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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.

Background: Although some have noted that combining technical and marketing content is precarious, technical communication professionals are increasingly involved in content marketing, which includes the creation of white papers. Literature review: The little existing literature on white papers provides conflicting guidance about managing the combination of technical and marketing content. Both soft-sell and hard-sell marketing approaches have been recommended. One source of such inconsistent guidance may be the lack of agreement about definitions. Research on print advertisements has described hard and soft selling as multidimensional rather than binary aspects of persuasive appeals. Research question: Which dimensions of hard- and soft-sell appeals are predominant in white papers? Research methodology: To complete our descriptive study, we collected a corpus of documents labeled as white papers in TechRepublic, and then selected and trained three raters to complete a series of judgments about dimensions of persuasive appeals in the corpus. We aggregated those ratings, calculating the mean and standard deviation for the dimensions to describe their distribution across the corpus. Results/discussion: Overall, hard-sell dimensions were more prevalent than soft-sell dimensions. However, the soft-sell category of “implicitness” was also dominant. Conclusion: Our results demonstrate the value of treating hard and soft selling as multidimensional, complementary, and combinatory marketing appeals that allow, for example, a single white paper to be both “subjective” (soft sell), and “precise” (hard sell), or both “creative” (soft sell) and “informative” (hard sell).

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.

Rapid increase in scholarly publications on the web has posed a new challenge to the researchers in finding highly relevant and important research articles associated with a particular area of interest. Even a highly relevant paper is sometimes missed especially for novice researchers due to lack of knowledge and experience in finding and accessing the most suitable articles. Scholarly recommender system is a very appropriate tool for this purpose that can enable researchers to locate relevant publications easily and quickly. However, the main downside of the existing approaches is that their effectiveness is dependent on priori user profiles and thus, they cannot recommend papers to the new users. Furthermore, the system uses both public and non-public metadata and therefore, the system is unable to find similarities between papers efficiently due to copyright restrictions. Considering the above challenges, in this research work, a novel hybrid approach is proposed that separately combines a Content Based Filtering (CBF) recommender module and a Collaborative Filtering (CF) recommender module. Unlike previous CBF and CF approaches, public contextual metadata and paper-citation relationship information are effectively incorporated into these two approaches separately to enhance the recommendation accuracy. In order to verify the effectiveness of the proposed approach, publicly available datasets were employed. Experimental results demonstrate that the proposed approach outperforms the baseline approaches in terms of standard metrics (precision, recall, F1-measure, mean average precision, and mean reciprocal rank), indicating that the proposed approach is more efficient in recommending scholarly publications.

The effects of furfural generation and partitioning on the aging assessment of oil-paper insulation of power equipment were investigated. Oil-paper samples with various furfural contents were prepared using an accelerated thermal aging experiment. The mass of the furfural generated during the aging of insulation paper was calculated and used to establish the quantitative equation between the accumulated furfural and the degree of polymerization (DP) of the insulation paper. Results showed that the reciprocal of the DP value was linearly related to the amount of furfural generated by the insulation paper. Effects of temperature, moisture, and temperature on the furfural partitioning ratio between oil and paper were analyzed using a furfural partitioning experiment, and a furfural partitioning model was established. Results showed that the furfural partitioning ratio in oil was positively correlated with temperature and moisture but negatively correlated with the DP of the insulation paper. A method for assessing the age of an insulation paper by integrating the furfural generation and partitioning models was proposed and applied on a 500-kV reactor that was returned for factory maintenance. The application result indicated that the method could accurately assess the overall aging condition of the oil-paper insulation of the power equipment.

A 3D modeling system with all-inclusive functionality is too demanding for a casual 3D modeler to learn. There has been a shift towards more approachable systems, with easy-to-learn, intuitive interfaces. However, most modeling systems still employ mouse and keyboard interfaces, despite the ubiquity of tablet devices and the benefits of multi-touch interfaces. We introduce an alternative 3D modeling and fabrication paradigm using developable surfaces, inspired by traditional papercrafting, and we implement it as a complete system designed for a multi-touch tablet, allowing a user to fabricate 3D scenes. We demonstrate the modeling and fabrication process of assembling complex 3D scenes from a collection of simpler models, in turn shaped through operations applied to virtual paper. Our fabrication method facilitates the assembly of the scene with real paper by automatically converting scenes into a series of cutouts with appropriately added fiducial markers and supporting structures. Our system assists users in creating occluded supporting structures to help maintain the spatial and rigid properties of a scene without compromising its aesthetic qualities. We demonstrate several 3D scenes modeled and fabricated in our system, and evaluate the faithfulness of our fabrications relative to their virtual counterparts and 3D-printed fabrications.

