Reviewerly/exHarmony huggingface dataset:
Research on the Security Technology of the Internet of Things in Nuclear Power Plant

The intellectualization and digitization of nuclear power plants have become the new direction of nuclear power development. The intellectualization of nuclear power plants cannot be achieved without the use of network control technology, the internet of things can be applied to multiple scenarios in nuclear power plants. With the application of internet of things technology in nuclear power plants, the security of nuclear power plants has been paid more and more attention because the destruction of nuclear power plants can cause great social panic and political influence. This paper focus on the security technology of the internet of things in nuclear power plant. The paper includes five parts. The safety analysis methods and security measures for the application of internet of things technology in nuclear power plants are emphasized. In this paper, the security measures of the internet of things have be divided into six aspects.
Analysing Facial Features Using CNNs and Computer Vision

This paper presents an automatic facial analysis system which is able to perform gender detection, hair segmentation and geometry detection, color attributes extraction (hair, skin, eyebrows, eyes and lips), accessories (eyeglasses) analysis from facial images. For the more complex tasks (gender detection, hair segmentation, eyeglasses detection) we used state of the art convolutional neural networks, and for the other tasks we used classical image processing algorithms based on geometry and appearance models. When data was available, the proposed system was evaluated on public datasets. An acceptance study was also performed to assess the performance on the system in real life scenarios.
Application of iterative hybrid MI approach to household survey data with complex dependence structures

The multiple indicator cluster survey (MICS) is a household survey tool designed to obtain internationally comparable, statistically rigorous data of standardized indicators related to the health situation of children and women. Missing data in a large number of categorical variables are a serious concern for MICS, following complex dependency structures and inconsistency problems that impose severe challenges to the investigators. Despite the popularity of multiple imputation of missing data, its acceptance and application still lag in large-scale studies with complicated data sets such as MICS. We propose interdependent hybrid multiple imputation (HMI) techniques which combines features of existing MI approaches to handle complex missing data in large scale household surveys. The iterative HMI approach is observed to be a good competitor to the existing approaches, with often smaller root mean square errors, empirical standard errors and standard errors. Regardless of any combination, the iterative HMI method is markedly superior to the existing MI methods in terms of computational efficiency. Results from household data example support the capacity of proposed method to handle complex missing data.
Nonlinear net models of multi-parametrical systems and processes

Abstract This paper is devoted to the mathematical and computer simulation of multi-parameter systems. We show that the method and algorithm can easily be used in nonlinear net simulation of the systems. Simulation is based on experimental data and achieved by the variation of one-dimensional spline approximations. A set of variable one-dimensional splines is the result of simulation. Each of the splines is the image of a section of input parameters area. Software realization is based on the single algorithm that is used repeatedly. The method have been used in investigation some technological conditions of laminating fabrics systems. Specifically, we investigated the stability of gluing joints, hardness and bending of various parts of clothes. Also, we got the simulator of constituent elements of the mixture which may be used in label products as a temperature indicator. The examples eventually demonstrate the efficiency of the presented method.
The Effect of Using a Mirror to Evoke Self-Consciousness in Bicycle Riding Suppression

It is important to protect the safety and comfort of both bicycle users and pedestrians. In this study, we investigated the effect of using a signboard with a mirror, which was expected to evoke self-consciousness. We conducted field experiments at an arcade shopping street. As a result, it was suggested that the effect of using the signboard with a mirror enhanced the manner of bicycle usage in situations where the bicycle decelerated or stopped.
A Hybrid Distributed Model for Learning Representation of Short Texts with Attribute Labels

Short text documents in real-world applications, such as incident tickets, bug tickets, feedback texts etc. contain fixed field entries in the form of certain attribute instances as well as free text entries capturing the summaries of them. We propose an approach based on the Paragraph Vector (due to Le and Mikolov) to learn fixed-length feature representation from these short texts of varying lengths appended with attribute instances. Our method contributes to the existing approach by learning representation from summary of tickets as well as their attribute contents captured using fixed field entries. Further we show such representation of short texts produce better performance on a few learning tasks compared to the other popular representations.
Research on Image Segmentation Combined G-L Fractional Differential and LIF Mode

