Reviewerly/exHarmony huggingface dataset:
Estimation of Soil Pollution With Heavy Metals Around Dashkesan Mining and Processing Factory

The article is devoted to the results of the determination and assessment of the content of heavy metals (HM) in the soil around the Dashkesan mining and processing factory of the Azerbaijan Republic. Combine open-pit mining method produces iron ore with its subsequent enrichment by flotation. Quarry blasting, transportation and crushing of ore by flotation swallowing; open pit and waste rock dumps after ore concentration (heaps) are the main sources of environmental pollution. Air currents and meltwaters contaminants HM fall into the soil. By the method of atomic absorption spectrometry in soil, the total content of Pb, Co, Cd, Cr, Cu, Zn was determined. The assessment of soil contamination by heavy metals was carried out by the Clarke number, the MPC and the total amount (Zc) of the TM. According to the Pb, Cd, Cu, Zn content, the soils are estimated as unpolluted, and according to the Co and Cr content - extremely polluted (MPC exceedance is more than 4 times). According to the total content of HM (Zc), soils are also assessed as extremely polluted. There is no regularity in the distribution of HM content in the soil around the source of pollution. As the distance from the source of contamination increases, the HM content in the soil changes spontaneously, which is a result of the influence of orographic and geological factors.
A VLIW architecture stream cryptographic processor for information security

As an important branch of information security algorithms, the efficient and flexible implementation of stream ciphers is vital. Existing implementation methods, such as FPGA, GPP and ASIC, provide a good support, but they could not achieve a better tradeoff between high speed processing and high flexibility. ASIC has fast processing speed, but its flexibility is poor, GPP has high flexibility, but the processing speed is slow, FPGA has high flexibility and processing speed, but the resource utilization is very low. This paper studies a stream cryptographic processor which can efficiently and flexibly implement a variety of stream cipher algorithms. By analyzing the structure model, processing characteristics and storage characteristics of stream ciphers, a reconfigurable stream cryptographic processor with special instructions based on VLIW is presented, which has separate/cluster storage structure and is oriented to stream cipher operations. The proposed instruction structure can effectively support stream cipher processing with multiple data bit widths, parallelism among stream cipher processing with different data bit widths, and parallelism among branch control and stream cipher processing with high instruction level parallelism; the designed separate/clustered special bit registers and general register heaps, key register heaps can satisfy cryptographic requirements. So the proposed processor not only flexibly accomplishes the combination of multiple basic stream cipher operations to finish stream cipher algorithms. It has been implemented with 0.18μm CMOS technology, the test results show that the frequency can reach 200MHz, and power consumption is 310mw. Ten kinds of stream ciphers were realized in the processor. The key stream generation throughput of Grain-80, W7, MICKEY, ACHTERBAHN and Shrink algorithm is 100Mbps, 66.67Mbps, 66.67Mbps, 50 Mbps and 800Mbps, respectively. The test result shows that the processor presented can achieve good tradeoff between high performance and flexibility of stream ciphers.
A Classification-Based Approach to Cognate Detection Combining Orthographic and Semantic Similarity Information

This paper presents proof-of-concept experiments for combining orthographic and semantic information to distinguish cognates from non-cognates.To this end, a context-independent gold standard is developed by manually labelling English-Dutch pairs of cognates and false friends in bilingual term lists.These annotated cognate pairs are then used to train and evaluate a supervised binary classification system for the automatic detection of cognates.Two types of information sources are incorporated in the classifier: fifteen string similarity metrics capture form similarity between source and target words, while word embeddings model semantic similarity between the words.The experimental results show that even though the system already achieves good results by only incorporating orthographic information, the performance further improves by including semantic information in the form of embeddings.
Research on Innovation and Entrepreneurship Education System under the New Business Background

The thesis takes innovation and entrepreneurship education system in the new business background as research object, aims to cultivate college students' entrepreneurial spirit and improve their entrepreneurial skills.It adopts the method combining practical research and theoretical analysis, proposes the construct strategies: implementing the goal of Ministry of Education's industry-university cooperation and education, carrying out in-depth cooperation with enterprises to optimize the design and implementation of business innovation and entrepreneurship education system, and further innovating the talent training mechanism of applied universities.The research results can effectively cultivate innovative and entrepreneurial composite high-quality talents, which will meet regional needs and the needs of industrial development.
Moving Towards an Actor-Based Model for Subject Indexing

