Reviewerly/exHarmony huggingface dataset:
A Fast 3D Reconstruction Method Based on Curve Segment of Binocular Vision

Aiming at the problem of low efficiency of the 3D reconstruction, a fast method based on piecewise quadratic curve is proposed. Firstly, a multi-line structured light binocular vision measurement system is used to obtain the two-dimensional image. Through the two-dimensional image, the center line and feature points of the laser strip are quickly acquired. Then, the acquired feature points are used as the given data points of curve interpolation, and NURBS curves are used to interpolate the feature lines of the image. According to the perspective invariance principle of plane curve, the zero curvature point and cusp point on the curve are detected and used as segmentation points. Using the segmentation results, a number of points on each NURBS curve segment are taken to fit as the quadratic curve. Finally, by constructing the right and left space straight taper surfaces, the three-dimensional reconstruction of the feature lines is completed by the method of surface intersection. Taking the black shoe sole as the experimental object, the results show that the method proposed in this paper can quickly complete the three-dimensional reconstruction of the inner and outer feature lines of the shoe sole, which can provide the basis and guarantee for the follow-up shoe sole process monitoring and quality inspection.
Signal properties correlation studying discrete control systems

Abstract In recent years, due to the intensive development of computer technologies in industrial automation, discrete control systems have been increasingly used. To determine the stability of the system, calculations of the correlation functions of signals of various types can be used. In practice, signals with different types of modulation are used: amplitude, phase and frequency, as well as their various combinations.
Image Retrieval Based on Color Feature Similarity

In the early days, many user interactive systems performed with basic concepts but such systems are not reaching the user specifications. A huge amount of interest had been taken in the CBIR system. In most recent years, a lot of work has been carried out in the content-based image retrieval system. There are three primitive visual features namely color, texture and shape of an image with reference to content-based image retrieval. Although visual features cannot be completely determined by semantic features, still semantic features are in use because they are easier to integrate into mathematical formulas. In this paper, we focus on the retrieval of images within an extensive image collection based on color projection. We applied a new approach for the retrieval of images within extensive image collections. Therefore good visual feature is one of the important tasks of representing image compactly. Among the visual features, color is the most vital, reliable and widely used features. In this paper RGB color combination considered for retrieval of images. This paper focuses on methods to extract color images quickly for CBIR. First, RGB was quantified in L*a*b and use with the new approach to finding out the most similar images out of given image collection data. The proposed approach shows an efficient image retrieval system which results in an improved system over the prior techniques.
GPU Local PSO Algorithm at Dimension Level-Based Medical Image Registration

For high dimension optimization problems, the performance of sequential particle swarm optimization is time-consuming. This paper presented a GPU-based parallel local particle swarm optimization algorithm at dimension level for medical image registration. Specially, a thread block represents a particle, while a thread in a block represents one dimension of an optimization function. Furthermore, the stop criterion is set as an acceptable range of derivation. In the experiment, for the high dimension optimization medical image registration problems, the speedup of GPU-based implementation can reach up to 95. The overall average difference of iterations to stop between the sequential algorithm and GPU-based algorithm is 17.
CBIR aided classification using extreme learning machine with probabilistic scaling in MRI brain image

Abstract An enormous number of magnetic resonance imaging (MRI) brain images were produced in hospitals and several MRI centers. To exploit the diagnosis in MRI brain image, “content-based image retrieval (CBIR)” system is accessed in the MRI brain image database. In this paper, a content-based MRI brain image retrieval system is presented, which is helpful in the medical field to seek a diagnosis in an MRI brain image that is similar to the example given. This paper consists of preprocessing, feature extraction, feature selection, similarity measure, and classification. In the preprocessing phase, the Wiener filter is used to remove the unwanted pixels from an MRI brain image. In the second phase, the features related to MRI brain image are extracted using characteristics of shape, margin, and density of the MRI. In the third stage, the features of MRI brain image were reduced using principal component analysis. CBIR classification is used in this method to gain effectual results. In the first stage, retrieval images are obtained using similarity measures using the similarity between the query image features and the derived trained image features. Finally, the classification stage is an extreme learning machine with probabilistic scaling used to classify the obtained retrieval output image and the query image. The result demonstrates that the proposed CBIR approach is robust and effectual compared with other latest work.
Effects of Locomotion Style and Body Visibility of a Telepresence Avatar

