Reviewerly/exHarmony huggingface dataset:
Analysis of Santa’s river water pollution caused by the environmental liability of Ticapampa using grey clustering method

In Peru, many environmental liabilities produce Acid Mine Drainage (AMD) which flow into rivers affecting their water quality, likewise, many of these liabilities transport large amounts of heavy metals, endangering every water-dependent living organism.In this context, for the evaluation of the parameters involved, we used the grey clustering method, which, based on the theory of grey systems, is presented as a remarkable alternative to the classical statistical methods.In this study we assessed the impact of the Ticapampa environmental liability on the water quality of Santa river using data collected in 2010 from four strategically located monitoring points along the river.The analyzed parameters were evaluated according to the parameters established by DS N° 004-2017-MINAM.Results showed that water quality from monitoring points located upstream (P1) and downstream (P2) with respect to the location of the environmental liability and according to Peruvian law, were of A1 (good) quality; which means that it can be purified using disinfectants.On the other hand, at two points located within the limit of the liability, the water quality was identified as A2 (moderate) and A3 (low) quality, which means it can be purified using conventional and special treatment respectively.Therefore, the grey clustering method has proven to be of great utility for water-quality-assessment related studies and can be applied in other studies which focus on this kind of analysis.In addition, the present results can be useful for Peruvian authorities in their decision making benefiting the communities nearby, animals and environment of study.
A Novel Provably Secure Key-Agreement Using Secret Subgroup Generator

Abstract In this paper, a new key-agreement scheme is proposed and analyzed. In addition to being provably secure in the shared secret key indistinguishability model under Decisional Diffie-Hellman assumption for subgroup of matrices over GF(2) with prime order, which considered as basic security requirement, the scheme has an interesting feature; it uses exponentiations over cyclic group using hidden secret subgroup generator as a platform for the key exchange, whereby - unlike many other exponentiation based key exchange schemes - it transcends the reliance on intractability of Discrete Logarithm Problem in its security.
Correction: Talk2Me: Automated linguistic data collection for personal assessment

[This corrects the article DOI: 10.1371/journal.pone.0212342.].
Socio-economic analysis of cybercrime

In the presented article, the author analyzes socio-economic damage caused and expected as a result of cybercrime, a global and transnational threat. In parallel, with the development of technology and the growing dependence of the population on internet resources in the digital era, there are discussed dangers of blooming opportunities for cybercriminals and harm imposed by their actions. Taking into account the scale of the proceeds of crime, the author of the article presumes that cybercrime has formed into organized criminal business and has become a threat not only to the security of states and proper functioning of their institutions but also to the property and assets of citizens and enterprises, banks and fund institutions. According to the author, even the rules implemented by countries with a strong economy and developed technologies, and the refinement/ development of methods to combat this crime, will not bring results and will not be effective, since cybercrime is global and transnational by its nature. To accomplish the goals effectively, response to this challenge should be comprehensive, based on unified, well-established international policy. This only can be achieved through close interstate cooperation and instant (bypassing bureaucratic formalism) mutual legal assistance.
Validation of the Virtual Reality Neuroscience Questionnaire: Maximum Duration of Immersive Virtual Reality Sessions Without the Presence of Pertinent Adverse Symptomatology

There are major concerns about the suitability of immersive virtual reality (VR) systems (i.e., head-mounted display; HMD) to be implemented in research and clinical settings, because of the presence of nausea, dizziness, disorientation, fatigue, and instability (i.e., VR induced symptoms and effects; VRISE). Research suggests that the duration of a VR session modulates the presence and intensity of VRISE, but there are no suggestions regarding the appropriate maximum duration of VR sessions. The implementation of high-end VR HMDs in conjunction with ergonomic VR software seems to mitigate the presence of VRISE substantially. However, a brief tool does not currently exist to appraise and report both the quality of software features and VRISE intensity quantitatively. The Virtual Reality Neuroscience Questionnaire (VRNQ) was developed to assess the quality of VR software in terms of user experience, game mechanics, in-game assistance, and VRISE. Forty participants aged between 28 and 43 years were recruited (18 gamers and 22 non-gamers) for the study. They participated in 3 different VR sessions until they felt weary or discomfort and subsequently filled in the VRNQ. Our results demonstrated that VRNQ is a valid tool for assessing VR software as it has good convergent, discriminant, and construct validity. The maximum duration of VR sessions should be between 55 and 70 min when the VR software meets or exceeds the parsimonious cut-offs of the VRNQ and the users are familiarized with the VR system. Also, the gaming experience does not seem to affect how long VR sessions should last. Also, while the quality of VR software substantially modulates the maximum duration of VR sessions, age and education do not. Finally, deeper immersion, better quality of graphics and sound, and more helpful in-game instructions and prompts were found to reduce VRISE intensity. The VRNQ facilitates the brief assessment and reporting of the quality of VR software features and/or the intensity of VRISE, while its minimum and parsimonious cut-offs may appraise the suitability of VR software for implementation in research and clinical settings. The findings of this study contribute to the establishment of rigorous VR methods that are crucial for the viability of immersive VR as a research and clinical tool in cognitive neuroscience and neuropsychology.
Perencanaan Pembangunan

