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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.

Researchers face difficulties in finding relevant papers to their research interest as the number of scientific publication is rapidly increasing on the web. Scientific paper recommenders have emerged as a leading solution to help researchers by automatically suggesting relevant and useful publications. Several approaches have been proposed on improving recommender systems. However, most existing approaches depend on priori user profiles, and thus they cannot recommend papers to new user. Furthermore, the existing approaches utilize non-public contextual information, and thus it cannot adequately find similarities between papers due to copyright restrictions. Also, the existing approaches consider only single level paper-citation relation to identify similarities between papers. Considering the above challenges, this paper presents a collaborative filtering based recommendation approach for scientific papers that does not depend on priori user profiles and which utilizes only public contextual information. Using citation context, we utilized 2-level paper-citation relations to find hidden associations between papers. The rational underlying this approach is that, two papers are co-occurred with same cited paper(s) and two papers are co-occurring with same citing paper(s) are significantly similar to some extent. To evaluate the performance of the proposed approach, publicly available datasets are used to conduct extensive experiments. The experimental results demonstrate that the proposed approach has significantly outperforms the baseline approaches in terms of precision, recall, F1, mean average precision, and mean reciprocal rank, which are commonly used information retrieval metrics. The novelty of this study is that, with the proposed approach, researchers are able to find relevant and useful publications over the internet regardless of their previous research experiences and research area.

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.

In paper production, a jumbo reel is cut into multiple intermediate rolls, and each intermediate roll is then sheeted as finished goods. This problem is called a cutting stock problem and is proven to be NP-hard. The objective is to minimize material waste or trim loss from all the cuttings. In the case that any intermediate roll is not entirely used for its associated order, the intermediate roll itself could turn to be a dead stock. We use the concept of universal sizes of intermediate rolls to eliminate the dead stock. A pre-defined number of universal sizes of intermediate rolls is to be used to serve all the orders. The problem is solved using Reinforcement Artificial Bee Colony algorithm with Integer Linear Programming subroutine. This proposed approach is then tested with a set of 1,055 orders and 127 different sizes of sheet papers from a paper manufacturer. The results reveal that our method outperforms other algorithms. Our method offers the total trim loss of 3.51%, compared to the trim loss reported by the industry of at least 5%. This approach not only reduces the number of partially cut rolls, but also decreases the number of the jumbo reels needed to serve all the orders. Therefore, both the inventory cost and material cost can be saved.

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.

The explicitly numerical or well-defined correlations between the dielectrics responses (DRs) and dielectric essences of oil-impregnated paper (OIP) insulation have not been fully understood yet. As a result, it is rather difficult to quantitatively diagnose the critical insulation condition, like determining moisture content in insulation paper (MCP) of power equipment only using electrical-based techniques such as frequency domain spectroscopy (FDS). To obtain MCP value, from a new perspective of parametric study on the circuital DR equivalence of OIP insulation-extended Debye model (EDM), the present contribution introduces a novel approach by exploring the pattern when EDM parameters vary with MCP and temperatures T. Further, mathematical correlations are developed between sensitive R-C values and MCP-T values. On the above analysis, small-scale physical models of real-life transformer bushings were prepared as test samples. Their OIP condenser bodies were artificially absorbed different controlled quantities of moisture and conditioned at different temperatures to record corresponding FDS results. Then a hybrid genetic algorithm combined with the Levenberg-Marquardt algorithm was proposed to estimate the EDM parameters by fitting the measured FDS data. Sensitive parameters therein were identified using subspectrum decomposition and formulated with MCP-T values so that a reliable moisture content estimation can be achieved once the testing temperature and FDS recordings of an insulation body are known.

