Reviewerly/exHarmony huggingface dataset:
Enhanced Fiilltterr-based SIFT Apprroach fforr Copy-Move Forrgerry Dettecttiion

Image forgeries are applied to give the digital images othermeanings or to deceive the viewers. Image forgeries appear inmany cases such as judges in courts, cybercrimes, military andintelligence deception, or defamation of important characters.There are many different types of image forgeries such as copymove forgery, image retouching, image splicing, image morphing,and image resampling. Copy move forgery is the widest type andeasy to apply between all digital image forgeries. Scale InvariantFeatures Transform (SIFT) algorithm is used strongly to detectcopy move forgeries due to its efficiency in digital image analysis.SIFT algorithm is extracting image features, which are invariant togeometrical transformations such as scaling, translation, androtation. These features are used in performing the matchingbetween different views of a scene or an object. This paperenhances the efficiency of using SIFT algorithm in detecting copymove forgery by two ways. Firstly, it enhances the image itself byapplying different types of digital filters to reinforce the imagefeatures giving the ability to detect forgeries. Butterworth low-passfilter, a high-pass filter, and the combination of them are appliedto this task. Secondly, the matching strategy is adapted based ona new thresholding approach to increase the true positive rateand decrease the false positive rate. Experimental results showthat the proposed approach gives better results compared withtraditional copy-move detection approaches. In addition, it gives better stability and reliability to different copy-move forgery conditions.
Scholarly Publishing Literacy at the University of South Florida Libraries: From Advising to Active Involvement

INTRODUCTION Successful open access (OA) publishing in libraries requires careful guidance and organization. Support and services offered vary depending on available resources as well as the robustness of a library’s publishing program. DESCRIPTION OF PROGRAM This article describes the connection between publishing services and scholarly publishing literacy through examples from the University of South Florida (USF) Libraries. The USF Libraries’ OA publishing program includes journals, textbooks, conference proceedings, and more. Our program balances advocating for open access with advising for actions that serve our partners’ goals. This invites trust, sustainable relationships, and opportunities for new work. NEXT STEPS At the USF Libraries, more work must be done to formally assess our efforts. Our program will also explore new ways to support the ethical standards expected of libraries by pursuing stronger policies on diversity and inclusion. Using everyday work to demonstrate best practices is a manageable way to strengthen scholarly publishing efforts. We hope to continue growing our services, empowering our partners, and exploring our roles as advisors and advocates.
Information literacy skill: An alternative to support biology student’s learning outcomes

Information literacy is a fundamental aspect to ease students in encompassing the knowledge-making process as well as empowering their capacity in using and creating various information and knowledge products. The purpose of this study was to determine the effect of integrating information literacy rubric with Project-Based Learning on students’ learning outcomes in Structure of Plant Development course. This quasi-experimental research used a non-randomized pretest-posttest control group design. The population in this study was the all biology department undergraduate students at the Universitas Negeri Malang in 2018/2019 academic year. The sample consisted of 120 students which were divided into two groups (control and experiment). The data gained was analyzed using one-way ANCOVA. The results showed that Project-Based Learning which was integrated with information literacy rubric had a significant impact on biology students’ learning outcomes. Based on the findings, it is suggested that educators should provide a proper strategy as an effort to support their students’ learning outcomes.
Bangla Spell Checking and Correction Using Edit Distance

Automatic spelling correction for Bangla language is a very important thing as the modern world is almost completely dependent on digital devices where electronic keyboards are used. Bangla is a largely used language (3.05% of world population), worldwide securing the 7th most spoken language. But concerning the natural language processing it is still in its initial stage. Automatic spelling correction of Bangla language is just crossing its primitive stage. A few works have been done on automated Bangla spelling correction but those numbers are not still adequate. This research work is based on correct word prediction of typed Bangla sentences by using edit distance method and fractional accuracy. The results are promising. So, there is a high chance that the proposed model will help and have a great impact on automated Bangla spelling correction.
Trust in universities as a factor for overcoming educational inefficiency

