Reviewerly/exHarmony huggingface dataset:
Translating Swahili linguistic terminology into Italian

This article investigates the process of translating Swahili linguistic terminology into Italian as a way to reflect upon the metalinguistic representation of two different language structures. On the one hand, some terms of ancient Greek etymology, such as the English loanwords fonolojia ‘phonology’, fonimu ‘phoneme’, and mofimu ‘morpheme’, can be easily translated into Italian as ‘fonologia’, ‘fonema’, and ‘morfema’; on the other hand, some conceptual correspondences appear more problematic, especially in the field of morphology. There are terms that specifically refer to Bantu linguistic concepts, such as viambishi nyambulishi vya vitenzi ‘verbal extensions’, (it) ‘estensioni verbali’. Moreover, several synonyms that indicate the concept of “structure” (i.e. muundo ‘structure’, uambajengo ‘(syntactic) structure,’ tungo ‘construction’) have different uses according to the linguistic context; thus, I have suggested a translation based on the etymology (Tramutoli, 2018). The study is based on a corpus of approximately 150 linguistic terms mostly collected during Swahili linguistic lectures at the Department of Swahili Studies (TATAKI) at the University of Dar es Salaam.
User Experience Influenced Model for Comparing Application Development Tools

There are many possible tools to develop mobile applications with. Choosing a development tool is done by considering many different factors, and the choice is currently done, in many cases, arbitr ...
LibGuides: Multimedia Instructional Design: Reports

This guide is for the NCU certificate Multimedia Instructional Design. It contains resources available in the NCU Library.
LibGuides: Resources for Online Teaching and Learning: Agricultural & Food Sciences: Online Textbooks

This guide contains online teaching and learning materials for Agricultural and Food Sciences majors.
Suite per arpa

Author(s): Mercanti, Gabriele | Abstract: This music score was submitted for the Kaleidoscope 2020 Call for Scores, an open access collaboration with the UCLA Music Library.
LibGuides: Social Justice: Home

This LibGuide is intended for teachers of middle and high school students to gain background knowledge on the topic of social justice and discover resources that can be used in the classroom.
Letture e figure dal mondo

The article illustrates the results of the rearrangement, cataloging, historical and iconographic research of the section of foreign language texts in the Indire’s Youth Literary Fund, which includes about 300 volumes of monographs and periodicals, dating from the late 1700’s to the 1970’s. Texts difficult to find and, in some cases unique (often they aren’t present in the Italian and foreign online library catalogs), and to which we wanted to place particular emphasis on the rich and original illustrations.
Subject Guides: Creativity and Culture - Augustana Library: Modern Languages

Includes interdisciplinary resources related to Art, Drama, English, Modern Languages, Music, and Scandinavian Studies
IMPROVEMENT OF STUDENT LEARNING OUTCOMES USING DISCOVERY LEARNING MODEL FOR ELEMENTARY SCHOOL STUDENTS

This research is motivated by the low of student learning outcomes in class IV SD Negeri 09 Belakang Balok Bukittinggi.This study aim to describe the improvement of student learning outcomes on learning Civics by applying the model Discovery Learning on the fourth grade students SD Negeri 21 Bandar Buat Kota Padang . Type of research is PTK by using qualitative and quantitative approach. The result of student learning cycle I 75 increased to 85 in cycle II. Thus, the learning of Civics by applying the Discovery Learning model on can improve the learning outcomes of Civics students grade IV SD Negeri 21 Bandar Buat Kota Padang. Key Word :Result study, PKn, model discovery learning
UMC Library: Online Learning: Library Collections

A research guide aimed at supporting online learning at the University of Minnesota, Crookston.
Library Guides: Iowa State University Library Guide for New Students: Technology for You

A quick look at the ISU library study spaces, technology and services that are available to ISU Students
Stay Gold: Ottawa University Literary Journal: Resources for Remote Learning: Low-Cost Internet for Students

These resources are provided by the Instructional Design and Academic Technology Team to help you use the tools needed for attending class and learning at a distance.
Innovation Trends of Digital Forensics –Cybercrime

Digital forensic  has  progressed  maneuvering easy computer crimes to research of elaborate circumstances that can become effect that is worldwide significant The success is studied by this paper for the  Digital forensic; its   origins, its present point also its tips being future. This paper sets the scene with checking out literature in which past methods are electronic may be forensic closely by the assessment and study of current condition of art both in professional  and forensics which can be educational The paper finally concludes with offering future trends in this arena.
Optimizing a software build system through multi-core processing

In modern software development, continuous integration has become a integral part of agile development methods, advocating that developers should integrate their code frequently. Configura currentl ...
Pengaruh Cerita Anak Bergambar Terhadap Kemampuan Berbicara Siswa Kelas 2 SD Negeri Gugus 1 Kota Bengkulu

