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The article presents questions and answers related to calculations on toilet paper squares including reduction in surface area; sales by type of toilet paper in the U.S. in 2014; and the volume of the toilet paper roll.

BACKGROUND: With the development of modern technology, the use of software-based applications in the field of health has become increasingly widespread. For this reason, computer-assisted personal registration forms have been developed using software programs. OBJECTIVE: The aim of this study was to compare surface contamination during the filling of orthodontic anamnesis-consent forms, traditionally on paper and digitally on a tablet equipped with a software application, measured in confined spaces using the 3M Clean-Trace Luminometer device. METHODS: In order for the participants to complete the orthodontic anamnesis-consent forms, two separate identical cabins with standard flat surfaces were prepared. In the first cabin, the participants conventionally completed these forms on paper (conventional group), while in the second cabin, the other group used a tablet equipped with a software program for this purpose (digital group). After the form completion process, surface pollution of the predetermined areas was measured in both cabins using a 3M Clean-Trace Luminometer device. RESULTS: Surface contamination was found to be statistically significantly higher in all measurement areas in the conventional group than in the digital group. Despite a statistically significant difference between the two groups in relation to the measurements performed using the pens (conventional or electronic), this was not as strong as those found for the remaining surfaces. CONCLUSION: The completion of orthodontic anamnesis-consent forms over tablets significantly reduced surface contamination in the close environment. This study reflects the importance of digitization – which has become beneficial in many fields – in reducing the spread of infections. [ABSTRACT FROM AUTHOR]

In this note, we describe a method to calibrate a flatbed scanner to perform traceable paper sample area measurements. Also a detailed uncertainty analysis is presented. The achieved relative uncertainty at the 95% confidence level of the area measurement is under 0.1%. Described calibration procedures can also be used in other applications where dimensional measurements are performed with a flatbed scanner. [ABSTRACT FROM AUTHOR]

Iron gall Inks corrosion causes paper degradation (browning, embrittlement) and treatments were developed to tackle this issue. They often include resizing with gelatin to reinforce the paper and its cellulosic fibers (of diameter approx. 10 µm). This work aimed at measuring the distribution of ink components at the scale of individual paper fibers so as to give a better understanding of the impact of gelatin (re-)sizing on iron gall ink corrosion. For this purpose, scanning transmission X-ray microscopy (STXM) was used at the Canadian light source synchrotron (CLS, Saskatoon). This technique combines nano-scale mapping (resolution of 30 nm) and near edge X-ray absorption fine structure (NEXAFS) analysis. Fe L-edge measurements enabled to map iron distribution and to locate iron(II) and iron(III) rich areas. N K-edge measurement made it possible to map gelatin distribution. C K-edge measurements allowed mapping and discrimination of cellulose, gallic acid, iron gall ink precipitate and gelatin. Three fibers were studied: an inked fiber with no size, a sized fiber that was afterwards inked and an inked fiber sprayed with gelatin. Analysis of gelatin and ink ingredients distribution indicated a lower amount of iron inside the treated cellulosic fiber, which may explain the beneficial effect of gelatin on iron gall ink corrosion. [ABSTRACT FROM AUTHOR]

Abstract: A method is described for the simultaneous calibration of online grammage and moisture measurement by applying machine reel sampling and traceable sample area measurement. The area measurement is based on a flatbed scanner and image analysis. It is demonstrated that a relative uncertainty of 0.5% can be achieved in dry grammage calibration at the 95% confidence level. The determination of grammage and moisture were performed by applying the EN ISO 536 and the EN ISO 287 standards, respectively. The described technique can also be applied with the calibrations performed for the paper industry. [Copyright &y& Elsevier]

This paper focuses on the characterization of radio propagation, and data communication in a marine environment. More specifically, we consider signal propagation when three different sub-gigahertz industrial, scientific, and medical (ISM) bands, i.e., 169 MHz, 434 MHz, and 868 MHz, are used. The main focus of the paper is to evaluate the path loss (PL), i.e., the power loss that a propagation radio wave would experience when communication occurs between a sail boat and a buoy. We describe the measurement results obtained performing three different radio power measurement campaigns, at the three different aforementioned ISM sub-gigahertz bands. We also want to correlate the radio propagation quality with the weather conditions present in the measurement areas. The obtained results show that higher distances are achieved by transmitting at lower frequencies, i.e., 169 MHz, and, on average, the propagation is directly dependent from the dew point index. [ABSTRACT FROM AUTHOR]

