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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 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.

Prediction and detection of skin diseases have always been a challenging and critical task for health care professionals. There are many clinics and skin practitioners who are offering their services at exorbitant costs. At the same time, skin condition prevails in our country in every part. In the current scenario majority of the skincare practitioners are using traditional methods to diagnose the disease which may take a considerable amount of time. Skin Diseases are serious problems in recent times as it is a matter of environmental factors, socioeconomic factors, lack of full diet, etc. This paper is a comparative study about understanding various skin diseases related to normal skin issues as well as cosmetology. A comparison between oily, dry, and normal skin is also projected in this study. A survey of different papers is done on basis of technologies used, results with accuracy, ethical conduct, number of diseases diagnosed, datasets, etc are done.

This paper describes approaches to the use of wearables and related monitoring and diagnostic tools to glean and present data to patients and their caregivers in the form of Personal Health Dashboard. Raw data from devices such as fitness watches, blood glucose and blood pressure monitors can be analyzed by machine learning algorithms ensembles over the cloud or at the edge, and the resulting patterns can be presented to allow for actionable responses. The advent of low-cost computational, sensing, monitoring and diagnostic tools allow for cost-effective solutions that can have wide adaptability. The paper draws from prior and ongoing research conducted by the team to present these positions in the advancement of healthcare.

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%.

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.

In power transformers in which is dominated the oil-paper insulation system, it is the effort to use innovative insulating materials to achieve greater quality, reliability and longer service life of the transformer. In this paper, we present the results of research into the insulating properties of an oil-paper insulation system in a DC and AC electric field. In the experiments MOL TO 40A transformer oil and two types of paper used in transformers, KREMPEL DPP and insulating paper used in BEZ transformers, were used. The results from the experiments show that KREMPEL insulating paper has a higher electrical strength and the electrical strength of both oil-impregnated insulating papers is greater when applying DC voltage.

The assessment of the aging condition is becoming increasingly important for operators of high voltage assets. Power transformers are especially one of the most important units in the electrical power grid. Due to the fact that oil-paper insulation is still the most economical form of insulation, and is therefore found in the majority of transformers, the condition assessment of the paper insulation is decisive for estimating the remaining service life. Since the determination of the condition via furans is associated with certain fluctuations, several other aging parameters are investigated. Therefore, this study intends to determine how those aging markers of the insulating liquid behave in the absence of insulating paper and how the values change with insulating paper; thus, from the difference between important parameters, indicating the paper aging might be possible. For the investigation, a non-inhibited and an inhibited insulating oil as well as a further inhibited oil with a different composition, are tested as the most common insulating liquids. For this purpose, an open system is reproduced, which has permanent contact with the environment air. Accordingly, the study is carried out for long-term thermal stress to obtain samples with a wide spectrum of aging status. The entire study extended over a period of 14–15 weeks at a temperature of 130 °C with performing the measurements of the parameters at various aging times. The study reveals that the results can be used for an improved condition assessment of transformers.

This paper presents a novel, low cost flexible paper substrate suitable for biosensing applications. A microstrip patch antenna consisting of copper tape foil and a cellulose filter paper as a substrate with thickness of 180 μm is fabricated and tested. The substrate has measured dielectric constant (e r ) of 1.9 and losses (tan δ ) of 0.025. For 3.8 GHz resonance, the antenna has size of 29.5 mm x 38 mm on a ground plane of 50 mm x 60 mm. Measurements of the final design are in excellent agreement with simulations. Moreover, measurements of the patch antenna on the proposed substrate (cellulose filter paper) collected at different bending radii and folding angles demonstrate performance consistency.

The degree of polymerization is a useful technique to monitor insulation capabilities of oil impregnated paper. In present work, accelerated thermal ageing experiments have been conducted by taking Kraft and thermal upgraded papers along with two types of dielectric oil (mineral oil and vegetable oil) at different temperatures $(90^{\circ}C, 110^{\circ}C$ and $130^{\circ}C)$. An improved 2nd order kinetic model has been developed based on experimental results which utilized to develop a relationship between temperature and final degree of polymerization. The proposed model can be used to analyze and monitor thermal deterioration of oil paper insulation at any temperature. Moreover, the proposed novel mathematical modelling can be employed to predict premature failure as well as end of life criteria of power transformers.

Paper-based digital microfluidic biochip (PB-DMFB) technology provides a promising solution to many biochemical applications. However, PB-DMFB manufacturing process may suffer from potential security threats. For example, both Trojan insertion and man-in-the-middle attack may affect the functionality of PB-DMFBs. To ensure the correct functionality of PB-DMFBs, we propose a watermarking scheme to hides information in the PB-DMFB layout, which allows users to check design integrity and authenticate the source of the PB-DMFB design. As a result, it serves as a first countermeasure against both Trojan insertion and man-in-the-middle attacks for PB-DMFBs.

