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There is a relative lack of research on the development of creepage discharge in aged oil-paper insulation subjected to AC-DC combined voltage in converter transformers. In this study, based on the physical and chemical properties of oil-paper, we propose a sphere-plate electrode model to study the creepage discharge parameters and characteristic spectra of aged oil-paper subjected to AC-DC combined voltage. The results show that the creepage discharge inception voltage of aged oil-paper is related to the AC voltage component of the AC-DC combined voltage. However, when the DC voltage component is 60 kV, the flashover phenomenon was found to occur in one of the severely aged samples before the AC voltage was applied. Despite being subjected to the same DC voltage, the flashover phenomenon did not occur in three other samples aged to different degrees. Large-amplitude discharges were found to appear earlier in the severely aged samples. At the same creepage discharge stage, as the aging time of the oil-paper increased, the number of large-amplitude discharges was found to rapidly increase, and the time interval between adjacent discharges was found to gradually decrease. At each stage of the creepage discharge, the small-amplitude discharge has a “hump” shaped distribution. The larger the DC voltage component, the shorter the endurance time of aged oil-paper, and the more severe the damage to the oil-paper. The DC voltage component was found to have an accelerating effect on the development of creepage discharge in aged oil-paper insulation.

This paper presents a broadband, simple, re-useable and low-cost approach for noninvasive sweat monitoring using a passive microwave circuit and a cellulose filter paper as a superstrate. The proposed sensor is composed of filter paper with the ability to absorb the sample liquid under test (LUT) placed on top of a coplanar waveguide (CPW) transmission line. Various samples of sodium chloride (NaCl) solutions with concentrations in the range of 0.01-2 mol/L and models of artificial sweat are used to test the proposed sensor. The difference in transmission coefficient (S21) between dry and wet states is used to determine the concentrations of tested solutions in the band of 1-6 GHz. The sensor detects concentrations as low as 0.01 mol/L (0.58 g/L) and quantities as low as 137 μL with a maximum sensitivity of 46.7 dB/g/L. The proposed sensor presents a simple approach to sample and characterize liquids with enhanced sensitivity and consistent performance using microwave signals.

The oil-paper insulation in power transformer is under a complicated environment, and there is little research on the combined effects of winding vibration-generated mechanical stress and thermal stress on the aging of insulating paper. To investigate the effects of combined mechanical-thermal stress on the aging properties of insulating paper, this paper carried out accelerated aging test using the as-designed mechanical-thermal stress combined aging oven in the aging environment at the temperature of 130 °C, and the mechanical stress intensities of 1 MPa, 1.5 MPa and 2 MPa. Besides, the degree of polymerization (DP), tensile strength, infrared spectroscopy, and scanning electron microscope (SEM) tests were performed on the aging paper samples. The test results suggested that, the combined mechanical-thermal aging might be regarded as thermal aging with lower degradation activation energy; the DP and tensile strength of insulating paper markedly declined during the mechanical-thermal aging process. At the same time, mechanical stress promoted the destruction of glycosidic bond, intramolecular and intermolecular hydrogen bonds, and increased the insulating paper cracks and holes. Typically, the above factors accelerated the aging of insulating paper. Finally, an improved degradation rate equation for insulating paper with consideration of mechanical stress was put forward.

Insulated tubular busbar is a new type of current-carrying equipment with excellent performance. However, the research on this equipment is insufficient because of the short application and the lack of technical digestion, which has resulted in many accidents. In this paper, the full-scale model of epoxy-impregnated-paper insulated tubular busbar with bubble defects was designed and produced, its electrical breakdown process was investigated by withstand voltage test. In the experiment, the failure mode of breakdown caused by gas expansion was found for the first time. The research showed that the electrical-mechanical breakdown process could be divided into two stages: gas increase stage and breakdown threshold stage. The research also obtained the characteristics and the change criterions of the two stages. The gas in the bubble defects generated from epoxy decomposition which caused by partial discharge. When the gas pressure exceeds the critical fracture toughness of the bubble defects wall, the unstable crack extension occurs, therefore, improving the ability about resistance to partial discharge of epoxy resin or improving the fracture toughness of epoxy resin by modifying would enhance the breakdown performance of insulated tubular busbar. The result also has reference significance for other epoxy-impregnated-paper insulated electrical equipment.

This paper presents the design and analysis of a paper-based chipless RFID sensor for wetness content measurement in plant leaves. The sensor is designed using a passive microwave resonator to measure the ambient physical parameter. The resonator is designed with a rectangular loop inductively coupled with an interdigital capacitor. The experimental analysis of the designed sensor is illustrated here to prove its efficacy. The resonator provides adequate backscattered signal for wireless measurement in the microwave frequency band. When interrogated with a couple of UWB antennas and a VNA, it yields accurate leaf wetness response of the plant. The commercial competence of this sensing device is validated through its experimental analysis on three different types of leaf samples. This sensor is suitable for plant health monitoring in any small-scale gardening applications such as nurseries and greenhouses.