Local Image Fitting (LIF) model is sensitive to the initial location of evolving curve when segmenting images with intensity inhomogeneous, weak texture and edges, it usually falls into local optimal. To address this issue, a new method for image segmentation based on fractional differential and LIF model is proposed. It introduces Grünwald-Letnikov (G-L) fractional gradient into LIF model, and adds a new global fractional fitting term. So the gradient of the intensity inhomogeneous and weak texture regions is enhanced. Evolution curve is driven by both the local intensity fitting term and the global fractional differential gradient fitting term, As a result, both robustness to curve's initial location and segmentation efficiency are improved. The proposed model is a improvement of LIF model. It can be used for segmenting the intensity inhomogeneous, weak edge and weak texture images.
Towards Efficient Crawling of Georeferenced Documents from Location-based Social Networks

We propose a method that efficiently retrieves documents belonging to a target area from a georeferenced information database. A circular target area can be effectively searched by k-nearest neighbor searching, whereas a rectangular target is more appropriately searched by the bounding-box approach. However, queries of actual geographic information are often sourced from complex areas with different topographies and features. For efficient searching, queries on arbitrary and complex areas should be broken down into multiple simple queries, for example, a technique that divides the target area into grids. Our proposed method is a parameterless subquery construction method that efficiently searches georeferenced documents belonging to an arbitrary area specified by the user. Compared to the baseline method, the experimental results show that the number of subqueries could be reduced by up to 80%.
Distribution Of Pacs Functions Among Ieds Using The Knowledge Base Mechanism

This paper describes the application of knowledge base technology and logical conclusion mechanism for automating the digital substation design process, notably the distribution of protection, automation and control (PAC) functions of substation equipment among intelligent electronic devices in accordance with regulatory and technical documentation.
PROFESSIONALLY ORIENTED FOREIGN LANGUAGE TEACHING IN NONLINGUISTIC UNIVERSITIES

The productive methodical models for activity of educational process, contents and analysis of the professional focused training students of technical institutions are considered in this article.
Feature Selection for High-Dimensional Data Through Instance Vote Combining

Supervised feature selection (FS) is used to select a discriminative and non-redundant subset of features in classification problems dealing with high dimensional inputs. In this paper, feature selection is posed akin to the set-covering problem where the goal is to select a subset of features such that they cover the instances. To solve this formulation, we quantify the local relevance (i.e., votes assigned by instances) of each feature that captures the extent to which a given feature is useful to classify the individual instances correctly. In this work, we propose to combine the instance votes across features to infer their joint local relevance. The votes are combined on the basis of geometric principles underlying classification and feature spaces. Further, we show how such instance vote combining may be employed to derive a heuristic search strategy for selecting a relevant and non-redundant subset of features. We illustrate the effectiveness of our approach by evaluating the classification performance and robustness to data variations on publicly available benchmark datasets. We observed that the proposed method outperforms state-of-the-art mutual information based FS techniques and performs comparably to other heuristic approaches that solve the set-covering formulation of feature selection.
Segmentation and Text extraction from Document Images: Survey

Segmentation and text extraction from complex document image helps in analyzing, storing, retrieving and auto indexing of required information. In this paper, we considered 23 existing methods of segmentation and text extraction for complex document images. After review of the existing methods, we found that connected component method [1],[2],[5],[8],[10],[13] are more suitable for segmentation of text and non-text from document and also LSTM &RNN found that potential methods for extraction of text from complex document[15].
Development of the Mathematical Model of a Multi-Container Steganographic System

The structural and functional diagram of a message transmission unit of a mathematical model of a multi-container steganographic system has been developed. The stability of the simulated system to passive, active and cryptographic attacks is shown. The structure of message fragments is proposed, which allows to realize the assembly of the transmitted message, data integrity control.
Behavioural and Abstractor Specifications for a Dynamic Logic with Binders and Silent Transitions

We extend dynamic logic with binders (for state variables) by distinguishing between observable and silent transitions. This differentiation gives rise to two kinds of observational interpretations of the logic: abstractor and behavioural specifications. Abstractor specifications relax the standard model class semantics of a specification by considering its closure under weak bisimulation. Behavioural specifications, however, rely on a behavioural satisfaction relation which relaxes the interpretation of state variables and the satisfaction of modal formulas $$\langle \alpha \rangle \varphi $$ and $$[\alpha ]\varphi $$ by abstracting from silent transitions. A formal relation between abstractor and behavioural specifications is provided which shows that both coincide semantically under mild conditions. For the proof we instantiate the previously introduced concept of a behaviour-abstractor framework to the case of dynamic logic with binders and silent transitions.
Information Collection of the Agricultural Database in the Agricultural Economy

