Reviewerly/exHarmony huggingface dataset:
Arsenic characteristics in the terrestrial environment in the vicinity of the Shimen realgar mine, China

In this study, multiple types of samples, including soils, plants, litter and soil invertebrates, were collected from a former arsenic (As) mine in China.The total As concentrations in the soils, earthworms, litter and the aboveground portions of grass from the contaminated area followed the decreasing order of 83-2224 mg kg -1 , 31-430 mg kg -1 , 1-62 mg kg -1 and 2-23 mg kg -1 , respectively.XANES analysis revealed that the predominant form of As in the soils was arsenate (As(V)).In the grass and litter of the native plant community, inorganic As species were the main species, while minor amounts of DMA, MMA were also detected by HPLC-ICP-MS.The major As species extracted from earthworms were inorganic and AsB was the only organic species present in the earthworm samples, although at low proportions.The internal bioconversion of other As species is hypothesized to contribute greatly to the formation and accumulation of AsB in earthworms, although the direct external absorption of organic As from soils might be another source.This study sheds light on the potential sources of complex organoarsenicals, such as AsB, in terrestrial organisms.
Update from the Standards Vice President: Immersive Media

<fig orientation="portrait" position="float" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <graphic orientation="portrait" position="float" xlink:href="devli-3021883.tif"/> </fig> The quest for a truly immersive media experience is almost the history of media technology. We have sought to create an experience <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">just like being there</i> from the earliest days of recorded sound, right up to the present day. Curiously, the desire for richer and more immersive productions has spawned technologies that help us in other areas.
An Intangible Information Security Frame Work Against Attacks in Business Environment

The objective of the research work is to propose a strategic reasoning for information security Frame work against various attacks in business organization. The earlier information security research works and incidents include the activation of appropriate safeguards; the prevention and reduction of risks and recovery from impacts were considered for various security needs. The information security requirements that are well aligned with the business needs are essential for a secured design that may enhance product viability and return on investment (RoI) factor. Hence the strategic reasoning for information security models are implemented to unravel the issues of information security requirements based on the environments and development of business applications. The sensitive information in any business organization could be leaked by a poor planning system with various vulnerable policies to ensure that planned actions occur. A Systematic information approaches are implemented with evidences of the security breaches of an organization to enhance the overall security
SEARCH FOR ENTITIES BASED ON THE IMPLICIT SEMANTIC RELATIONS

The ability to infer undefined information/knowledge by similar inference is one of the natural abilities of human. The paper aims to study, simulate the above ability. The IRS model searches for undefined information/knowledge from an unfamiliar domain using similarities from familiar domains, through query. Because the semantic relations or similarities are not explicitly stated in the query, the IRS model is called an implicit semantic entity search model. The paper presents extracting, clustering, ranking techniques and a model of implicit relational search on Vietnamese language domain.
French language abstracts

Free accessAbstractFirst published online January 9, 2019French language abstractsVolume 25, Issue 1https://doi.org/10.1177/1356389018819914
Indonesia’s Public Application Programming Interface (API)

Indonesia places the fifth position of the most internet users in the world. Consequently, data transaction through HTTP protocol saw an increase. An open API can facilitate Indonesia's users to access data and build application through HTTP protocol. In this paper, 38 open APIs were investigated and classified by using five criteria, namely technology, authentication, scope, source, and approval request. In general, the open APIs in Indonesia employ RESTful as a web service and JSON format as data format. In term of authentication, API key is a common method in most of open APIs.
Earth sciences, an “out of system” science: epistemology, models and skills

With regard to a long experience in teaching and spreading Earth sciences in the Italian context, both to students and to the general public, the work proposes a brief analysis of the relationship between Earth Sciences and the lack of interest towards this discipline in all the public. From this analysis emerged that Earth sciences appear as an “out of system” discipline, particular definition used and illustrated in the text. As a result, it seemed to be necessary to deepen some aspects of its epistemology and of the methodological and experimental procedures that the different branches of the discipline require. More precisely, it has emerged the peculiarity of a science that questions the application of the experimental scientific method, highlighting the need to identify different models and tools in experimental and investigative practice. The relationships between facts, phenomena and events require, and in the same time they can promote e, among students but also researchers, specific and transversal and skills and abilities, including the capacities of analysis, synthesis and abstraction that are fundamental both as soft skills and in the world of research.
Framework towards the Process of Estimating or Predicting Perceived QoE Based on the Datasets Obtained From the Mobile Network