Telepresence avatars enable users in different environments to interact with each other. In order to increase the effectiveness of these interactions, however, the movements of avatars must be adjusted accordingly to account for differences between user environments. For instance, if a user moves from one point to another in one environment, the avatar’s locomotion speed must be adjusted to move to the corresponding target point in another environment at the same time. Several locomotion styles can be used to achieve this speed change. This paper investigates how different avatar locomotion styles (speed, stride, and glide), body visibility levels (full body and head-to-knee), and views (front views and side views) influence human perceptions of the naturalness of motion, similarity to the user’s locomotion, and the degree of preserving the user’s intention. Our results indicate that 1) speed and stride styles are perceived as more natural than the glide style, while the glide style is more intention-preserving than the others, 2) a greater locomotion speed of the avatar is perceived as more natural, similar, and intention-preserving than slower motion, 3) the perception of naturalness has the greatest impact on people’s preferences for locomotion styles, and that 4) head-to-knee body visibility may enhance the perception of naturalness for the glide style.
Curriculum for Digital Culture at ITMO University

In many scopes of human activities, both personal and professional, new digital tasks are emerging every day. The new educational module “Digital Culture” at ITMO University aims at building digital competencies of university students, both bachelors and masters, that is to teach students the existing approaches and methods of tasks solving, as well as to show them data processing and analysis techniques to implement in the future in their professional fields. Apart from conducting data analysis, the graduates are supposed to know how to interpret the obtained results correctly and how to navigate in the digital space easily. The disciplines of the first two years of study have been already introduced in the educational process of ITMO University both in bachelor’s and master’s degree programmes. This paper presents the curriculum content, the learning method and the results of the first years of the educational module. The disciplines of the module received positive feedback from both students and external experts in the intercollegiate seminars on digital education.
Jan Blommaert. <i>Durkheim and the Internet: On Sociolinguistics and the Sociological Imagination</i>

Abstract This article reviews Durkheim and the Internet: On Sociolinguistics and the Sociological Imagination 978-1-3500-5518-6
A Highly Reliable Wearable Device for Fall Detection

A late treated fall may cause irreparable damage or even the death of a human being. This problem gets worse with the older ages of the person suffering the fall. Solutions to this problem do exist in the market but do not appropriately address the reliability of using the proposed devices. None of the existing solutions clearly present their capabilities in terms of testing, operation safety and fault tolerance. This work not only gets structured the offline and online tests to which the device should be exposed, but also proposes the use of hardware and software redundancy to provide for a more reliable solution for the problem. A prototype of a wearable device for fall detection has been developed, that provides for safe operation and tolerate faults, while delivering very low current consumption and low cost, those that are essential specifications to meet the market demands for wearable devices.
A Model for Reinforcing the Principal’s ICT Leadership

This paper addresses the issue of motivating teachers to integrate ICT into their teaching practices from the viewpoint of the school principal's ICT leadership. The results of a previous prospective research, highlights the demand of school principals to be trained to carry out a plan to integrate ICT in their schools. In this paper, we propose a model ICT integration motivation strategy to support the principal in preparing his or her vision of ICT integration. The proposed PMI_TICE pyramid describes the five levels of teacher motivation regarding the integration of ICT in their classrooms, which the school principal must take into account when designing and deploying his or her strategic plan for ICT integration in the school.
A Flexible Web Authoring Tool for Building Mobile Learning Experiences

This paper presents a flexible web authoring tool called MoLE for teachers to build their own mobile learning experiences. MoLE allows teachers to define learning activities (set of learning tasks within a workflow) that can be accessed from a mobile learning application. Through MoLE, the reuse of learning tasks and learning activities is favored so that a community of teachers can co-create activities and share them. Additionally we present an evaluation of it in order to assess the usability of the tool for users with different backgrounds.
Transformation of REST Service Description for Structured Service Registry

On the early stage of its life cycle, a web service must first be discovered before it is accessed by its clients. A web service description is a document published by the service provider that allows potential clients to get hold of information of a web service during the discovery process. Web services built based on simple object access protocol (SOAP) use a standardized XML document known as Web Service Description Language (WSDL) to describe itself. On the other hand, most web services built based on representational state transfer (REST) has yet to be described in a structured form. REST service description is mainly written in text in HTML documents aimed to be read by human readers, thus containing little to none machine-readability properties. This work proposes a solution that accounts standardization and machine-readability property while still considers the simplicity and human readability property of REST service description written in HTML documents. The solution combines concepts that have been proposed before to construct a new service description mechanism to allow human-readability and machine-readability while still maintaining its simplicity and standardization.
[DC] Privacy-Preserving Relived Experiences in Virtual Reality