This paper investigates the impact of institutes and papers over time based on the heterogeneous institution-citation network. A new model, IPRank, is introduced to measure the impact of institution and paper simultaneously. This model utilises the heterogeneous structural measure method to unveil the impact of institution and paper, reflecting the effects of citation, institution, and structural measure. To evaluate the performance, the model first constructs a heterogeneous institution-citation network based on the American Physical Society (APS) dataset. Subsequently, PageRank is used to quantify the impact of institution and paper. Finally, impacts of same institution are merged, and the ranking of institutions and papers is calculated. Experimental results show that the IPRank model better identifies universities that host Nobel Prize laureates, demonstrating that the proposed technique well reflects impactful research. Refereed/Peer-reviewed

In forensic document analysis, the authenticity of a document must be properly checked in the context of suspected forgery. Hyperspectral Imaging (HSI) is a non-invasive way of detecting fraudulent papers in a multipage document. The occurrence of a forged paper in a multi-page document may have a substantial difference from rest of the papers in its age, type, color, texture, and so on. Each pixel in an HSI data can be used as the material fingerprint for the spatial point it corresponds to. Hence, hyperspectral data of paper samples made of the same substance have similar characteristics and can be grouped into a single cluster. Similarly, paper samples made of different substances have different spectral properties. This paper relies on this heuristic and proposes a tensor based clustering framework for hyperspectral paper data, with an application to detect the forged papers in multi-page documents. Information embedded in the hyperspectral patches of the papers to be clustered is arranged into individual lateral slices of a third-order tensor in this framework. Further, this work employs the self-expressiveness property of submodules and an objective function is formulated to extract self-expressive representation tensor with low multirank and f-diagonal structure. Objective function of the proposed method incorporates $l_{\frac {1}{2}}$ -induced Tensor Nuclear Norm (TNN) and $l_{\frac {1}{2}}$ regularization to impart better low rankness and f-diagonal structure to the representation tensor. Experimental results of the proposed method were compared to the state-of-the-art subspace clustering approaches. The results demonstrate improved performance of the proposed method over the existing clustering algorithms.

Moisture content and aging of oil-paper insulation are two important factors that cause deterioration of the insulation performance of power transformers. The water molecules and aging products are polar, which affects the dielectric response characteristics of the insulation system. Currently, the dielectric response testing technology has realized non-destructive evaluation of the moisture content of transformer insulation. However, the changes in the dielectric response caused by aging products are easily concealed by the influence of moisture, which makes the diagnostic technology ineffective for use in the evaluation of the aging of the oil-paper system. In order to avoid drawback, a new method utilizing frequency domain dielectric spectroscopy (FDS) and the water balance characteristics of the oil-paper insulation is proposed in this paper to evaluate the aging state of oil-paper insulation. The aging of oil-paper insulation will affect the water balance between oil and paper. In this paper, the experimental studies have shown that the water distribution coefficient between oil and paper and the degree of polymerization (DP) of the insulating paper shows a significant linear relationship. Accordingly, in this paper, FDS curves were used to evaluate the moisture content in the insulating paper, oil samples were taken to measure the moisture content in oil, and then the ratio of moisture content in oil and paper were calculated as the aging characteristic parameter. The linear relationship between the characteristic parameter and DP was used to evaluate the aging state of oil-paper insulation. The feasibility of the proposed method is preliminarily verified using oil-paper insulation samples at different aging states and with different moisture levels in the laboratory.

Studying the moisture diffusion in non-oil-immersed insulation paper is helpful to optimize the drying process and improve the drying efficiency of oil-immersed equipment. Moisture diffusion factor (MDF) is the key parameter to describe the moisture diffusion in non-oil-immersed insulation paper. Thermal aging affects the moisture absorption capacity of insulation paper obviously, thus, this paper intends to modify the empirical expression of MDF by considering the effects of thermal aging. The transient moisture contents of non-oil-immersed insulation paper with different thicknesses were measured at 40 °C and 60 °C, respectively. Then, the experimental values of MDF were extracted, and the empirical expression of MDF was modified by considering the effects of thermal aging. Finally, the modified expression of MDF was verified. The following conclusion can be obtained: 1) the equilibrium time constant of non-oil-immersed insulation paper increases with thermal aging; 2) the moisture absorption rate of non-oil-immersed insulation paper decreases with thermal aging, and; 3) the modified expression of MDF is reasonable and effective.

