Reviewerly/exHarmony huggingface dataset:
Reading and Studying on the Screen, and, Addendum: two articles

As distance education moves increasingly towards online provision, and because of the benefits provided by online approaches, students will be expected to engage with more resources available on screen. Contemporary forms of reading from the screen include reading from tablet devices, LCD monitors, and smartphones. However, print remains the preferred means of reading text, and student preference for print is accentuated when reading involves thorough study (Ackerman &amp; Lauterman, 2012; Foasberg, 2014). Education providers face an interesting challenge. Although many learners prefer having access to printed materials, on-screen reading can improve education’s convenience, portability, media-richness, engagement, support, and data-evidenced practice. In this context it is timely to consider the potential for on-screen reading from the perspective of learning design. This article considers studies related to reading on screen, and suggests good practice principles for on-screen-only learning design.In 2016 the article “Reading and Studying on the Screen: An Overview of Literature Towards Good Learning Design Practice” was published. The article overviewed comparative studies related to reading on screen and reading from print, and proposed recommendations for on-screen learning design. This addendum to that article considers additional studies that have been analysed in subsequent blog posts (see “An Update to ‘Reading and Studying From the Screen’” [http://tel-lingit.blogspot.com/2018/02/an-update-to-reading-and-studying-from.html] and “A Further Update to ‘Reading and Studying From the Screen’” [https://tel-lingit.blogspot.com/2018/11/a-further-update-to-reading-and.html]) up to the end of November 2018. As this is an invited addendum, I’ll take the opportunity to adopt a more personal and self-disclosing style to talk more about my own position and experience regarding digital education and on-screen reading. This piece alternates is both scholarly and polemic.
Performance comparison of RSA and AES to SMS messages compression using Huffman algorithm

Improved security of short message services (SMS) can be obtained using cryptographic methods, both symmetric and asymmetric, but must remain efficient. This paper aims to study the performance and efficiency of the symmetric crypto of AES-128 and asymmetric crypto of RSA with message compression in securing SMS messages. The ciphertext of RSA and AES were compressed using the Huffman algorithm. The average AES encryption time for each character is faster than RSA, which is 5.8 and 24.7 ms/character for AES and AES+Huffman encryption and 8.7 and 45.8 ms/character for RSA and RSA+Huffman, from messages with 15, 30, 60 and 90 characters. AES decryption time is also faster, which is 27.2 ms/character compared to 47.6 ms/character in RSA. Huffman compression produces an average efficiency of 24.8 % for the RSA algorithm, better than 17.35 % of AES efficiency for plaintext of 1, 16, 45, and 88 characters.
Network-Based College English Multimedia Teaching Model

With the rapid development of multimedia network technology, in the college English teaching, the multimedia network teaching mode has gradually replaced the traditional single teaching mode based on teacher teaching. The development of multimedia network technology brings opportunities and challenges to traditional college English teaching, and also provides a good platform for college English multimedia network teaching. Based on the obvious characteristics of virtual reality, digital teaching, distance education and other network eras, this paper proposes a comprehensive college English teaching model based on multimedia network. This attempt has certain enlightenment effect on college English teaching reform.
The Effectiveness of Incinerator at the Integrated Waste Treatment Plant in the Campus of Engineering Faculty - Hasanuddin University

Abstract Waste is an endless environmental problem. The amount of waste production has increased due to the increasing population. Besides being produced in a city, waste generation is also produced by universities or campuses. One of them is the Gowa campus, the campus of Faculty of Engineering, Hasanuddin University. Current waste management is carried out by holding, collecting and burning in open areas without further management. It can cause environmental pollution and health problems. The objectives of this study were to determine the amount of campus waste generation, to analyze the needs of incinerators in campus, to determine incinerator tools, and to determine the advantages, disadvantages, efficiency and effectiveness of the incinerators in Gowa Campus. The results showed that the amount of waste generated at the Gowa campus was 0.25 liters/person/day and 0.12 kg/person/day. This incinerator requirements analysis uses the geometry method and the efficiency and effectiveness method. From the calculation, it is known that the use of incinerators for the next ten years is one unit. The disadvantage of using an incinerator is that the cost is very high. However, the advantage is that it can reduce waste generation and overcome environmental and health problems. The comparison between Double Chamber and Maxpell incinerator gave the results that the most effective and efficient is the Maxpell incinerator with an effectiveness of 97.5% and efficiency of 17.17%.
Determination of Geochemical Correlation of Cu, Pb, Zn in Stream Sediment Samples in Barru Area, South Sulawesi