It is common for people to capture and share experiences using photos or videos, but sharing experiences through photos, videos, or even 360-degree videos limits people to reliving memories from the original perspective. This research is to design a unique time-machine-like experience sharing method through virtual reality (VR), which allows people to capture their experience in 3D and to ‘enter’ into others’ past experiences in VR, move around and relive their memories from different perspectives. Through my doctoral research, I describe a three stages of research to understand user experience, to investigate people’s privacy perceptions and to develop effective privacy protection mechanisms for such relived experiences in VR.
An Architecture for Opinion Mining on Journalistic Comments: Case of the Senegalese Online Press

Comments from the Senegalese online press can create important opportunities for the socio-economic and political actors of our country. These are potentially promising data and useful sources of information. However, the complexity of these data sets no longer allows current methods of opinion mining to exploit this type of comments. This complexity is caused by ambiguous sentences, out-of-context comments and the use of terms borrowed from national languages. To avoid the risk of not reflecting the collective opinion of Senegalese readers, we are interested in proposing an architecture solely for the purpose of valorizing journalistic comments. The architecture will highlight a new solution to solving these types of problems.
Mechanical Trust

Perhaps one of the least appreciated roles of Computer is that of moderator. We often repeat the superficial observation that IEEE periodicals identify the most exciting and most promising results of current research; we forget that they also calm the discussions of current research. They curb overblown expectations, expose the fallacy of unsubstantiated benefits, and reveal shortcomings that require further exploration. Furthermore, they are often quite good at identifying the true significance of a new technology and explaining the applications that should produce the greatest value.
A Data Tracking and Monitoring Mechanism

There is a rising trend among companies to collect data including personally identifiable information (PII) from service users. An individual’s privacy can be violated when his/her PII is accumulated, utilized or divulged. Users of the technology are unable to comprehend what information about them is being utilized, how, when and by whom. With this situation in mind, data transparency is an absolute necessity to combat this issue. Extensive research is being carried out to understand and address the problem. In this research, we propose a security mechanism known as D2TRacker, which can perform data monitoring and data tracking on the processes that are taken on the user’s data and ultimately provides data transparency to these service users. Through the development and execution, the results obtained showed that data transparency could be provided to the system users. Overall, this solution serves as a stepping stone in solving the issues encountered. This solution works as intended in a simulated environment, but deployment in real world would need further enhancements.
Body. Sound Spaces and the Embodied Musical Mind

Each sound refers to the prenatal intrauterine life in which the Self, since the first months of intrauterine life, was formed. It is the sound world, the expression of the continuous maternal-foetal interaction, that defines the space where the foetus is immersed and determines the close relationship that will occur during the whole life between the body, its feeling, and sounds. Language and music have as a common ancestor the vocal signals that characterized primates’ communication, allowing them to exchange information as well as its related emotional content. Therefore, sound bears a wider meaning than that which can be expressed through words; it is able to embrace the same subconscious or unconscious dimension that characterizes both the individual being and its action. Apparently, music dynamics have direct access to the affective structures of our nuclear consciousness; therefore, sound becomes an expression of the deepest Self. Before emotion, at the base of the emergence of the Self, we have our body that characterizes the very quality of musical experience and today increasingly appears inextricably connected with cognitive processes.
A Survey on Feature Fatigue Analysis Using Machine Learning Approaches for Online Products

On recent days, the leading manufacturers are very keen in online business processing; the products are brought into heavy competitive online market. To be successful in the online market, the manufacturers launch the new products with many features to compete with other manufacturers’ products. The online customers are also interested in choosing the products with more attractive features, but the customers face problems in the features of the product by using it. Here, the term “feature fatigue” refers to the concept of customers’ dissatisfaction. In the real market, the products with maximum attractive features are preferred by the customers in the initial stage. Later, the customers realize that some of the features are inconsistent which results in dissatisfaction on the product. Moreover, this dissatisfactory of the customers on the product majorly affects the goodwill and growth of the manufacturer. Many researchers have contributed several techniques to overcome the concept of feature fatigue. In this paper, the most significant feature fatigue analysis methods are discussed as a review to elevate the feature fatigue.
A Novel Approach for Border Security; Surveillance Drone with Live Intrusion Monitoring