Oil-immersed insulation paper (OIP) bushing is one of the most important equipment in power transmission and distribution systems. Moisture is one of the most serious factors that affect the insulation status of OIP bushing. In this paper, the OIP bushing was assumed to be in a stable and simplicity condition, and then the transient moisture distribution of capacitor core and its effects on the electric field were studied. First, by dissecting a 110 kV OIP bushing, the specific sizes for modelling were obtained. Afterwards, a moisture diffusion model for OIP bushing was established based on COMSOL Multiphysics software, and it was also verified by moisture diffusion experiment. Then, the moisture distribution for different conditions were obtained and analyzed. Finally, a model for the electric field of OIP bushing was established, and then the effects of moisture on the electric field were studied.

The volume of research articles in digital repositories is increasing. This spectacular growth of repositories makes it rather difficult for researchers to obtain related research papers in response to their queries. The problem becomes worse when a researcher with insufficient knowledge of searching research articles uses these repositories. In the traditional recommendation approaches, the results of the query miss many high-quality papers, in the related work section, which are either published recently or have low citation count. To overcome this problem, there needs to be a solution which considers not only structural relationships between the papers but also inspects the quality of authors publishing those articles. Many research paper recommendation approaches have been implemented which includes collaborative filtering-based, content-based, and citation analysis-based techniques. The collaborative filtering-based approaches primarily use paper-citation matrix for recommendations, whereas the content-based approaches only consider the content of the paper. The citation analysis considers the structure of the network and focuses on papers citing or cited by the paper of interest. It is therefore very difficult for a recommender system to recommend high-quality papers without a hybrid approach that incorporates multiple features, such as citation information and author information. The proposed method creates a multilevel citation and relationship network of authors in which the citation network uses the structural relationship between the papers to extract significant papers, and authors' collaboration network finds key authors from those papers. The papers selected by this hybrid approach are then recommended to the user. The results have shown that our proposed method performs exceedingly well as compared with the state-of-the-art existing systems, such as Google scholar and multilevel simultaneous citation network.

Transformer insulation paper is a key indicator for transformer remaining operational life. Paper decomposition is evaluated using the degree of polymerization (DP) which calls for samples of insulation paper from operating transformers. Since collecting such paper samples is extremely difficult, other indicators have been used to indirectly reveal the DP value of insulation paper. This includes dissolved gases in transformer oil such as carbon oxides and hydrocarbon gases, furan compounds, methanol, ethanol, and moisture along with some oil characteristics such as interfacial tension. However, for the same oil sample, these individual parameters lead to different DP values. This is attributed to the lack of accuracy of the established mathematical and artificial intelligence models correlating DP with each of the above mentioned individual parameters. This paper presents a self-learning method to estimate the DP value of transformer insulation paper based on multiple transformer oil aging parameters. The proposed method comprises data processing, fuzzy c-means and linear regression. Results reveal that estimating the DP value based on multiple aging parameters is more accurate than estimating it using one single parameter as per the current practice. The proposed method not only helps to understand the correlation between multiple oil aging parameters and the DP value of paper insulation, but also promotes the establishment of more accurate life assessment models for power transformers based on these oil aging parameters.

Evolutionary game dynamics is a combination of game theory and dynamical systems. Using dynamical theory, we investigate chaotic behavior in asymmetric Rock-Paper-Scissors games under imitative dynamics with two different populations. Our theoretical analysis and numerical simulations demonstrate that the dynamical system can give rise to chaotic behavior in zero-sum and positive-sum asymmetric games. However, chaos cannot occur in a negative-sum asymmetric game. In particular, the numerical simulations show that there is a limit cycle in a negative-sum asymmetric game.

Methanol is regarded as an available indicator to analyze the aging condition of cellulose insulation. However, the diffusion mechanism of methanol molecules in the paper-oil insulation system is still unclear, since it cannot be explored by using only experiments. Given this issue, the molecular dynamics simulations were performed to investigate the diffusion mechanism of methanol molecules. In the current work, the mean square displacement of methanol during the diffusion process was calculated and analyzed, as well as its trajectory tracking. Then, the research on interaction energies and hydrogen bonds in paper/oil system were conducted. Finally, the effect of temperature on the diffusion of methanol molecules was also studied. Findings revealed that the diffusion of methanol in cellulose insulation is faster than that in insulating oil, besides, the presence of hydrogen bonds affects the diffusion rate of methanol molecules in cellulose insulation and insulating oil. Thus, the present findings could support the investigation of the diffusion mechanisms of methanol molecules, by which the aging condition evaluation of cellulose insulation could be also promoted.