Abstarct.Ambon city, which mostly consists of hilly areas, is an area that is very highly susceptible to the occurrence of debris mass movements, both in the form of debris flows and landslides (debris flows, erosions, and slope failures). In the city of Ambon, rivers are passed such as Way Ruhu, Way Batu Merah, Way Tantui, Way Tomu, Way Batu Gajah and Way Batu Hang. The purpose of this paper is to plan the check dam building for Way Batu Merah – Ambon City. The method used is Hydrological Analysis: hydrology as the basis for planning the Q25 Check Dam Building, which consists of rainfall analysis and the basis for calculating the planned discharge used in planning, using the Sabo Technical Center method. From the calculation results, it is obtained that the planned Q25 flood discharge of the Way Batu Merah River is 516.43 m / year with a return period of 25 years, the sediment volume can be accommodated 22,102 m / year and controlled by the Check Dam 56,050 m / year, then with a sediment discharge of 60,685 m³ / year . By comparing the amount of sediment that enters the Check Dam with the capacity of the Check Dam, it is dredged again for 3.5 years.Keywords: Sediment; Hydrological Analysis; Checkdam; Sediment Discharge
Analysis of Teeline Shorthand Recognition using Machine Learning and Deep Learning Techniques.

In order to take notes of the speech delivered by the VIPs in the short time short hand language is employed. Mainly there are two shorthand languages namely Pitman and Teeline. An automatic shorthand language recognition system is essential in order to make use of the handheld devices for speedy conversion to the original text. The paper addresses and compares the recognition of the Teeline alphabets using the Machine learning (SVM and KNN) and deep learning (CNN) techniques. The dataset has been prepared using the digital pen and the same is processed and stored using the android application. The prepared dataset is fed to the proposed system and accuracy of recognition is compared. Deep learning technique gave higher accuracy compared to machine learning techniques. MATLAB 2018b platform is used for implementation of the experimental setup.
Proper background checks reduce risks for everyone involved in hiring process

When you need to fill an opening in your busy athletics department, you're likely focused on getting that seemingly ideal new candidate on board as quickly as possible to lighten the load for your overworked staff.
Similarity Check to Detect Text Data Plagiarism

Picking the affirmed progression of the others works can be considered as shaped bowing which impacts all quarters of works from the get-togethers. Expanding accessibility and[12] straightforwardness of information is engaging the people to have legitimately clear zone to data, which is irritating the issues of consistency. With the rising basic for delineating the data as defiled or non-appropriated reliant on the volume of words that are to be taken[4] from the sources, it is fundamental that it will flop stupendously. Subordinate upon the region there are conditions where the closeness scores are either considered as copied or the non-tainted. While in certain area, any little copy is correspondingly to be treated as copyright encroachment, in unequivocal spaces there is degree for suggesting or underscoring the information sources. In a plan, it might be granted that there isn't regularly any liberal definition for even printed scholastic robbery which is reliably kind of a zone subordinate and the ones that are tangling the issue in principal way.[1],[3] The setting of the dispute considered above prompts focusing in this doctoral theory, towards. checking the substance information academic thievery utilizing reasonable assessment and cosine likeness in reports. making contemporary plan of answer for astute robbery obvious affirmation squashing the objectives investigated in before outline.
Advance Technique for Early Detection of Breast Cancer Using Textual Analysis from Digital Mammogram

The field of image processing gaining importance is not only for its rapid and continuous progress but also for accurate and advanced analysis. Mammography is the most popular imaging technique for the detection of breast cancer Anatomical structure of a lesion is obtained properly compared to other imaging modalities like CT( Computed Tomography), MRI (Magnetic Resonance Imaging), PET (Positron-emission tomography). In this work, an algorithm has been developed for the detection of breast cancer. The proposed method has consisted of three steps: preprocessing, segmentation and feature extraction. After segmentation of cancerous region, it is characterized with statistical features using first-order histogram and Gray Level Co-occurrence Matrix (GLCM)). Based on these two types of feature extraction methods, normal and cancerous mammograms have been diagnosed.
Generalized Disjunctive Programming

This chapter documents how to express and solve Generalized Disjunctive Programs (GDPs). GDP models provide a structured approach for describing logical relationships in optimization models.We show how Pyomo blocks provide a natural base for representing disjuncts and forming disjunctions, and we how to solve GDP models through the use of automated problem transformations.
Improved Framework for Bug Severity Classification using N-gram Features with Convolution Neural Network