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.

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.

Dirty paper coding is an interference pre-cancellation method for known interference at the transmitter and serves as a basic building block in the digital watermarking system. In this letter, we investigate the dirty paper model in the simplest digital communication system, where both the codeword and the interference are binary. For watermark embedment, we derive the relevant coding, the constant coding, and the symmetric relevant coding when the encoder focuses on the binary codeword and interference. The channel capacity is analyzed and the optimal parameter is discussed in the case.

The applicability of using 2-furfural (2-FAL) and methanol as aging markers for synthetic ester impregnated paper insulation was investigated through laboratory aging experiments at temperatures of 80, 100 and 120 °C. Methanol in the synthetic ester increased linearly with paper aging until degree of polymerisation (DP) reached 400. During this period concentration of methanol in oil was higher than that of 2-FAL, which proved the concept of using methanol to indicate early paper aging in the synthetic ester. However, the rate of methanol increase against the reduction of DP in the synthetic ester was about three times higher than that seen in mineral oil. This is due to a difference in the partitioning of the marker between oil and paper. Since the synthetic ester is more polar than the mineral oil, it attracted more methanol molecules from the paper, resulting in a higher concentration of methanol in oil for the same reduction of DP. In addition, a reduction in methanol was observed at the later stage of paper aging at 120 °C. This could be due to either a change in the partitioning between oil and paper, or an esterification reaction which consumes methanol in the system.

This article presents a comparative study of two types of transformer solid insulation: standard Kraft and thermally upgraded Kraft papers. The paper samples were impregnated with two different fluids, namely a synthetic dielectric ester fluid, Midel 7131, and a synthesized mineral oil, Luminol Tri. The impregnated papers were submitted to, accelerated aging at 150°C, temperature higher than the temperatures found inside transformers, for extended periods. The results show that for the first hours of aging, the cellulose depolymerization was similar for all the four studied cases. At a specific point, the paper samples aged in the ester fluid exhibited a lower depolymerization exceeding the 8000 hours of aging without reaching the levelling-off degree of polymerization (LODP). A similar trend was observed through the decrease of mechanical properties of papers in the ester-based oil. However, the difference in performance of both fluids was amplified due to the temperature used; at lower temperatures the difference should be smaller. Additionally, a relationship between the degree of polymerization and the mechanical properties accessed by the tensile testing was obtained regardless of the type of paper or oil. The total acidity in the ester fluid was higher than in mineral oil. Methanol, a chemical marker that is closely linked to the rupture of 1,4-s-glycosidic bonds of cellulose, showed a partial sensitivity to the cellulose aging in the ester fluid. Furan (C 4 H 4 O) content was monitored during the aging and its concentration was found to be sensitive to the depolymerization along with the decrease in the mechanical properties of cellulose papers regardless of the type of paper. More importantly, its concentration was found to be dependent on the type of oil. More investigations are needed to further confirm the importance of furan as an indirect indicator of the mechanical performance along with its correlation with the depolymerization of paper aged in ester fluids.

Breakdown (BD) and partial discharge (PD) characteristics of insulating paper and transformer board materials are investigated as cost-effective alternatives to high-price materials like polyimide (PI) or polytetrafluoroethylene and fiber reinforced plastic materials typically used in superconducting devices based on high temperature superconductors cooled with liquid nitrogen (LN 2 ). Three different cotton and cellulose based insulating papers are tested in LN 2 at atmospheric pressure and compared to synthetic sheet materials and polypropylene laminated paper (PPLP). Additionally, the BD performance and PD characteristics of three different transformer board materials are investigated in LN 2 . The results reveal that the paper and board materials have nearly the same or even slightly higher BD voltages in LN 2 in comparison to the values in insulating oil. The pure paper materials with thicknesses of 130 μm have a dielectric strength of 70-90 kV/mm, whereas values of 130-140 kV/mm are measured for PPLP and PI with nearly the same thickness. The dielectric strength of the board materials has a maximum value of 76 kV/mm. In the frame of the investigations, the BD performance of the pure paper materials in LN 2 is not influenced by the water content of the materials, dried and undried specimens have nearly the same BD voltage. Only the PPLP material has a 15% higher BD voltage in the dried state in comparison to the undried state.

The vast majority of power transformers have an insulation system consisting of both insulating mineral oil and Kraft paper. The principal oil degradation agents are oxygen and temperature, whereas the main mechanisms of insulating Kraft paper degradation are water and acids (acidic hydrolysis degradation), temperature (pyrolytic degradation), and oxygen (oxidative degradation).