Trap plays an important role in the charge transportation of three-layer oil-paper and the investigation of trap parameters at different degradation degree is of great significance for further research of the partial discharge (PD) mechanism. This article considers the turn-to-turn structure of on-board traction transformer. A defect model of three-layer oil-paper insulation was designed for PD test. The PD degradation samples are selected from the inception of PD to the breakdown of PD to study the characteristics of surface potential decay on degradation samples by using isothermal surface potential decay method. Given that, the trap distribution at different degradation stages was calculated and its influence on PD characteristics was investigated. The result shows that AC fluctuation voltages caused by inter-harmonic has a great influence on PD distribution, surface charge distribution and trap distribution. With the increase of degradation, the decay rate of surface potential increases and the decay rate of AC fluctuation voltages is larger than that pure AC. And also, the number of shallow trap with AC fluctuation voltages is larger than that with pure AC. The rate of free charge increases with the number of shallow trap increasing. More free electrons involves in the process of PD, accelerating the aging rate of three-layer oil paper samples. Therefore, it can be concluded that surface charge and trap distribution are helpful to clarify PD mechanism.

The oil-paper insulation system is widely used for the insulation purposes of power transformers as a result of its ability to withstand high thermal and electrical stresses. The presence of a gas cavity between impregnated papers layer is a serious problem. When localized breakdown takes place within this cavity, partial discharge (PD) occurs and ages the rest of the insulation system. This aging phenomenon declines the expected life time of the insulation system and subsequently the life time of the power transformers. Dissolved gas analysis is a recommended technique that is used in order to assess the state of the insulation system inside the transformers. In this paper, PD is recorded in the case of gas cavity presence between the layers of the impregnated papers under the effect of AC and DC voltage stress. This record is extended from the instance of PD inception until the breakdown of the whole insulation system. Furthermore, the concentration of the gases that dissolve in the insulating oil due to the aging of the impregnated paper is measured eight times during the record of the PD. Finally, the degradation of the insulating papers is studied optically through the use of a microscope at different stages of the aging test. Depending on PD measurements, dissolved gas analysis (DGA) results, and the optical study of the paper aging, the evolution of the aging of oil-paper insulation system as a result of internal PD is declared when AC and DC voltage stresses are applied. It is obtained that the aging evolutionary process totally differs with the alteration of the applied voltage.

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.

An electrical tree discharge model of multilayer insulation paper was prepared, and a voltage of 20 kV was used for electrical tree cultivation and initiation tests. Based on the microscopic image information and partial discharge (PD) information during the aging of the electrical tree, the development of electrical tree discharges between layers of paper comprising epoxy resin-impregnated paper insulation was studied. The results show that, by analysing PD information such as the discharge volume phase spectrum and the discharge repetition rate phase spectrum, the development of the electrical tree branch progresses in four stages: initial, growth, stagnation, and bursting. During the growth and stagnation stages, the main discharge paths of the electrical tree are mainly formed, and there are many filamentous fibres on the path edge. During the burst stage, more branches will be formed on the electrical tree, which will cause the greatest damage to the insulation. With the extension of the electrical tree path, the discharge magnitude and discharge times also increase. There are specific discharge patterns in different growth stages of the electrical tree, and the number of discharge events in each positive half-cycle is significantly greater than that in a negative half-cycle. Combining the microscopic image information and PD information during the aging of such an electrical tree, a theoretical basis for evaluating insulation state by PD monitoring is realised. The long-chain molecules of cellulose and epoxy resin break bonds and oxidise, which decompose into a large number of free radicals, monosaccharides, and other low-molecular-weight products.

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

The low frequency section of frequency domain spectroscopy (FDS) of oil-paper insu- lation system can effectively reflect the ageing state and moisture of the oil-immersed paper. Meanwhile, steady-state insulation resistance is the one of indexes for the condition of transformer. In actual measurement, these two both are time-consuming and poor accessibility, thereby restraining their field applications. Aim at this problem, this paper analyses the polarization process of the oil-paper insulation in transformer, and adopts a low frequency equivalent circuit model for the oil-paper insulation to characterize the polarization process at low frequency. The simulated annealing particle swarm optimization (SAPSO) algorithm is proposed to identify the parameters in equivalent circuit, which are affected by change of insulation state. Compared with the experimental results, the errors of the steady-state insulation resistance and the tan δ below 10-3 Hz, which are calculated by the identified parameters, are less than 2.5%. This method can avoid the influence from external environment and reduce the measurement time. The time and frequency domain parameters calculated can provide reference for the ageing assessment of oil-immersed paper.

