Reviewerly/exHarmony huggingface dataset:
Development of 3D Scanning system by Digital Fringe Projection

This paper describes the development of a 3D shape modeling system by digitally projecting sinusoidal structured light patterns. Here, a sequence of phase shifted sinusoidal patterns of multiple wavelengths are used to extract the 3D model of a given test object. Multi wavelength unwrapping procedure is implemented over spatial unwrapping procedure to achieve smoother unwrapping result irrespective of presence of step heights or shadow regions in the scanned sample. The components of the hardware used include a digital camera, digital light projector, synchronization electronics and a computer with the developed scanner module. Calibration of the camera and projector is carried out and the calibrated parameters are used to acquire the 3D point cloud data from the phase map.
Sentiment Classification using The Sentiment Scores of Lexicons Based on A Kuhns-II Coefficient in English

Many different approaches related sentiment lexicons have already been proposed for sentiment classification because they have had many advantages for the sentiment classification and It has had many significant contributions which have been applied to everyday life, political activities, commodity production, and commercial activities. In this survey, a novel model using the sentiment scores of the lexicons according to A Kuhns-II Coefficient (KIIC) has already been proposed for the sentiment classification of 8,500,000 documents of our testing data set comprising the 4,250,000 positive and the 4,250,000 negative in English. We do not use any training data sets. We do not use any vectors. We do not use any vector space modelling (VSM). In addition, we do not use any one-dimensional vectors. Any multi-dimensional vectors are not used in this model. We only use the sentiment values of the lexicons for the proposed model. We calculate frequency_valence of one term of one document which is a value of the frequency of this term in this document multiplied by the valence of this term. In one document, we calculate a total of all the frequency_valence measures of all the terms of this document which their valence is the positive polarity, called ATotalOfPositive_Frequency_Valences and then, we also calculate a total of all the frequency_valence measures of all the terms of this document which their valence is the negative polarity, called ATotalOfNegative_Frequency_Valences. The sentiment classification of this document is certainly identified by a comparison of ATotalOfPositive_Frequency_Valences with ATotalOfNegative_Frequency_Valences. The novel model has firstly been implemented in a sequential environment. Next, we have performed the proposed model in a parallel network environment secondly. The parallel system has more advantages of the results than the sequential environment. The accuracy of the testing data set has been achieved 88.64%. Our novel model has the benefits of the results which can widely be applied to many different fields in many commercial applications and surveys of the sentiment classification.
Modelling hemoglobin levels of blood donors

To protect blood donors from anemia, donors with low hemoglobin levels are generally deferred from donating. In this thesis we consider various statistical techniques to gain insight in the trajectory of hemoglobin and to predict future values, which both can be useful to prevent deferrals. We examine the longitudinal association of hemoglobin (Hb) and zinc protoporphyrin (ZPP), a biomarker which is believed to be predictive for future Hb levels. We apply a multivariate autoregressive mixed-effects model, and find that our data suggest that there is not a time-dependent association, but rather a correlation of individual specific average values of Hb and ZPP. In the context of out-of-sample predictions, the usefulness of ZPP as a predictor for future Hb levels seems very limited. In order to successfully predict future Hb levels we examine a variety of methods that can be used for longitudinal forecasting. We propose a hierarchical specification of the mean-reverting Ornstein-Uhlenbeck process model, which matches well with the theoretical properties of the trajectory of Hb levels, and we provide a way to generate dynamic predictions with this model. Furthermore, we implement a Bayesian variable selection technique to incorporate an additional relatively high-dimensional set of blood levels, and we consider two decision tree ensemble methods to capture possible non-linearities in our data. We focus on out-of-sample forecasting and find that (i) the hierarchical OrnsteinUhlenbeck model performs slightly better than traditional mixed-effects models, (ii) the tree based methods seem to be most successful in determining eligibility for donation and (iii) incorporating additional blood levels can improve predictions.
Short Paper: Application of Noisy Attacks on Image Steganography

The data hiding techniques have attracted a lot of attention in recent years and mainly with the intensive growth of multimedia and its possibility for covert communication. Steganography is one of the information hiding methods to confirm the ability of a multimedia carrier to exchange secret information between two end-points so that it is imperceptible, thus avoiding the detection of hidden information. The secret information can be embedded in several multimedia carriers, such as image or audio or video files. It works by embedding the message in a source cover which may make the observer feel it is the source cover itself. The type of multimedia carrier here is an image. However, this technique suffers from the problem of the carrier distortion. In this paper, we investigate the impact of some distortion types on the carrier images and discuss the possibility of using distraction images in steganography to protect the stego-image. Furthermore, we highlight the current challenges of image steganography. The experimentations show very interesting results.
Enhancing Cursor Control Using Eye Movements