Abstract The Barru area is known as the rock basement location in Sulawesi Island. The disclosure of ultramafic rock, metamorphic rock, and various sedimentary rock formations in the field and outcrops of unmapping intrusive rocks on a regional scale are certainly very interesting to be used as a media experiment in statistical methods in exploration of mineral resources. This is quite reasonable because among these rock formations are revealed intrusion of dacite and diorite rocks which are alterated and deposited as sulfides. The research gradually combines the pearson hybrid correlation geochemical stream sediment data and intrusive rocks on the relationship between SiO 2 , TiO 2 , Al 2 O 3 , Fe 2 O 3 , MnO, MgO, CaO, Na 2 O, K 2 O, P 2 O 5 , and Cr 2 O 3 variables which are illustrated by multidimensional spatial correspondence analysis and anomalous sources based on Cr, Cu, Fe, Mn, Ni, Zn, As, Mo, Co, Sb, Cd, and Pb variables. The results showed that the application of the hybrid statistical analysis method was effective enough to identify elemental variables in identifying sulfide deposits and the characteristics of anomalies were quite different from diorite and dacite due to magmatic hydrothermal and tectonic activity.
Image enhancement effect on the performance of convolutional neural networks

Context. Image enhancement algorithms can be used to enhance the visual effects of images in the field of human vision. So can image enhancement algorithms be used in the field of computer vision? ...
Comparative Performance Analysis of Various Classifiers on a Breast Cancer Clinical Dataset

Breast cancer is a major threat disease among women nowadays. It does not have any specific age to occur, and it is more common disease and causing death to many women. The highly influence of breast cancer occurrence is age, and age determines the treatments to be given and the lifetime of the patients. In this paper, we have considered age at diagnosis as the main feature for our analysis. We have performed a comparative analysis among the three classifiers such as Random Forest, Decision Tree, and Naive Bayes on the Metabric clinical dataset and obtained the rate of accuracy for each classifier.
A longitudinal assessment of Nigerias research output for evidence based science policy development

The study measured the trend of science and technology research output and investigated the pattern/breath of collaboration among actors of Nigeria's research and development system. Based on the results obtained, it considered its implications for science policy development. The study purposively selected the 148 science and technology journals out of the 221 journals queried over a five-year assessment period from 2012 to 2016 to elicit metrical data from the publications. Data harvested was analysed using percentages, relative growth rate and doubling time on a year-wise basis from 2012 to 2016, to identify the positive or negative growth trend of research outputs. VOS viewer was further used to examine the pattern of collaboration. The analysis from the study provided information on the extent of research that has been carried out in the various thematic areas in Nigeria's new science, technology and innovation (STI) policy.
A Reflection upon the Digital Copyright Laws in India

In this digital age, where everything is available at one place, to everyone, at all times, the vulnerability of copyrighted works has increased manifold. With high speed internet, peer-to-peer networks, excellent technologies facilitating rapid reproduction without loss of quality, fast and easy dissemination and high density storage devises, the copyright violation is becoming an effortless task. Though the traditional notion of copyright still remains the same i.e., protection from piracy, however, the mode of operation has and is undergoing a systematic change in the wake of technological development. The performance of rights in typical analogous copyright set-up is extremely different from the performance of such rights at digital platform. Further, ubiquity of internet coupled with various technical obstacles has made it extremely difficult for copyright holder to exactly locate and implicate the infringer/s, which in many cases may be located in different parts of the world. Now with the advent of artificial intelligence, creation of copyright subject matter by machines with very less or no human intervention is potentially raising question as to the authorship of such works. It is clear from the history of copyright laws that it has always responded in affirmation to the technological advancements by amending the existing systems to keep in tune with the changes taking place and to combat the challenges threatening its smooth and effective functioning. In this backdrop, this article presents an analysis of the phenomenal impact of digital technologies over copyright regime, its advantages and disadvantages, the protection of rights of copyright holder and the liabilities of intermediaries etc. Further, this article shall also explore the digital copyright laws available in India to combat the myriad challenges posed by the ever advancing digital technology and to find out their sufficiency.
Understanding Online Fitness Culture : Using Netnography for Marketing Research in Online Fitness Community