Modern higher education’s central issue – educational inefficiency among a considerable portion of students – is examined in close conjunction with developing relationships of trust within universities. The main goal of this article is to reveal the issue of educational inefficiency among Russian college students and to present trust within universities as a vital resource for solving the issue. The article interprets the basic concepts of trust within universities and students’ educational inefficiency. Trust within universities is shown to be a predictor for developing stable motivation in education, as well as students’ professional inclinations, which ultimately define success in education and human capital quality. Sociological analysis revealed the source of students’ educational inefficiency, as well as how it transfers through all levels of education – from preschool to university. Determined are the risks associated with an increase in the magnitude of students’ educational inefficiency and with an emergence of imitational strategies in universities, which serve to conceal this phenomenon. Brought forth is the issue of educational inefficiency being concentrated among students attending provincial universities. The authors maintain that “two-way” trust could become a factor in overcoming such inefficiency in universities – both on behalf of students towards other educational collectives, primarily the scientific-pedagogical community and administrative personnel, and coming from these university collectives towards students. This article reveals the main characteristics of such mutual trust, which can act as a resource for overcoming students’ inefficiency. Illustrated is the purpose for developing and fortifying trust within universities, based on the economic and socio-cultural necessity to transform those students who are experiencing trouble in the academic field into professionally and socially successful actors. The dominant idea in their life after university should be pursuing an aptitude for achievement in vital fields of activity.
Students� Perception of Digital Texts Reading: A Case Study at the English Education Department of Universitas Kristen Indonesi

This study was conducted to explore students' perceptions of reading digital texts. To attain the objective, the data were collected through an online questionnaire uploaded in Google Form and an interview. The questionnaire was intended to collect quantitative data concerning the participants� responses about their interest and motivation, digital text reading efficacy, problems in digital text reading, and preference towards digital or printed text reading. The participants of the study were 65 English pre-service teachers selected from the whole students of the English Education Department of Universitas Kristen Indonesia in the academic year 2019/2020, and the sample was 65 participants. The collected data were analyzed descriptively using Microsoft excel. The findings revealed that the participants perceived digital texts reading positively. They preferred reading digital texts because they were motivating, interesting, and suite their expected way of reading. The main problem they encountered in reading digital texts was due to the screen light which could irritate their eyes.
Evaluasi Layanan Teknologi Informasi ITIL Versi 3 Domain Service Desain pada Universitas Selamat Sri Kendal

&lt;p&gt;Information technology is a necessity for companies and organizations. To ensure the continuity of information technology business processes, it is also very necessary that companies get added value for their use. ITIL v3 is a method used to designing, ensure value is met, provide quality services, and ensure that the parts run as desired. Service design is used to assist companies in designing infrastructure, architecture, service quality, policies, and documents IT. ITIL v3 domain service design in this study is also used as a basis for developing information technology usage policies.&lt;/p&gt;
Statistical accuracy analysis of different detecting algorithms for surveillance system in smart city

&lt;span&gt;Several detecting algorithms are developed for real-time surveillance systems in the smart cities. The most popular algorithms due to its accuracy are: Temporal Differencing, Background Subtraction, and Gaussian Mixture Models. Selecting of which algorithm is the best to be used, based on accuracy, is a good choise, but is not the best. Statistical accuracy anlysis tests are required for achieving a confident decision. This paper presents further analysis of the accuracy by employing four parameters: false recognition, unrecognized, true recognition, and total fragmentation ratios. The results proof that no algorithm is selected as the perfect or suitable for all applications based on the total fragmentation ratio, whereas both false recognition ratio and unrecognized ratio parameters have a significant impact. The mlti-way Analysis of Variate (so-called K-way ANONVA) is used for proofing the results based on SPSS statistics.&lt;/span&gt;
Analysis Mobile Forensics on Twitter Application using the National Institute of Justice (NIJ) Method

Twitter is a social media that can be used on platforms using desktop, web, android smartphones and iOS, but lost of Twitter users are currently using the Android platform.The large number of Twitter user makes Twitter inseparable from crime or cybercrime, including pornography, online gambling, Hate speech, cyberstalking, cyber-tresspass, and cyberbullying.This research uses the method of the National Institute of Justice (NIJ).NIJ is a method with five stages, namely identification, collection, examination, analysis, reporting.This study uses two smartphones with different conditions, those are the rooted smartphone and the nonrooted smartphone.Evidence that has obtained from these two conditions will be read by a database using forensic tools.This research gives a comparison between the evidence with a smartphone that has been rooted and a smartphone that has not been rooted.The conditions of the rooted smartphone are found in the form of 2 user participants, 3 chat messages and 1 image, location, and profile of the perpetrators, while on the non-rooted smartphone only get 1 APK file.Evidence in the form of a conversation that obtained from a non-rooted smartphone proves the existence of the hate speech between the perpetrator and the victim.
Students’ Perceptions towards Using Mobile Application in Learning Speaking