This paper is about different techniques how we can control our cursor on the computer system without touching the mouse (Hardware). This is possible through the iris of instead of mouse or keyboard. Research that is described in this paper has an aim to reduce the complexities and difficulties that are involved the detection and tracking of the iris for the persons to interact with the computer without touching the mouse or keyboard. The research paper defines operations performed on the images of high resolution of the subject’s (Human) eye to compute/calculate the eye movement/tracking and patterns of iris in left & right direction. The detection takes place according to the center of the eye (Origin of the eye). The calculated/computed data from the position of the iris can be used in the technique of application based processing. The Cursor Control Using Iris research has various applications in the field of Human-Computer Interaction (HCI) like mouse cursor control. In this paper, there is a discussion about eye tracking using eyeball mouse.
Research on the Clustering Method of Agricultural Scientific Data Based on the Author’s Scientific Research Relationship

Focusing on semantic parse and bias problems during the clustering process of agricultural scientific data, a clustering method for agricultural scientific data based on author’s scientific research relationship is proposed in this paper. Meanwhile, an assessment algorithm of the scientific research relationship based on co-author ship and authors’ inter-citation is put forward. Finally, the experimental results proved that the proposed clustering method for the agricultural scientific data can effectively improve error classification caused by semantic parse and bias.
A v-Hog Tensor Based Discriminant Analysis for Small Size Face Recognition

Apart from Illumination, Pose and Expression variations, low dimension is also a primary concern that spiflicate the performance of face recognition system. This work distils to applying v-Hog Tensor discriminant analysis on small sized face image to yield good result in terms of correctness rate. Firstly the face image is mapped on to w-quintuple Colorspace to effectively interpret information existing in the image. Further discriminant features are extracted out of Tensor plane to bore on the confounded image due to reduction of image size. To exhibit the beauty of the feature, v-Hog [22] is adopted. The obtained features are further mapped to a lower dimension space for efficient face recognition. In this work the effect of fSVD [17] with bias is also considered to fortify the recognition system. Finally, for classification five different similarity measures are used to obtain an average correctness rate.
A linear logical framework in Hybrid (invited talk)

We present a linear logical framework implemented within the Hybrid system [Felty and Momigliano 2012]. Hybrid is designed to support the use of higher-order abstract syntax for representing and reasoning about formal systems, implemented in the Coq Proof Assistant. In this work, we extend the system with a linear specification logic, which provides infrastructure for reasoning directly about object languages with linear features.
Breaking Down Barriers to Collaboration in Military Satellite Systems

The current state of the military satellite command-and-control enterprise consists primarily of so-called “stove-piped” acquisitions that provide a complete end-to-end capability to operate a single satellite system, and which typically must be recreated for each new satellite system. In this paper we present several techniques and technologies that we believe can help address challenges of acquiring and operating these types of systems. We will focus on two phases of satellite command and control and show how the adoption of existing commercial technologies can be used to increase the pace of collaboration.
The Effects of Culture on Authentication Cognitive Dimensions

The purpose of this research is to answer the question: does selecting images from one’s culture improve the memorability of Recognition-Based Graphical Password (RBG-P)? The results show that the failure rate of authentication increases through the progression of consecutive three phases. The findings also suggest that cultural groups with higher number of images selected from own culture, inclined to experience lower failure rates and vice versa. In fact, the ISGs that selected from their own culture showed approximately half the means of failure of the groups that selected from other cultures. Resultantly, culture has significant effects on the password memorization, therefore, the designer must be motivated to provide cross-cultural interfaces that reduce the risk and improve usability of RBG-P which minimize the frustration associated with login failures. The quick depreciation of the success rate with the progress of the phases suggests the possibility of memory decay due to temporal effects.
Applying Random Forest Method to Analyze Elderly Fitness Training Routine Data

This study used the random forest algorithm to predict Senior Fitness test results on the execution of Synchronized Monitoring Analysis Record Care (SMARC) programs with the aim of aiding healthcare professionals in modifying patients’ training routines to improve their effectiveness. Twenty-three subjects in a community center performed a fitness training routine using the SMARC series of equipment and training modes, and took timed “Up and Go” tests before and after their performances. The 74 combined features (categorical + numerical) of the series were used as input features, and performance was measured by the Timed Up and Go (TUG) score. The results show that the top five features ranked with the highest importance were associated with Machines F (16.5%), D (15.4%), E (13.9%), H (13.9%), and B (12%), with 35% unassignable. The results can aid healthcare professionals in planning and adjusting more targeted health-promotion exercises programs using assistive devices for the elderly.
Phone service by balloon

