Reviewerly/exHarmony huggingface dataset:
Parametric synthesis of a robust PID-controller for interval control system with aperiodic transient process

Abstract The paper is dedicated to a problem of synthesizing a PID-controller, which provides and aperiodical transient process of desired duration in a control system of the third order with interval parametric uncertainty. To solve the problem, a new method of synthesis was developed. It is based on a decomposing a characteristic polynomial of a considered system in two multipliers: dominant polynomial, which determines allocation of a dominant pole and, consequently, quality of a transient process in a considered system, and non-dominant polynomial, which determines allocation of all other system poles. In order to provide a desired allocation of system poles, parameters of a PID-controller are divided to unrestricted ones and dependent ones. The research resulted in algebraic expressions for calculating dependent parameters of a PID-controller and a system of inequalities for finding its unrestricted parameter. Developed method of a PID-controller parametric synthesis allows placing an interval real dominant pole according to desired control quality and placing all other poles of a system in a desired part of a complex plane to provide necessary degree of a robust pole domination.
Research on sub‐micron measurement methods of M55J carbon fibre/cyanate ester composites

In view of the axial dimensional stability of the main loaded cylinder of the space camera, the thermal expansion characteristics of the carbon fibre M55J/cyanate ester (CE) composite were studied. In this paper, the coefficient of thermal expansion (CTE) of four kinds of carbon fibre composites used in aerospace are analysed and measured in both directions. The results show that the CTE of M55J/CE composite is negative, which cannot be achieved by carbon/epoxy composite. According to this characteristic, the layering mode of M55J/CE laminates was optimised, The CTE of M55J/CE laminates was analysed by the finite element method. Then the loaded cylinder was developed using the optimal ply program. Two different measuring methods, ‘Heating blanket/Three-coordinate measurement’ and ‘High–low temperature chamber/submicrometer displacement detector measurement method’ were proposed to measure the CTE of the loaded cylinder, and the advantages and disadvantages of the two measuring methods are also analysed. The test results were compared, which verified the credibility of the measurement method and data, The test results of ‘High–low temperature chamber/Submicrometer displacement detector measurement method’ were closer to the laminate, which laid the foundation for engineering applications.
Projection Decoding of Some Binary Optimal Linear Codes of Lengths 36 and 40

Practically good error-correcting codes should have good parameters and efficient decoding algorithms. Some algebraically defined good codes, such as cyclic codes, Reed–Solomon codes, and Reed–Muller codes, have nice decoding algorithms. However, many optimal linear codes do not have an efficient decoding algorithm except for the general syndrome decoding which requires a lot of memory. Therefore, a natural question to ask is which optimal linear codes have an efficient decoding. We show that two binary optimal [ 36 , 19 , 8 ] linear codes and two binary optimal [ 40 , 22 , 8 ] codes have an efficient decoding algorithm. There was no known efficient decoding algorithm for the binary optimal [ 36 , 19 , 8 ] and [ 40 , 22 , 8 ] codes. We project them onto the much shorter length linear [ 9 , 5 , 4 ] and [ 10 , 6 , 4 ] codes over G F ( 4 ) , respectively. This decoding algorithm, called projection decoding, can correct errors of weight up to 3. These [ 36 , 19 , 8 ] and [ 40 , 22 , 8 ] codes respectively have more codewords than any optimal self-dual [ 36 , 18 , 8 ] and [ 40 , 20 , 8 ] codes for given length and minimum weight, implying that these codes are more practical.
A System for Seamless Support from Security Requirements Analysis to Security Design Using a Software Security Knowledge Base

Owing to the widespread use of the internet, software services are being provided to millions of consumers and the importance of software security has increased considerably. Specifically, difficulties in developing a security design based on the results of a security requirements analysis are a focal point for investigation. One promising approach for addressing these difficulties is to create a knowledge base for secure software development and a process for utilizing it. The information obtained regarding the security design of the knowledge base, which is associated with the knowledge used in the security requirements analysis, can be considered during the design phase. This paper describes the development of a system that seamlessly supports the design phase based on the results of a security requirements analysis and the knowledge base. We then present an example to demonstrate the usefulness of the proposed system. This knowledge base maintains an association between knowledge types and is traceable. Therefore, if the knowledge used to create a type of artifact evolves, it is possible to detect artifacts used knowledge associated with it.
Sc-Ge: Multi-Factor Personalized Point-of-Interest Recommendation Model

