Reviewerly/exHarmony huggingface dataset:
Proposal of Ad-Hoc Secure Device Pairing Method Using Similarity Between Marker Movement and Acceleration

Currently, IoT devices often use wireless technologies to communicate with each other. An example is ad-hoc device pairing such as wireless distribution of meeting materials from a PC to mobile device. The problem in this case is spoofing by an impersonator. In order to solve this problem, we proposed secure device pairing method using similarity between displacement data of a marker displayed on devices and acceleration data obtained from devices. We performed experiments to confirm similarity and whether impersonator can pair with the server. As a result, we found that similarity was low and unstable. Therefore, in this paper, we propose an extended method that marker changes at an interval. These sequence of markers displayed on the device is used to recognize the device by a camera in addition to calculation of the similarity. We performed 3 experiments to confirm the similarity displacement data and examined whether an eavesdropper outside the camera range can perform pairing. Also, we performed pairing of some device together. As a result, average similarity was higher than that of previous method and pairing of three devices succeeded at rate of about 70%.
On the fidelity of quantum gates under T1 and T2 relaxation

The present work analyses the effect of T1 and T2 relaxation on the fidelity of quantum gates in terms of Choi-Jamiolkowski isomorphism. Numerical computations is used to show that the value of fidelity is nearly independent of the gate Hamiltonian. This fact leads to the universal estimate of fidelity, and the accuracy of this estimate is studied, especially for the case of one qubit.
Securing the regions comprising information in a document image with novel key selection technique – a parallel approach

Securing the information contents in an image with increase in speed is a challenging issue even today. In this paper, a parallel approach to secure information contents of important regions in a document image is proposed. The novelty of the approach are to identify intelligently the regions comprising information is to be secured, generating and selecting the key sequence. The proposed method comprises of four stages. In the first stage, rules of cellular automata are selected randomly to generate the key sequence. In the second stage, key sequences are selected on the basis of sarpabandha which depicts pattern of the movement of snake. The input color image is decomposed into non overlapping blocks of uniform size which are processed in parallel. Using Grey Level Co-occurrence Matrix (GLCM), entropy feature is extracted for each block and based on the feature value classification of blocks are carried out in the third stage. In the last stage encryption operation is performed for each plane of input color image separately. Red, green and blue color planes of input color image are fused with the key sequences to perform the encryption. Cipher is feedback to enhance the diffusion of information. The proposed methodology is analyzed in terms of parameters peak signal to noise ratio, entropy, structural similarity index and correlation coefficient. In the proposed work, identification of regions and encryption both are processed in parallel to reduce the time of computation.
Segmentation and Extraction for the Diamond Grain Image Based on the Gauss-polymerized Enhancement

To solve the problem of many background noises in image segmentation of diamond grains under the complicated texture background, an image segmentation and extraction method for diamond grains based on the Gauss-polymerized enhancement was proposed in this work. Firstly, the original diamond grain image was pre-processed by the method of histogram equalization in order to enhance the overall contrast effect of the image. Secondly, the image was further processed by the method of Gauss-polymerized enhancement through setting proper Gauss filter parameters, which purpose is to enhance the boundary definition between the grain and the matrix, and reduce the complex background noises. On this basis, the morphological dilation was used to eliminate the non-interested regions of the complex background noises, and obtain the segmentation region of the interested target grain. Finally, the diamond grain can be extracted from the grain image based on the segmented region of the target grain through the operation of image multiplication. The results show that the proposed method can effectively reduce the influence of the complex texture background on the segmentation and extraction of the target grain. The extracted image of the target grain can be further used to analyse the grain size characteristics and grain wear pattern identification in a higher level.
THEORETICAL FOUNDATIONS AND METHODOLOGICAL SCHEME FOR THE ASSESSMENT OF INDIVIDUAL EDUCATIONAL RESULTS OF STUDENTS IN THE PROCESS OF ADDITIONAL EDUCATION