Under long-term synergy effect of multi-factors, especially the thermal stress, insulating paper will be degraded and its insulation performance will decline due to carbonization and degradation of cellulose. This paper presents an optical approach for aging feature extraction of the insulating paper, where one of the image processing methods called texture analysis is utilized. By conducting laboratory accelerated thermal aging tests, insulating paper samples with different aging conditions for both Nomex and Kraft, evaluated with the aging time, are prepared. After taking optical microscopic images of insulating paper samples belong to different aging groups, up to 14 texture features are extracted using the gray-level co-occurrence matrix (GLCM). With different feature selection methods applied, several of them are finally selected to represent the aging condition of insulating. Numerical tests with both supervised and unsupervised algorithms, as well as a linear regression method verifies the validity of these features in characterizing the aging condition of the insulating paper.

Traction transformer is vital equipment in high-speed railway. Insulation status decides its safety and reliability, and the frequency-domain dielectric spectrum (FDS) test is one of the most effective methods reflecting the changing of insulation status. For field applications, the following problems should be addressed: 1) how to obtain the result of paper insulation from the combined result of the oil–paper insulation system and 2) how to discriminate the defects of insulation paper between aging and damp. In this article, the first problem was transferred to a nonlinear equation set, and a cuckoo search algorithm optimized by the differential evolution algorithm and the quadratic interpolation (QI) method (CS-DQ algorithm) was proposed to solve it. Then, the insulation states were discriminated by establishing a multiclass least-squares support vector machine (LS-SVM) model, in which the CS-DQ algorithm was also used. Finally, a diagnostic approach for the insulation paper in the traction transformer was proposed. The results in the laboratory show that the pure result of insulation paper can be obtained, and the insulation states can be discriminated effectively by using the proposed approach. Meanwhile, the proposed CS-DQ algorithm has a better performance than the conventional CS algorithm. The results of field testing also verify the proposed approach.

The International Technology Roadmap for Wide-Bandgap Power Semiconductors (ITRW) has four distinct technical working groups, each providing its own perspective on the technology and industrial drivers for the adoption of wide-bandgap (WBG) power semiconductors in power electronics. This article summarizes the progress toward an initial roadmap for the packaging and integration working group of the ITRW.

Moisture accumulates with the growing aging progress of oil-paper insulation and further shortens the remaining life of the transformer. The frequency-domain spectroscopy (FDS) technique can be used to realize the moisture estimation. However, the moisture estimation results would be unreliable once the aging effect on FDS was ignored. Given this issue, an alternative model including the aging effect is thus proposed using FDS and intelligent algorithm. In this work, the feature parameters of FDS data are used to build the databases for characterizing the aging degree and moisture. Then, the moisture estimation models are developed using the weighted K-nearest neighbor (K-NN) algorithm. The accuracy and applicability of the proposed models are finally discussed in laboratory and field conditions. In that respect, the findings reveal that the reported model is available for moisture estimation of transformer oil-paper insulation under various aging degrees and test temperatures.

Finding relevant papers is a non-trivial problem for scholars due to the tremendous amount of academic information in the era of scholarly big data. Scientific paper recommendation systems have been developed to solve such problem by recommending relevant papers to scholars. However, previous paper recommendations calculate paper similarity based on hand-engineered features which are inflexible. To address this problem, we develop a scientific paper recommendation system, namely VOPRec, by vector representation learning of paper in citation networks. VOPRec takes advantages of recent research in both text and network representation learning for unsupervised feature design. In VOPRec, the text information is represented with word embedding to find papers of similar research interest. Then, the structural identity is converted into vectors to find papers of similar network topology. After bridging text information and structural identity with the citation network, vector representation of paper can be learned with network embedding. Finally, top- $Q$ Q recommendation list is generated based on the similarity calculated with paper vectors. Through the APS data set, we show that VOPRec outperforms state-of-the-art paper recommendation baselines measured by precision, recall, F1, and NDCG.

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.