For most current POI (point-of-interest) recommendation algorithms, only the common visited POIs among users are used to calculate the similarity among users. Due to the high sparsity of the data, the recommendation result of POI is inaccurate. Aiming at this problem this paper proposes a method to determine the similarity among users by combing the similarity that using Cosine similarity with the similarity among users by Jensen-Shannon divergence (JS divergence) after mining the user interest distribution with the Latent Dirichlet Allocation (LDA). At the same time combining POI’s commentary text information, rating information, geographical location information and friend relationship information in social networks, a multi-Factor personalized POI recommendation model Sc-Ge is proposed to improve the precision and recall rate of POI recommendation. Experiments are carried out on the comment dataset Yelp, and it is concluded that this model is better than other mainstream POI recommendation algorithms.
Some Cryptanalytic Results on TRIAD

In this paper, we study TRIAD-AE, which is submitted in the on-going NIST Lightweight competition. We first estimate an upper bound of the algebraic degree of internal state and key-stream bit seen as multivariate Boolean polynomials. Using this estimation, we find good cubes to analyze reduced round TRIAD-AE. We get a cube of size 32 which gives zero-sum up to 540 rounds, and a cube of size 34 which can distinguish TRIAD-AE up to 550 rounds with a confidence level around $$95 \%$$ . Further, we also obtained some small size good cubes which distinguishes TRIAD-AE from a random generator. We believe that our analysis can help to understand the security of the cipher better.
Outreach to Support Exhibitions

The author describes an outreach project developed between the Western Carolina University fine and performing arts librarian and the campus art museum involving the creation of select bibliographies related to museum exhibitions. The article outlines the initiative and the benefits and challenges of this form of outreach. The author uses examples from the project to explore the potential influence librarians may have on non-departmental campus relationships, library marketing, and collection development.
Meta-cognitive Neural Networks for Adaptive Identification and Control

In this paper, we demonstrate the usage of Meta-cognitive Neural Networks in the identification and control of nonlinear dynamical systems. The algorithm for Meta-cognitive Neural Network with Online Sequential Learning Algorithm and Backpropagation as the cognitive elements has been explained and a comparative analysis of the improvement brought about by the use of Meta-Cognition over other neural network learning methods has been presented.
Transformation of the Euclidian data space into a homogeneous event space for the inductive construction of classification rules

The following topics are dealt with: neural nets; optimisation; learning (artificial intelligence); mathematical analysis; elasticity; fuzzy set theory; pattern clustering; computational complexity; pattern classification; video signal processing.
Development Of Binary Similarity And Distance Measures (BSDM) Algorithm For The Bond Of High Development System Of Video

Abstract This research makes new innovations in high measurement more effective in minimizing the time in measurement. But there has been no research for recognition of height measurement patterns using the Otsu algorithm and Binary Similarity and Distance Measures (BSDM) algorithms. These two algorithms are combined to optimize the working process of the system to be built. Based on the results of the algorithm’s complexity, BSDM has several binary similarities and distances that can be used in testing the system to be built. One of the binary similarities and distances used in testing this research is BSDM S INNERPRODUCT and BSDM S JACCARD . From testing the system using BSDM S INNERPRODUCT as effective as BSDM S JACCARD , between the two closer to the result of the actual height is testing BSDM S INNERPRODUCT . The test data used in this research is in the form of video image in real-time. To improve the quality of system work in future research, can add pattern matching algorithm for height measurement, The addition of the approach will certainly affect the speed of computation on pattern recognition.
Tourism transportation’s optimum route in Banyumas using the weighted fuzzy graph

Tourism is a significant contributor to Indonesian economy as well as source of foreign exchange earnings. Banyumas that is located in Central Java is one of the regions in Indonesia with great potential tourism. It has a lot of tourism destinations, such as Baturraden, Small World, Andang Pangrenan, The Village, Caping Park, and many more. Unfortunately, there are no means of public transportation to go there. In fact, public transportation plays a significant role for city development. It offers main facilities to tourists and reduces traffic congestion during holidays. The important thing to do before building a public transportation is to determine the optimum route. Scientific contributions are needed to develop it. One of the fields of study about it is graph theory. It is commonly used to study transportation problem. This paper aims to provide the optimum public transportation route for tourism in Banyumas. We used Floyd-Warshall algorithm to find the optimum public transportation routes. In addition to the distance factor, it is necessary to consider the road width to determine the optimum path. Therefore, we use fuzzy logic to determine edge weights with several considerations of distance and width factors. In this study, we get the optimum route that connects tourism objects along the path that can be traversed after considering distance and width factors. From the result reflects that the addition of the road width factor in the weight of the graph has sufficient influence in determining the optimum route.
Aligning Users Across Social Networks by Joint User and Label Consistence Representation

