Reviewerly/exHarmony huggingface dataset:
Enhanced global optimization methods applied to complex fisheries stock assessment models

Statistical fisheries models are frequently used by researchers and agencies to understand the behavior of marine ecosystems or to estimate the maximum acceptable catch of different species of commercial interest. The parameters of these models are usually adjusted through the use of optimization algorithms. Unfortunately, the choice of the best optimization method is far from trivial. This work proposes the use of population-based algorithms to improve the optimization process of the Globally applicable Area Disaggregated General Ecosystem Toolbox (Gadget), a flexible framework that allows the development of complex statistical marine ecosystem models. Specifically, parallel versions of the Differential Evolution (DE) and the Particle Swarm Optimization (PSO) methods are proposed. The proposals include an automatic selection of the internal parameters to reduce the complexity of their usage, and a restart mechanism to avoid local minima. The resulting optimization algorithms were called PMA (Parallel Multirestart Adaptive) DE and PMA PSO respectively. Experimental results prove that the new algorithms are faster and produce more accurate solutions than the other parallel optimization methods already included in Gadget. Although the new proposals have been evaluated on fisheries models, there is nothing specific to the tested models in them, and thus they can be also applied to other optimization problems. Moreover, the PMA scheme proposed can be seen as a template that can be easily applied to other population-based heuristics.
New Combined Method to Improve Arabic POS Tagging

One of the important tasks in Natural language processing is the part of speech tagging. For the Arabic language we have a lot of works but their performances do not rise to the required level, due to the complexity of the task and the Arabic language characteristics. In this work we study a combination between twodifferent approaches for Arabic POS-Taggers. The first one isa maximum entropy-based one, and the second is a statistical/rule-based one. Furthermore, we add a knowledge-based method to annotate Arabic particles. Our idea improves the accuracy rate. We passed from almost 85% to almost 90% using our combined method, which seem promoter.
The Extension of Graph Convolutional Neural Network with Capsule Network for Graph Classification

In this paper we extend a graph convolutional neural network (GCNNs) which is the one of the existing state-of-art deep learning methods using the notion of capsule networks for graph classification.Through experiments, we show that by extending GCNNs using capsule networks can significantly overcome the challenges of GCNNs for the task of graph classification.
Impact of Advances in Mobile Technology on Higher Education in Developing Countries

Last few decades witnessed vast advancements in mobile wireless communication systems.Mobile wireless technologies have been developing gradually, giving birth to various different techniques that consist of a number of generations ranging from 1G to 5G.This paper investigates the radical and innovative changes in mobile telecommunication networks.Literature survey research approach was used.The impact of radical changes in telecommunication networks is highlighted.Research found that impact of technology advancements and their usage in higher education in emerging economies are both Positive and Negative.However, positive impacts are enormous and negative impacts are minimal comparatively.The study also found that such advancements in mobile communication networks have changed the definition of distance learning, from print media to digital and an interactive education.
Digital Approximations for Pseudo-Differential Equations and Error Estimates

We consider a discrete version of pseudo-differential operators and equations in appropriate discrete functional spaces. Using a special factorization for an elliptic symbol we obtain certain results on a solvability for such discrete equations and give a comparison between discrete and continuous solutions.
Using Transposition Padding to Get CCA2 Security From Any Deterministic Encryption Schemes

We study how to make any deterministic encryption scheme probabilistic and secure against adaptively chosen ciphertext attacks. A new transpositional padding encryption scheme is proposed, with which we construct a universal scheme, namely, a transpositional padding encryption scheme, which has three novel attributes: 1) it can pad a given plaintext into several different values once the randomness is chosen while the previous padding schemes only pad a given plaintext into a fixed value; 2) it introduces the randomness into a ciphertext without employing hash function or random oracle, and; 3) it enables the encrypted message to contain more useful information that may exceed the upper limit of plaintext space. Then, we give this encryption scheme an instantiation of RSA, which is proven to be indistinguishable under adaptively chosen ciphertext attacks without random oracle that assumes a variant of the standard RSA problem. The variant problem is a novel arithmetic problem, and it is weaker than the standard RSA problem.
Estimation of global solar radiation for Ikeja, Enugu and Kano, Nigeria

Estimations of global solar radiation based on a model of using normalized clearness index and normalized sunshine duration for a period of up to 25 years for Ikeja (06.39°N, 03.20°E), Enugu (06.28 0 N, 07.35 0 E), and Kano (12.03 N, 08.32E), Nigeria for each climatological stations were established.The monthly average total solar radiation was also estimated.The reliability index of the calculation varies from 2.4 to 2.6 percent.The overall results show that for Kano, the received radiation on the plane surface is higher than for Ikeja and Enugu.
Online Safety and Academic Scholarship: Exploring Researchers’ Concerns from Ghana