This paper studies the secure transmission in a multiuser broadcast channel where only the statistical channel state information of the eavesdropper is available. We propose to apply secret dirty-paper coding (S-DPC) in this scenario to support the secure transmission of one user and the normal (unclassified) transmission of the other users. By adopting the S-DPC and encoding the secret message in the first place, all the information-bearing signals of the normal transmission are treated as noise by potential eavesdroppers and thus provide secrecy for the secure transmission. In this way, the proposed approach exploits the intrinsic secrecy of multiuser broadcasting and can serve as an energy-efficient alternative to the traditional artificial noise (AN) scheme. To evaluate the secrecy performance of this approach and compare it with the AN scheme, we propose two S-DPC-based secure transmission schemes for maximizing the secrecy rate under constraints on the secrecy outage probability (SOP) and the normal transmission rates. The first scheme directly optimizes the covariance matrices of the transmit signals, and a novel approximation of the intractable SOP constraint is derived to facilitate the optimization. The second scheme combines zero-forcing dirty-paper coding and AN, and the optimization involves only power allocation. We establish efficient numerical algorithms to solve the optimization problems for both schemes. Theoretical and simulation results confirm that, in addition to supporting the normal transmission, the achievable secrecy rates of the proposed schemes can be close to that of the traditional AN scheme, which supports only the secure transmission of one user.

Frequency Domain Spectroscopy (FDS) is proposed as a suitable diagnostic method in this paper for implementation on energized oil-paper insulation systems. In present FDS tests, the measurement method is only designed for offline applications. To overcome the deficiencies with the offline testing, this work investigates the feasibility of performing FDS measurements on energized transformers with the view to developing an online diagnostic tool using neutral connections as injection and measurement paths. In the proposed technique, a low-pass filter system is designed to remove the high frequency noise as well as the power frequency signals present in the measured neutral currents. The technique has been successfully applied in a laboratory environment on transformers with oil-paper insulation systems with different operational ages and is feasible for single-phase as well as 3-phase transformers with the accessible neutral points. Compared with the conventional FDS results, a nonlinear dielectric phenomenon is observed from the energized insulation systems as higher dissipation factor Tanδ values primarily due to the increased losses under power frequency voltage excitation. The degree of the nonlinearity is found to correlate well with the degradation status of insulation systems under test.

Thermally upgraded Kraft (TUK) "Insuldur®" papers prepared from the same batch process but with a different percentage of stabilizing additives (1.2, 2.6 and 4.4% of nitrogen) were studied under accelerated aging at 170 °C. The increment of stabilizing additives in paper with the consequent increment of nitrogen content slows down the rate of molecular chain scission of the cellulose and reduces the paper tensile strength loss rate. However, a progressive reduction in the enhancement of the paper life span by the increment of nitrogenous additives in paper was observed. The cellulose degradation methanol and ethanol markers were found to be reliable and accurate for tracking the aging of TUK papers even with the variation of nitrogen content in paper. A promising correlation between methanol concentration and the paper tensile index with different nitrogen content was determined. This correlation could be used as a basis for developing tools to assess power transformers residual life. FTIR-ATR analyses of dicyandiamide in aged papers showed a rapid reaction and decomposition of dicyandiamide in other compounds that slows down cellulose aging. The nitrogen content of aged paper, measured with the Dumas method, showed a slight variation during the study. This implies that the nitrogen compounds continue to be attached, presumably by polar forces to the paper. Thermogravimetric analysis (TGA) of new and aged Insuldur® paper samples showed that nitrogen additives improve the thermal stability of paper at high temperatures.

Oil impregnated paper in power transformers deteriorates in long-term operation, which leads to the variations of its dielectric characteristics. This paper focuses on investigating the generation mechanism of the dielectric processes in oil impregnated paper and their variations with thermal aging. Firstly, a set of thermally stimulated current tests with bias-voltages were conducted in distinguishing the dielectric processes and revealing their generation mechanism. Secondly, the standard thermally stimulated current spectrum and the M″ spectrum of 0–1000 h aged samples were joint analyzed in investigating the variations of dielectric processes in thermal aging process. Finally, additional experiments of moisture, acidity and microscopic observation were conducted in explaining these variations. It is concluded that three dielectric processes can be found in oil impregnated paper, i.e. the dipole polarization, the interfacial polarization and the electric conduction. These processes are all strengthened with thermal aging. The generation of molecules with strong polarity, the structural changes in insulating paper, and the generation of hydrogen ions are responsible for the strengthening of these processes sequentially. This investigation on distinguishing dielectric processes and obtaining their mechanism can promote further understanding on oil impregnated paper and provide information for insulation design in power transformers.

Cellulosic insulation materials are very widely used in power transformers, in designs up to 1,500 MVA [1]. Cellulosic insulation is formed of either wood, pressboard, or Kraft paper. The wood and thick sections of pressboard are used to manufacture the base of the transformer; pressboard is also used for the spacers and barriers of the windings, and the paper is wrapped around the current carrying conductors. The water content of this cellulosic insulation must be monitored, because if it becomes too high, a transformer can fail on overload, and will reach the end of its functional life sooner because the paper insulation will age faster [2]. Eventually, the paper will become brittle, and will either tear or lift off the conductor. The water content of paper (WCP) is the ratio of the mass of adsorbed water to the mass of dry paper, usually expressed as a percentage. Water can migrate out of the wood and pressboard and around the system, eventually increasing the WCP. If the WCP becomes too high, the transformer may be dried out by the relevant utility [3].