The dramatic advancement technologies, particularly mobile applications, have influenced the education sector. The integration of mobile applications in education to change the teaching-learning process has taken place and led to innovative learning, including English language learning. Hence, this study aimed to find out the students’ perceptions and the factors influencing students’ perceptions toward the use of mobile application in learning English particularly speaking. To reach the objectives, this study used case study as the research method. The data were collected mainly through interview and observation. The participants were five vocational school students in Surakarta, Central Java, Indonesia. They were purposively selected because they had been familiar with mobile application and they had been taught speaking English using mobile application by their teacher, so that they could give adequate information. The research findings showed positive perception from the students toward the use of Learn English Conversation application in learning speaking. They declared that the use of Learn English Conversation application could facilitate them in practicing speaking, bring fun and enjoyable learning during the learning process. Moreover, their positive perceptions were influenced by several factors such as the flexibility and the new learning experience given by the mobile application, the ease to run the mobile application and unrequired a lot of internet quota when the students run the mobile application.
Penerapan Konsep Finite State Automata (FSA) pada Aplikasi Simulasi Vending Machine Yoghurt Walagri

Language theory and automata is a theory that related to abstract machines which in there is Finite State Automata. FSA can be implemented in design of a vending machine. Vending machines in Indonesia operate mostly with products such as canned drinks, plastic bottles, coffee, snacks, and tickets. This research discuss about simulating application design of Walagri Yoghurt vending machine, a yoghurt produced by Biotechnology Departement at the University of Muhammadiyah Bandung, based on the implementation of Finite State Automata. The conclusion obtained in this study is that Finite State Automata can be used as a basic logic for making vending machine simulations.
Pengintegrasian Wahana Permainan Wisata Alam Ngarai Sianok dan Wisata Buatan MiFan Water Park Padang ke dalam Materi Fisika

Edupark is a park with a variety of rides and ecosystems that can be used as a learning tool. Ngarai Sianok, Bukittinggi is a national Geopark area that has a nature tourism vehicle and Minang Fantasy (MiFan) Padang Panjang Water Park is an artificial tourist game vehicle. In general, visitors to attractions only take advantage of the natural landscape or a vehicle to take photos, sports such as jogging, hiking, camping, family gathering or low impact outbound. Without them knowing it, there are many physics concepts in both natural and artificial games that can be used as learning resources by integrating into high school physics learning in the form of physics teaching materials or integrated in learning models. However, there are actually educa-tional values, especially the physical concepts contained in the game. The purpose of this study is to integrate Edupark Ngarai Sianok and MiFan Water Park because it remembers so many Physics concepts found in natural or artificial tourism. The process of collecting data through observation and study of literature. The results showed that Edupark physics could be integrated in learning physics according to the 2013 curriculum
Comparison of human detection using background subtraction and frame difference

Image processing is mostly used for exploring image behaviour. There are several steps in image processing. Image acquisition, pre-processing, feature extraction, and classification are the processes used for the detection of human movement based on high-level feature extraction (HLFE), in which HLFE was used for feature extraction in this paper. This study proposed the use of background subtraction and frame difference. This research was conducted to analyse the difference of background subtraction and frame difference methods based on movement of human. Movement of human detected by using feature extraction were centroid image technique used. Furthermore, support vector machine (SVM) was used for classification.
Visual Saliency Detection via Convolutional Gated Recurrent Units

Context is an important aspect for accurate saliency detection. However, the question of how to formally model image context within saliency detection frameworks is still an open problem. Recent saliency detection models designed using complex Deep Neural Networks to extract robust features, however often fail to select the right contextual features. These methods generally utilize physical attributes of objects for generating final saliency maps, but ignores scene contextual information. In this paper, we overcome such limitation using (i) a proposed novel end-to-end framework with a Contextual Unit (CTU) module that models the scene contextual information to give efficient saliency maps with the help of Convolutional GRU (Conv-GRU). This is the first work reported so far that utilizes Conv-GRU to generate image saliency maps. In addition, (ii) we propose a novel way of using the Conv-GRU that helps to refine saliency maps based on input image context. The proposed model has been evaluated on challenging benchmark saliency datasets, where it outperforms prominent state-of-the-art methods.
Gaussianity and typicality in matrix distributional semantics