This paper presents a preliminary exploration of an actor-based model for subject indexing, which considers four types of actors: professional indexers, domain experts, casual indexers, and machine algorithms. The paper describes each of the four actors, enumerating differences in approach, training, methodology, priorities, and tools, as well as similarities and historical collaborations between actors. The paper then explores how the actor-based model for subject indexing might serve as a complement to existing models that focus on processes, methods, disciplinary norms, and cultural biases by defining and exploring the following key properties of an actor-based model for subject indexing: 1) actors are the primary drivers of subject indexing work, 2) observing and understanding many types of actors’ processes in real-life situations is as valuable as prescribing correct methods for professional subject indexing, and 3) multiple and different types of actors can perform subject analysis work and subject representation work on the same information objects, and these hybrid (multi-actor) approaches to subject indexing are explicitly supported. These key properties suggest that an actor-based model for subject indexing might open new research opportunities and encourage new hybrid and collaborative approaches to knowledge organization.
Board 137: MAKER: Facial Feature Detection Library for Teaching Algorithm Basics in Python

This paper describes an approach to teach face detection algorithms to beginner level programming learners using a face detection tool built in Python.Learners are expected to understand and practice their Python coding skills and algorithm knowledge in a facial feature detection and image processing application.This project is a Science Technology Engineering and Math (STEM) extensive module and includes research analysis and activity components.Existing work focuses on teaching algorithms to students using interactive tools and games [3,4,7].This work lets students learn face detection algorithms using a library.Furthermore, students learn how to use the Dlib, Yattag, Cv, Numpy, Tkinter classes in Python along with the algorithmic details.This application enriches school curriculum by adding machine/software interactions and digital image processing.After completing the module activities, students are evaluated on basic understanding of face detection applications, computer vision, and the ability to complete the programming tasks.This classroom model has been implemented in a high school computer science class to provide an interesting way to help students learn programming and to motivate students to learn more about computer science.
Sip4J: Statically Inferring Access Permission Contracts for Parallelising Sequential Java Programs

This paper presents Sip4J, a fully automated, scalable and effective tool to automatically generate access permission contracts for a sequential Java program. The access permission contracts, which represent the dependency of code blocks, have been frequently used to enable concurrent execution of sequential programs. Those permission contracts, unfortunately, need to be manually created by programmers, which is known to be time-consuming, laborious and error-prone. To mitigate those manual efforts, Sip4J performs inter-procedural static analysis of Java source code to automatically extract the implicit dependencies in the program and subsequently leverages them to automatically generate access permission contracts, following the Design by Contract principle. The inferred specifications are then used to identify the concurrent (immutable) methods in the program. Experimental results further show that Sip4J is useful and effective towards generating access permission contracts for sequential Java programs. The implementation of Sip4J has been published as an open-sourced project at https://github.com/Sip4J/Sip4J and a demo video of Sip4J can be found at https://youtu.be/RjMTIxlhHTg.
Let’s Be Reasonable: The Consumer Expectations Test is Simply Not Viable to Determine Design Defect for Complex Autonomous Vehicle Technology

Although highly automated vehicles (“HAVs”) have potential to reduce deaths and injuries from traffic crashes, product liability litigation for design defects in vehicles incorporating autonomous technology is inevitable. During the early stages of implementation, courts and juries will be forced to grapple with the application of traditional product liability principles to a never before experienced category of highly technical products. Recent decisions limiting the use of the consumer expectations test in cases involving complex products prompted the authors to examine more closely the history behind and the future viability of the consumer expectations test in HAV litigation.
TV Series Subtitle Translation Based on Skopos Theory

Subtitle translation has ever been dominated by the principles of "faithfulness" and "equivalence", and neither of them can convey the meaning of the original film dialogues very well.The main principle of Skopos Theory lays stress on the fact that result determines the whole translation behavior, making the target spectators understanding the dialogue the main goal of TV series subtitle translation.Taking Friends as an example, this paper conducts a study on the better ways of subtitle translation based on Skopos Theory.
Multi-sensor Information Fusion Cubature Kalman Filter for Nonlinear System

In this paper, a multi-sensor information fusion Cubature Kalman Filter for nonlinear systems is presented. Based on the Gaussian Approximation filter, Cubature Kalman Filter is introduced in this paper. In order to improve the estimation accuracy, a multi-sensor information fusion method is adopted. The fusion method includes centralized fusion and covariance intersection fusion. The centralized fusion algorithm is optimal, but the computational burden is too large. To avoid the calculation of cross-covariance matrices, a distributed fusion filter is presented by using the covariance intersection fusion algorithm, which can reduce the computational burden. And the relationship between the accuracy and the computation complexities among the two fusion algorithm are analyzed. A simulation example of the target tracking controllable system with two sensors shows its effectiveness and correctness.
Enhanced Homomorphic Encryption technique using RSA ALGORITHM with multiple keys