The existing plethora of document classification techniques exploits different data sources either from the content or metadata of research articles. Various journal publishers like Springer, Elsevier, IEEE, etc., do not provide open access to the content of research articles, whereas metadata is freely available there. Metadata like title, keyword, and abstract can serve as a better alternative to the content in various scenarios. In the current literature, researchers have assessed the role of some of the metadata individually. We believe that the collective contribution of metadata parameters can play a significant role in classifying research papers. This paper presents a comprehensive evaluation of the role of metadata, individually as well as in combinations to achieve the objective of research paper classification. Moreover, we have classified the research articles into ACM hierarchy root categories (e.g. general literature, hardware, software, etc.). In this comprehensive evaluation, we have assessed all the possible combinations of metadata features against different classifiers such as Random Forest, K Nearest Neighbor, and Decision Tree. The results of this research reveal that the title & keywords combination outperforms other combinations with an F-measure score of 0.88.

The heat dissipation factor of conventional epoxy impregnated paper bushings is a subject of concern due to the large quantities of power in a High Voltage Direct Current (HVDC) system. The present work deals with the selection of better insulation as a replacement to the conventional resin impregnated material employing nano-hexagonal-Boron Nitride and nano-hexagonal-Boron Nitride added with nano-cellulose-fiber. The bushing of the converter transformer is designed using the Finite Element Method (FEM), and the electrothermal analysis is performed at the loaded working condition. Besides, numerous optimization schemes are also presented for adapting the structure of the thermal conductor enclosed in the inner conductor. The electrothermal performances of the above materials with the optimized structure are compared and an advanced scheme is proposed. Further, the results obtained from the designed system are employed in the form of an Artificial Neural Network to simplify the process of thermal computation characterized by the selected scheme. The internal parameters of the neural network are tuned implementing a hybrid amalgamation of Particle Swarm optimization - Grey Wolf Optimiser and the performance is compared against the actual values. The supremacy of the implemented algorithm is justified by a comparative analysis with other well-established algorithms using various statistical parameters.

Accurate modeling and simulation of electric field transients in HVDC cables is an important support to optimize insulation system design and to evaluate the influence of voltage transients and steady-state conditions on accelerated ageing mechanisms and insulation reliability. Traditionally, field models considering time-independent permittivity and conductivity are used, but this approach neglects polarization mechanisms and charge trapping-detrapping phenomena. This article includes polarization dynamics in the field model and shows that its impact on transient electric field simulations in HVDC paper-insulated cables can be significant. A method is presented to infer the model parameters from experimental polarization and depolarization current measurements.

Over the decades, the immense growth has been reported in research publications due to continuous developments in science. To date, various approaches have been proposed that find similarity between research papers by applying different similarity measures collectively or individually based on the content of research papers. However, the contemporary schemes are not conceptualized enough to find related research papers in a coherent manner. This paper is aimed at finding related research papers by proposing a comprehensive and conceptualized model via building ontology named COReS: Content-based Ontology for Research Paper Similarity. The ontology is built by finding the explicit relationships (i.e., super-type sub-type, disjointedness, and overlapping) between state-of-the-art similarity techniques. This paper presents the applications of the COReS model in the form of a case study followed by an experiment. The case study uses InText citation-based and vector space-based similarity measures and relationships between these measures as defined in COReS. The experiment focuses on the computation of comprehensive similarity and other content-based similarity measures and rankings of research papers according to these measures. The obtained Spearman correlation coefficient results between ranks of research papers for different similarity measures and user study-based measure, justify the application of COReS for the computation of document similarity. The COReS is in the process of evaluation for ontological errors. In the future, COReS will be enriched to provide more knowledge to improve the process of comprehensive research paper similarity computation.

We present a novel implementation of a Rock-Paper-Scissors (RPS) game interaction with a social robot. The framework is tailored to be computationally lightweight, as well as entertaining and visually appealing through collaboration with designers and animators. The fundamental gesture recognition pipeline employs a Leap motion device and two separate machine learning architectures to evaluate kinematic hand data on-the-fly. The first architecture is used to recognize and segment human motion activity in order to initialize the RPS play, and the second architecture is used to classify hand gestures into rock, paper or scissors. The employed tabletop robot interacts in the RPS play through unique animated gestural movements and vocalizations designed by animators which communicate the robot's choices as well as cognitive reflection on winning, losing and draw states. Performance of both learning architectures is carefully evaluated with respect to accuracy, reliability and run time performance under different feature and classifier types. Moreover, we assess our system during an interactive RPS play between robot and human. Experimental results show that the proposed system is robust to user variations and play style in real environment conditions. As such, it offers a powerful application for the subsequent exploration of social human-machine interaction.