Everything is being automated day-by-day. Automation has made life flexible. Border security is one of the most crucial aspects of a country's defense. Monitoring the border with human labor is a very tough job as it requires constant attention and overwatch. In this paper, we have proposed an idea to make border security more vigilant and active. As quadcopters fly in the sky and record everything with a wide-angle, it becomes easy to watch an extensive area with one drone. Along with the help of machine learning, we can easily detect the intrusion (human & another animal) from the video captured by the drone. If we fly a drone around a large area, then only one drone can do the work of 10 to 30 border guard humans very quickly, which is very much feasible.
Library: Illustration: Tools for Illustration

Illustration is a type of art that is a visual explanation or interpretation of a written text.
Coherent state truncation by conditional interferometry

Based on a conditional interferometry proposed by Paris [Phys. Rev. A 62, 033813 (2000)], we prepare any chosen superposition of the vacuum, one-photon, and two-photon states, which is truncating from an input coherent state. Feeding two perfect single-photon states and a coherent state into the interferometry and employing two one-photon detections, the conditional state can be obtained in the signal port. Ideal and realistic features of the one-photon counting are taken into account together with the effect on the fidelity between the ideal state and the realistic case. The ideal state is just a particular case of the realistic state with the unit efficiency. We study the antibunching effect and Wigner function of the generated states. The results show that the generated states will exhibit their specular character.
Data Extraction and Preprocessing for Automated Question Answering Based on Knowledge Graphs

This article discusses the algorithms and methods of data representation for knowledge graphs. The proposed algorithms make it possible to automate the process of extracting and processing data from users’ requests within the mixed learning process and reduce the role of an expert in the preparation of question-answering data sets necessary for training models of dialogue systems. The results show that the method of enrichment of the knowledge graph leads to an increase in the number of links and the accuracy of vector representation models.
Overview of an Approach on Utilizing Trust and Provenance Metrics Combined with Social Network Metrics on Recommender Systems

In this paper the focus will be to estimate and evaluate the measures and metrics of Social Network Analysis (SNA) and network trust and provenance in order to achieve better recommendations. Since, each of these fields are usually treated separately, the aim is to merge and correlate Social Network Analysis metrics and network provenance in order to develop and enhance the baselines of certain Recommender System (RS). A thorough background research has been conducted in order to distinguish the main components of each field separately, followed by the methodology that is in intention to be our main approach. At the end, we will have an evaluation overview of one RS, with a detailed explanation on the metrics that have to be added in order to improve the desired recommendation at the end.
Effects of Physical Prop Shape on Virtual Stairs Travel Techniques

Experiences of Virtual Reality training and architectural virtual environments benefit when provided a higher sensation of stair climbing. Passive haptic props can add that sensation. These methods present a safe approach by placing short ramps on the floor rather than a physical staircase. To improve a user’s level of immersion, we conducted an experiment to explore the shape of physical props to change the way users were aligned and moved while traveling up or down a virtual set of stairs. We investigated three methods for physical props while ascending and descending virtual stairs. Results suggest that elongated props provide a better experience and are more preferred.
Measurement of biomechanical behavior of dentin hard tissue in response to unbound water loss using stereo-digital image correlation

Abstract Understanding the biomechanical behavior of dentin hard tissue with fluid-filled dentin tubules and hydrated matrices is essential for studying this functionally graded biological composite. The stereo-digital image correlation technique with an adaptive high-magnification field of view (FOV) for fully hydrated biological tissue measurement was investigated. The adaptive magnification is controlled by the length of extension tubes. To determine both the unbound water loss induced and load-induced three-dimensional (3D) deformation of dentin hard tissue from a fully hydrated state to a non-hydrated condition, samples of dentin blocks and half teeth in sagittal sections were studied for a period of 2 h in situ over varied speckle patterns. The effects of speckles on water evaporation, camera pre-heating, and measurement accuracy in the wet, curved and long-term measurement were analyzed. The elastic modulus and Poisson’s ratio of both dentin and pulp in response to unbound water evaporation were measured. With the unbound water loss, the mean values of the elastic modulus generally increased from ∼8 GPa to ∼10 GPa in pulp region and from ∼10 GPa to ∼12 GPa in dentin region. The mean values of the Poisson’s ratio increased both in pulp and in dentin. Poisson’s ratio in the dentin regions (∼0.3) were generally smaller than those in the pulp regions (even can reach 0.6), irrespective of the partial dehydration time. Further analysis of the full-field deformation results provided insight into the unbound water-induced regional deformations and mechanical changes in human dentin. It’s found that the unbound water loss induced deformations were more prominent when compared to load induced deformations.