Aligning users belonging to the same person in different social networks has attracted much attention. Recently, embedding methods have been proposed to represent users from different social networks into vector spaces with same dimension. To handle the challenge of vector space diversity, existing methods usually make vectors of known aligned users closer/consistent and overlap different vector spaces. However, compared to large amount of users in each social network, the consistence constraint on aligned users is not enough to reduce the diversity. Besides, missing edges/labels may provide incorrect information and affect the effect of the overlap between learned vector spaces. Therefore, we propose the OURLACER method, i.e, jOint UseR and LAbel ConsistencE Representation, to jointly represent each user and label under the consistence constraints of know aligned users and shared labels. Specifically, OURLACER utilizes collective matrix factorization to complete missing edges and labels for each user, which can provide sufficient information to distinguish each user. Moreover, OURLACER adds the consistence constraint on shared labels in different social networks. Because each user has own labels, label consistence can restrict each user and greatly reduce the diversity between learned vector spaces. Extensive experiments conducted on real-world datasets demonstrate that our method significantly outperforms other state-of-the-art methods.
Design of quaternary quantum reversible half subtractor, full subtractor and n-qudit borrow ripple subtractor

In this paper, we proposed novel plans of quaternary quantum reversible half and full subtractor circuits. The subtractor element is the essential part of the ALU in the digital computational devices. Thus, the improvement of subtractor block has a significant impact on the overall system performance. According to the comparison results, the proposed quaternary quantum half and full subtractor circuits show tremendous improvement in quantum cost, hardware complexity, number of constant input and garbage output as compared to their counterparts. Moreover, for the first time, the quaternary quantum borrow ripple subtractor structure is realized using the proposed quaternary quantum half and full subtractor circuits.
Bisimulation Maps in Presheaf Categories

The category of presheaves on a (small) category is a suitable semantic universe to study behaviour of various dynamical systems. In particular, presheaves can be used to record the executions of a system and their morphisms correspond to simulation maps for various kinds of state-based systems. In this paper, we introduce a notion of bisimulation maps between presheaves (or executions) to capture well known behavioural equivalences in an abstract way. We demonstrate the versatility of this framework by working out the characterisations for standard bisimulation, ∀-fair bisimulation, and branching bisimulation.
Movement Patterns and Trajectories in Three-Dimensional Software Visualization

Software visualization is a growing field of research, in which developers are assisted in understanding and analyzing complex applications by mapping different aspects of a software system onto visual attributes. Under the assumption that virtual reality, due to the higher degree of immersion, may enhance user experience, researchers have begun to port existing visualization techniques to this environment. Oftentimes, layout algorithms and user interaction methods are more or less transferred one-to-one, though little is known about the effect of virtual reality in visual analytics and program comprehension. Moreover, little research on the behavior of developers in different three-dimensional visualization environments has been done yet. This paper extends the results of a previous controlled experiment, in which the EvoStreets visualization technique was compared in different two-and three-dimensional environments. In the original experiment, we could not find evidence that any of the environments, namely, 2D, 2.5D, and virtual reality, effects the time required to find an answer or the correctness of the given answer. However, we found indications that movement patterns differ between the 2.5D and the virtual reality environments. For this paper, we analyzed and refined the movement trajectories that have been recorded in the previous experiment. We found significant differences for some of the tasks that had to be solved by the participants. In particular, we found evidence that the path length, average speed, and occupied volume differ. Though we could find significant correlations between these metrics and correctness, we found indications that there is a correlation with time, which, in turn, differs significantly between the 2.5D and the VR environments for many tasks. These findings may have implications on the design of visualizations, interactions, and recommendation systems for these different environments.
Aynı Şartlar Altında Farklı Üretici Çekişmeli Ağların Karşılaştırılması

As the first successful general purpose way of generating new data, GANs have shown great potential for a wide range of practical applications (including those in the fields of art, fashion, medicine and finance). It is one of the most popular research topics of recent times. GANs are the new class of exciting machine learning model that leads to applications that bring to mind their ability to produce synthetic but realistic looking data. Generative Adversarial Networks are composed of two neural networks that work in opposite directions. In this paper, it is aimed to examine the same initial situation, same dataset, same number of iterations, parts of the same size in order to compare Generative Adversarial Networks. This paper Generative Adversarial Network (GAN), Deconvolusional Generative Adversarial Network (DCGAN), Semi-Supervised Generative Adversarial Network (SGAN/SeGAN) Conditional Generative Adversarial Network (CoGAN / CGAN) were used. These methods were calculated on the performance of MNIST dataset. The results are presented both numerically and visually.
Vector Hourglass Network for Human Pose Estimation based on Deep Learning