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.

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.

Kevlar pulp treated with low-temperature plasma and nano cellulose fibrils (NCFs) have been introduced as reinforcements in the preparation for composite insulating paper with low relative permittivity, dielectric loss, good mechanical properties, and thermal stability. More polar groups of Kevlar fibers could be exposed after plasma treatment. Results showed that the relative permittivity of the composite paper containing 20% Kevlar pulp, 10% NCF, and 70% softwood pulp is decreased by 29.6% and the dielectric loss is decreased by 43.2% at 50 Hz, 25°, compared with the conventional paper formed by pure softwood pulp. The change was due to the introduction of Kevlar pulp with intrinsic low dielectric constant and loss, which decreases the whole polarizability of the paper. The mechanical properties of the composite paper became worse after introducing 20% Kevlar pulp. About 10% NCF can work as a mechanical reinforcement to compensate for the tensile and Yang's modulus loss. Scanning electron microscopy results showed that NCF could fill the void defects and improve the interface bonding of the fibers to enhance the paper mechanical properties. The composite paper also had better insulating and thermal properties than the conventional paper. It has been concluded that the Kevlar pulp/NCF/softwood pulp composite paper has the potential to replace the pure softwood paper for the application of high-voltage ac transformer insulation.

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.

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.

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.

Researchers from academia and the corporate-sector rely on scholarly digital libraries to access articles. Attackers take advantage of innocent users who consider the articles' files safe and thus open PDF-files with little concern. In addition, researchers consider scholarly libraries a reliable, trusted, and untainted corpus of papers. For these reasons, scholarly digital libraries are an attractive-target and inadvertently support the proliferation of cyber-attacks launched via malicious PDF-files. In this study, we present related vulnerabilities and malware distribution approaches that exploit the vulnerabilities of scholarly digital libraries. We evaluated over two-million scholarly papers in the CiteSeerX library and found the library to be contaminated with a surprisingly large number (0.3-2%) of malicious PDF documents (over 55% were crawled from the IPs of US-universities). We developed a two layered detection framework aimed at enhancing the detection of malicious PDF documents, Sec-Lib, which offers a security solution for large digital libraries. Sec-Lib includes a deterministic layer for detecting known malware, and a machine learning based layer for detecting unknown malware. Our evaluation showed that scholarly digital libraries can detect 96.9% of malware with Sec-Lib, while minimizing the number of PDF-files requiring labeling, and thus reducing the manual inspection efforts of security-experts by 98%.

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.

When the inner insulation of oil-impregnated paper bushing breaks down in service, gases decomposed by oil and paper may cause an explosion. The explosion of bushing occurs from time to time because of the lack of an effective monitoring method. In order to provide an effective online monitoring method for the bushing to avoid explosion, this paper presents a method to monitor the PD defect in bushing by measuring the inner pressure of bushing. In this paper, the relationship of variation between characteristic gases content and inner pressure is studied, the effect of inner temperature on inner pressure is analyzed and the method for reducing this effect is also presented, and the monitoring method is proved to be useful by PD tests on a real bushing. The results show that the inner pressure increases obviously due to the generation of characteristic gases by internal discharge in oil-impregnated paper bushing, and the pressure increases with the deterioration of the discharge; although the inner pressure has a great influence on the inner pressure, the influence can be reduced or eliminated greatly by the method of common-mode rejection. According to the results, the internal discharge defect of the oil-impregnated paper bushing can be detected by monitoring the pressure, and the bushing explosion can be avoided.

Paper-based strain sensors have attracted attention as a cost-effective and environmentally friendly approach to wearable electronic devices. This paper proposes a paper-based strain sensor created solely using hand-painting, which is a simple, equipment-free process utilized in green electronics. Commercial printing paper is coated with polydimethylsiloxane diluted with heptane, which provides moisture resistance and mechanical robustness while increasing the hydrophobicity of the surface. The electrodes and conduction channels are fabricated using a pencil for graphite deposition and a brush for the deposition of tin-doped indium oxide nanoparticles, respectively. With a gauge factor of 41.98 in tensile strain tests and 21.36 in compressive strain tests, our strain sensor exhibits a good sensitivity that is similar to that of previously reported paper-based sensors. We also demonstrate that our proposed strain sensor can be used as a weak motion detection device for humans and robots.