In this paper, we present a new scheme for implementing virtual keyboards, which uses only two to four motion-recognition rings per hand and a two-dimensional keyboard template (e.g., an A4 size paper with printed key positions). It has the benefit of portability, customizability, and low-cost when compared with existing approaches. Essentially, we have shown that wearing two wireless IoT rings on the middle phalanges of two fingers of each hand, users can input the alphabetic characters into a computing device by typing on a flat paper on a desk, and potentially in mid-air. We have demonstrated that two rings are sufficient in capturing the gestures and motions of all fingers in a typing hand for keystrokes recognition. A single wireless IoT ring, which weighs 7.8 grams, consists of a Bluetooth low energy (BLE) unit, a micro inertial measurement unit (mIMU), and a cell battery. The 3-axes attitude angles and the Z-axis acceleration of each ring are adopted as the features for keystroke recognition. The overall keystroke recognition accuracy rate can reach as high as 94.8% when two IoT rings are worn by a user on each hand; this accuracy rate increases to 98.6%, when four rings are worn on each typing hand.

The study is a vital instance to merge the psychology and the computer science disciplines to provide benefits about the developments of the theory of mind (ToM) skills of and interaction with for the students with neurodevelopmental disorders (SWND). In this research, a traditional two-dimensional (2D) method (paper), a 2D display touch screen and the three-dimensional (3D) [augmented reality (AR)] visual displays based on the computer are constructed for the SWND to do the ToM test questions. In this work, The Little Prince story written by Antoine de Saint-Exupéry is adapted to the ToM test questions to measure the SWND's ToM abilities. In this novel approach, three environments: a traditional 2D method (paper), the 2D display touch screen, and the AR visual display environments are experienced by the SWND. The experimental results are compared according to SWND's ToM success ratios, their ToM perspective skills', their satisfaction on these different test environments. This research suggests the novel approach to measure the ToM abilities of the SWND with human-computer interaction aspect. This article displays the positive effects of the 2D display touch screen and the AR usage on the Tom Test for the SWND.

This study explores the method of applying surface enhanced Raman scattering (SERS) in diagnosing the aging stage of oil-paper insulation equipment in the power system, which provides access to the on-line mornitoring of electrical equipment. Oil-paper samples in different aging stages were obtained by accelerated aging experiments. Effective Raman signals of insulating oil were collected by using the self-made hexagonal sliver nano-plates SERS substrates and the self-assembled Raman detection platform. For the SERS data of oil-paper insulation samples, kernel entropy component analysis (KECA) was applied to extract the Raman spectral features and support vector machine (SVM) was used to recognize the the aging stage of oil-paper insulation. The results demonstrate that the KECA-SVM method exhibits a good diagnostic capacity and the recognition accuracy of the propsed method reached 81.43 % (57/70). In summary, a new spectral method is proposed to diagnose the aging stage of oil-paper insulation, which lays a foundation for the actual diagnosis of the aging condition in running oil-paper insulation equipment by Raman spectroscopy.

Citation count is a widely-used indicator for calculating the academic impact of scientific papers, but it is limited because it assumes all citations are of similar value and weights each equally. By examining the influence changes in papers’ citation distribution and the cited papers’ unequal contributions to the citing ones, this study aims to distinguish citations and, on this basis, evaluate the academic impact of the papers. Three indices of time-weighted citation count, citation width and citation depth are proposed to distinguish citations and perform the evaluation task. The experimental results show that papers exhibit different influence intensity characteristics in different periods of citation life. Those papers got larger citations in recent years are more influential and more active to gain new citations. The papers show the different scope of influence in their citing environment, although they were originally published in the same journal and the same year. In addition, the different frequency of mentions and the different subject similarities with the citing works suggest that the papers have different importance and usefulness for subsequent research. These results suggest that these three indices do help to distinguish citations and reveal the different intensity and contribution of influences in citations. Finally, the three indices are integrated into the overall evaluation of the academic impact of the paper, and the weight of each index is calculated by the entropy weight method. Quite different overall impacts in the paper are shown due to their different performances in the three indices, even though they have the same total number of citations.

This paper presents a thorough review of transmitarray devices particularly aiming antenna beamsteering, gathering some of the most relevant solutions published by the scientific community in the field. First, the background for realizing 1-D and 2-D antenna beamsteering with a transmitarray is introduced. Subsequently, several examples of unit-cells for transmitarray implementation and complete transmitarray designs presented in the literature are outlined. Each solution is analyzed in detail, identifying the nature of its layout, e.g., based on microstrip patches, frequency selective surfaces (FSS), or metamaterials (MMs), and the method employed to enable electronic reconfigurability, e.g., p-i-n diodes, varactor diodes, or microelectromechanical systems (MEMS). In addition, some models with the capability of controlling the wavefront polarization modes are also included herein since these are the base of hybrid transmitarrays, i.e., transmitarray with both electronic beamsteering and polarization control. Finally, all the models are compared against each other in order to highlight their benefits and limitations, summarizing their main characteristics, such as the frequency of operation and bandwidth, insertion loss, physical dimensions, and maximum beamsteering range, when available.