INTRODUCTION This paper investigates factors, including fears of cybercrime, that may affect researchers’ willingness to share research in institutional repositories in Ghana. METHODS Qualitative research was conducted to understand more about the experiences of Ghanaian researchers when sharing research in institutional repositories. Interviews were conducted with 25 participants, documents related to policy and infrastructure in Ghana were examined, and observations were held in meetings of information technology committees. FINDINGS The findings indicate that researchers are specifically concerned about three areas when sharing research online: fraud, plagiarism, and identity theft. DISCUSSION This paper adds to research that examines barriers toward using institutional repositories, and highlights the lack of basic preventative strategies in Ghana—such as training, security, and infrastructure that are commonplace in developed countries. CONCLUSION This study draws on findings from Bossaller and Atiso (2015) that identified fears of cybercrime as one of the major barriers to sharing research online for Ghanaian researchers. While several other studies have found that fear of identity theft or plagiarism are barriers toward sharing work in the institutional repository, this is the first study that looks specifically at the experiences researchers have had with cybercrime to understand this barrier more fully.
Empirical prior latent Dirichlet allocation model

In this study, empirical prior Dirichlet allocation (epLDA) model that uses latent semantic indexing framework to derive the priors required for topics computation from data is presented.The parameters of the priors so obtained are related to the parameters of the conventional LDA model using exponential function.The model was implemented and tested with benchmarked data and it achieves a prediction accuracy of 92.15%.It was observed that the epLDA model consistently outperforms the conventional LDA model on different datasets with an average percentage accuracy of 6.33%; this clearly demonstrates the advantage of using side information obtained from data for the computation of the mixture components.
Handwritten tifinagh character recognition using simple geometric shapes and graphs

&lt;p&gt;In this paper, a graph based handwritten Tifinagh character recognition system is presented. In preprocessing Zhang Suen algorithm is enhanced. In features extraction, a novel key point extraction algorithm is presented. Images are then represented by adjacency matrices defining graphs where nodes represent feature points extracted by a novel algorithm. These graphs are classified using a graph matching method. Experimental results are obtained using two databases to test the effectiveness. The system shows good results in terms of recognition rate.&lt;/p&gt;
Feasibility of estimating copper content using visible and near-infrared spectra of bedrock, weathered rock and soil - a case study of the Baogutu stock II, Xinjiang, China

Geochemical anomalies are important symbols for prospecting. To determine a new method for identifying geochemical anomalies rapidly, this study examines the possibility of using visible and near-infrared spectra of bedrock, weathered rock, and soil to assess copper content in the Baogutu stock II, Xinjiang, China. Partial least squares regression was employed to study the relationship between visible and near-infrared spectra and the ore-forming element contents of collected bedrock samples, weathered rock samples, and soil samples. More specifically, our study aims to achieve three objectives. First, to explore the correlations between the contents of different elements and the correlations between the visible and near-infrared spectra and the ore-forming element contents for the three sample types. Second, to evaluate the performance of the reflectance-based partial least squares regression model. The models for iron in bedrock samples and copper in soil samples were chosen for estimating copper content. Third, to assess the effectiveness of data transformation methods in the partial least squares regression model. In our case study, the square root-based models for iron in bedrock samples and copper in soil samples with coefficients of determination for prediction are 0.614 and 0.409 respectively, maximized the model performance. Therefore, it is evident that visible and near-infrared spectra can be an alternative method for estimating ore-forming element contents based on bedrock, weathered rock, and soil samples.
Codes over $\mathbb{Z}_{p}[u]/{\langle u^r \rangle}\times\mathbb{Z}_{p}[u]/{\langle u^s \rangle}$

In this paper we generalize $\mathbb{Z}_{2}\mathbb{Z}_{2}[u]$-linear codes to codes over $\mathbb{Z}_{p}[u]/{\langle u^r \rangle}\times\mathbb{Z}_{p}[u]/{\langle u^s \rangle}$ where $p$ is a prime number and $u^r=0=u^s$. We will call these family of codes as $\mathbb{Z}_{p}[u^r,u^s]$-linear codes which are actually special submodules. We determine the standard forms of the generator and parity-check matrices of these codes. Furthermore, for the special case $p=2$, we define a Gray map to explore the binary images of $\mathbb{Z}_{2}[u^r,u^s]$-linear codes. Finally, we study the structure of self-dual $\mathbb{Z}_{2}[u^2,u^3]$-linear codes and present some examples.
The study of security application of LOGO recognition technology in sports video