The aging of the transformer oil-paper insulation distributes spatially, which results in changes in paper resistivity in different regions. This paper establishes an iterative inversion algorithm using the finite element method to calculate the oil-immersed paper resistivity in different regions of a transformer. This algorithm sets the transformer dielectric loss factor tan δ at low frequency, the dielectric parameters of the transformer oil as inputs and the oil-immersed paper resistivity as output. The resistivity obtained from inversion can be used as a reference to access the insulation state of the oil-paper insulation. This paper aims at achieving the nondestructive detection of the partial state of the oil-paper insulation.

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.

Failures of bushing caused by corrosive sulfur has gradually appeared in recent years. Apart from copper and sulfur, certain amount of aluminum was also found both in oil and paper after disassembling. The corrosion mechanism of the aluminum foil and its effect on oil-paper insulation were unknown. In this study, series of sulfur corrosion experiments were taken to investigate the sulfur corrosion of aluminum foil. The results showed the aluminum foil could certainly be corroded in oil containing corrosive sulfur (DBDS). Thermal products of insulting paper triggered the corrosion by removing the alumina film on the surface. Then, the contact corrosion occurred between aluminum and DBDS. In addition, the mechanisms of corrosion products generation both in oil and on paper were studied. The corrosion products in oil was DBDS-Al(3,4) and that on paper was RCOOAln. It caused the decrease of electrical properties of oil-paper. Particularly, the dielectric loss of oil and paper were dramatically enhanced.

The accelerating rate of scientific publications makes it extremely difficult for researchers to find out the relevant papers and related works. Recommender systems that aim at solving the information overload problem have attracted lots of attention. However, existing paper recommendation works generally rely on the simple citation-ships between papers, which ignore the heterogeneity of the academic graphs. In this paper, we solve the personalized paper recommendation problem in the setting of heterogeneous information networks. A heterogeneous graph representation based recommendation method named HGRec is proposed. First, the author and paper profiles are constructed based on the extracted contents information. Second, we initialize the node vectors by employing the word-embedding technique. Third, we jointly update the node embeddings in the heterogeneous graph by proposing two meta-path based proximity measures. Finally, the paper recommendation is completed by calculating the similarity of the generated author and paper feature vectors. We present experiments on a real academic network, the DBLP network. The comparative results demonstrate the effectiveness of the proposed personalized recommendation approach compared to state-of-the-art methods.

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.

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.

Tight assembly of stator windings with no insulation paper damage is a manufacturing challenge. We evaluate different sets of parts according to the following parameters: magnet wire thickness, stator slot smoothness, length of the straight magnet wire after the slot end, and type and amount of insulation cap at the end of the slot. These parameters have discrete values with small differences between them. The damage criterion is the decrease of the insulation paper breakdown voltage after assembly/disassembly of parts, assembled in a small set of designed experiments. Parameter values, i.e., levels at individual experiments are set by an orthogonal experiment matrix. Repetition of each experiment provides statistical significance. Data analysis shows that the additive model alone is not sufficient due to the high correlation of the parameters’ influences. We extend the model to include interparameter influences, which we model by adding a virtual parameter. The extended additive model generates parameter values that do not degrade the insulation paper breakdown voltage within the manufacturing process. These values are verified by repetitions of the control experiment.

Software fault prediction (SFP) is a research area that helps development and testing process deliver software of good quality. Software metrics are of various types and are used in SFP for measurements. Inheritance is a prominent feature, which measures the depth, breadth, and complexity of object-oriented software. A few studies exclusively addressed the efficacy of inheritance in SFP. This provokes the need to identify the potential ingredients associated with inheritance, which can be helpful in SFP. In this paper, our aim is to collecting, organizing, categorizing, and investigating published fault prediction studies. Findings include identification of 54 inheritance metrics, 78 public datasets with various combinations of 10 inheritance metrics, 60% use of method level & use of private datasets, an increased number of studies using machine learning approaches. This study will facilitate scholars to studying previous literature on software fault prediction having software metrics, with their methods, public data sets, performance evaluation of machine learning algorithms, and findings of experimental results in a comfortable, and efficient way, emphasizing the inherited aspect specifically.