Constructions in type-driven compositional distributional semantics associate large collections of matrices of size $D$ to linguistic corpora. We develop the proposal of analysing the statistical characteristics of this data in the framework of permutation invariant matrix models. The observables in this framework are permutation invariant polynomial functions of the matrix entries, which correspond to directed graphs. Using the general 13-parameter permutation invariant Gaussian matrix models recently solved, we find, using a dataset of matrices constructed via standard techniques in distributional semantics, that the expectation values of a large class of cubic and quartic observables show high Gaussianity at levels between 90 to 99 percent. Beyond expectation values, which are averages over words, the dataset allows the computation of standard deviations for each observable, which can be viewed as a measure of typicality for each observable. There is a wide range of magnitudes in the measures of typicality. The permutation invariant matrix models, considered as functions of random couplings, give a very good prediction of the magnitude of the typicality for different observables. We find evidence that observables with similar matrix model characteristics of Gaussianity and typicality also have high degrees of correlation between the ranked lists of words associated to these observables.
ON COMPUTATION AND GENERALIZATION OF GENER- ATIVE ADVERSARIAL IMITATION LEARNING

Generative Adversarial Imitation Learning (GAIL) is a powerful and practical approach for learning sequential decision-making policies. Different from Reinforcement Learning (RL), GAIL takes advantage of demonstration data by experts (e.g., human), and learns both the policy and reward function of the unknown environment. Despite the significant empirical progresses, the theory behind GAIL is still largely unknown. The major difficulty comes from the underlying temporal dependency of the demonstration data and the minimax computational formulation of GAIL without convex-concave structure. To bridge such a gap between theory and practice, this paper investigates the theoretical properties of GAIL. Specifically, we show: (1) For GAIL with general reward parameterization, the generalization can be guaranteed as long as the class of the reward functions is properly controlled; (2) For GAIL, where the reward is parameterized as a reproducing kernel function, GAIL can be efficiently solved by stochastic first order optimization algorithms, which attain sublinear convergence to a stationary solution. To the best of our knowledge, these are the first results on statistical and computational guarantees of imitation learning with reward/policy function ap- proximation. Numerical experiments are provided to support our analysis.
An Indicator-based Multi-Objective Optimization Approach Applied to Extractive Multi-Document Text Summarization

The massive amount of textual information on the Internet makes that automatic text summarization methods are becoming very important nowadays. Particularly, the purpose of extractive multi-document text summarization methods is to generate summaries from a document collection by, simultaneously, covering the main content and reducing the redundant information. In the scientific literature, these summarization methods have been addressed through optimization techniques, being almost all of them single-objective optimization approaches. Nevertheless, multi-objective approaches have gained importance because their results have improved the single-objective ones.On the other hand, in the multi-objective optimization field, indicator-based approaches have obtained good results in other applications. For this reason, an Indicator-based Multi-Objective Artificial Bee Colony (IMOABC) algorithm has been developed and applied to the extractive multi-document text summarization problem. Experiments have been carried out based on Document Understanding Conferences (DUC) datasets, and the obtained results have been evaluated and compared with Recall-Oriented Understudy for Gisting Evaluation (ROUGE) metrics. The results have improved to the ones in the scientific literature between 7.37% and 40.76% and 2.59% and 11.24% for ROUGE-2 and ROUGE-L, respectively.
Correction to: Semi-supervised Ladder Networks for Speech Emotion Recognition

The article Semi-supervised Ladder Networks for Speech Emotion Recognition written by Jian-Hua Tao, Jian Huang, Ya Li, Zheng Lian and Ming-Yue Niu, was originally published on vol. 16, no. 4 of International Journal of Automation and Computing without Open Access. After publication, the authors decided to opt for Open Choice and to make the article an Open Access publication. Therefore, the copyright of the article has been changed to © The Author(s) 2019 and the article is forthwith distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/ ), which permits use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
A Mobile Robot Platform for Search and Rescue Applications

In public emergencies such as nuclear accidents or natural disasters, an immediate and accurate overview as well as an assessment of the area is the basis of all coordinated plans and actions for the rescue team.The persistent lack of such information leads to high risks and casualties for rescue workers.Mobile robots help to minimize risks and support the rescue teams with urgent information, as well as with debris clearing and search and rescue operations.This work discusses the necessities and requirements of mobile robots in search and rescue (S&R) applications such as a nuclear disaster and evaluates an implementation based on the system architecture of the mobile S&R robot "Robbie" of UAS Technikum Wien.