The purpose of this study is to determine the effect of illustration children's stories on students' speaking abilities . This research is quantitative. The method used is a quasi experimental design with the matching only posttest group design. The population in this study was the cluster 1 SD Negeri Bengkulu City. The sampling technique uses cluster random sampling. The sample in this study was class 2B SD Negeri 1 Bengkulu City as an experimental class and class 2B SD Negeri 7 Bengkulu City as a control class. The instrument used in the study was the observation sheet of speaking ability. Data collection techniques based on posttest results using observation sheets. Data analysis techniques are by looking for means (mean) and variance, normality test with the Liliefors formula, homogeneity test and t-test. Based on the results of the normality test that the data are normally distributed. The experimental class obtained a speaking ability score with a percentage of 78.1% in the very good criteria , while the control class spoke the ability to speak with a percentage of 64.6% in the good criteria. The t-test results showed that Ha was accepted and Ho was rejected because t count > t table with t count 13,6 and t table 12,8 which means that there was an influence of children's picture stories on students' speaking abilities
Design and Fabrication of a Work Desk with Integrated Charging Ports, Desk Lamp and Storage Capability

Abstract This paper presents the design, development, and fabrication of a new work desk with integrated charging ports, desk lamp and storage capability for students’ use at the Outdoor Discovery Centre (ODC) hub at Jerudong International School (JIS), Brunei Darussalam. It contains a solar-powered lamp to provide light for students while conducting projects in the hub and storage compartments for students to place their belongings. It can organize and store wires, solar charge controllers, and switch box of a solar power system. Removable fans can be connected to the desk for students’ comfort. Charging ports are provided in the desk to charge electronic devices. The dimensions of the desk are based on anthropometric data of students of ages 14 - 18 years old. Feasible concepts of the product are generated and the final concept is selected based on product specifications such as aesthetics, cost, function, size, materials, environment-friendliness, and safety. The product is termed a better solution for use in ODC hub by its in-charge, Miss Follows Smith and the in-charge of renewable energy project at JIS, Dr. Lloyd.
An Overview On Systems Creating Summary Based On Natural Language Processing

Because of the exponential development of printed data accessible on the Web, end clients should have the option to get to data in synopsis position. There are two sorts of outline for example abstractive and extractive rundown. Programmed making of drawing outlines from a solitary report has generally been given the test of removing the most fitting sentences from the first record. The strategies worked by and large to dole out a position to each sentence in the report, considering certain highlights. The most proper sentences are then chosen, as indicated by the rank acquired for each sentence. These highlights remember the situation of the sentence for the record, its significance to the title, the sentence length, and the recurrence of the terms in the sentence. Notwithstanding, it has still not been conceivable to achieve a nature of rundown that coordinates that performed by people and in this way strategies keep on being presented that have objective to improve the outcomes. The principle reason for this paper is to study the current content outline models and to recognize a decent methodology that assists with growing new content synopsis framework.
A Novel Task Scheduling DSJF algorithm with K means clustering and Honey Bee Load Balancing Technique in Cloud Computing

Cloud computing (CC) is fast-growing and frequently adopted in information technology (IT) environments due to the benefits it offers. Task scheduling and load balancing are amongst the hot topics in the realm of CC. To overcome the shortcomings of the existing task scheduling and load balancing approaches, we propose a novel approach that uses k means clustering and DSJF algorithm for task scheduling. In this paper, load balancing algorithm based on honey bee behaviour (LBA_HB) is proposed. Its main goal is distribute workload of multiple network links in the way that avoid underutilization and over utilization of the resources. Many scheduling algorithms have been proposed to schedule the tasks in cloud computing environment such as (SJF) and (FCFS) algorithms. This paper aims to improve the shortest job first scheduling algorithm in the cloud computing. In tasks scheduling (TS), the most important parameters are makes pan and response time. The proposed task scheduling technique is compared with the existing Heterogeneous Shortest Job First (DSJF) technique in terms of a) Make span time, b) Processing Time, c) Processing Cost, d) Execution Time.
LibGuides: Nutrition and Healthy Eating for Kids: Home: Start Exploring!

A guide for kids to find resources on the food groups, healthy eating, and making informed decisions.
COMPRESSION OF GENOMIC SEQUENCES BASED ON BURROWS-WHEELER TRANSFORM: A SURVEY

Abstract: With increasingly complete genomes becoming available and the completion of the human genome in the horizon, fundamental questions have been increased regarding the characteristics of these sequences. In this paper, one of the basic questions such as the compressibility of DNA or genomic sequences is discussed since the compression of DNA sequences is a very complex process. The primary objective of this study is investigating the approaches to genomic sequence data compression based on the Burrows-Wheeler Transform (BWT) algorithm. The BWT is an essential data structure of genome indexing which has several fundamental applications, but it is still non-trivial to constrict BWT for the huge collection of genomes. Therefore, this paper highlights some researches related to the compression of genomic or DNA sequence using BWT algorithm and is discussed briefly. In addition, a comparative analysis is carried out to observe the issues in those methods and proposed a modification in BWT to increase the further compression ratio while compressing the genomic sequence data.
LibGuides: Literally Awesome: E-Books