© 2013 IEEE. With the rapid growth of scientific publications, it is hard for researchers to acquire appropriate papers that meet their expectations. Recommendation system for scientific articles is an essential technology to overcome this problem. In this paper, we propose a novel low-rank and sparse matrix factorization-based paper recommendation (LSMFPRec) method for authors. The proposed method seamlessly combines low-rank and sparse matrix factorization method with fine-grained paper and author affinity matrixes that are extracted from heterogeneous scientific network. Thus, it can effectively alleviate the sparsity and cold start problems that exist in traditional matrix factorization based collaborative filtering methods. Moreover, LSMFPRec can significantly reduce the error propagated from intermediate outputs. In addition, the proposed method essentially captures the low-rank and sparse characteristics that exist in scientific rating activities; therefore, it can generate more reasonable predicted ratings for influential and uninfluential papers. The effectiveness of the proposed LSMFPRec is demonstrated by the recommendation evaluation conducted on the AAN and CiteULike data sets.

Oil-paper insulation will inevitably endure impulse voltage with a superimposed dc voltage (superimposed voltage) because of introduced lightning or switching, which can induce charge accumulation and trigger flashover during the operation of a converter transformer. Temperature rise is also a nonnegligible factor that can significantly influence the performances of oil-paper insulation. This paper aims to reveal the effects of ambient temperature and superimposed voltage on surface charge and flashover behaviors in an oil-paper insulation system. Surface potential decay (SPD) experiments were performed under superimposed voltage with various polarity and amplitude combinations and at the temperature ranging from 20 °C to 80 °C. The results show that the initial surface potential and decay rate increase as the amplitude of the impulse voltage increases at 20 °C. The initial surface potential declines, and the process of SPD is accelerated at higher temperatures because of the increased concentration of shallow traps. Subsequently, flashover tests were conducted under superimposed voltage. It is found that flashover occurs after applying superimposed voltages even with a rather low dc voltage. In addition, the dc voltage component is primarily responsible for flashover. Weibull results also indicate that it is prone to trigger flashover at higher temperatures, because thermal excitation helps more carriers to escape from deep traps and participate in the process of flashover. Accordingly, the insulation characteristics of oil-paper system can be significantly influenced by superimposed voltage and temperature, which should draw great concern among the power grid.

With the rapid growth of scientific publications, research paper recommendation which suggests relevant research papers to users can bring great benefits to researchers. In this paper, we focus on the problem of recommending conference papers to the conference attendees. While most of the related existing methods depend on the content-based filtering, we propose a unified conference paper recommendation method named $CPRec$ , which exploits both the contents and the authorship information of the papers. In particular, besides the contents, we exploit the relationships between a user and the authors of a paper for recommendation. In our method, we extract several features for a user-paper pair from the citation network, the coauthor network, and the contents, respectively. In addition, we derive a user’s pairwise preference towards the conference papers from the user’s bookmarked papers in each conference. Furthermore, we employ a pairwise learning to rank model which exploits the pairwise user preference to learn a function that predicts a user’s preference towards a paper based on the extracted features. We conduct a recommendation performance evaluation using real-world data and the experimental results demonstrate the effectiveness of our proposed method.

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.

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.