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.

Paper-based digital microfluidic biochips (or P-DMFBs) are becoming highly impelling due to its low-cost and in-place fabrication of electrodes and control wiring on a single piece of paper having an inkjet printer and conductive ink. Despite enormous advantages, several complex design rules also subsist, such as avoidance of induced control interference, minimum separation among the control lines, and congestion-free wiring on a single layer, which is to be correlated leading toward overall feasibility of the design. Several cost raising issues, such as schedule length, control pin count, and wire length, must be considered for attaining a successful fluid-control codesign. Moreover, design gaps exist among the subtasks of the fluid level, control level, and fluid-control design as a whole, which undeniably impose expensive design cycles increasing overall cost. This article builds a machine learning-based model for the pin-constrained P-DMFBs to predict violation in control design beforehand and accordingly guides the fluid-control codesign to tackle important cost-driving issues while attaining congestion- and conflict-free wiring. This model effectively eliminates the design cycles producing a low-cost platform. The predictive model has been evaluated over a balanced data set. Several benchmarks for assessing the performance are studied.

Dirty paper coding (DPC) offers an information-theoretic result for pre-cancellation of known interference at the transmitter. In this letter, we propose practical DPC schemes that use only one error correction code. Our designs focus on practical use from the viewpoint of complexity. For fair comparison with previous schemes, we compute the complexity of proposed schemes by the number of operations used. Simulation results show that compared to previous DPC schemes, the proposed schemes require lower transmission power to maintain the bit error rate to be within $10^{-5}$ .

Over the last decade, the rapid development in health care industry and security has driven innovations in the field of wearable electronics and smart sensors. This report demonstrates the fabrication of molybdenum diselenide (MoSe2) by a facile, low-cost and scalable hydrothermal synthesis method followed by a vacuum filter deposition on cellulose paper. The fabricated device is utilized as a pressure and strain sensor. The fabricated device is passivated using polydimethylsiloxane (PDMS), and also, PDMS film enhances the flexibility of the device. The calculated sensitivity of pressure sensor is ~0.3 kPa−1, which is comparable and relatively better than the pressure sensor fabricated using sophisticated techniques. Furthermore, the device exhibited significant of merit for strain sensing with a gauge factor of ~6.84. The fabricated device showed excellent resilience in 500 cycle bending tests, which promises the robustness of the device. As an application, the fabricated sensor is used to develop a wireless keyboard by integrating the sensor on fingertips of an individual and a real-time human motion monitoring application in which the data are transmitted wirelessly to a smartphone with a dedicated android application. The successful fabrication of MoSe2/paper-based cost-effective, flexible, and biodegradable pressure-strain sensor shows tremendous applications in future intelligent user interface systems, human security, and personal health care monitoring.

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.

Oil-paper insulation ageing of transformer has characteristics of spatial locality due to uneven temperature distribution. The transformer is sealed, it is difficult to obtain the local ageing state of oil-paper insulation by sampling directly. Currently, there are no effective detection method to detect the insulation state of local regions. The oil-immersed paper resistivity inversion method can nondestructively assess the local state of oil-paper insulation. However, the current inversion methods still have shortcomings and need to be improved. In this paper, combining the back propagation neural network (BPNN) and Newton downhill method (NDM), an improved inversion method is proposed to optimize the current inversion method, so as to reduce the effect of initial value on it and make calculated results converge better. Finally, a 3D 10 kV transformer model is established to verify the effectiveness of the proposed method. The resistivity calculated by the improved method show that the method can provide initial resistivity values for technicians and improve the convergence and accuracy of current inversion method, which is more suitable for extending to the engineering practice.

Paper-based digital microfluidic biochips (P-DMFBs) have recently emerged as a promising low-cost and fast-responsive platform for biochemical assays. In P-DMFBs, electrodes and control lines are printed on a piece of photograph paper using an inkjet printer and carbon nanotubes (CNTs) conductive ink. Compared with traditional digital microfluidic biochips (DMFBs), P-DMFBs enjoy significant advantages, such as faster in-place fabrication with printer and ink, lower costs, and better disposability. Since electrodes and CNT control lines are printed on the same side of this paper, a critical design challenge for P-DMFB is to prevent control interference between moving droplets and the voltages on CNT control lines. Control interference may result in unexpected droplet movements and thus incorrect assay outputs. To address this design challenge, a control-fluidic codesign methodology is proposed in this paper, along with two demonstrative design flows integrating both fluidic design and control design, i.e., the droplet-oriented codesign flow and the electrode-oriented codesign flow. The droplet-oriented flow is suitable for designing biochips with sparse electrodes and relatively larger number of droplets, whereas the electrode-oriented flow is suitable for biochips with dense electrodes and smaller number of droplets. The computational simulation results of real-life bioassays demonstrate the effectiveness of the proposed codesign flows.