The modern agriculture usually refers to that with the application of the modern agricultural technology and equipment and the science and technology in the production activities under the implementation of the modern management mode. The establishment of the basic agricultural database and the special agricultural information service system has provided a powerful grasp for combing and integrating the agricultural information resources, provided a powerful data support for the management decision-making, improved the management levels, and well met the current needs of the innovative management of the agricultural economy.
The Scheme for Solving the Conflicts Between Downstream and Backward Data in an Integrated Test System

To solve the conflict problem between the downstream data and the backward data in an Integrated Test System, the reciprocal data transferring routine is analyzed. The message source ID for the downstream data is modified, and the message sink ID is also added as a combined flag in the Interface software. The scheme is verified through the system test-bed, and it has shown the conflict is vanished.
Binocular Gaze Estimation with Single Camera and Single Light Source

According to commonly consented theories, the minimum hardware requirement for gaze tracker is one camera and two light sources to realize gaze estimation with free head movements [1]. However, in some scenarios such as eye tracking on mobile devices, it is preferable to use less components, especially light sources. We propose a gaze estimation method with one camera and one light source. A "virtual light source" is introduced, which is geometrically placed symmetrically to the real light source with respect to the camera, and generates a "virtual glint" in the acquired image. We estimate the "virtual glint" by exploiting the relationship between the distance between two pupils and two glints in the captured image, and estimate the gaze with polynomial regression assuming two light sources are available. A new normalization factor for regression method is verified, which turns out to be practical for one-glint system. The performance is proved to be acceptable, while degradation is noticed compared to system with two actual light sources.
Application of the Computer Simulation Technology in the College Football Teaching

With the development of our society and the wide application of the computer technologies, the traditional teaching methods in college football teaching cannot meet the needs of the social development, so it is very helpful and necessary to add the computer simulation technology to the college football teaching to train new talents. The application of the computer simulation technology in the college football teaching is not only a bold breakthrough and innovation in the football teaching mode, but also an important demand for optimizing students’ understandings and cognitions. Compared with other computer technologies, the simulation technology has higher requirements for the computer hardware, more rigorous implementation steps and more standardized process.
Position Control and Production of Various Strategies for Deep Learning Go Programs

Computer Go programs have exceeded top-level human players by using deep learning and reinforcement learning techniques. On the other hand, “Entertainment Go AI” or “Coaching Go AI” are also interesting directions which have not been well investigated. Several researches have been done for entertaining beginners or intermediate players. Position control or producing various strategies are important tasks, and some methods have been proposed and evaluated using a traditional Monte-Carlo tree search program. In this paper, we try to adapt the method to LeelaZero, a program based on AlphaGo Zero. There are some critical differences between the previous program and the new program. For example the new program does not use random simulations to the ends of games, then the previous method for producing various strategies cannot be used. In this paper we summarized the differences and some expected problems, and proposed several approaches to solve the problems. It was shown that the modified LeelaZero could play gently against weaker players (48% won against a program Ray). Through experiments using human subjects, it was shown that the average number of unnatural moves per game was 1.22, where that by a simple method without considering naturalness was 2.29. Also we evaluated the proposed method for training “center-oriented” and “edge/corner-oriented” players, and it was confirmed that human players could identify the produced strategy (center or edge/corner) with a probability of 71.88%.
E-mail spoofing based on the datalink layers and its application to e-mail aggregation systems

It is well known that DHCP snooping is a famous countermeasure against DHCP spoofing. Actually, to what extent DHCP snooping can protect the DHCP clients from being injected malicious DHCP transactions running over the network segment? In this paper, we discuss the problem asking if there exists what is to SMTP spoofing as DHCP snooping is to DHCP spoofing, and the problem asking if it is possible for SMTP spoofing to be applied to a socially useful system..
7bgzf: Replacing samtools bgzip deflation for archiving and real-time compression

Genomic sequence data are not only massive but also increasing rapidly every day; therefore, it is essential to compress such data for sharing. Though there are some specific compressors, they lack interoperability. In this study, a SAMtools bgzip variant named 7bgzf has been developed, incorporating several compression and deflation algorithms other than the widely used zlib algorithm. An extensive benchmarking study has been carried out with available data compression software. On both x64 and ARM machines, igzip performed very rapidly. For high compression, using libdeflate on the x64 platform achieved high compression with tolerable speed loss. Based on appropriate algorithm selection, the proposed compression method performed better than the original bgzip method while maintaining interoperability with existing software. Therefore, this software is useful for both distribution of genomic sequence archives and real-time compression in mobile computing.
Bit Representation for Candidate Itemset Generation