Mineral oil has traditionally been used as a cooling fluid in power transformers, but its low biodegradability and low fire point have motivated the search of alternatives. In this work, six different dielectric fluids have been studied, including four vegetable liquids, from sunflower, rapeseed, soybean, and palm, one synthetic ester and a mineral oil used for comparison. These oils were subjected to an accelerated thermal ageing in glass vessels at 150°C for four weeks (672 hours) in presence of Kraft insulating paper. Different oils parameters were measured during the ageing, i.e. breakdown voltage, dielectric dissipation factor, permittivity, DC resistivity, density, kinematic viscosity, flash and fire points, interfacial tension, acidity, and dissolved gases; additionally, the degree of polymerisation (DP) of the paper was measured. Results showed that the changes of the natural esters properties, except for the palm oil, were similar along the ageing time. Palm oil results were similar to those of the mineral oil, whereas synthetic ester showed a behaviour similar to natural esters. The kraft paper degradation was higher in the mineral oil, followed by the synthetic ester and the palm oil. No significant differences were found in the ageing with the natural esters. This work was supported in part by the European Union’s Horizon 2020 Research and Innovation Program, through the Marie Sklodowska-Curie, under Grant 823969, and in part by the Ministry of Economy, through the National Research Project: Gestión del Ciclo de Vida de Transformadores Aislados con Fluidos Biodegradables, under Grant PID 2019-107126RBC22.

Temperature compensation occupies a significant function in the insulation condition evaluation of converter transformer bushings based on the Frequency Domain Spectroscopy (FDS), which could influence the accuracy of its insulation diagnosis. In order to accurately obtain the variation law of FDS at different temperature, a Resin Impregnated Paper (RIP) insulation bushing for converter transformer was designed by the equivalence of maximum electric field, coaxial cylinder structure and RIP materials. The increment law of dielectric parameters both dissipation factor and capacitance at wideband frequency (1mHz ~ 10kHz) was measured for a quality RIP insulation samples at the temperature from 30°C to 100°C. 1) Under the uniform temperature, it was found that the value of dissipation factor was rising with the frequency from 10 Hz to 0.001Hz, while the tendency was reversed at the frequency from 100Hz to10kHz. 2) The minimum value of tan $\delta $ from 0.001Hz to 10kHz could be driven to higher frequency moving (10Hz to 10kHz) by the action of temperature rising 30°C to 100°C.3) The effect of temperature on the lower frequency 0.001Hz ~ 1Hz tan $\delta $ of RIP insulation closely conformed to the index law of Arrhenius equation, while it was in accordance with the linear decrease at higher frequency 1kHz ~ 10kHz. The effect of temperature on dissipation factor could be eliminated by curve segment shifting based the experiment equation, which it at 0.001Hz dissipation factor could be eliminated by curve shifting based the index equation originated Arrhenius equation. The method is beneficial to eliminate the influence of temperature on the dielectric spectroscopy test results, and then to eliminate the influence of temperature on the dielectric spectroscopy diagnosis of RIP bushings.

Oil-paper insulation as an irreplaceable insulation system in the electrical power transformer is inevitably suffering the water intrusion on working condition, which will make dielectric performance degraded and insulation aging accelerated. In high interest of explaining the deterioration effect of absorbing moisture on the dielectric properties of oil-paper insulation system and corresponding mechanism, the space charge and trap level characteristics are investigated for the specially prepared oil-impregnated pressboards with different moisture contents. The Pulsed Electro Acoustic and Isothermal Surface Potential Decay experiments are performed to test the space charge distributions and evaluate the trap level depths, respectively. It is indicated that the polarity of injected space charges is alternated with the decaying rate being raised when the absorbing moisture is aggravated in oil-impregnated pressboards. The charge carriers are more prone to be captured by the shallow-level traps that have been introduced by water permeation near pressboard surface than the intrinsic deep-level traps inside pressboard. The captured charge carries accounts for the significantly exacerbated space charge accumulation as manifested by the surface charges of oil-impregnated pressboards.

Frequency domain spectroscopy (FDS) technique is widely applied in the condition assessment of the oil-paper system in power transformers. However, the synergistic effect generated by moisture and temperature on the FDS data cannot be analyzed by the existing model since the single independent variable (moisture or temperature) is considered in the construction of the model. To quantify such the synergistic effect, a novel method that utilized for normalizing (or standardizing) the FDS curve is reported based on the theory of the power series and fitting analysis. The present findings reveal that the reported method is capable of predicting the dielectric loss (tan $\delta$ ) curve under diverse test conditions, in which the average error is less than 7%. The synergistic effect can be also explored by using the extracted feature parameters. The potential application is then proved to make up for the measurement errors during the FDS test, the findings are expected to promote the moisture analysis of the transformer insulation.