Imaging disdrometers are widely used in field campaigns to provide information on the shape of hydrometeors, together with the diameter and the fall velocity, which can be used to derive information on the shape–size relations of hydrometeors. However, due to their higher price compared to laser disdrometers, their use is limited to scientific research purposes. The 3D stereo (3DS) is a commercial imaging disdrometer recently made available by Thies Clima and on which there are currently no scientific studies in the literature. The most innovative feature of the 3DS is its ability in capturing images of the particles passing through the measurement volume, crucial to provide an accurate classification of hydrometeors based on information about their shape, especially in the case of solid precipitation. In this paper. the performance of the new device is analyzed by comparing 3DS with the Laser Precipitation Monitor (LPM) from the same manufacturer, which is a known laser disdrometer used in many research works. The data used in this paper were obtained from measurements of the two instruments carried out at the Casale Calore site in L'Aquila during the CORE-LAQ (Combined Observations of Radar Experiments in L'Aquila) campaign. The objective of the comparison analysis is to analyze the differences between the two disdrometers in terms of hydrometeor classification, number and falling speed of particles, precipitation intensity, and total cumulative precipitation on an event basis. As regards the classification of precipitation, the two instruments are in excellent agreement in identifying rain and snow; greater differences are observed in the case of particles in mixed phase (rain and snow) or frozen phase (hail). Due to the different measurement area of the two disdrometers, the 3DS generally detects more particles than the LPM. The performance differences also depend on the size of the hydrometeors and are more significant in the case of small particles, i.e., D < 1 mm. In the case of rain events, the two instruments are in agreement with respect to the terminal velocity in still air predicted by the Gunn and Kinzer model for drops with a diameter of less than 3 mm, while, for larger particles, terminal velocity is underestimated by both the disdrometers. The agreement between the two instruments in terms of total cumulative precipitation per event is very good. Regarding the 3DS ability to capture images of hydrometeors, the raw data provide, each minute, from one to four images of single particles and information on their size and type. Their number and coarse resolution make them suitable to support only qualitative analysis of the shape of precipitating particles. [ABSTRACT FROM AUTHOR]

Compared with aeromagnetic total-field data, aeromagnetic vertical gradient field data contain less low-frequency information. In this paper, a continuation conversion filtering algorithm is proposed to filter out part of the low-frequency information of the aeromagnetic total-field data so that these data can be better compared with the total-field data obtained from aeromagnetic gradient data conversion. We discuss the feasibility of single aeromagnetic vertical gradient measurement in areas where it is inconvenient to erect base stations. We design a simple model and a complex model with a background field and random noise to analyze the conversion effect. The model analysis shows that the effect of applying the algorithm depends heavily on the selection of upward continuation height. The magnetization intensity of the background field also affects the selection of continuation height. When the magnetization intensity of the background field is weak, the continuation height chosen is the same as the buried depth of the background field. If the magnetization intensity of the background field is strong, then the higher the continuation height, the better the effect will be. The conclusion of the model analysis is applied to the analysis of the measured aeromagnetic data. In addition, we can conclude that the effect on total-field data of conversion by the continuation conversion filtering algorithm is better than that of conversion from the aeromagnetic vertical gradient data. [ABSTRACT FROM AUTHOR]

Obtaining accurate and timely crop area information is crucial for crop yield estimates and food security. Because most existing crop mapping models based on remote sensing data have poor generalizability, they cannot be rapidly deployed for crop identification tasks in different regions. Based on a priori knowledge of phenology, we designed an off-center Bayesian deep learning remote sensing crop classification method that can highlight phenological features, combined with an attention mechanism and residual connectivity. In this paper, we first optimize the input image and input features based on a phenology analysis. Then, a convolutional neural network (CNN), recurrent neural network (RNN), and random forest classifier (RFC) were built based on farm data in northeastern Inner Mongolia and applied to perform comparisons with the method proposed here. Then, classification tests were performed on soybean, maize, and rice from four measurement areas in northeastern China to verify the accuracy of the above methods. To further explore the reliability of the method proposed in this paper, an uncertainty analysis was conducted by Bayesian deep learning to analyze the model's learning process and model structure for interpretability. Finally, statistical data collected in Suibin County, Heilongjiang Province, over many years, and Shandong Province in 2020 were used as reference data to verify the applicability of the methods. The experimental results show that the classification accuracy of the three crops reached 90.73% overall and the average F1 and IOU were 89.57% and 81.48%, respectively. Furthermore, the proposed method can be directly applied to crop area estimations in different years in other regions based on its good correlation with official statistics. [ABSTRACT FROM AUTHOR]