Human pose estimation (HPE) is the basis of human action recognition and analysis. It is better to locate the key points of the human body more accurately to achieve the desired results in certain applications. The paper will discuss and explore it. The overall pipeline refers to the method AlphaPose. Among them, the single person pose estimation network uses the proposed improved hourglass network - the proposed method calls it Vector Hourglass network. The main process of Vector Hourglass network is as follows. First, the heatmap values of each graph obtained from the first-level and the second-level hourglass network are saved respectively. For the heatmap values obtained from the first-level network, the geometric center of gravity of each obtained joint point's heatmap is taken as the joint coordinates for calculating the PAF weight, and then calculate the PAF values. By weighting the heatmap value getted by the first-level network to the thermal value obtained by the second-level network, the new thermal value of the second-level hourglass network is obtained. In the test phase, since the method of this project can only detect the pose of a single person, LSP (Leeds Sports Pose Dataset) single person sports dataset is selected as the test set from the existing open dataset. To verify the validity of the method, the project calculates the mean square error (MSE) and the mean absolute error (MAE) values of the heatmap that weighted PAF weights before and after. The results show that the positioning accuracy of key joint points is improved by 1.43 pixels in the image of 64×80 pixel size. The method applies the idea of intermediate supervision and part affinity fields (PAF) between the two levels of hourglass network to improve the positioning accuracy of the joints and makes the obtained human posture contour more obvious.
Cyber-Physical Systems Security Based on a Cross-Linked and Correlated Vulnerability Database

Recent advances in data analytics prompt dynamic data-driven vulnerability assessments whereby data contained from vulnerability-alert repositories as well as from Cyber-physical System (CPS) layer networks and standardised enumerations. Yet, current vulnerability assessment processes are mostly conducted manually. However, the huge volume of scanned data requires substantial information processing and analytical reasoning, which could not be satisfied considering the imprecision of manual vulnerability analysis. In this paper, we propose to employ a cross-linked and correlated database to collect, extract, filter and visualise vulnerability data across multiple existing repositories, whereby CPS vulnerability information is inferred. Based on our locally-updated database, we provide an in-depth case study on gathered CPS vulnerability data, to explore the trends of CPS vulnerability. In doing so, we aim to support a higher level of automation in vulnerability awareness and back risk-analysis exercises in critical infrastructures (CIs) protection.
I Rest My Case! The Possibilities and Limitations of Blockchain-Based IP Protection

We have identified, mapped and discussed existing research on Blockchain-based solutions for intellectual property (IP) protection, an investigation that emerged from a case in antibody production for scientific and medical applications. To that end, we have performed a systematic literature review and created an instrument that classifies the contributions according to the materiality of the object they protect (from immaterial to physical), the type of protection (authorship notarization or prevention of illegal use) and the type of research (conceptual or empirical). Our results can be used to understand which avenues to pursue in the effort to create a new generation of more effective technology-assisted IP protection systems, a priority for 152 signatory countries of the patent cooperation treaty.
Solar Radiation Potential Using Surface Meteorological Data: (A Case Study of Lokoja City, Kogi State)

Monthly mean global solar radiation data are fundamental in the study, design and installation of solar energy conversion devices. This research aimed at evaluating the potential of solar energy resources. The data of daily sunshine hours, maximum and minimum temperature collated from Nigeria meteorological Agency (NIMET), Lokoja station was to predict the monthly mean values of the global solar radiation of the area. Geographically, Lokoja is the state capital of Kogi State lies between 6.74°E longitudes and 7.8°N latitudes and occupies a surface area of about 63.82 square kilometers at elevation of 55m above sea level; it is located in the Midland area. The data for temperature (maximum and minimum) and the sunshine hours were considered for the period of twenty years; (1995 to 2014) which were used in computing the monthly mean daily solar radiation and the annual mean global solar radiation on the horizontal surface. The Hargreaves-Samani model and the Angstrom-Prescott model were used to evaluate the daily mean values of Global Solar Radiation (GSR) potential for Lokoja city. The mean solar power potential obtained for the period over Lokoja was between the ranges of 3.54kW/m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> /day - 4.88kW/m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> /day for both parameters considered. Base on figure 4 and 5, there is a correlation in the global solar radiation obtained for the two available data (i.e. sunshine hour and minimum/maximum temperature) used in the calculations respectively. Angstrom-Prescott model (AP) and Hargreaves-Samani (HS) models can confidently predict the global solar radiation of Lokoja in the absence of experimental data.