Nowadays, the research study community visualizes a standard shift that is going to put the focus on Quality of Experience metrics, which relate directly to complete consumer satisfaction. Yet, determining QoE coming from QoS sizes is a daunting job that powerful Software Defined Network operators are currently able to tackle through artificial intelligence strategies. In this paper, our experts pay attention to a few essential QoE factors, and we to begin with proposing a Bayesian Network design to anticipate re-buffering proportion. This paper suggested a structure for modeling mobile network QoE, making use of the vast records analytics approach. The planned platform explains the method of estimating or forecasting perceived QoE based upon the datasets obtained or collected from the mobile network to enable the mobile network operators efficiently to deal with the network functionality as well as supply the individuals an adequate mobile Internet QoE.
DYNAMICS OF DEVELOPMENT OF THE EDUCATORS’ PROFESSIONAL SELF-CONSCIOUSNESS IN THE PROCESS OF PROFESSIONAL SKILLS IMPROVING

The article is devoted to the study of the problem of dynamics of development of professional self-consciousness of educators in the process of professional skills improving. To the empirical research were involved 385 individuals — senior students who do not have professional experience; educators who at the time of the study worked on the specialty less than 5 years, from 5 to 10 years or more than 10 years. It was found that the value-semantic component is the most important component in the self-consciousness of specialists of pedagogical profession, regardless of the level of qualification. The cognitive component gaines more weight for educators with 5 to 10 years of experience and more than 10 years of experience. The weight of the evaluative component decreases with the increase of professional experience. Emotional component acquires the greater value for pedagogues with more than 10 years of experience and the least value for educators with up to 5 years of experience. The regulatory component gaines more weight for employees with up to 5 years of experience and undergraduate students. Motivational component has the least importance for the undergraduate students. The volitional aspect of professional self-consciousness gaines the most weight for future educators. Therefore, there are differences in the process of development of all components of educators’ professional self-consciousness with different levels of qualification. Making sense of one’s own professional activity and awareness of oneself as part of professional community is important, regardless of professional experience. With the increase of professional qualification, the role of professional self-esteem and self-acceptance in the activity decreases, but the level of self-understanding in the profession increases. With the increase of skills level, educators pay less attention to the issues of self-control and self-regulation in their professional activities.
PERANCANGAN SISTEM INFORMASI PENJADWALAN KUNJUNGAN SALES PADA TOKO AMEERA

The right and appropriate information system is important in managing the company. Ameera Store is a company engaged in the distribution of baby products from various kinds of principles, marketing products on credit and cash to customers. Salesmen who work at the Ameera company have an important role in distributing a product to customers. In each order, the sales and admin records data twice. Customer data and visits can only be seen manually by sales. Therefore, it is necessary to process customer data, visit frequency, order goods and billing. Currently there is no application for salesmen to remind you of every scheduled visit, this raises problems in the form of: frequent interchanges between bills and orders, so that visits are not on target and have an impact on decreasing sales value and time effectiveness. Therefore, designing an information system for scheduling sales visits becomes the basis for managing data. The method used is descriptive analytical method by means of interviews, observation and literature study. For the development of information systems applications using the waterfall methodology and modeling the business process information systems using Data Flow Diagrams (DFD). The research objective is to produce responsive web-based applications in the distribution process. The application of this system will greatly facilitate and benefit more parties, both sellers and buyers
Highly Secured Method for Image Encryption Based Mathematical Model and Bit Plane

The important area of network communication research is the protection of clandestine image data from prohibited access. Therefore, we develop a highly guaranteed model for image encoding as we use a new mathematical model. This helps anyone to encrypt and decrypt gray image more securely and skillfully. Image encryption technique plays a vital role in image processing. Lot of image encryption technique has been developed so far. The technique such as segment the image into four parts, exchange first part of matrix instead of fourth part ,as well as exchange second part instead of third part, after that we exchange the main diagonal of fist part with fourth part ,as well as, the main diagonal of second part exchange with third part. After that, we will use mathematical function to hide the image. The decrypted gray image has two distinct steps. First, using invertible mathematical model to obtain gray image with noise. Second, using Bit Plane in order elicit the actual image back.
Maneuvers of Multi Perspective Media Retrieval

Recently, Learning Machines have achieved a measure of success in the representation of multiple views. Since the effectiveness of data mining methods is highly dependent on the ability to produce data representation, learning multi-visual representation has become a very promising topic with widespread use. It is an emerging data mining guide that looks at multidisciplinary learning to improve overall performance. Multi-view reading is also known as data integration or data integration from multiple feature sets. In general, learning the representation of multiple views is able to learn the informative and cohesive representation that leads to the improvement in the performance of predictors. Therefore, learning multi-view representation has been widely used in many real-world applications including media retrieval, native language processing, video analysis, and a recommendation program. We propose two main stages of learning multidisciplinary representation: (i) alignment of multidisciplinary representation, which aims to capture relationships between different perspectives on content alignment; (ii) a combination of different visual representations, which seeks to combine different aspects learned from many different perspectives into a single integrated representation. Both of these strategies seek to use the relevant information contained in most views to represent the data as a whole. In this project we use the concept of canonical integration analysis to get more details. Encouraged by the success of in-depth reading, in-depth reading representation of multiple theories has attracted a lot of attention in media access due to its ability to read explicit visual representation.
Growing self-organizing tree-based kernel smoother for machine learning and data mining