In association rule mining, storing the itemsets in the memory is one of the main challenges. If the database is very large, storing the generated itemsets in the memory becomes infeasible. Sometimes, an additional storage or a secondary memory is required for such database. This not only increases the cost but also the time to retrieve the itemsets from the main memory to secondary memory and vice versa. To overcome this problem, a representation using bit is used. It is one of the most promising and efficient ways to represent the itemsets especially when we are dealing with large memory requirement. This paper will represent the itemsets for the candidate generation using bit representation.
Social Font Search by Multimodal Feature Embedding

A typical tag/keyword-based search system retrieves documents where, given a query term q, the query term q occurs in the dataset. However, when applying these systems to a real-world font web community setting, practical challenges arise --- font tags are more subjective than other benchmark datasets, which magnify the tag mismatch problem. To address these challenges, we propose a tag dictionary space leveraged by word embedding, which relates undefined words that have a similar meaning. Even if a query is not defined in the tag dictionary, we can represent it as a vector on the tag dictionary space. The proposed system facilitates multi-modal inputs that can use both textual and image queries. By integrating a visual sentiment concept model that classifies affective concepts as adjective--noun pairs for a given image and uses it as a query, users can interact with the search system in a multi-modal way. We used crowd sourcing to collect user ratings for the retrieved fonts and observed that the retrieved font with the proposed methods obtained a higher score compared to other methods.
Skills Engineering in Sustainable Counter Defense Against Cyber Extremism

This article identifies and classifies the core and additional soft skills required not only by engineers that design the security measures against cyber extremism but by other professionals in the field of cybersecurity. Furthermore, it recommends steps in how these competencies may be developed and evolved. IT-based solutions rely on the process of cognition-extrapolation-algorithm-programming from problem identification to the final product delivery. In all approaches to problem-solving, regardless of the nature of the challenge, the end product is only as good as the parameters that define the programming scope. The program capability and scope are defined by the creativity of its creators. Thus, when creating robust security measures that are designed to guard against cyberattacks by extremists, IT measures are only as useful as the creativity of the designer in the cognition-extrapolation phases of product design. Unexpectedly, this implies that the technical-based capabilities of technologically engineered solutions rely on soft human skills in order to have a practical application Additionally, as engineered products become more complex, work packages are broken down even further to more significant numbers of programmers and thus are even further devoid of individual creativity which is grounded and substantiated by soft skills.
Teaching Physics Using Equidistant AR/VR-Projections

Modern augmented/virtual reality (AR/VR) technologies offer us new educational opportunities. They possess the immense untapped resources for significant improvements of the physics education. The transformation of the learning scene (or arena) to the abstract symbolic environment leads to the emergence of the new views at teaching. The AR/VR-glasses allow us to do this, changing, supplementing and augmenting the picture of the physical world around the observer (teacher or student) and even completely replacing it. The paper deals with the teaching experience of the equidistant (spherical) projection use in the physics classes. It describes the list of useful tools to facilitate the perception of AR/VR 360-panoramas, recommendations for the practical use, the students' opinion about this technology. It also presents the description of equidistant panoramic slides that are already available, tested in the practice, and ready for physics teaching. Here we consider the place of equidistant AR/VR-projections in the educational process, characteristics of the educationally tested AR/VR-devices, the most effective techniques of their use.
Detail-Preserving Exposure Fusion Based on Adaptive Structure Patch Decomposition

Exposure fusion aims at improving the overall visual quality, especially in the extremely bright and dark regions, by merging different exposure images. Structure patch decomposition based exposure fusion (SPD-EF) method can generate images with overall good visual quality without any post-processing steps. However, SPD-EF inevitably induces halo artifacts due to large local contrast. In this paper, we propose an adaptive SPD-EF, which can preserve the fine details and avoid halo artifacts. In the first step, each input image is partitioned into overlapping patches with the same size, each of which is decomposed into signal strength, signal structure, and mean intensity. In the second step, we propose to adjust the signal strength based on the local contrast and intensity, following which three components are merging separately. The qualitative and quantitative comparisons with four current state-of-the-art methods demonstrate that our method can not only remove halo artifacts, but also preserve the vivid color appearance and details.