With the rapid development of information technology and network technology and the rapid popularization of computers and intelligent devices, network video media have gradually replaced traditional media and became the main carrier of information production, storage, dissemination, sharing, and use. However, digital information can be easily copied, modified, and disseminated, which leads to the problem of network video copyright theft which is very prominent. Aiming at the copyright problem of sports video, this paper proposes an idea of using LOGO to identify the copyright of sports video, which can automatically and effectively detect whether the video is genuine or not. Firstly, encrypted LOGO is added to the video by encryption technology, and then, LOGO recognition technology is used to distinguish whether the LOGO is missing in the video, so as to distinguish the legitimacy of the video. In addition, aiming at the shortcomings of traditional LOGO recognition technology, this paper proposes a LOGO detection and recognition technology based on convolution neural network. This method improves the traditional histogram algorithm, proposes an analysis algorithm based on non-uniform block HSV histogram, and introduces region weighting coefficients to extract key frames from the video. Then, the convolution neural network is used to extract the features of the key frames of the video. Finally, the features of the sample LOGO are matched to complete the LOGO detection and recognition. Simulation results show that the effect of feature extraction using convolution neural network is better. Compared with the traditional LOGO recognition technology, the LOGO detection and recognition technology based on convolution neural network proposed in this paper has better detection and recognition performance. It effectively detects the LOGO information in the video and realizes the recognition of whether the video is genuine or not.
STUDENTS’ PERCEPTION ON THE IMPLEMENTATION OF MOODLE WEB-BASED IN LEARNING GRAMMAR

Students in tertiary educational level in Indonesia, particularly at a state university in Centra Sulawesi are required to write a scientific paper as one of the requirements to complete their study period. The government even requires them to publish it in the academic online journal. It means that students construct it in the English language which students consider that writing an English article is difficult. Students produce several grammatical mistakes in their writing. They thought that learning grammar is such a difficult lesson and learning instruction is not interesting as teachers rely on one main resource. Nowadays, based on the researchers' investigation that there are several constraints that make the teaching-learning grammar is not effective and interesting; lack of references, time and space. While students need time to practice the language. Moodle as a part of information technology tools contributes to the solution to that constraint. After experiencing the grammar teaching-learning instruction, most students respond positive view toward the implementation of Moodle in the grammar teaching-learning process. Overall, almost all students respond that online learning instruction is needed.
THE IMPORTANCE OF CROSS-CULTURAL UNDERSTANDING IN FOREIGN LANGUAGE TEACHING IN THE ASIAN CONTEXT

Foreign language learning is not only about grammar or vocabulary but also life skill to be able to communicate. Furthermore, mastering culture along with learning language is essential. Language learners must have knowledge of cultural understanding because every language reflects many kinds of cultures. The same thing can happen between Indonesian and German. If the communication is not good, it could lead to something negative, especially when the communications are related to business cooperation as well as other important partnerships. So, in foreign language learning, teachers must teach the cultures of both the native and foreign language too, so that learners can understand differences between German and Indonesian culture. This research is a kind of literature review research. The literatures were based on the result of previous studies on cultural differences in verbal communication between German and Indonesian culture. It is also supported by observing and studying reference system to generate appropriate learning strategies. The study reveals that there are various strategies that can be implemented to enable students to understand cultural differences. There is some cultural knowledge in communications which can be given by providing information, while some others need to be practiced in the classroom and also to be applied in the real communication practices. In learning and understanding cultural differences, we can focus on the empowerment of student centered learning, by asking students to explore these differences, select which should be practiced and applied, as well as decide which activities that should always be supervised by the teacher, so misunderstanding would not occur. permalink/DOI: dx.doi.org/10.17977/um015v46i22018p124
Collecting Comparable Corpora

The availability of parallel corpora is limited, especially for under-resourced languages and narrow domains. On the other hand, the number of comparable documents in these areas that are freely available on the Web is continuously increasing. Algorithmic approaches to identify these documents from the Web are needed for the purpose of automatically building comparable corpora for these under-resourced languages and domains. How do we identify these comparable documents? What approaches should be used in collecting these comparable documents from different Web sources? In this chapter, we firstly present a review of previous techniques that have been developed for collecting comparable documents from the Web. Then we describe in detail three new techniques to gather comparable documents from three different types of Web sources: Wikipedia, news articles, and narrow domains.
3D printed scaffold to monitor hanging drops on inverted microscopes