Kenya runs on mobile phones. There are almost 43 million in use by Kenya's nearly 50 million citizens, meaning the East African country has the 33rd highest mobile phone usage in the world. By comparison, it has fewer than 70,000 fixed landlines.
Measurement of the Direct Flux of Solar Radiation During Operation of a Big Solar Furnace

Methods for measuring solar radiation are considered and long-term data obtained by actinometric measurements of solar radiation at the location of the big solar furnace of the Academy of Sciences of Uzbekistan Institute of Materials Science Scientific Production Association Physics-Sun, with a thermal power of 1 MW, are analyzed. Concentrators of solar radiation efficiently operate at high values of the direct flux of solar radiation, whereas photovoltaic stations operate on diffuse and total radiation, too. Therefore, the main attention is paid to the measurement of the direct flux of solar radiation. The first results until 2013 were obtained by a semi-automatic mode with the help of actinometers of the AT-50 type, after that an automated meteorological station of the MHP type with high-precision pyrheliometers CHP1, manufactured by Kipp & Zonen, was produced by the Netherlands, which is the leader in the production of solar sensors. During the operation of the Big Solar Furnace, a direct stream of solar radiation is continuously measured, since the power of the installation is directly proportional to this. The obtained long-term results of measuring the direct flux of solar radiation are processed in order to obtain average statistical data by years. To obtain reliable data on solar energy, solar sensors are annually calibrated. The last verification was carried out in January of 2018 at Kipp & Zonen.
Removing Stray Noise Quickly from Point Cloud Data Based on Sheep Model

The noise data could be produced when we scanned the object by Handy 3D scanner due to human factors, the target surface and the instrument itself factors etc. Noised point cloud data could seriously affect the precision and efficiency of three-dimensional reconstruction in late stage. To this problem, we used the sheep body’s three-dimensional point cloud data and changed the algorithm of k-nearest neighbors and presented method that combined the k-nearest neighbor denoising and median filtering. Firstly, the improved k-nearest neighbors algorithm could establish topology relationship fast, identify and delete some noise data; then, using the filter method processed the point cloud data and all noise data could be identified and deleted. The experimental results show that the method we presented can eliminate the stray noise from the point cloud data quickly and accurately and keep ideal target.
From Data Chaos to the Visualization Cosmos

Data visualization is a general term that describes any effort to help people enhance their understanding of data by placing it in a visual context. We present a ubiquitous pattern of knowledge evolution that the collective digital society is experiencing. It starts with a challenge or goal in the real world. When implementing a real-world solution, we often run into barriers. Creating a digital solution to an analogue problem create massive amounts of data. Visualization is a key technology to extract meaning from large data sets.
STUDY REGARDING CREDIT GRANTING TO NONGOVERNMENTAL CLIENTS FROM THE WEST REGION BY THE BANKING SYSTEM

This paper analyzes the bank credit which plays a major role in financing the Romanian market economy. It is demonstrated by scientific research that the lending process represents the main source of funding for a country's economy, the types of credit varying and adapting to market requirements. The methods used by the authors consisted in data collection, documentary analysis, synthesis, graphic representation. Accessing a credit must be advantageous to both parties, both for the bank, by expanding and diversifying the credit portfolio so as to obtain extra profit, and for the client, who can grow their business through the credit they are accessing, earn profit and can thus repay debts to the bank.
Police algorithm favours easy cases

Machines are deciding which crimes police investigate, finds Joshua Howgego
Smart Hand Offs and Earthdata Search

Often a science user will discover data of interest in a general-purpose discovery tool like Earthdata Search. At that point it might be beneficial for the science user to switch to a more specialized tool. Smart handoffs allow the user to switch from one tool to another with their context (collection, spatial and temporal constraints) intact. This provides an efficient means of traversing tools and services. The idea of smart handoffs could be expanded to commercial search engines such as Google, visualization tools like State of the Ocean and Giovanni and domain-specific search tools like Earthdata Search.
The impact of exchange rates on economic growth in Iraq for the period 1995-2015