Most existing studies and public datasets for handwritten Chinese text recognition are based on the regular documents with clean and blank background, lacking research reports for handwritten text recognition on challenging areas such as educational documents and financial bills. In this paper, we focus on examination paper text recognition and construct a challenging dataset named examination paper text (SCUT-EPT) dataset, which contains 50 000 text line images (40 000 for training and 10 000 for testing) selected from the examination papers of 2 986 volunteers. The proposed SCUT-EPT dataset presents numerous novel challenges, including character erasure, text line supplement, character/phrase switching, noised background, nonuniform word size, and unbalanced text length. In our experiments, the current advanced text recognition methods, such as convolutional recurrent neural network (CRNN) exhibits poor performance on the proposed SCUT-EPT dataset, proving the challenge and significance of the dataset. Nevertheless, through visualizing and error analysis, we observe that humans can avoid vast majority of the error predictions, which reveal the limitations and drawbacks of the current methods for handwritten Chinese text recognition (HCTR). Finally, three popular sequence transcription methods, connectionist temporal classification (CTC), attention mechanism, and cascaded attention-CTC are investigated for HCTR problem. It is interesting to observe that although the attention mechanism has been proved to be very effective in English scene text recognition, its performance is far inferior to the CTC method in the case of HCTR with large-scale character set.

The problem of sulfur corrosion has seriously affected the safe and stable operation of the power transformers. Currently, adding passivators into the transformer oil is the most effective method to suppress the problem. However, no explicit provisions have been made for the optimum concentration of the specific passivators. In this paper, the transformer oils with different corrosive sulfurs and different aging degrees were used to study the protective performance of three different passivators. By comparing the copper surface, the optimum concentrations for each passivators were acquired. Moreover, by testing the breakdown voltage, dielectric loss factor, volume resistivity, and moisture content of the insulating oil after adding passivators with the optimal concentration, the effect of three passivators on the oil quality was obtained. Results show that the three passivators have different protective performance on different types of corrosive sulfurs. Irgamet 39 has a better protective effect at lower concentrations than the other two. The protective effect of all three passivators on dodecyl mercaptan is poor, and a new type of passivator capable of protecting against dodecyl mercaptan needs to be developed. Moreover, the three passivators have different protection performance on the transformer oils with different aging degrees. The protective performance is poor especially for the oils with longer running years or passivators with lower concentrations. Among the three passivators, Irgamet 39 had the smallest impact on the oil quality, followed by T571 and then TTA. The above research can provide some references for guiding the passivator addition in actual projects and preventing the occurrence of sulfur corrosion failures.

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.

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.

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.

With the wide application of vegetable insulating oil in power transformers, it is essential to investigate the influence of moisture on the frequency domain dielectric spectrum (FDS) analysis in order to propose an accurate moisture assessment method for vegetable oil-paper insulation system. In this regard, various vegetable oil-paper samples are prepared in a laboratory environment. FDS curves for all samples are obtained at different moisture contents and operating temperatures. A new method to estimate the moisture content in insulation paper is proposed based on the low-frequency characteristic quantity. Also, the effect of operating temperature and water migration between the oil and paper insulation on the FDS analysis is investigated. Based on this analysis, a compensation factor is introduced to eliminate the influence of temperature on paper moisture assessment. Furthermore, an improved normalization method for the temperature effect on the FDS of vegetable oil-paper insulation with different moisture contents is proposed. The proposed moisture assessment and temperature normalization methods are validated thorough their application on an operating power transformer.

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.

The condition of a power transformer can be predicted based on the contents of the transformer oil. One of the most common parameters that are observed in the transformer oil is 2-Furaldehyde, a compound that is produced due to the aging of Kraft paper. Although the optical characterization of 2-Furaldehyde has been widely reported, the fundamental theories of the observation of the optical absorbance peaks have not been elaborated. This study investigates the optical characteristics of 2-Furaldehyde in the near infrared region. Ten samples with different concentrations of 2-Furaldehyde were prepared and verified using the conventional method. The samples were then characterized using optical spectroscopy method with 50 mm path length cuvettes. Three peaks were observed at 1610 nm – 1640 nm, 1100 nm – 1115 nm and 860 nm – 890 nm wavebands and were correlated to the overtones of the aromatic C-H stretch in 2-Furaldehyde. The appearance of these overtones corresponding to the Morse Oscillation Theory was discussed. This fundamental knowledge is significant in developing a portable optical device that enables the detection of 2-Furaldehyde on site.

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.