The article is devoted to the problem of assessing the individual educational results of students in the process of additional education. This assessment in the concept of the authors is considered as the most important condition for the independent progress of the student along the individual educational trajectory. In this case, the student is the subject of its design. A model for assessing the individual educational results of students in the format of an educational event is proposed. The basic principle is formulated, which consists in fixing activity manifestations in a given situation, which testify to the student's ability to independently solve a creative task. These manifestations include: adequate understanding of the meaning of the problem being solved, competent determination of means and methods for solving it, competent access to various resources, and implementation of productive communications, ability to present and defend the solutions obtained. It is shown that the main components of such an educational event should be: joint solution of original creative tasks by students, expert-analytical support of this activity and free creative communication of different participants. A methodological scheme for the preparation and conduct of such an educational event is described. Its structural elements are: a preliminary analysis of data monitoring the development of students' creative activities; development and testing of a package of creative tasks; preparing a team of experts and equipping it with the necessary tools; development of the Festival program using a variety of creative communication formats of the participants; organization of information and analytical support of the Festival. Recommendations on the preparation of local working spaces for various types of activities of the Festival participants are given.
Method on multi-dimensional modulation in inter-satellite quantum communication

A multi-dimensional modulation scheme in inter-satellite quantum communication based on pulse position modulation and polarization encoding is put forward and designed. By this way we can send additional classical signal simultaneously when transmitting quantum signal. The basic principle of multi-dimensional modulation scheme is introduced. Simulation experiment is performed using Optisystem and Matlab simultaneously. The binary sequence before modulation and that after demodulation are compared and analyzed. The error bit rate, eye diagram and quality factor of classical optical date are obtained. Stabilities of classical optical signal during the transmission are tested. The results show that this multi-dimensional modulation scheme can decrease the numbers of information channels needed, increase information transmission efficiency and reduce the demands for power load systematic complexity in communication terminals. The proposed coexistence system is confirmed to be effective and applicable.
Data Visualization: The Current Situation of African Internet

The current Internet penetration in African is significantly below the world average level, while African has the second largest population in the world. This article aims at analysing the current situation of the African Internet to see the insights behind the massive related datasets, containing the design and implementation processes of a resulted platform. The platform consists of three web pages for showing the results, databases, and webpage controller implemented by Java. After collecting available datasets online, we now need a visualized tool to analyse the reasons behind those raw data, to explore the attributes and environment of the complex network, hence we derived a web-page platform for the task, where researchers can query detailed information according to certain requirements. The first page of our platform shows the structure of the African network topology, the second web page allows users to interact with the data, generating corresponding graphic results, and the third web page handles queries, request with certain manner defined by users.
Problems of development professional competence graduate of bachelor in direction 38.03.04 «State and municipal management»

The article deals with the problems associated with the independent development of higher education institutions of professional competence in the direction of training 38.03.04 «State and municipal management» in the absence of professional standards for civil servants. For the solution of this problem it is offered to use the qualification requirements established by methodical materials of Ministry of labor of Russia.
Unsupervised segmentation of micro-CT images based on a hybrid of variational inference and adversarial learning

This paper presents a novel unsupervised segmentation method for the 3D microstructure in micro-computed tomography (micro-CT) images. Micro-CT scanning of resected lung cancer specimens can capture detailed and surrounding anatomical structures of them. However, its segmentation is difficult. Recently, many unsupervised learning methods have become greatly improved, especially in their ability to learn generative models such as variational auto-encoders (VAEs) and generative adversarial networks (GANs). Meanwhile, however, most of the recent segmentation methods using deep neural networks continue to rely on supervised learning. Therefore, it is rather difficult for these segmentation methods to cope with the growing number of unlabeled micro-CT images. In this paper, we develop a generative model that can infer segmentation labels by extending α-GAN, a principled combination that iterates variational inference and adversarial learning. Our method consists of two phases. In the first phase, we train our model by iterating two steps: (1) inferring pairs of continuous and discrete latent variables of image patches randomly extracted from an unlabeled image and (2) generating image patches from the inferred pairs of latent variables. In the second phase, our trained model assigns labels to patches from a target image in order to obtain the segmented image. We evaluated our method using three micro-CT images of a lung cancer specimen. The aim was to automatically divide each image into three regions: invasive carcinoma, noninvasive carcinoma, and normal tissue. Our experiments show promising results both quantitatively and qualitatively.
Region-guided adversarial learning for anatomical landmark detection in uterus ultrasound image