In this short paper, our main objective is to construct binary locally repairable codes (LRCs) with good properties. Two constructions of LRCs with short lengthes are proposed. The first one is that define a u-linearly independent set (u-LIS) of an LRC with disjoint repair groups (DRGs) and enlarge it into another one with bigger size to construct new LRCs. The second is puncturing check matrices of known codes to construct new LRCs. As an application, many new binary LRCs are constructed from distance optimal linear codes, which are also locality optimal according to the Cadambe-Mazumdar (C-M) bound.

For current steganalysis of the image content-adaptive steganography, there are multiple problems to be improved, such as high difficulty and low accuracy, when detecting images with various contents and textures. For this problem, an improved steganalytic method is proposed in this paper based on the pre-classification and feature selection. First, using the features extracted based on the dependency analysis of image adjacent data, the images with various content and texture complexities are pre-classified as multiple clusters by the K-means algorithms. Then, the performance of existing various steganalytic features are analyzed for different clusters of images, and the optimal features for each cluster are selected for final classification. The experimental results show that the detection accuracy could be improved by the proposed method, and the rationality and availability are also verified. At the same time, the analysis and experimental results in this paper also show that the images with rich content and complex texture should be paid more attention both in steganography and in steganalysis.

Power transformers are considered as one of the main parts of any power system. Because of their importance and high cost, it is important to check the state of the insulation system inside them from time to time. Dissolved gas analysis test as well as Furan compounds analysis has been widely used as recommended methods to assess the transformer insulation system state. This paper introduces an empirical form that can predict the degree of polymerization of the paper insulation system inside the transformer by measuring Furan compounds. This proposed empirical form is validated by comparing its results with other methods reported in the literature in two different case studies. Subsequently, the proposed formula is used to predict the lifetime and the insulation system state of a transformer that operates in Abo Sultan steam power plant in Egypt. The 2-FAL had been measured five times for this transformer in the period between 2013 and 2015. Depending on these five measurements, an equation that can predict 2-FAL level inside this transformer in relation to its age has been proposed. This proposed equation is validated by comparing the measured and estimated 2-FAL in the period between 2016 and 2019. According to the attained results, it was found that the insulation system inside the investigated transformer seems to face a serious problem and this transformer cannot remain in service after 2027. Finally, the paper introduced a general technique that can be used for any transformer in order to predict its remaining lifetime.

Recently, it has been shown that channel feedback helps to enhance the physical layer security (PLS) of communication systems. The current use of feedback focuses on generating secret keys protecting the transmitted messages, and this feedback scheme is proved to be optimal for some physically degraded channel models. In this paper, we revisit the model of the state-dependent wiretap channel with the noncausal state at the transmitter, which plays an important role in the PLS of the wireless communication systems. We propose a new feedback scheme for this model and show that the proposed new scheme performs better than the already existing secret key-based feedback scheme. The results of this paper are further explained via a Gaussian example.

The ReaxFF molecular dynamics simulation and Monte Carlo method were adopted to analyze the pyrolysis process of cellulose in insulating papers from the perspective of microscopic atom. Molecular dynamics failed to continuously describe the motion behavior of an atom. According to this principle, the system can only calculate the atomic state on the node and then move the atom by a time step to continue calculating the atom. This paper would put forward the optimal step setting method of cellulose thermal decomposition in insulating paper: setting one step every other 0.1 fs. Specifically, for small molecules with a simple structure, such as H2O, the step size was set to 0.4 fs or less, while the step size of macromolecules with complex structures (CH2O2) should be set to 0.2 fs or less. In addition, the relationship between the step size and the temperature to which the system was heated was given as well in this paper. In previous literatures, empirical values were used to set the step size. This study would not only provide a theoretical basis for the study on the bond formation and fracture process of cellulose pyrolysis products, but also offer the data and guidance for related fields in the future, thus rendering an efficient simulation process.

In general, considering standard production, as well as coconut oil production, in oil consumption industries is an important factor. Oil color is an important element, as it is an important factor for consumers or buyers in selecting coconut oil. In the process of producing coconut oil, the cold-pressed method has been chosen to maintain the essential quality of coconut oil. The quality of the coconut oil is inspected from the production process by means of light passing through the coconut oil. Then, the production staff compares the turbidity of coconut oil with the master sample. The turbidity of coconut oil in every production must be compared with a master sample to maintain standards control. According to previous studies, there are many methods for determining coconut oil turbidity. One method that has been utilized is determining turbidity from light passing through the medium in which the transmitted light can be absorbed through the turbidity of the variable medium. This process is applied together with image processing to determine the coconut oil turbidity. In this research, we propose a method for measuring coconut oil turbidity by the Moving Average Median of Hue (MAMoH), which is better in detecting the coconut oil turbidity than the Median of Gray Scale (MoGS) method, Median of Hue (MoH) method, and Random Position Median of Hue (RPMoH) method. In terms of the percentage accuracy of the efficiency test; the MAMoH method has 99 percent accuracy, while the MoGS method is not applicable, the MoH method has 88.04 percent accuracy, and the RPMoH method has 85.91 percent accuracy. Thus, the MAMoH method is considered an appropriate method for measuring coconut oil turbidity.