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.

Paper degradation products dissolved in the oil are used as chemical markers for predicting the power transformers lifespan in paper-oil systems. For a compound to be useful as a solid insulation marker, it must be derived exclusively from insulating paper, must be thermally and chemically stable over time, and must have known migration behavior and paper/oil partitioning at different temperatures. Methanol was considered to be potentially useful as marker. The stability of methanol in the presence of organic acids formed by degradation of insulating oil and paper was evaluated in detail, using FTIR and Gas Chromatography Mass Spectrography (GC/MS), in samples of fresh mineral insulating oil (MIO) and high-acidity MIO removed from a transformer in the field, to which formic and acetic acid and methanol were added. The samples were subjected to thermal aging and the results showed that the main problem in using methanol as a marker for paper degradation was its high volatility, apart some possible esterification with low molecular mass acids formed with of paper and /or oil degradation.

It is well established that copper sulfide is formed due to reaction of sulfur with copper conductors in transformers and reactors. However, there is very little experimental evidence to demonstrate copper sulfide diffusion into bulk of paper. Diffusion experiments have been carried out on three samples of kraft paper having different thickness. Positron Annihilation Lifetime Spectroscopy has been used to investigate the possibilities of copper sulfide diffusion into bulk of paper. This study has demonstrated that copper sulfide can diffuse into the bulk of paper leading to either increase or decrease in free volume of paper. The reasons for changes in free volume of paper due to copper sulfide deposits are explained. The consequences of copper sulfide diffusion on PD, voltage-current characteristics under ac and volume resistivity are discussed. Electric field simulation has been used to explain the effects of Cu ions and copper sulfide formation on electric stress distribution across paper.

The HVDC dry-type bushing, with its main insulating medium being epoxyimpregnated- paper composite, is a key device in the ultra-high voltage direct current power transmission system. The HVDC bushing is under the combined effect of electricity, heat, and mechanical stress when it is in operation, in which case the electric field strength in the core of bushing is high, the temperature in the central conductor is high, and the interfacial effect between the epoxy layer and insulating paper is strong. Consequently, space charge will accumulate in the epoxy-paper composite insulation. Previous studies mainly focuses on the characteristics of space charge distribution in polymer-micro-nano filler, whereas the studies on that in epoxy-insulating-paper composite are quite limited. This paper, based on the HVDC bushing made up of epoxy-insulating-paper composite, establishes and a space charge measuring system which is suitable for the pulse electro-acoustic (PEA) method at high temperature (⩽110 °C). A modified PEA method which is applicable to the measurement of space charge in the multi-dielectric-layer composite with different acoustic impedance is put forward. By controlling the thicknesses of dielectric layers in the composite sample, the effect of sound wave reflection on the measuring system can be eliminated. An in-depth study is conducted on the effects of temperature and field strength on the characteristics of space charge distribution in epoxy-paper composite.

Furfural content in oil is a valuable indicator of cellulose paper degradation and is widely utilized in aging assessment for power transformers. However, with the same aging degree of insulation paper, the actual furfural content in oil is influenced by temperature because furfural partitioning behavior in the oil-paper insulation system of power transformers changes with temperature. Thus, correction of the temperature effect on furfural partitioning is crucial for accurate assessment of the aging of power transformers. In this research, oil-paper samples with different furfural contents were prepared through an accelerated thermal aging test. A furfural equilibrium experiment was conducted at different temperatures to construct a furfural partitioning diagram. The mass fraction of furfural in oil and paper was calculated. Results showed that the mass fraction of furfural in oil increases with temperature rising and aging deepening, which means that furfural tends to migrate from paper to oil at high temperatures and deep aging conditions. The change in furfural partitioning between oil and paper at different temperatures causes a deviation in paper aging assessment. To correct the temperature effect on furfural partitioning, a furfural correction factor was developed to normalize furfural contents in oil at different temperatures to a reference temperature. The furfural correction factor was verified by experimental data and then introduced into the relation between degree of polymerization of paper and furfural content of oil. Verification results showed that the corrected equation can enhance the accuracy of paper aging estimation at different temperatures. The findings of this work indicated temperature effect on furfural partitioning should be considered when determining the furfural thresholds and evaluating the aging condition of power transformers.