It is of great scientific and practical value to use effective technical means to monitor and warn the structural damage of bridges in real time and for a long time. Traditional image recognition network models are often limited by the lack of on-site images. In order to solve the problem of automatic recognition and parameter acquisition in digital images of bridge structures in the absence of data information, this paper proposes an automatic identification method for bridge structure damage areas based on digital images, which effectively achieves contour carving and quantitative characterization of bridge structure damage areas. Firstly, the digital image features of the bridge structure damage area are defined. By making full use of the feature that the pixel value of the damaged area is obviously different from that of the surrounding image, an image pre-processing method of the structure damaged area that can effectively improve the quality of the field shot image is proposed. Then, an improved Ostu method is proposed to organically fuse the global and local threshold features of the image to achieve the damaged area contour carving of the bridge structure surface image. The scale of damage area, the proportion of damage area and the calculation rule of damage area orientation are constructed. The key inspection and characteristic parameter diagnosis of bridge structure damage area are realized. Finally, test and analysis are carried out in combination with an actual project case. The results show that the method proposed in this paper is feasible and stable, which can improve the damage area measurement accuracy of the current bridge structure. The method can provide more data support for the detection and maintenance of the bridge structure. [ABSTRACT FROM AUTHOR]

For users of Precise Point Positioning (PPP), Multi-GNSS Advanced Orbit and Clock Augmentation PPP signals provide corrective data. When using the PPP approach and/or PPP-Ambiguity Resolution (AR) method, the QZSS signal provides globally applicable error corrections on satellite orbit, clock offset, and code/phase biases. In addition, from FY2024, as a part of the MADOCA-PPP technology demonstration, wide-area ionospheric correction data will be provided for the Asia-Oceania region. A software estimator of precise satellite information developed by JAXA, Multi-GNSS Advanced Demonstration Tool for Orbit and Clock Analysis (MADOCA), allows u-blox CO99-ZED-F9P and MSJ 3008-GM4-QZS utilizing MADOCA-PPP to be used in GNSS applications that need sub-decimetre precision but don't have to be expensive. Errors caused by positioning satellites are computed by using observation data from domestic and overseas GNSS monitoring station networks such as IGS and MIRAI, and obtained correction data is transmitted from QZSS signal to provide highly precise positioning augmentation services that can be used in the Asia-Oceania Region. Users may utilize the PPP technique for high-precision locating by employing a GNSS receiver that supports the QZSS signals. This paper describes an experiment carried out with the static method to combine GPS, GLONASS, and QZSS signals in the project site (ISHI, USUD and MIZU stations in Japan). This paper examines the GPS/GLONASS/QZSS obtainable accuracy. These obtained results indicate that integrating GPS system with GLONASS and QZSS is favoured for surveying applications. It appears that integrating GPS/GLONASS/QZSS (MADOCA precise ephemeris file) static measurements in the study area between 0-4 millimetres accuracy can be guaranteed on all occasions. [ABSTRACT FROM AUTHOR]

Accurate fish size measurement in breeding areas is crucial for the fishing industry. Unlike acoustic methods with high equipment cost and low measurement accuracy, current image‐based methods offer a promising alternative. However, these image‐based methods still face challenges in selecting measurement points. To address this issue and achieve precise measurements of individual fish, this paper introduces an automatic fish size measurement method based on key point detection. We established a Fish‐Keypoints dataset and utilized deep learning techniques for the detection of fish and their key points. Using a binocular camera system, we reconstruct a three‐dimensional coordinate system to measure key points at the fish's head and tail, facilitating fish length calculation. The detection model achieves an accuracy of 85.1% in key point detection. The proposed method is tested in both land and underwater environments, demonstrating a relative measurement error of approximately 7% for fish in pools. This confirms the proposed method's ability to accurately detect measurement points, offering superior accuracy compared to other methods. [ABSTRACT FROM AUTHOR]

This paper discusses the challenges in accurately measuring the far-field performance of array antennas, which have become more complex and larger due to recent trends in increasing the number of elements and the antenna size. The far-field measurement method, which is a general method for measuring a radiation pattern in a far-field, is difficult to be utilized at a high frequency due to limitations in physical chamber size and difficulty in diagnosing an antenna. In order to improve these problems, a near-field measurement method is used as an alternative. Even though using a near-field measurement, the accuracy of the derived far-field pattern is reduced at low elevation angles due to zero-padding of data outside the measurement area. The integration of the near-field measurement with the source reconstruction is a promising approach to enhance the measurement limits of the far-field pattern analysis. This paper aims to extend the previous work to accurately predict the far-field radiation pattern, especially in the low elevation angles. The verification of the proposed method is performed for a standard gain horn and 4 by 4 patch array antennas, with and without beam steering. [ABSTRACT FROM AUTHOR]