Purpose: Understanding the culture and the language of online consumesr and its specific underlying social motivations is a crucial aspect of achieving the market orientation. It can successfully conceptualize new products, employ existing and new channels. It also helps to writep otent advertising materials that meaningfully communicates to markets. Netnogrphay is enthnography adapted to the study of online communities.BR Method: This method provided information on the symbolism, meanings, and consumption patterns of online consumer groups. This study applied ‘netnography’ as an online marketing research technique for providing consumer insight. We examined some important cultural themse contained within the online fitness community.BR Results: We examined four themes; (1) discover communal values of health: decoding the language of diet, (2) networked sociality, (3) consumption webs: mapping the paths of desire, (4) commodified diet-related brands: brand images and community concerns. In addition, eacho f cultural theme was influenced by the character narrative and communal norms of online consumers.BR Conclusion: In summary, Online communities devoted to consumption-related topics are an increasingly important source of data for marketing research. This netnography study has implications for how marketers should plan, target, and how scholars should understand the online community as a new research area in a networked world.
Sistema multiparamétrico para la comparación forense de hablantes

espanolEn la comparacion forense de hablantes se pueden examinar diversos parametros. En el presente trabajo se utilizo un sistema multiparametrico que combina parametros acusticos de largo plazo (F0, cualidad de voz y aspectos duracionales) con los parametros de corto plazo (MFCC) empleados por un sistema automatico estandar basado en el enfoque i-vector/PLDA (sistema base). El objetivo era determinar si el nuevo sistema de comparacion de hablantes ofrece mejor rendimiento que el sistema base. Para ello se llevaron a cabo tres experimentos con disenos diferentes –que permitieron evaluar el nuevo sistema multiparametrico en condiciones extremas, a modo de prueba de estres–: (1) uso de grabaciones con caracteristicas forenses realistas (p. ej. ruido de fondo, reverberacion, variabilidad intra-hablante, compresion de la senal); (2) comparacion de las voces de 12 parejas de gemelos monocigoticos; y (3) cotejo de voces con enmascaramiento mediante pinzamiento de nariz. Los resultados obtenidos con el nuevo sistema muestran una mejora de rendimiento con respecto al sistema base, si bien el aporte medio de los parametros de largo plazo al nuevo sistema fue de un 6.5%, siendo el restante 93.5% responsabilidad de los parametros de corto plazo. EnglishIn Forensic Speaker Comparison (FSC) several different parameters are commonly analysed. In this investigation we propose a multiparametric system combining long-term features (F0, voice quality and durational aspects) with short-term features (MFCCs), used by a standard automatic system based on i-vector/PLDA approaches (baseline system). The objective was to determine if the performance of the new FSC system is better than that of the baseline system. For this, three experimental designs were carried out –allowing us to evaluate the new multiparametric system in extreme conditions, as if it was a stress test–: (1) use of forensically-realistic characteristics (e.g. background noise, reverberation, intra-speaker variability, signal compression); (2) voice comparison of 12 monozygotic twin pairs; and (3) comparison of disguised voices through nose pinching. The results show that the new system performs better than the baseline system although the mean contribution of long-term features to the new system was 6.5%, with the short-term features being responsible for the remaining 93.5%.
Undercutting Bitcoin Is Not Profitable.

A fixed block reward and voluntary transaction fees are two sources of economic incentives for mining in Bitcoin and other cryptocurrencies. For Bitcoin, the block reward halves every 210,000 blocks and it is supposed to vanish gradually. The remaining incentive of transaction fees is optional and arbitrary, and an undercutting attack becomes a potential threat, where the attacker deliberately forks an existing chain by leaving wealthy transactions unclaimed to attract other miners. We look into the profitability of the undercutting attack in this work. Our numerical simulations and experiments demonstrate that (i) only miners with mining power > 40% have a reasonable probability of successfully undercutting. (ii) As honest miners do not shift to the fork immediately in the first round, an undercutter's profit drops with the number of honest miners. Given the current transaction fee rate distribution in Bitcoin, with half of the miners being honest, undercutting cannot be profitable at all; With 25% honest mining power, an undercutter with > 45% mining power can expect income more than its fair share; With no honest miners present, the threshold mining power for a profitable undercutting is 42%. (iii) For the current largest Bitcoin mining pool with 17.2% mining power, the probability of successfully launching an undercutting attack is tiny and the expected returns are far below honest mining gains. (iv) While the larger the prize the undercutter left unclaimed, the higher is the probability of the attack succeeding but the attack's profits also go down. Finally, we analyze the best responses to undercutting for other rational miners. (v) For two rational miners and one of them being the potential undercutter with 45% mining power, we find the dominant strategy for the responding rational miner is to typical rational.
Application of Modern Information Technology in Course Teaching in Universities

Integrating information technology and teaching means is a hot issue in the popularization of information technology. The application of information technology in teaching enriches teaching resources and expands teaching methods, thus making modern education more efficient [1]. As Rain Classroom, Ketangpai, Cloud Space, and other information technologies are used in classroom teaching, a variety of flipped classroom and new teaching modes are springing up constantly, enabling the space of course teaching greatly extended. As for the practical courses, information technology tools can effectively link up and extend the links before, during and after class. However, some problems still need to be explored and improved in practical applications.
OS-Aware Interaction Model for the Verification of Multitasking Embedded Software