Due to the increasing size of s (s), their design and optimization phases (i.e., ) grow increasingly complex. At design time, a large design space needs to be explored to find an implementation that fulfills all specifications and then optimizes metrics like energy, area, delay, reliability, etc. At run time, a large configuration space needs to be searched to find the best set of parameters (e.g., voltage/frequency) to further optimize the system. Both spaces are infeasible for exhaustive search typically leading to heuristic optimization algorithms that find some trade-off between design quality and computational overhead. ML can build powerful models that have successfully been employed in related domains. In this survey, we categorize how () may be used and is used for design-time and run-time optimization and exploration strategies of s. A meta-study of published techniques unveils areas in that are well-explored and underexplored with, as well as trends in the employed algorithms. We present a comprehensive categorization and summary of the state of the art on for. Finally, we summarize remaining challenges and promising open research directions.

A Midwestern pulp and paper mill had arc-flash ratings around 100 cal/cm2 on 50 480-V unit substations. New relays were installed to replace the existing protection and add light detection to improve arc-flash detection times. During a couple of one-day outages, sample installations took place. During the cold mill outage, 44 installations were completed over 12 days by working around the clock. Old relays were removed, new plates were mounted and wired in, and fiber sensors were routed through the buswork and into the breaker cubicles. Updated arc-flash studies show an average arc-flash rating reduction of 90%.

To paraphrase the son of lady macduff in william Shakespeare's Macbeth, "DC is not dead, for all your saying!" When the paper industry was first electrified, the only type of machine capable of variable-speed operation was powered by dc. There were numerous manufacturers and users who knew how the machines worked and how to maintain them. Over time, the control of these machines has changed from relatively simple analog to complex digital systems. Those whose task it was to keep the machines healthy have since moved on to other things. The modern pulp, paper, and forest industries still have applications powered by dc equipment; however, the most recent installation trend is toward ac machines.

Activation energy is popularly used for the estimation of remaining life of transformer insulation. It is defined as the average rate of all reactions that happen with cellulose. Existing literature shows that the activation energy of oil–paper insulation can be obtained from polarization depolarization current (PDC) and return voltage measurement (RVM) data that are measured at a specific temperature. It is practically difficult to ensure the same measurement temperature for both PDC and RVM data. On the other hand, PDC data and its analysis get influenced by de-trapping current. This de-trapping current is generated by ionic charge carriers that get freed from trap sites during PDC measurement process. Formation of these trap sites is related to physical, chemical reactions that happen at oil–paper interface. This paper proposes a methodology which uses de-trapped charge, dislodged from deep and shallow traps, to assess insulation condition and for the prediction of activation energy. Thus, eliminating the need of RVM data. The proposed method is tested using data collected from various real-life in-service transformers.

Assessment of insulation condition by sensing moisture content of oil-impregnated paper at periodic intervals is necessary for reliable operation of transformers. The conventional method of moisture sensing requires application of two cycles of sinusoidal excitation voltage at discrete measurement frequency points over a wide range starting from 0.1 mHz to 1 kHz, which is inadvertently time consuming and practically problematic. Besides, the insulation system in real-life operation is often stressed by voltage waveforms which deviate significantly from sinusoid. Therefore, modification of the existing method is necessary for a reliable insulation diagnostic. Considering the above-mentioned fact, in this article, a new measurement technique for sensing moisture content of oil-paper insulation is proposed using frequency modulated square wave excitations. The proposed technique was experimentally validated on several real-life transformers tested in the laboratory. Investigations revealed that the use of frequency modulated square wave excitations is capable of sensing moisture content in oil-paper insulation almost accurately in comparison with the conventional method but with a significantly reduced measurement time without compromising on measurement accuracy.

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.

Recent studies have reported that thermal aging of insulation paper affects its moisture absorption property, which can affect moisture equilibrium in oil-paper insulation. In engineering practice, Fessler's model is one of the most widely used methods to estimate the moisture content of paper through measurement of moisture content of oil. However, this model lacks consideration of the thermal aging effect on equilibrium moisture. This study comprehensively investigated the effect of thermal aging on moisture equilibrium in oil-paper insulation. Based on the accelerated ageing and moisture measurements, the equilibrium moisture content of insulation paper with different aging and temperatures were obtained. The effects of aging condition and the temperature on equilibrium moisture are discussed and Fessler's model was modified accordingly. The results show that: 1) the decreasing of specific surface area is the dominant factor that affects the moisture equilibrium in oil-paper insulation, which is caused by thermal aging; 2) the modified Fessler model is reasonable and suitable to estimate the equilibrium moisture content of insulation paper with different aging.