Urban site analysis includes tangible factors such as the physical site features and intangible factors as the sensory site features like odors affect the inhabited area in the site. Environmental and chemical studies have much greater attention and studies to the odor effects in urban areas than urban designers. This paper aims to provide a validated and applicable method for urban designers in odor measurement. The objective of this research is to present the various methods of measuring odors adopted in chemical and environmental studies to achieve an applicable odor measurement method in the urban design field. The odor measurement tools are usually dedicated to measuring odor concentration at the odor source or at the receptor location that are used in chemical and environmental studies. However, in urban design studies the odor measurement could be performed using a method called citizen science considering the FIDOL factor to evaluate the odor nuisance including odor frequency, intensity, duration, offensiveness, location, and hedonic tone. This research conducts a case study in Tripoli city and determines Tripoli landfill as a significant odor source that affects people in their inhabited areas. A questionnaire was distributed in the affected area by the odor source, and the respondents of the inhabitants ensured that the summer season is the most season that they can feel the odor in their places associated with the wind direction. The results ensure that the citizen science method in measuring odors is validated, applicable, and available for urban designers to detect and estimate the affected area by odor source. [ABSTRACT FROM AUTHOR]

The designed MYRRHA reactor, in its subcritical version, will be equipped with a set of detectors monitoring its condition by measuring the current value of negative reactivity, which is a crucial parameter for its safe operation. In subcritical systems, accurate and precise measurement of negative reactivity is disturbed by the so-called spatial effect, i.e., the response of detectors depends on their placement in the reactor core. This paper focuses on the Monte Carlo simulations of reactivity measurements using the area method for natU, 238U, 241Am, 239Pu, and 232Th detectors. The simulations were performed in six positions with increasing distance from the center of the core and at three axial levels. The obtained results allow for selecting optimum locations for detectors and detector nuclides in terms of the accuracy of reactivity measurement and illustrate the dependence of the reactivity on the distance. Additionally, the possibility of using 103Rh in self-powered neutron detectors was investigated. The influence of spatial effect in calculations using the area method was directly indicated in the MYRRHA reactor core for chosen isotopes and in-core positions. The results closest to true values were obtained for the second fuel assembly for 239Pu, and the third fuel assembly for natU, 238U, 232Th, and 241Am; thus, these nuclides and positions should be preferred when selecting detectors for MYRRHA. [ABSTRACT FROM AUTHOR]

Purpose: Considering the industrial site environment and installation requirements, the straight-beam ultrasound probe with easy installation and good coupling agent adaptability is adopted to replace the traditional water immersion focusing probe for film thickness measurement in cylindrical roller bearings. The straight-beam probe has a large echo receiving range, which will result in measurement regions overlapping and bring about large measurement errors. In this paper, an improved measurement method for film thickness of cylindrical roller bearing with the straight-beam probe is developed. Design/methodology/approach: An improved method is proposed to enhance the spatial resolution of the straight-beam probe. By introducing a correction coefficient based on the percentage of the effective measurement area, the method improves the measuring accuracy successfully. Findings: The experimental results demonstrate that the lubricant-film thickness can be measured to reasonable accuracy by this method and have a better agreement with the theoretical film thickness solutions. Originality/value: This paper used analytical method and model that is helpful for the improvement of the spatial resolution, which has great influence on the measuring accuracy, is mainly determined by the echo reflection area size of the ultrasound transducer. [ABSTRACT FROM AUTHOR]