The length and thickness of the uterus and endometrium are morphology characteristics as important measures for uterine diagnosis. In diagnosing uterine, doctors mark anatomical landmark points of uterus and endometrium in order to measure their length and thickness. However, it is difficult to reliably detect the landmarks of the uterus and endometrium due to the ambiguous boundaries and heterogeneous textures of uterus transvaginal ultrasound image. In this paper, we propose a novel region-guided adversarial learning framework for anatomical landmark detection in transvaginal ultrasound image, aiming at automatically detecting the landmark points of uterus and endometrium of transvaginal ultrasound image to a diagnostical precision. In the proposed adversarial learning scheme, the proposed framework consists of a landmark predictor and two discriminators for the uterus and endometrium. The proposed landmark predictor is to detect the desired landmarks of both uterus and endometrium regions from transvaginal ultrasound image. The discriminator is to determine whether the predicted landmarks of uterus and endometrium are related with their regions or not (i.e., whether the predicted landmark points are on the region boundaries or not.). By adversarial learning between the predictor and the discriminators with uterus and endometrium region images, the performance of the landmark predictor can be improved. In testing, with the trained predictor only, uterus and endometrium landmarks are predicted. Experimental results demonstrated that the proposed method achieved a high accuracy in detecting landmarks of the uterus and endometrium in the ultrasound image.
“Is There Anybody There?”

The Open University (UK) Library supports its distance-learning students with interactive, real-time events on social media. In this chapter the authors take a case study approach and concentrate on the examples of Facebook and Livestream to illustrate how live engagement events on social media have helped to build communities of learners in spaces they already occupy, raise the visibility of the library's services and resources with staff and students, and foster collaboration with other departments, while also being effective mechanisms for instruction. The chapter concludes with the library's plans for the future and recommendations for other academic libraries wishing to run live engagement events on social media.
Analyzing and Recognizing Pedestrian Motion Using 3D Sensor Network and Machine Learning

How to analyze and recognize pedestrian movements is an important issue dependent on motion capture devices. In our work, we used two types of popular 3D sensors such as 3D depth sensor and 3D motion sensor to construct a sensor network for tacking motion of target because of their convenience and low cost. In this paper, we first describe how to get data from the sensor network and how to process raw data. Next, we provide algorithms for applying machine learning to the analysis and recognition of human motions. Finally, we give some evaluation experimental results.
Attentive Conditional Channel-Recurrent Autoencoding for Attribute-Conditioned Face Synthesis

Attribute-conditioned face synthesis has many potential use cases, such as to aid the identification of a suspect or a missing person. Building on top of a conditional version of VAE-GAN, we augment the pathways connecting the latent space with channel-recurrent architecture, in order to provide not only improved generation qualities but also interpretable high-level features. In particular, to better achieve the latter, we further propose an attention mechanism over each attribute to indicate the specific latent subset responsible for its modulation. Thanks to the latent semantics formed via the channel-recurreny, we envision a tool that takes the desired attributes as inputs and then performs a 2-stage general-to-specific generation of diverse and realistic faces. Lastly, we incorporate the progressive-growth training scheme to the inference, generation and discriminator networks of our models to facilitate higher resolution outputs. Evaluations are performed through both qualitative visual examination and quantitative metrics, namely inception scores, human preferences, and attribute classification accuracy.
Development of the Laboratory Panel and the Laboratory Research on the Subject “Optical Electronics”

This article describes the laboratory panel and the laboratory research on the subject of "Optical Electronics". The laboratory panel is developed on the basis of the NI Engineering Laboratory Virtual Instrumentation Suite II - NI ELVIS II. Many instruments are applied in those studies. Laboratory panel includes such optical devices as monochromical LEDs, RGB-LEDs and semiconductor laser SYD1230. In addition, the panel contains photocell: light-dependent resistor GL5528.The principles of various optical devices' operation and their comparative characteristics including volt-amps diagrams are studied in the research. Moreover, the reaction of photocells is compared depending on the intensity of the light flux.
An Unambiguous Acquisition Algorithm for BOC (n, n) Signal Based on Sub-correlation Combination

To overcome the acquisition problems caused by the multiple peaks of the auto-correlation function of Binary Offset Carrier (BOC) modulated signal, a technology to eliminate secondary peaks based on sub-combination correlation is proposed in this paper. According to the characteristics of the sub-function of the BOC autocorrelation, this new method recombined the sub-correlation function obtain the ability to eliminate the edge. MonteCarlo simulations show that the proposed method can improve 3 dBHz sensitivity in detection probability compared with ASPeCT when the number of non-coherent is 10 for BOCs (1, 1). In addition, it can be applied to BOCc (1, 1) and achieved the same the detection probability compared with the traditional BSPK-LIKE method by appropriately increasing the number of non-coherent.
Formation of Emotional Intelligence of Students of Economic Universities