The most demanding, in present scenario for wide range of applications is security for transmitting confidential information over the network.The confidential information is prone to many malicious attacks.Hence, the need for protecting confidential information has become a major challenge over the Internet.Cryptographic algorithms are the best choice for providing security against malicious attacks.By applying various techniques information can be protected.For securing information over the cloud is another major challenge, which is still has to be considered.The idea of Homomorphic Encryption is a promising method for securing information in the cloud.In this paper, RSA algorithm using multiple public key pairs with Homomorphic Encryption is proposed.The idea is to generate a key pair from multiple keys using RSA homomorphic encryption, which is partially homomorphic in nature, instead of a single key pair.This technique utilises one key for enciphering and other for deciphering..The beauty of this scheme is that a single key pair is selected from multiple key pairs which communicate with other parties.This technique of multiple keys generation utilises some mathematical logic for obtaining public key directly, when compared to RSA scheme with single key.By doing so, the attacks for finding the private key are stopped.
The impact of airway management training by utilizing smartphone on the learning of undergraduate medical students

Intrduction: Smartphone-based learning is a novel learning technique in medical education. Smartphones have good potentialities to be used as a learning tool for their wide application among students. The aim of this study was to investigate the impact of training airway management by utilizing smartphones on the learning of undergraduate medical students. Methods: In this semi-experimental study, it was tried to intervene in the students’ way of learning by using smartphone training application. The participants included 120 undergraduate medical students of School of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran. Forty students were randomly selected and divided into two groups of control and experimental. Then, teaching through two methods of traditional method (face to face) and combined method (traditional + smartphone-based software) was performed for control and experimental groups, respectively. After that the teaching was finished, the level of knowledge and practical skills of both groups were evaluated. Students' practical skills were assessed using a standard checklist on the moulage. The knowledge score was obtained using a multiple-choice written test. Finally, data were analyzed by SPSS software using independent samples t-test. Results: There was a significant difference between the mean score of knowledge and practical skills of the experimental group when compared to the controls (P &lt; 0.05) and the smartphone application was efficient in improving student learning. Conclusion: Utilizing smartphone application can be a complementary method for traditional education in enhancing medical skills. Accordingly, the use of blended training in medical education is suggested.
The Impact Of Online Game On The Children’s Character Change

&lt;p&gt;&lt;em&gt;Online games are very fast growing lately. The longer, it becomes more fun, including the appearance, style of play, game graphics, image resolution, and so on. There is also a variety of player types such as war, adventure, strategy, fight and all types of online games which are surely interesting to play. The kind of technology development greatly impacts the development of the children's character. When technology is used positively, surely it will help us in our daily life and vice versa. Program (PKM), 1 title Village Partner Development Program (PPDM)&lt;strong&gt;&lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;
The Research of Handheld Stabilization System Based on Active Disturbance Rejection Control Strategy

The handheld stabilization system is a strong-coupling, nonlinear and time-varying system and its model parameters are not accurate enough. Under the control of traditional control methods, the anti-interference performance of the three-axis handheld stabilizer is often insufficient. In order to solve this problem a control strategy based on the active disturbance rejection control has been proposed. The results of simulation and experiment show that the active disturbance rejection controller has the characteristics of high robustness, low model dependence and simple operation. It can control system stability in a high speed when parameters of the system changed rapidly.
Analisis Kefasihan Pembelajar Bahasa Korea dalam Membaca Teks Berbahasa Korea

Fluency in reading is one of the important factors in language learning, especially foreign languages. Fluency in reading can be seen from understanding vocabulary, reading speed, rhythm and expression, also understanding the reading’s contents. Reading fluently is one of the effective learning methods to help for understanding the vocabulary and the content of the text. Reading fluency is needed by Korean leaners when working with Korean stakeholders. This study analyzes the fluency of Korean language learners in reading Korean texts using qualitative descriptive methods. This study found that the learning period and the Korean Language Proficiency Test score of the learner are not always directly assesed to leaner’s fluency in reading. Fluency in reading is also influenced by some factors, such as how much intensity and frequency of learners learn new vocabulary through text, and how instructors provide learning about morphology in how to read a word in Korean.
KORELASI KETERAMPILAN MEMBACA TEKS LAPORAN HASIL OBSERVASI DAN KETERAMPILAN MENULIS TEKS LAPORAN HASIL OBSERVASI SISWA KELAS VII SMP NEGERI 21 PADANG