The currency is the main engine of the process of trade at the internal and external levels, and the exchange rate is one of the fundamentals of the foreign trade to settle international payments, as the import process to the currency of the country of origin to pay the value of imported goods on the one hand, on the other hand, we find that individuals in the case their travel to another country they need the currency of the country they travel to, and in this case they find themselves in the process of exchange, so that shifting in the exchange rate affect the process of trade and thus on economic growth. Based on the above, the title of the topic, which aims to identify the theoretical framework of exchange rates and economic growth models as well as measuring the impact of exchange rate fluctuations on economic growth in Iraq, has been chosen by formulating a standard model for the period 1995-2015
Open Access digital repositories in India and China- A comparative study

The main objective of the study is to make a comparative study of Indian and Chinese repositories on various parameters like regional distribution, subject coverage, language diversity, content archived, collection development, operational management, etc. To achieve the objectives of the study, the OpenDOAR was selected as the source for the identification of repositories from India and China. The results reveal a total number of 115 repositories were registered in the OpenDOAR from India and China in which India has more repositories than China; however, repositories from China are content rich (in terms of collection size) as compared to India. The repositories from China accept contents only in two languages - Chinese and English whereas repositories from India accept contents in 11 languages. More repositories from China have active links and are OAI-PMH compliant than India whereas more repositories from India have well-defined metadata, preservation and content submission policies than China.
Quantum-to-classical transition in the driven-dissipative Josephson pendulum coupled to a resonator

We investigate the driven quantum phase transition between bound oscillating motion and the classical nearly free rotations of the Josephson pendulum coupled to a harmonic oscillator in the presence of dissipation. This model describes the standard setup of circuit quantum electrodynamics, where typically a transmon device is embedded in a superconducting cavity. We find that by treating the system quantum mechanically this transition occurs at higher drive powers than expected from an all-classical treatment, which is a consequence of the quasiperiodicity originating in the discrete energy spectrum of the bound states. We calculate the photon number in the resonator and show that its dependence on the drive power is nonlinear. In addition, the resulting multi-photon blockade phenomenon is sensitive to the truncation of the number of states in the transmon, which limits the applicability of the standard Jaynes-Cummings model as an approximation for the pendulum-oscillator system. We also compare two different approaches to dissipation, namely the Floquet-Born-Markov and the Lindblad formalisms.
Smart Anonymous Authentication Protocol for E-Governance

Authentication services used many times a day.If there is no user authentication, then it would be impossible to use email accounts, discussion boards, e-banking or even electronic communication.On the other hand, It releases a lot of personal information during every authentication process.User login can be linked to used services and assets by service providers.The frequency of usage and therefore the map of our behavior on the Internet can be created to make more focused advertisement, to track us or even to steal our electronic identity.The purpose of this paper is to state the requirements and provide the initial design for an anonymous authentication scheme which prevents the leakage of private information.The new scheme, to be widely acceptable, must be beneficial for both users and service providers, who implement the authentication systems.Therefore the new authentication system must provide a feature for revealing dishonest users.These users can be eventually deanonymized and charged for damages.This paper provides such a responsibility-protecting feature in this new scheme.
Feature Pair Index Graph for Clustering

Abstract Text documents are significant arrangements of various words, while images are significant arrangements of various pixels/features. In addition, text and image data share a similar semantic structural pattern. With reference to this research, the feature pair is defined as a pair of adjacent image features. The innovative feature pair index graph (FPIG) is constructed from the unique feature pair selected, which is constructed using an inverted index structure. The constructed FPIG is helpful in clustering, classifying and retrieving the image data. The proposed FPIG method is validated against the traditional KMeans++, KMeans and Farthest First cluster methods which have the serious drawback of initial centroid selection and local optima. The FPIG method is analyzed using Iris flower image data, and the analysis yields 88% better results than Farthest First and 28.97% better results than conventional KMeans in terms of sum of squared errors. The paper also discusses the scope for further research in the proposed methodology.
Setting the template for Naira denominations detection

The ubiquitous method of counting money by hand is definitely not acceptable when large amount money is to be dealt with, from time and accuracy stand points, which have led to the use of Automated Money Counter to determine the number of fed notes without distinguishing their denominations. Although numerous algorithms and devices have been developed to detect denominations for several currencies but, based on all accessible literatures, this paper seems to be the first attempt to automatically detect Nigeria currency denominations as it provides an algorithm that detects both paper-based and polymer-based Nigeria currencies. Thus, this paper set the pace for future research studies in the area of automatic Nigerian Naira denominations recognition systems. The algorithm used is achievable with relatively cheap hardware requirements, yet with substantial overall accuracy of 98.75% for non-mutilated notes but it is yet to be tested with defaced and mutilated notes. The algorithm developed can be deployed to function as mixed-denominations money counter or as denomination detector.