With Internet of Things (IoT) being prevalently adopted in recent years, traditional machine learning and data mining methods can hardly be competent to deal with the complex big data problems if applied alone. However, hybridizing those who have complementary advantages could achieve optimized practical solutions. This work discusses how to solve multivariate regression problems and extract intrinsic knowledge by hybridizing Self-Organizing Maps (SOM) and Regression Trees. A dual-layer SOM map is developed in which the first layer accomplishes unsupervised learning and then regression tree layer performs supervised learning in the second layer to get predictions and extract knowledge. In this framework, SOM neurons serve as kernels with similar training samples mapped so that regression tree could achieve regression locally. In this way, the difficulties of applying and visualizing local regression on high dimensional data are overcome. Further, we provide an automated growing mechanism based on a few stop criteria without adding new parameters. A case study of solving Electrical Vehicle (EV) range anxiety problem is presented and it demonstrates that our proposed hybrid model is quantitatively precise and interpretive. key words: Multivariate Regression, Big Data, Machine Learning, Data Mining, Self-Organizing Maps (SOM), Regression Tree, Electrical Vehicle (EV), Range Estimation, Internet of Things (IoT)
A Comparative Study on Image Compression Method Using Stand-Alone DWT Techniques and Hybrid of DWT with Huffman Coding Technique for WSN Application

The advent of wireless technologies nowadays gives high impact toward many users to communicate to each other.Wireless Sensor Net-work is a network of nodes which connect to each other by using a device.In addition, transmitting and receiving messages and files are common in most users.There are many platform of network which contributes the same aim that is communication purposes.A ZigBee network is known as one of a platform with its own Standard (IEEE 802.15.4).Unfortunately, ZigBee has a low data rate which limits the capacity of storage in transmitting data.Thus, a large multimedia such as image data are hard to transmit via ZigBee network.Therefore, image compression are necessary in transmission process due to the ability in reducing dimension size and removing redundant image data.In this paper, three method are observed which are stand-alone DWT, stand-alone Huffman, and Hybrid of DWT and Huffman Coding.After conducting a comprehensive observation, it is found that DWT technique are able to compress the image data with less time taken while Huffman technique are suitable in maintaining the quality of image but need a long time to process.Hence, hybrid of DWT with Huffman method are proposed to support each other in terms of compression, computing time and quality of image.
Prediction of Cybercrime by using Euclidean Voronoi on Persons Arrested under Cybercrime

Cybercrime has many dimensions. Mails sent from one person to another may have much illegal content. Cybercrime has gained recent significance in current situation. Mathematical models have proved to give more accurate results in Cybercrime analysis and prediction. Euclidean distance with Voronoi diagrams is a recent mathematical diagram which is divided into regions based on points in a plane. Thiessen polygons gain popularity in science and technology. This paper finds the solution to analyse data based on persons arrested under cybercrime.
Anonymization Based Fisher–Yates Shuffle Method for Streaming of Twitter Data

In this era of Big Data, many organizations are functioning with personal data, that has to be preserved for privacy reason. There are hazards to identify the individual details by using Quasi Identifier (QI). So to preserve the privacy, anonymization points us to convert the personal data into unidentified personal data. There are many organizations that produce the large data in real time. With the help of Hadoop components like HDFS and MapReduce and with its ecosystems, large volume of data can be processed in real time. There are many basic data anonymization techniques like cryptographic, substitution, character masking, shuffling, nulling out, date variance and number variance. Here privacy preservation is achieved for streaming data by using one of the anonymization techniques called ‘shuffling’ with Big data concept. K-anonymity, t-closeness, l-diversity are usually used technique for privacy concern in a data. But in all these techniques information loss and data utility are not preserved very well. Dynamically Anonymizing Data Shuffling (DADS) technique is used to overcome this information loss and also to improve data utility in streaming data.
Diagnosis Penyakit Rubella Menggunakan Metode Fuzzy Tsukamoto