Growing cells in 3D cell culture became a major field in cell biology over the last decade.Cells growing in a dimensionally unrestricted space spontaneously form organoids or spheroids that express cellular behavior different from cells growing on a plane surface.However, monitoring three dimensional spheroids on standard inverted microscopes proved difficult since hanging drops are often outside the focus range.Here I present the design and production of a cover slip tray by conventional additive printing (3D printing) able to fit into a single well of a six-well plate to enable the observation of hanging drop spheroids using inverted microscopes.josha.org
The influence of orientation of photovoltaic panels on the amount of electric energy production for consumers

The paper presents how the energy demands of selected consumers of electric energy may be satisfied with the use of a photovoltaic plant. The essence of the problem concerns, on one hand, dynamics of change of a daily profile of electric energy consumption by a consumer and on the other hand, provision of properties and parameters of a PV power plant. The production size of electric energy was determined for panels positioned at the 30 degree angle with east, south, west and east and west orientation operating simultaneously. The obtained results were compared with a daily dynamics of electric energy demands for a dairy, sewage treatment plant, water uptake station and rural farms. The analysis was carried out for the selected summer months (June, July and August) based on hourly time intervals both for the energy source and a recipient. Based on the collected data and calculations made, a level of substitution of conventional energy with energy from a PV plant for particular recipients was determined with the use of the coefficient of satisfaction of electric energy demand. Based on the experiment one may expect that the PV energy demand will be satisfied at the level between 23 a d 39%. In this case, the direction of panels' location was not significant. Moreover, the coefficient of energy excess, which a consumer cannot use, was determined. The lowest values of this excess for positioning of panels at the east and west direction simultaneously were achieved. In these conditions, the unused electric energy constituted not more than 7%.
PENGEMBANGAN MODUL PEMBELAJARAN PERANCANGAN SISTEM INFORMASI PADA MATERI PERANCANGAN TERSTRUKTUR BERBASIS TEKNOLOGI KOMPUTER

This research discussed the issue of the development of learning module based computer technology especially a powerpoint. This module is intended to help students receive the material that was delivered by lecturer especially design structured matter which currently learning module media shaped print and the contents of the text are form module so the university students ca not see the material . Based on these problems was built a module learning computer technology with a powerpoint . The reason the manufacture of the module was structured design material with a picture and a symbol of in designing a system so it needs to ease student visualiasi received mater learning. Method of development this module use the model ADDIE (analysis, design, development, implementation and evaluation). Results in this research validated by 2 ( two ) experts namely the people of material said 80% module very reasonable used without revision and media experts said 84% module very reasonable used without revision while results trial by college students by means of pre-test and post-test. The results obtained module very well be used.
Saxena-Easo Fuzzy Time Series on Indonesia’s Inflation Rate Forecasting

Saxena-Easo Fuzzy Time Series (FTS) is a softcomputing method for forecasting using fuzzy concept. It doesn’t need any assumption like conventional forecasting method. Generally it’s focused on three important steps like percentage change as the universe of discourse, interval partition, and defuzzification. In this research, this method is applied to Indonesia’s inflation rate data. The aim of this research is to forecast Indonesia’s inflation rate in 2017 by using input from Autoregressive Integrated Moving Average (ARIMA) process, Saxena-Easo FTS, and actual data from 1970-2016. ARIMA is focused on four steps like identifying, parameter estimation, diagnostic checking, and forecasting. The result for Indonesia’s inflation rate forecasting in 2017 is about 5.9182 using Saxena-Easo FTS. Root Mean Square Error (RMSE) is also computed to compare the accuracy rate from each method between Saxena-Easo FTS and ARIMA. RMSE from Saxena-Easo FTS is about 0.9743 while ARIMA is about 6.3046. Keywords: saxena-easo fuzzy time series, ARIMA, inflation rate, RMSE.
Visual Quality Guidance for Document Exploration with Focus+Context Techniques

Magic lens based focus+context techniques are powerful means for exploring document spatializations. Typically, they only offer additional summarized or abstracted views on focused documents. As a consequence, users might miss important information that is either not shown in aggregated form or that never happens to get focused. In this work, we present the design process and user study results for improving a magic lens based document exploration approach with exemplary visual quality cues to guide users in steering the exploration and support them in interpreting the summarization results. We contribute a thorough analysis of potential sources of information loss involved in these techniques, which include the visual spatialization of text documents, user-steered exploration, and the visual summarization. With lessons learned from previous research, we highlight the various ways those information losses could hamper the exploration. Furthermore, we formally define measures for the aforementioned different types of information losses and bias. Finally, we present the visual cues to depict these quality measures that are seamlessly integrated into the exploration approach. These visual cues guide users during the exploration and reduce the risk of misinterpretation and accelerate insight generation. We conclude with the results of a controlled user study and discuss the benefits and challenges of integrating quality guidance in exploration techniques.