting methods to prove its effectiveness. The proposed inpainting method is also extended to process colorful images.
A General Procedure for Improving Language Models in Low-Resource Speech Recognition

It is difficult for a language model (LM) to perform well with limited in-domain transcripts in low-resource speech recognition. In this paper, we mainly summarize and extend some effective methods to make the most of the out-of-domain data to improve LMs. These methods include data selection, vocabulary expansion, lexicon augmentation, multi-model fusion and so on. The methods are integrated into a systematic procedure, which proves to be effective for improving both n-gram and neural network LMs. Additionally, pre-trained word vectors using out-of-domain data are utilized to improve the performance of RNN/LSTM LMs for rescoring first-pass decoding results. Experiments on five Asian languages from Babel Build Packs show that, after improving LMs, 5.4-7.6% relative reduction of word error rate (WER) is generally achieved compared to the baseline ASR systems. For some languages, we achieve lower WER than newly published results on the same data sets.
COMMON ERRORS OF CONNECTOR IN WRITING PARAGRAPH

Second year students of English department in IAIN Bengkulu were still faced a lot of difficulties in learning English. Most of them still have difficulties in understanding grammatical rules and because of their lack understanding of writing English especially in using connector. They were still unable to write a good paragraph, even the smaller unit like a sentence correctly. This research was a case study, the objective of the study were to find out the common error of connector, the dominant error of connector in students writing paragraph and To find out the factors that caused error of connector in students writing paragraph. The researcher used descriptive qualitative research design, it was used to get the description about connector by analyzing, interpreting, and concluding. In this case, the researcher aimed to find out about the common errors of connectors particularly in using coordinate, subordinate, and correlative connectors made by students in writing paragraph. The object of this research was the the fourth semester students of English department in IAIN Bengkulu in the academic year 2014/2015. 19 students were taken as the respondent by using purposeful random sampling. The data were collected by using students written paragraph and an interview, then the researcher interpreted all the data and found that the most common errors of the fourth semester students of English department on IAIN Bengkulu in their writing paragraph was coordinate connector and which was occurred 57,8 % from the total number of error. The errors of connectors were identified based on “Writing Academic English” book written by Oshima and Hoque. From the total number of error in this study, the researcher found that 21,05 % of error was stringy sentence, 26,31 % was unparalleled, 15,78 % was comma splice, and 36,84 % was miss function. So the dominant factor of connector error in writing paragraph that made by the fourth semester students of English department on IAIN Bengkulu was caused by miss function of connector. The result was relevant with the interview, where the students admitted that the factor of error in using connector was because  they has lack knowledge about connector and its functions. moreover the students were not taught specifically about connector by the teacher.
TO THE PROBLEM OF MUSICAL THINKING: FROM THINKING ON AN INSTRUMENT TO THINKING WITH AN INSTRUMENT

The purpose of the work. The article explores the conditions and factors of the formation of musical and instrumental thinking and its influence on the general principles of musical cognitology. The methodology of research consists in the application of logical-semantic, historical-cultural, organizational, generalizing and musicological methods in their systemic unity. The scientific novelty of the work is to identify a specific algorithm for the development of musical thinking in the aspect of the specificity of instrumentalism, in particular in the movement from «thinking on an instrument» to «thinking on an instrument» in the context of the supersymbolic culture of the modern information society. Conclusions. It is proved that a musical instrument acts not only as an instrument for expressing a musical idea, but also as a thinking instrument for an instrumental musician and composer who owns an instrument (or relies on the sound absorption of a like-minded instrumentalist). Deepening the instrumentalization of composers, the absolutization of timbre with the semantization of specific «untranslatable» textural formulas in the search for a new sound, the strengthening of the role of the executive factor contribute to the birth of a new stage of thinking with sounds — thinking with an instrument, when the latter «tells» the composer the direction of figurative and intonational and dramatic development.
Webbdesign i Wordpress

This report describes an independent work in the Web Development program. The work is performed at a company called CHAMP CLOUD LTD. located in Sligo, Ireland. The purpose of the work is to give th ...
Figshare:?a proof of concept implementation

Presentation slides from Digital Science Showcase event held in Melbourne, Australia in February 2020. Jane Miller, Director, Digital Libraries and Repositories Deakin University breaks down Deakin University's Research Data and Repository Landscape.
Where Data Lives: NeSI, taonga and growing repository services

Data transfer and data sharing have been a part of NeSI's service catalogue for severalyears, but the service priority has always been in support of compute-intensive research(and related training & consultation). The launching of a national data transfer platform anda new relationship with Genomics Aotearoa have provided NeSI the opportunity to reevaluate its data service offering.A key project in the Genomics Aotearoa Workplan is bioinformatics capability (Project1811), which encompasses the development of a national genomics data repositoryincluding bespoke processes for Māori management of indigenous data, which is activelypopulated across all New Zealand genomics research activities.GA's functional requirements for this repository include securely storing, preserving andproviding mediated access to genomics data for the longer term. It is also intended that therepository be interactive and usable by a large number of NZ researchers. NeSI's earlyresponse has been to focus on implementing the base -level infrastructure requirements forthe repository while beginning to investigate platform options and prototype permissionsworkflows. This presentation will provide an update on progress to date, including storage and accessmanagement through Globus, and introduce topics from data publishing and discoveryservices (from simple metadata to interrogation of genome summaries), to indigenous datagovernance requirements, and longevity/persistence.ABOUT THE AUTHOR(S) Brian Flaherty is Data Services Product Manager at NeSI. He has a background in digital librariesdigital scholarship, research infrastructure & support and discovery services.
A probabilistic analysis of transactions success ratio in real-time databases

Nowadays, due to rapidly changing technologies, applications handling more data and providing real-time services are becoming more frequent. Real-time database systems are the most appropriate systems to manage these applications. In this paper, we study statistically the behaviour of real-time transactions under the generalised earliest deadline first scheduling policy (GEDF). GEDF is a new scheduling policy in which a priority is assigned to a transaction according to both its deadline and a parameter which expresses the importance of the transaction in the system. In this paper, we focus our study on the influence of transactions composition. Precisely, we study the influence of transaction distribution on the system performances and on approximation of transactions success ratio behaviour by a probability distribution. To this end, we have developed our RTDBS simulator and we have conducted intensive Monte-Carlo simulations.
e-Happiness Using RStudio Programming Language

The measurement of happiness that has existed so far is only describing the macro conditions of people's happiness.This study offers a product in the form of an assessment of happiness of a household (individual) Until now there has been no making of e-happiness assisted by the RStudio programming language.e-happiness is an assessment of happiness of a household in real time and fast, because it is built with a programming application.The basis for calculating happiness refers to the dimensions of happiness by the BPS Statistics-Indonesia.This study used the RStudio programming language, which is a programming language commonly used by academics and unpaid, so it is expected that this application can be used by anyone.the results of the assessment of household happiness are around the score 0-100, and the keyword from the happiness score is not possible is 0 or 100.