Introduction: The electrocardiogram (ECG) plays an important role in the diagnosis of heart diseases. However, most patterns of diseases are based on old datasets and stepwise algorithms that provide limited accuracy. Improving diagnostic accuracy of the ECG can be done by applying machine learning algorithms. This requires taking existing scanned or printed ECGs of old cohorts and transforming the ECG signal to the raw digital (time (milliseconds), voltage (millivolts)) form. Objectives: We present a MATLAB-based tool and algorithm that converts a printed or scanned format of the ECG into a digitized ECG signal. Methods: 30 ECG scanned curves are utilized in our study. An image processing method is first implemented for detecting the ECG regions of interest and extracting the ECG signals. It is followed by serial steps that digitize and validate the results. Results: The validation demonstrates very high correlation values of several standard ECG parameters: PR interval 0.984 +/−0.021 (p-value < 0.001), QRS interval 1+/− SD (p-value < 0.001), QT interval 0.981 +/− 0.023 p-value < 0.001, and RR interval 1 +/− 0.001 p-value < 0.001. Conclusion: Digitized ECG signals from existing paper or scanned ECGs can be obtained with more than 95% of precision. This makes it possible to utilize historic ECG signals in machine learning algorithms to identify patterns of heart diseases and aid in the diagnostic and prognostic evaluation of patients with cardiovascular disease., We present a MATLAB-based tool and algorithm that converts a printed or scanned ECG into a digitized ECG signal. Validation on 30 ECG scanned curves more than 95% precision. This makes it possible to utilize historic ECG signals in machine learning algorithms to identify patterns of heart diseases and aid in the diagnosis and evaluation of patients with cardiovascular disease.

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.

The interaction between technology and healthcare has a long history. However, recent years have witnessed the rapid growth and adoption of the Internet of Things (IoT) paradigm, the advent of miniature wearable biosensors, and research advances in big data techniques for effective manipulation of large, multiscale, multimodal, distributed, and heterogeneous data sets. These advances have generated new opportunities for personalized precision eHealth and mHealth services. IoT heralds a paradigm shift in the healthcare horizon by providing many advantages, including availability and accessibility, ability to personalize and tailor content, and cost-effective delivery. Although IoT eHealth has vastly expanded the possibilities to fulfill a number of existing healthcare needs, many challenges must still be addressed in order to develop consistent, suitable, safe, flexible, and power-efficient systems that are suitable fit for medical needs. To enable this transformation, it is necessary for a large number of significant technological advancements in the hardware and software communities to come together. This keynote paper addresses all these important aspects of novel IoT technologies for smart healthcare-wearable sensors, body area sensors, advanced pervasive healthcare systems, and big data analytics. It identifies new perspectives and highlights compelling research issues and challenges, such as scalability, interoperability, device-network-human interfaces, and security, with various case studies. In addition, with the help of examples, we show how knowledge from CAD areas, such as large scale analysis and optimization techniques can be applied to the important problems of eHealth.

Aviation is often seen as an innovative sector eager to seek technological solutions. It is often assumed that aircraft cockpits have panels with electronic displays and many buttons, some labeled "auto." While this might be the case for commercial aviation (Figure 1), the vast majority of noncommercial civil aircraft cockpits look nothing like these modern cockpits. Non-commercial civil aircraft, known as general aviation (GA), typically have cockpits that mainly consist of analog instruments that show the heading of the aircraft, the altitude, and the air speed (Figure 2). While flying, the pilots make calculations using a compass and an aviation calculator. Due to the slow entry rate of new, glass-cockpit aircraft [1], the composition of the GA aircraft fleet is not going to change any time soon.

THE YEAR IS 2028. IT'S 8 P.M. ON A Wednesday night and you're famished. You're staring wistfully at the only remaining item in your refrigerator: a package of sausages with an unappetizing grayish hue. Ugh. Did they always look like that? Are they still safe to eat? In 2018, you'd have to rely on your sense of smell and take a gamble. But in 2028, you might simply wave your smartphone over the package. The smartphone interrogates the package's embedded sensor, which measures the concentration of gases associated with meat decomposition. The smartphone displays the message "Safe to eat within the next 20 hours," and then offers a list of recipes for cooking with sausages. Too hungry to bother with the recipes, you tear open the package, toss the sausages into a frying pan, and discard the package-along with its sensor technology.