Rubella or better known as German measles is a viral infection characterized by a red rash on the skin. Lack of general public understanding of this disease makes the number of patients with Rubella increasing. So Fuzzy Tsukamoto's method is used to detect Rubella disease. The purpose of this study is to facilitate the public in understanding about Rubella disease so as to reduce the number of sufferers of this disease. The first step to detecting Rubella disease is to determine the fuzzy set and the domain which includes 3 variables: red rash, swollen lymph nodes, and fever. The output of fuzzy calculations is someone experiencing Rubella or normal symptoms. The value obtained from the calculation process usig the Tsukamoto method is 6.00.
Key Factors for Consortial Success: Realizing a Shared Vision for Interlibrary Loan in a consortium of Canadian Libraries

&lt;p&gt;Purpose&lt;/p&gt; &lt;p&gt;The purpose of this paper is to identify the factors associated with the successful implementation of a shared interlibrary loan (ILL) system by the Ontario Council of University Libraries (OCUL), a consortium of 20 Ontario universities.&lt;/p&gt; &lt;p&gt;Design/methodology/approach&lt;/p&gt; &lt;p&gt;The paper is a descriptive review of the approaches taken in the consortial implementation of OCLC's VDX software. The paper elaborates on the building‐blocks and barriers to success as they were experienced, first by participants in OCUL's centralized implementation activities, and second at the local level by staff at Ryerson University Library, a member institution. Now end users can simultaneously search world‐wide catalogues, submit and track progress of requests, and receive materials rapidly. System functionality includes auto‐mediated interlibrary loans (direct requesting); use of link‐resolver software to transfer citation information from borrowing library catalogues to ILL request forms; and ISO peer‐to‐peer messaging.&lt;/p&gt; &lt;p&gt;Findings&lt;/p&gt; &lt;p&gt;Post‐implementation analysis reveals several key factors that contributed to the project's success. These include: planning, leadership, financial support, technical support, cooperation, staff commitment, communication, staff‐and end‐user centered focus, training and evaluation.&lt;/p&gt; &lt;p&gt;Practical implications&lt;/p&gt; &lt;p&gt;This may have broad application for similar complex projects.&lt;/p&gt; &lt;p&gt;Originality/value&lt;/p&gt; &lt;p&gt;The OCUL VDX implementation has achieved the originally expected economies of scale, service performance improvements and reduction in localized maintenance and system support. However, there have also been several unforeseen benefits such as the formulation and standardization of the OCUL ILL policies, and the development of Canada‐wide consortial reciprocal agreements. At the operational level, staff have had to adjust their management styles and develop confidence not only in their individual skills but also in cooperative thinking, reliance on centralized support, and in the overall system. Throughout the project the objectives have been clearly identified, and, for the most part, enthusiastically adopted, by consortium members. Recognizing that ILL is a service that is in transition, staff now look at business transformation and ways to identify, share and adopt best working practices.&lt;/p&gt;
Supplementary material to &amp;quot;Comparative geochemical study on Furongian (Toledanian) and Ordovician (Sardic) felsic magmatic events in south-western Europe&amp;quot;

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BirdQuestVR: a cross-platform asymmetric communication game

BirdQuestVR is a cross-platform asymmetric communication game between one player in Virtual Reality and another on a mobile device. The game explores asymmetric co-operative gaming in a shared physical space, taking the physical surroundings of the VR user into account in its design. Asymmetric games feature different rules, abilities, or objectives for different players, generating unique and nuanced game experiences. Multiplayer asymmetric games in particular have been shown to increase teamwork and a collaborative mindset even after a play session has ended. Asymmetric design is commonplace in both digital and analog games but has yet to see widespread adoption in the emerging Virtual Reality (VR) gaming space. BirdQuestVR seeks to leverage the affordances of current consumer-grade VR headsets to build asymmetric gameplay around communication, embodied performance, and physical humour. Keywords: Asymmetric, Virtual Reality, Cross-Platform, Social Play, Avatar Embodiment
Hybrid Invariant Local Features for Multiple Satellite Image Matching and Registration

Automatic image registration (IR) is very challenging and very important in the field of hyperspectral remote sensing data. Efficient autonomous IR method is needed with high precision, fast, and robust. A key operation of IR is to align the multiple images in single co-ordinate system for extracting and identifying variation between images considered. In this paper, presented a feature descriptor by combining features from both Feature from Accelerated Segment Test (FAST) and Binary Robust Invariant Scalable Key point (BRISK). The proposed hybrid invariant local features (HILF) descriptor extract useful and similar feature sets from reference and source images. The feature matching method allows finding precise relationship or matching among two feature sets. An experimental analysis described the outcome BRISK, FASK and proposed HILF in terms of inliers ratio and repeatability evaluation metrics.