Need a book recommendation? Have a look here at some our our TC staff and student reviews to help you!
Blockchain Vending Machine: A Smart Contract-Based Peer-to-Peer Marketplace for Physical Goods

In this paper, we propose an autonomous vending machine that is governed by a public Blockchain and smart contracts platform.Set up as a decentralized autonomous organization, it serves as an open marketplace for physical goods, where anyone can buy and/or sell objects.We propose a basic architecture for the machine, analyze pricing and fee mechanisms and examine potential pitfalls.Moreover, we discuss open issues, possible extensions and further areas for improvement.We conclude that the deployment of such machines could significantly improve our understanding of decentralized autonomous organizations and build a bridge between virtual and physical markets.Insights gained from such an experiment may raise important questions for further research.
Den moderna skamstocken? : En diskursiv jämförelse mellan skamstraff och namngivningar kopplade till #metoo

In the #metoo movement some men were named in accusations of sexual harassment or sexual abuse. Some people compared the naming to a mob society and that was the inspiration behind this essay. The ...
Tracking of Multiple Closely Spaced Extended Targets Based on Prediction-Driven Measurement Sub-Partitioning Algorithm

For multiple extended target tracking, the accuracy of measurement partitioning directly affects the target tracking performance, so the existing partitioning algorithms tend to use as many partitions as possible to obtain accurate estimates of target number and states. Unfortunately, this may create an intolerable computational burden. What is worse is that the measurement partitioning problem of closely spaced targets is still challenging and difficult to solve well. In view of this, a prediction-driven measurement sub-partitioning (PMS) algorithm is first proposed, in which target predictions are fully utilized to determine the clustering centers for obtaining accurate partitioning results. Due to its concise mathematical forms and favorable properties, redundant measurement partitions can be eliminated so that the computational burden is largely reduced. More importantly, the unreasonable target predictions may be marked and replaced by PMS for solving the so-called cardinality underestimation problem without adding extra measurement partitions. PMS is simple to implement, and based on it, an effective multiple closely spaced extended target tracking approach is easily obtained. Simulation results verify the benefit of what we proposed—it has a much faster tracking speed without degrading the performance compared with other approaches, especially in a closely spaced target tracking scenario.
A Conceptual Framework for the Analysis of Multilayer Networks in the Humanities

If network analysis has made its way into the humanities toolbox, and especially in history (During et al. 2016), it is because it helps to grasp the complexity of the objects of these disciplines. However, to understand the multidimensionality of the data requires a consequent reflection on its modeling.This paper seeks to be part of a series of publications aimed at making advanced network analysis concepts more accessible to the humanities scholars: from ontological questions (Langmead et al. 2016) to the necessary discussion of the integration of temporality in graphs (Lemercier 2015; Conroy et al. 2019), the development of typologies of uses (Grandjean 2017a) or attempts to provide aids to interpretation (Grandjean & Jacomy 2019). The question of multilayer networks becomes especially more and more important, whether in a general way (McGee et al. 2016) or applied to the humanities (eg. Vugt 2017; Grandjean 2017b).Our purpose is to discuss a unifying conceptual framework allowing the transition between a current formal multilayer model (Kivela et al. 2014; Knudsen et al. 2019) and the language of the humanities. This framework is expressed by a visual representation that contains a multiplicity of layers that synthesizes and clarifies the different possible networks and facilitate the appropriation of the model by researchers.
Statistical Methods for the Forensic Analysis of User-Event Data

Author(s): Galbraith, Christopher Michael | Advisor(s): Smyth, Padhraic | Abstract: A common question in forensic analysis is whether two observed data sets originate from the same source or from different sources. Statistical approaches to addressing this question have been widely adopted within the forensics community, particularly for DNA evidence, providing forensic investigators with tools that allow them to make robust inferences from limited and noisy data. For other types of evidence, such as fingerprints, shoeprints, bullet casing impressions and glass fragments, the development of quantitative methodologies is more challenging. In particular, there are significant challenges in developing realistic statistical models, both for capturing the process by which the evidential data is produced and for modeling the inherent variability of such data from a relevant population. In this context, the increased prevalence of digital evidence presents both opportunities and challenges from a statistical perspective. Digital evidence is typically defined as evidence obtained from a digital device, such as a mobile phone or computer. As the use of digital devices has increased, so too has the amount of user-generated event data collected by these devices. However, current research in digital forensics often focuses on addressing issues related to information extraction and reconstruction from devices and not on quantifying the strength of evidence as it relates to questions of source. This dissertation begins with a survey of techniques for quantifying the strength of evidence (the likelihood ratio, score-based likelihood ratio and coincidental match probability) and evaluating their performance. The evidence evaluation techniques are then adapted to digital evidence. First, the application of statistical approaches to same-source forensic questions for spatial event data, such as determining the likelihood that two sets of observed GPS locations were generated by the same individual, is investigated. The methods are applied to two geolocated event data sets obtained from social networks. Next, techniques are developed for quantifying the degree of association between pairs of discrete event time series, including a novel resampling technique when population data is not available. The methods are applied to simulated data and two real-world data sets consisting of logs of computer activity and achieve accurate results across all data sets. The dissertation concludes with suggestions for future work.
Piece No. 3