Foreseeing the seriousness/severity of bugs has been established in former research study in order to recover triaging and the process of bug resolution. Therefore, numerous prediction/classification methodologies were developed throughout the years to give an automated reasoning over the seriousness classes. Seriousness or severity is a significant trait of a bug that chooses how rapidly it ought to be measured. It causes designers to comprehend significant bugs on schedule. Though, manual evaluation of severity is a dreary activity and could be off base. This paper comprises of using the text/content mining together along with the use feature selection and bi-grams to improve the order of bugs in six classes. In the proposed methodology the features are refined by the use of convolution layers. Here, the process of convolution-based refining indicates mapping of the features utilizing non-linear methods of all the classes as compared to the existing methodologies.
The development of instructional materials for reading literacy using the WISE approach

This study aimed to develop instructional materials for reading literacy using the WISE approach.WISE stands for wondering, investigating, synthesizing, and expressing.The development of the instructional materials followed ADDIE stages (analysis, design, development, implementation and evaluation).The development of materials for reading literacy using the WISE approach consists of seven chapters: introduction, WISE principles, activities to promote the wondering skill, activities to promote the investigating habit, activities to promote the synthesizing skill, activities to promote the expressing skill and follow-up activities.The formation of the WISE technique in students is possible if wondering is encouraged in students.Students also need to stimulate curiosity by themselves to develop and implement an investigation design, analyze the investigation results and use creativity to synthesize and express ideas.
The Origin of Gravitation

&lt;p&gt;More than three hundred years ago: Newton thought that the reason of apple falling was due to gravity, although he discovered the gravity in the earth, he did not know what how produce gravitation; he said that God is the first driving force. From then on, more than three centuries have passed many people had been exploring the origin of gravitation, until today people have no notion on the origin of gravitation. In order to find the origin of gravitation, I did some experiments and discovered that moving photons generate gravitation. This discovery come to light the origin of gravitation: applying this discovery to others particles show the same effects; in the same time these discoveries have been applied in macro world to calculate the acceleration of gravity, first time display the more accurately formula than Universal law of gravitation to describe the gravity field of earth. These works indicate that moving elementary particles bring on interaction force which appearing behavior of gravitation in the macro world. This show that these discoveries reveal the essence of Universal law of gravitation from micro world to macro world, and reveal the origin of gravitation: namely, tell us where gravitation come from, and solve the enigmas what Universal law of gravitation cannot solve until today.&lt;/p&gt;
Development of Cross Language Clone Detector for C, C &amp; Java Repositories using Natural Language Processing

Reusing the code with or without modification is common process in building all the large codebases of system software like Linux, gcc , and jdk. This process is referred to as software cloning or forking. Developers always find difficulty of bug fixes in porting large code base from one language to other native language during software porting. There exist many approaches in identifying software clones of same language that may not contribute for the developers involved in porting hence there is a need for cross language clone detector. This paper uses primary Natural Language Processing (NLP) approach using latent semantic analysis to find the cross language clones of other neighboring languages in terms of all 4 types of clones using latent semantic analysis algorithm that uses Singular value decomposition. It takes input as code(C, C++ or Java) and matches all the neighboring code clones in the static repository in terms of frequency of lines matched.
A mediação da informação em bibliotecas universitárias Brasileiras

In a scenario of major changes caused mainly by the use of technology in academic environments, the article approaches information mediation concepts in the Brazilian, Portuguese and French scientific literature with the objective of identifying the main theoretical aspects from the areas of information science and of the communication, employees to the university library together with the vision of the Brazilian reference librarians on the term mediation of the information to find convergent and / or divergent points and to understand how occurs the mediation of the information realized in university libraries. In the methodology applied, of a qualitative character, the bibliographical research was used to identify the approaches given by the authors about the mediation of the information. Next, an online questionnaire was used to gather information about the understanding of reference librarians on the subject, focusing on the services offered in libraries. The results lead us to state that reference librarians understand the mediation of information and are aware of their role as mediators. However, the reference process was poorly detailed by the librarians and some confusion of what it is, how it is done, and in what medium it is made were identified in the answers. However, it can be reiterated that the reference process occurs in face-to-face or digital media, mainly in the orientation of the librarian to the user to meet an expressed informational need.
Accuracy of Monocular Two-Dimensional Pose Estimation Compared With a Reference Standard for Kinematic Multiview Analysis: Validation Study (Preprint)