As the behavior of multitasking embedded software is dependent on the underlying operating system(s), rigorous and efficient verification in this domain requires models of operating systems (OS) that enable OS-aware verification of application programs at reduced cost. However, the heterogeneity of the languages used for OS models and of the program source code makes it difficult to compose these seemingly independent components and thus requires translation of one language into another, causing various issues in verification. To alleviate this problem, we propose a hybrid approach that composes formal OS models with application programs in an interaction model. Based on typical OS-application interaction behavior, our interaction model is a composition framework that connects an OS model to application programs as long as they share the same Application Program Interface (API). It provides seamless composition of two heterogeneous software artifacts by formulating source code annotations based on control-flow analysis and by synchronizing state transitions over API function calls to regulate the context switching of multitasking programs. A prototype implementation of the interaction model was applied to eight benchmark programs of the Erika OS and a control program with real-scale complexity from the automotive domain. It was shown that the framework supports systematic and effective verification of multitasking embedded software, which has not been possible using code-level model checking.
What Programs Want: Automatic Inference of Input Data Specifications.

Nowadays, as machine-learned software quickly permeates our society, we are becoming increasingly vulnerable to programming errors in the data pre-processing or training software, as well as errors in the data itself. In this paper, we propose a static shape analysis framework for input data of data-processing programs. Our analysis automatically infers necessary conditions on the structure and values of the data read by a data-processing program. Our framework builds on a family of underlying abstract domains, extended to indirectly reason about the input data rather than simply reasoning about the program variables. The choice of these abstract domain is a parameter of the analysis. We describe various instances built from existing abstract domains. The proposed approach is implemented in an open-source static analyzer for Python programs. We demonstrate its potential on a number of representative examples.
VAE-LIME: Deep Generative Model Based Approach for Local Data-Driven Model Interpretability Applied to the Ironmaking Industry.

Machine learning applied to generate data-driven models are lacking of transparency leading the process engineer to lose confidence in relying on the model predictions to optimize his industrial process. Bringing processes in the industry to a certain level of autonomy using data-driven models is particularly challenging as the first user of those models, is the expert in the process with often decades of experience. It is necessary to expose to the process engineer, not solely the model predictions, but also their interpretability. To that end, several approaches have been proposed in the literature. The Local Interpretable Model-agnostic Explanations (LIME) method has gained a lot of interest from the research community recently. The principle of this method is to train a linear model that is locally approximating the black-box model, by generating randomly artificial data points locally. Model-agnostic local interpretability solutions based on LIME have recently emerged to improve the original method. We present in this paper a novel approach, VAE-LIME, for local interpretability of data-driven models forecasting the temperature of the hot metal produced by a blast furnace. Such ironmaking process data is characterized by multivariate time series with high inter-correlation representing the underlying process in a blast furnace. Our contribution is to use a Variational Autoencoder (VAE) to learn the complex blast furnace process characteristics from the data. The VAE is aiming at generating optimal artificial samples to train a local interpretable model better representing the black-box model in the neighborhood of the input sample processed by the black-box model to make a prediction. In comparison with LIME, VAE-LIME is showing a significantly improved local fidelity of the local interpretable linear model with the black-box model resulting in robust model interpretability.
Arbitrary Multiscale Explainable Decision-Making for Symbiotic Autonomous Systems

In the near future to solve complex, arbitrary multiscale system problems, we need a unified, integrated framework that can offer an effective and convenient, universal mathematical approach, by considering information not only on the statistical manifold of model states, but also on the combinatorial manifold of low-level discrete, directed energy generators and empirical measures of noise sources, related to experimental high-level overall perturbation. To overcome past modeling limitations in dynamic cooperative multi-agent system, we propose the modeling of agent as purposive subject modeled by the Elementary Pragmatic Model (EPM) approach. In this context, predicative competence and natural language processing can play a fundamental role for developing a new generation of user-friendly, more autonomous, but still colloquial systems to offer explainable decision-making processes. In order to achieve this goal, a deep layer of “machine thought” is vital for developing highly competitive, reliable and effective symbiotic autonomous systems. Based on it, a new approach to computational predicative competence will be presented.
Comprehensive Teaching Mode Based on Blockchain

This article starts from the study of traditional education models and finds that there are significant disadvantages in grade management system. In order to achieve efficient management of grade and the objectivity of performance sources, this article introduces the idea of “blockchain + education” and explores new teaching modes based on the characteristics of the blockchain. The teaching system can realize new features such as scores that cannot be tampered with, real names, and diversity, so that students’ results no longer come from a single scoring standard, and further improve the quality of education and teaching.