Even today, oil-paper insulation is one of the most important insulation systems for high-voltage components, which is mainly used in transformers. Due to an increase of regulations and obligations for transformer operators, alternative insulating liquids are becoming more and more important, especially esters, as these liquids are characterized as an environmentally friendly and low flammability substitute. So far there is only little experience on the ageing behaviour of ester-paper insulations and on the formation of ageing products with this mixed dielectric. The aim of this study is to investigate the influence of a synthetic based ester, a rapeseed-based and a soya-based natural ester on the ageing behaviour of a Kraft paper insulation. In this context, the correlation of ageing markers, such as the acid value, the moisture content etc., is measured in the liquid and the current condition of the paper insulation is investigated. It could be observed that the ageing behaviour of studied samples is different to mineral oil based liquids and also differences between synthetic and natural esters could be seen.

Basic repair and maintenance tasks of industrial machines are usually performed by local service personnel at the location of the component to be maintained. Complex maintenance tasks require an expert who travels to the customer to solve a specific problem. This process is time and cost intensive. Augmented Reality (AR) Remote Assistance offers means to support newcomers on site by guiding personnel through the maintenance process with novel visualizations. This paper describes an Augmented Reality based remote assistance tool for industrial purposes. We present the technology and our implementation approach, as well as the challenges and limitations we have encountered. The potential of the tool was evaluated and analyzed in an industry oriented use case for repairing an industrial PC. The results were compared with a maintenance procedure that was carried out using standard paper repair instructions. Our approach enabled the users to perform complex tasks faster and with fewer errors. Overall, the error rate decreased significantly due to the AR-based remote support. We also found that paper-based instructions are still more efficient in solving simple tasks.

This article adds more information to the problem of natural ester use as an electroinsulating fluid in cellulose paper-oil systems, e.g., for use in power transformers. An accelerated thermal aging (120, 140 and 160 °C) of samples consisting of cellulose paper (transformerboard), a treated natural ester (filtered, basic Al2O3, 0.53% DBPC), a copper plate and moisture was studied. Research was especially focused on the impact of moisture on the aging of the above system. Samples with three different oil moisture levels (80, 143 and 305 ppm water content) were subjected to thermal aging to display the change in a selection of properties (tanδ, acid number, water content). For a study of the polarization effects, broadband dielectric spectroscopy (BDS) was performed to observe the complex permittivity and conductivity dependencies on the temperature and frequency (±30 °C, 0.01-107 Hz). Havriliak-Negami (H-N) diagrams were used to further understand the results. The degradation products during thermal aging were recognized by Fourier transform infrared (FT-IR) spectroscopy. Hydrolysis and hydrogenation occurred in the insulating system with a natural ester aged by elevated temperatures, which is in contrast to CO2 formation in the case of electric aging. The results showed an increase in the acid number, dissipation factor, and number of hydrolysis and hydrogenation products. Furthermore, changes in polarization were observed as a consequence of the thermal aging of paper-natural ester insulation system with the presence of copper and moisture.

Due to the shortcomings of electrical properties and furfural in characterizing the aging characteristics of paper insulation and the limitations of field application, this paper focuses on the feasibility of evaluating the polymerization degree of insulating paper by the ethanol (EtOH) content in transformer oil. The accelerated thermal aging test is conducted, during which ethanol is produced by degradation of insulating paper. For each oil-paper samples, with different ethanol concentrations are prepared by controlling the aging time. In this paper, a gas chromatograph equipped with a mass spectrometer (GC-MS) measurement method with headspace injection is applied to obtain a fitting curve between ethanol content in oil and average degree of polymerization (DPv), which is a method for judging the degree of paper insulation aging condition. Then, showing the influence of temperature on ethanol generated in this experiment. At last, it is indicated that it is feasible to evaluate the polymerization degree of insulating paper by using the ethanol content in transformer oil.

In this paper, we study the state-dependent Gaussian wiretap channel with action encoder and noncausal state at the transmitter, which is also called the action-dependent dirty paper wiretap channel. Two lower bounds on the secrecy capacity of this model are provided, and we find that the two bounds have their advantages and disadvantages, i.e., none of the two always performs better than the other. In addition, we find that taking action on the state helps to increase the achievable secrecy rate of the dirty paper wiretap channel.

Moisture in transformer paper insulation is one of the most important parameters to be monitored in order to assess the useful life of the transformer. Time domain spectroscopy based on polarization and depolarization current measurements is one of the methods that can be used for detection of moisture content in the transformer paper insulation. However, these measurements could be influenced by thermal transient during the application of voltage, which may lead to an inaccurate interpretation of the insulation condition. In this paper, a novel method is proposed in order to avoid this thermal transient effect by using the high frequency component of the of depolarization current acquired during the measurement. Preliminary results show a correlation between the high frequency component of the depolarization current waveform and the moisture content in the paper insulation within a moisture content range of about 3 %. At higher moisture content, a resistive leakage current seems to have a negative effect on the measured depolarization current., 2019 IEEE 20th International Conference on Dielectric Liquids (ICDL), June 23-27, 2019, Roma, Italy

© 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.