Piece No. 3 explores communication and miscommunication. The texture is formed by a web of improvisatory communicative links between performers. Soft-synths are directed to respond to each other and to physical instruments, which in turn interact with each other. These links are built flawed however, as each part’s sonic content is only vaguely related to all the others’, the synthesiser controls are alien, and the nature of the interactions is combative. Recordings of a human voice underscore this, attempting to express frustration, disillusionment, and panic, but being able to only in fragments. Hopefully, the specific rules of interaction in the score are not central to fruitfully listening to the piece, and the (mis)communications between parts are audible to some degree. Further, while these connections create form and texture, and hold much meaning for me, the surface, the impression of the work is intended to reflect the messaging in the underpinning structures. Performed by members of the ANU Laptop Ensemble and Canberra Experimental Music Studio: Abigail Thomas, Weitong Huang, Lynden Bassett (laptops), Jaime Langer (keyboard, laptop), and Miles McLaughlin (banjo, laptop) at the Lonsdale St Studio.
N-Grams as a Measure of Naturalness and Complexity

We live in a time where software is used everywhere. It is used even for creating other software by helping developers with writing or generating new code. To do this properly, metrics to measure s ...
Scaling up data analytics in Python using multiple FPGAs

Big data applications are becoming more commonplace due to an abundance of digital data and increasingly powerful hardware. One of these classes of hardware devices are FPGAs, which are being used today in various ways such as data centers and embedded systems. High performance, power efficiency, and reprogrammability are the primary reasons behind their wide use. Another trend over the previous years has been to use distributed data processing frameworks such as Apache Spark to improve the performance of big data applications. Traditionally, such frameworks are deployed on commodity hardware to save costs. This approach is fairly popular, with organizations often having on-premise compute clusters or using a cloud provider to access a managed cluster. This project attempts to combine the above-mentioned worlds - FPGAs and dis- tributed data processing. We have designed an architecture that allows us to use FP- GAs as end-devices in a compute cluster to perform the actual computation instead of CPUs. This architecture is designed by composing together several open source technologies and allows us to interact with an FPGA cluster using Python. Using a high-level programming language such as Python makes this system easy to use for software developers and data scientists, and also abstracts away the internal commu- nication within the cluster. We have built prototypes based on this architecture for 3 hardware platforms (FPGA families) and 3 specific applications to demonstrate general applicability. We have observed noticeable performance gains in these applications by scaling up the FPGA cluster.
Martinus Scriblerus’s ‘Sevenfold Shield’

Martinus Scriblerus’s ‘Sevenfold Shield’ Melvyn New Melvyn New University of Florida E-mail: melnew@UFL.EDU Search for other works by this author on: Oxford Academic Google Scholar Notes and Queries, Volume 67, Issue 3, September 2020, Pages 414–415, https://doi.org/10.1093/notesj/gjaa107 Published: 23 July 2020
LibGuides: Library / Open Access Database Tools and Tips: Tools for Citing Sources

Most databases have common elements which help streamline your research and save time. This How-To guide shares tools and tips for using the library databases at ACC.
Autonomous navigation of mobile robot using shallow and deep neural network

Neural network provides an efficient solution for the manoeuvrability problems of autonomous mobile robots. Freire et al. (2009) studied the autonomous navigation of SCITOS-G5 (mobile robot) by training four types of neural networks to perform a classification task. The multi-layer perceptron (MLP) network gave the best performance in comparison to others (mixture of experts, Elman and logistic perceptron). In this paper, a different model of MLP network has been trained using the same training set whose performance is found to be better than that obtained by Freire, in terms of faster computations and a higher success rate. Also, since deep learning started gaining popularity in terms of its association with the neural network therefore, a recurrent neural network model is developed whose performance is compared to a simple MLP network. The results show that it gives superior performance, in comparison to the developed MLP network, using fewer training samples.
Foreign Language Learners' Interaction with Google Translate - Affordances Lost and Found

Google Translate and similar free online machine translation services are well-known to be frequently used by learners of foreign languages, albeit machine translation was not originally intended f ...