<sec> <title>BACKGROUND</title> Expensive optoelectronic systems, considered the gold standard, require a laboratory environment and the attachment of markers, and they are therefore rarely used in everyday clinical practice. Two-dimensional (2D) human pose estimations for clinical purposes allow kinematic analyses to be carried out via a camera-based smartphone app. Since clinical specialists highly depend on the validity of information, there is a need to evaluate the accuracy of 2D pose estimation apps. </sec> <sec> <title>OBJECTIVE</title> The aim of the study was to investigate the accuracy of the 2D pose estimation of a mobility analysis app (Lindera-v2), using the PanopticStudio Toolbox data set as a reference standard. The study aimed to assess the differences in joint angles obtained by 2D video information generated with the Lindera-v2 algorithm and the reference standard. The results can provide an important assessment of the adequacy of the app for clinical use. </sec> <sec> <title>METHODS</title> To evaluate the accuracy of the Lindera-v2 algorithm, 10 video sequences were analyzed. Accuracy was evaluated by assessing a total of 30,000 data pairs for each joint (10 joints in total), comparing the angle data obtained from the Lindera-v2 algorithm with those of the reference standard. The mean differences of the angles were calculated for each joint, and a comparison was made between the estimated values and the reference standard values. Furthermore, the mean absolute error (MAE), root mean square error, and symmetric mean absolute percentage error of the 2D angles were calculated. Agreement between the 2 measurement methods was calculated using the intraclass correlation coefficient (ICC[A,2]). A cross-correlation was calculated for the time series to verify whether there was a temporal shift in the data. </sec> <sec> <title>RESULTS</title> The mean difference of the Lindera-v2 data in the right hip was the closest to the reference standard, with a mean value difference of –0.05° (SD 6.06°). The greatest difference in comparison with the baseline was found in the neck, with a measurement of –3.07° (SD 6.43°). The MAE of the angle measurement closest to the baseline was observed in the pelvis (1.40°, SD 1.48°). In contrast, the largest MAE was observed in the right shoulder (6.48°, SD 8.43°). The medians of all acquired joints ranged in difference from 0.19° to 3.17° compared with the reference standard. The ICC values ranged from 0.951 (95% CI 0.914-0.969) in the neck to 0.997 (95% CI 0.997-0.997) in the left elbow joint. The cross-correlation showed that the Lindera-v2 algorithm had no temporal lag. </sec> <sec> <title>CONCLUSIONS</title> The results of the study indicate that a 2D pose estimation by means of a smartphone app can have excellent agreement compared with a validated reference standard. An assessment of kinematic variables can be performed with the analyzed algorithm, showing only minimal deviations compared with data from a massive multiview system. </sec>
Deep Learning Security Systems

Now-a-days, Data Center Infrastructure Management is increasing workplace efficiency, reducing overhead costs, and maintaining availability are some of the top priorities for data center administrators. The markets of data center have evolved not only in reply to the quantity of data, but also to increasing demands approximately connectivity up-time, security, and lesser IT costs. Information Technology is growing more rapidly than ever and new challenges appear every day. Various challenges are data storage and processing, and data centers have a critical role in this situation. As data centers get bigger and bigger, more energy is required and availability is primary. In this paper it is discussed the quality of DCIMby taking into requirements and the quality evaluation problem, here is a proposed method to analyze the quality of DCIM for energy costs, availability and new systems of data center infrastructure management (DCIM). With the proposed method of evolution will definitely resolve the problems of Data Centers so that the throughput of data centre will increase efficiently.
Multi-Grid Redundant Bounding Box Annotation for Accurate Object Detection

Modern leading object detectors are either two-stage or one-stage networks repurposed from a deep CNN-based backbone classifier network. YOLOv3 is one such very-well known state-of-the-art one-shot detector that takes in an input image and divides it into an equal-sized grid matrix. The grid cell having the center of an object is the one responsible for detecting the particular object. This paper presents a new mathematical approach that assigns multiple grids per object for accurately tight-fit bounding box prediction. We also propose an effective offline copy-paste data augmentation for object detection. Our proposed method significantly outperforms some current state-of-the-art object detectors with a prospect for further better performance.
Cryptographic Key Exchange Authentication using Two Servers PAKE

The key trade procedure is well thought-out significant fractions of cryptographic method towards defend protected end-to-end communications. All existing techniques need two servers to be active to authenticate but this technique can authenticate even one server is up and other server is down due to attack as active server authenticate user by taking his parts. In this paper, design an idea Password-authenticated key exchange (PAKE) method to verify clients by utilizing two servers, first client secret phrase will be splitted into two sections and afterward mystery key will be produced for each part and after that by utilizing key and splitted secret phrase will be encoded utilizing Elgamal Encryption. Each encoded part and key will be send to every server. Every server will have its very own key and in the event that aggressor traded off one server, at that point he won't ready to login till he got client information of second server, by utilizing this strategy no assailant can bargain the two servers.
Supplemental Material: Noble metal nanonugget insolubility in geological sulfide liquids

Detailed experimental and analytical methods, and the LA-ICP-MS data set including the R code used to generate Figure 2. &lt;br&gt;