The production index of gold cyanidation leaching process has an important influence on the economic benefits of the plant-wide hydrometallurgical process. In the actual leaching production process, due to the fluctuations of the previous procedure, the leaching process is often affected by the uncertainty and process disturbance. And hence, the prediction accuracy of the traditional point prediction models (such as ANN: Artificial Neural Network) decreases seriously and cannot provide any quantified information about the uncertainty or process disturbance. To solve the above problem, the interval prediction technique based on Radial Basis Function (RBF) ANN is proposed and used to model a gold cyanidation leaching plant encountering uncertainty and process disturbances in this paper. The objective function trained in the interval prediction model is not based on the prediction error, but the comprehensive measure index, namely, the coverage width criteria, which consists of the prediction interval coverage probability and the prediction interval normalized averaged width. Compared to the traditional point prediction, when the process uncertainty and disturbances are present, the interval prediction model will provide more helpful process information to the operators or process designers for determining further optimization and control strategies. The simulation and practical application results show that most of the real values of gold recovery can be covered between the upper and lower bounds with a predefined probability, which indicates the effectiveness and reliability of the interval prediction model, thus laying an important foundation for plant-wide optimization and control.

This paper examines the history of electrical engineering education, leveraging the concept of “expansive (dis)integration” to frame a number of key trends and challenges in the field. Our account is organized historically, starting with the origins and early development of electrical engineering education beginning in the late 1800s, and then tracing out the rise of new subfields and specialties during the inter-war and post-WWII periods. The development of computer engineering as a field is given special attention as a case study in disciplinary (dis)integration, while setting the stage for a discussion of broader trends associated with the rising influence of digital techniques and technologies across electrical engineering. The final sections of this paper report on some contemporary challenges and opportunities that may further transform the field in upcoming years and decades, with particular emphasis on issues of demographic diversity and perceptions of broader relevance and impact. The approach of this paper is largely historical, drawing on a wide variety of primary and secondary source materials. It is expected that this paper will be of interest to anyone who would like to know more about the historical development of electrical engineering education, including in relation to more contemporary currents in the field.

Formaldehyde is one of the indoor air quality pollutants produced by indoor decoration. The World Health Organization has listed Formaldehyde as a primary carcinogen. Wood planks for house interior decoration are common sources of formaldehyde. Based on the technology research and development of monitoring and control of the smart home, the air quality should be effectively improved through emission and suppression. This study uses extremely unventilated student renters in Taiwan as simulation spaces. Two classes of wood plank construction materials, F1 and F3, which are classified according to as different concentrations of formaldehyde standard board grades by Taiwanese. Through three different temperature control experiments, each group of experiments use electrochemical formaldehyde detectors to measure at least two consecutive days of data to analyze the influence to which temperature, the control factor, affected formaldehyde emission rate. The results revealed that the F3 class wood planks can increase the rate of formaldehyde emission through heating, which has a significant effect on home environment control, but they need a temperature below 10 °C to barely maintain within the regulations in Taiwan. The F1 class wood planks have an emission rate of nearly zero in a low-temperature environment due to its low formaldehyde emission. The emission rate of the F1 in a high-temperature environment is not as effective as the F3. The addition of experimental data can be used as a reference basis for AI decision making, which is conducive to the establishment of indoor intelligent control systems.

Abandoned mineral management has become an important global issue, and the collection, recycling, and disposal of mineral processing tailings (MPT) is critical in both mining engineering and environmental protection. In this study, flocculation sedimentation experiments and slurry rheological tests were carried out with unclassified tailings, and the flocculation sedimentation behaviour of the tailings under different conditions was investigated. The experimental results showed the followings: (1) Under close sedimentation effect conditions, different flocculants showed different effects on the fluidity of the slurry underflow, which was used as an important basis for optimization of the flocculation effect. (2) A tailings solid mass concentration of 40% and a flocculant dosage of 25 g/t were obtained as preferable sedimentation conditions. (3) Based on a microparticle agglomeration characteristics tests at the initial stage of flocculation, a flocculation concentration kinetic model was established that conformed to the fractal characteristics of the particles, which improved the applicability and accuracy of the concentration kinetic equation and the characteristic variables. In this study, an objective method for determining the parameters of full tailings flocculation sedimentation was realized. The results of an industrial trial operation also verified the reliability of the preferred parameters, which provided an effective basis for refined control of an efficient tailings recycling process.