The article reveals the concept, content and meaning of emotional intelligence. The relationship of emotional intelligence with the success of professional activities in the field of economics is investigated. The basic educational tools used to form emotional intelligence are listed.
Inside Mall: Visual Analytics of Customer Behavior and Activities

This paper presents a coordinated multi-view system consisting of visualizations for displaying customer behavior and activities in a shopping center environment based on indoor tracking information gathered by Bluetooth beacons. Different perspectives to find structures and hidden patterns within the data set are supported including different customer flow visualization methods based on actual floor plans as well as abstract flow graphs. These are linked and coordinated with Parallel Sets to gain insight into the specifics of the customer base and with different time-oriented visualizations to show and to compare the different periods of customer presence.
Quantitative Nomic Truth Approximation

Assuming that the target of theory oriented empirical science in general and of nomic truth approximation in particular is to characterize the boundary or demarcation between nomic possibilities and nomic impossibilities, I have presented in Chap. 4 (“Models, postulates, and generalized nomic truth approximation”) the ‘basic’ version of generalized nomic truth approximation, starting from ‘two-sided’ theories. Its main claim is that nomic truth approximation can perfectly be achieved by combining two prima facie opposing views on theories: (1) the traditional (Popperian) view: theories are (sets of models of) postulates that exclude certain possibilities from being realizable, enabling explanation and prediction and (2) the model view: theories are sets of models that claim to (approximately) represent certain realizable possibilities. Nomic truth approximation, i.e., increasing truth-content and decreasing falsity-content, becomes in this way revising theories by revising their models and/or their postulates in the face of increasing evidence. The basic version of generalized nomic truth approximation is in many respects as simple as possible. Among other things, it is qualitative in the sense that it is purely based on set-theoretic relations. The present chapter presents the straightforward quantitative concretization of it. According to the ‘expected success theorem’, based on some probabilistic experimental conditions, greater truthlikeness, or verisimilitude, leads to greater expected empirical success. This enables tentative nomic truth approximation conclusions by abductive reasoning.
Ternary as Fuzzy Logic in Creation and Comparison of Syntax Trees when Determining Functional Styles

Problems of creation of syntax trees when analyzing Russian language are considered in this work. Problems are analyzed and the method of comparison of syntax trees among themselves is offered. Modification of the method on the basis of a ternary in case of homonymies is offered and also the research emphasizing the advantage of the offered approach in the analysis of syntax trees for definition of functional text style is conducted.
RoScan 2.0 - Multispectral Hi-Resolution Scanner

The main aim of this paper is to describe novel hi-resolution multispectral scanning device for various purposes called RoScan 2.0, developed by our team at Brno University of Technology. It is a successor of RoScan 1.0 and Orpheus-X4 multispectral scanning head. The main difference comparing to RoScan 1.0 is its ability to scan in all used spectra concurrently and the ability to use more sources of physical movement for the sensory head. This means many technical and scientific challenges needed to be solved to make the device useable. Currently two positioning devices are developed a linear actuator and 2-DOF (degree of freedom) rotational manipulator, both with high precision and resolution. Hardware of RoScan 2.0 is described, as well as calibration process necessary for fast, precise and reliable multispectral measurement of different objects. The problem of common field-of-view vs. resolution, and its impact to thermal imager and color camera depth-of-focus is mentioned.
Probability Mass Functions for which Sources have the Maximum Minimum Expected Length

Let P <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sub> be the set of all probability mass functions (PMFs) (p <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> , p <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> , . . . , p <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sub> ) that satisfy p <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</sub> > 0 for 1 ≤ i ≤ n. DeIne the minimum expected length function L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">D</sub> : P <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sub> → R such that L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">D</sub> (P) is the minimum expected length of a prefix code, formed out of an alphabet of size D, for the discrete memoryless source having P as its source distribution. It is well-known that the function L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">D</sub> attains its maximum value at the uniform distribution. Further, when n is of the form D <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m</sup> , with m being a positive integer, PMFs other than the uniform distribution at which L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">D</sub> attains its maximum value are known. However, a complete characterization of all such PMFs at which the minimum expected length function attains its maximum value has not been done so far. This is done in this paper.