ABSTRACT The purpose of this study consists of three things. First, to describe the skills to read the report text of the observation results of class VII students at SMP Negeri 21 Padang. Second, to describe the writing skills of report observation texts of class VII students of SMP Negeri 21 Padang. Third, to describe the correlation between the skills to read the text of the observation report and the text writing skills of the observation results of the seventh grade students at SMP Negeri 21 Padang.This type of research is quantitative with descriptive method. The design of this study is correlational. The population of this study was seventh grade students of SMP Negeri 21 Padang who were enrolled in the 2018/2019 school year as many as 219 people and spread in seven classes. The sample of this study amounted to 42 people who were determined using proportional random sampling technique. The research data was obtained through two types of tests, namely objective tests and performance tests. Objective tests are used to collect data on the skills to read the text of the observation report while the performance test is used to collect data on the skills to write the text of the observation report. Kata kunci: Korelasi, Keterampilan Membaca, Teks Laporan Hasil Observasi
Automated Scoring of Self-explanations Using Recurrent Neural Networks

Intelligent Tutoring Systems (ITSs) focus on promoting knowledge acquisition, while providing relevant feedback during students’ practice. Self-explanation practice is an effective method used to help students understand complex texts by leveraging comprehension. Our aim is to introduce a deep learning neural model for automatically scoring student self-explanations that are targeted at specific sentences. The first stage of the processing pipeline performs an initial text cleaning and applies a set of predefined rules established by human experts in order to identify specific cases (e.g., students who do not understand the text, or students who simply copy and paste their self-explanations from the given input text). The second step uses a Recurrent Neural Network with pre-trained Glove word embeddings to predict self-explanation scores on a scale of 1 to 3. In contrast to previous SVM models trained on the same dataset of 4109 self-explanations, we obtain a significant increase of accuracy from 59% to 73%. Moreover, the new pipeline can be integrated in learning scenarios requiring near real-time responses from the ITS, thus addressing a major limitation in terms of processing speed exhibited by the previous approach.
Evaluating the performance of the staircase and qCD methods in measuring specificity/transfer of perceptual learning

The degree of transfer/specificity is a fundamental property of perceptual learning. Many conclusions about the level and mechanisms of perceptual learning depend critically on the accuracy and precision of the estimated transfer/specificity index. Traditionally, the transfer index is derived from learning curves during initial learning and transfer measured with the staircase method. Recently, Zhao et al. (2017) developed and validated a Bayesian adaptive qCD method to measure the trial-by-trial time course of perceptual sensitivity change in dark adaptation. The method was also validated in perceptual learning in a 4-alternative forced-choice (4AFC) global motion direction task, where the qCD method characterized the time course of perceptual learning more accurately, precisely and efficiently than the 3-down/1-up staircase method. Here, we evaluated the qCD and staircase methods in assessing the transfer index in a 2AFC task. Three observers with different time constants (40, 80, and 160 trials) of an exponential learning curve were simulated, with the same time constants and 50% transfer in the transfer phase. Each simulated observer was assessed with the 3-down/1-up staircase (10% step size) and the qCD procedure with a uniform prior of the parameters of the exponential learning curve, each with five initial stimulus levels (+50%, +25%, 0, −25%, and −50% from the true threshold in the first trial). 1000 simulated runs of 1600 trials were tested for each observer. Thresholds were estimated every 80 trials in the staircase method. The estimated transfer indexes from the qCD and staircase methods, averaged over starting levels, were 0.39±0.17 (Mean±SD) and −1.21±4.91 for Observer 1, 0.43±0.14 and 0.25±2.19 for Observer 2, and 0.47±0.09 and 0.46±0.48 for Observer 3, respectively. The results indicated that the qCD method provided more accurate and precise measures on transfer of perceptual learning than the staircase method, especially when the learning is more rapid. The qCD has great potentials in studies of perceptual learning.
Engaging with an Indian Epic: A Digital Approach

India's heritage texts have had a long history of being mined for knowledge of language and culture by Christian missionaries to India, colonial officers of the East Indian Company and the British Raj, German, European and American Indologists and later by native scholars driven by nationalist sentiments.It was during their investigative exercises that a vast body of India's heritage texts was recovered and made the subject of rigorous study.A large number of editions in English translation as well as in modern Indian vernacular languages started appearing on the scene.The focus then was primarily on patthoddhar [retrieval of the 'ur'-text] or making shuddhasanskarana [correct edition].The exercise was purely manual and time-consuming and concentrated on a limited number of texts.But there still lies a vast treasure of ancient knowledge in India's palm leaf manuscripts, waiting to be discovered, deciphered and interpreted for contemporary readers and scholars.It is impossible to ignore the ubiquitousness of Information Technology based tools and the scope that they offer for large-scale data mining.Of late, a large body of historical texts is being made available digitally by repositories and institutions worldwide.The time is ripe for digitally inspired editions, beginning with studies in corpus linguistics.This paper throws light on the challenges to be addressed for the preparation of a digital historical corpus edition of Sarala Mahabharata, a local version of the famous Sanskrit Mahabharata by Vyasa, from Odisha in the eastern part of India.