The energy crisis is a problem that countries all over the world pay more and more attention to, and a series of ecological problems caused by it have become increasingly prominent. It is difficult for traditional fossil fuels to maintain a healthy and coordinated sustainable development of society and economy. The establishment of a sustainable energy system has become the development trend of various countries to solve energy problems. Electric energy is a secondary energy that all primary energy can be converted into, and an irreplaceable consumable for all industrial technologies and people's lives. Electric power data has the characteristics of large rate span, numerous data sources, complicated interaction methods, and various types of data. The existence of abnormal data in the power system will greatly reduce the accuracy of the system state estimation and the state estimation convergence rate. This paper introduces the power grid industrial control system, combines the data flow of power big data, and analyzes the abnormal information detection process in detail. It takes the data stream acquired by the acquisition unit PMU of the wide area measurement system as the research object. The rapid development of the Hadoop big data platform provides important technical support for the research of power grid big data. Based on the Hadoop platform, the clustering algorithm is used to complete the anomaly detection of real-time data. The LOF algorithm has poor performance when dealing with a large amount of high-dimensional data, and has high time and space complexity. In order to make up for the shortcomings of the LOF algorithm, this paper uses the K-means clustering algorithm to propose an improved algorithm K-LOF of the density-based local abnormal factor detection algorithm LOF, and optimizes the neighborhood query process. It is verified by experiments that the K-LOF algorithm can effectively reduce the time complexity of the anomaly detection algorithm and improve the detection accuracy by 2–4.2%. [ABSTRACT FROM AUTHOR]

This paper presents a fault detection and identification system for power systems using an artificial neural network approach while discussing its advantages and disadvantages. The initial data for the proposed technique are a set of simulated post-fault bus voltages and currents obtained at a sampling rate which emulates a complete phasor measurement unit (PMU)-based wide area measurement system (WAMS). Several types of faults are considered, such as short circuits and line and load contingencies. All fault and steady-state simulations have been performed on MATLAB using the Power System Toolbox. The artificial neural network was designed using an architecture proper for pattern recognition with supervised learning. As a result, satisfactory predictions within short time periods are obtained. The test system used in all simulations is the IEEE 39-Bus New England Power System, which has 10 generation units, 21 loads, and three distinct areas alongside transient and sub transient models, with PMUs distributed over up to 14 buses. Future works are also discussed in this paper, showing the possibilities for feature engineering in this type of problem, as well as the application of other machine learning and data analytics techniques for PMU-based WAMS databases. [ABSTRACT FROM AUTHOR]

Slope has an important effect on the runoff production process. Slope correction of runoff curve number in the SCS-CN runoff production model is important to improve the model prediction accuracy, In order to conduct an investigation of the effect of average watershed slope in the runoff production process, in this paper, based on Huang's slope modification formula, the first 40 out of 70 rainfall runoff measurements in the study area from 1955 to 1981 were used as the validation data, and a1 and a2 parameters in Huang's slope modification formula were re-determined, so as to propose the slope modification formula of the CN value for the study area under three different antecedent moisture conditions, and then the SCS-WJG method, which is of good applicability to the region, was established and compared to the SCS-CN look-up table method, and the SCS-Huang method, which is a direct transfer of the Huang's slope modification formula. The conclusion is as follows: the λ-value of the initial rainfall loss rate determined using the ergodic method is 0.09, so the standard value of 0.2 is not applicable to the study area. After comparing the size of the CN values obtained by the three methods, it is found that the CN value obtained by the SCS-Huang method is the largest, followed by the SCS-CN look-up table method, and the smallest is obtained by the SCS-WJG method, so the CN value obtained by the SCS-WJG method is more suitable for the study area as shown in the simulation results. Comparison of the SCS-CN lookup table method and the SCS-Huang method reveals that the NSE of the SCS-Huang method is lower and the RMSE is higher; therefore, it is necessary to propose a slope correction formula for the CN value applicable to the study area and establish the SCS-WJG method. When λ = 0.09, the NSE of the SCS-CN lookup table method, and the SCS-Huang method are -2.85 and -3.25, respectively, while the NSE of the SCS-WJG method is increased to 0.86, and the RMSE of the SCS-WJG method is reduced by 77%, and 78%, respectively, compared with the first two methods. The simulation accuracy of the SCS-WJG method is significantly better than that of the remaining two methods, indicating that the SCS-WJG method has good regional applicability and can provide a reference for the simulation of runoff production in small watersheds. [ABSTRACT FROM AUTHOR]

In the first part of this paper, a free-form surface matching method called variance-minimization matching (VMM) was proposed to address uneven/open point distributions and measuring noise. The convergence property and sensitivity to measuring defects were theoretically studied. In the second part of this paper, a series of experiments are presented to verify the feasibility of the proposed method in free-form surface matching. The experiments are divided into four sets: a measuring defects experiment, a noise experiment, a convergence experiment, and an artificial experiment. In the first set of experiments, the existing methods are prone to becoming trapped in a local optimum affected by uneven/open point distributions, which shows that measured points incline toward dense areas. However, in VMM, there is little inclination regardless of the increase in the number of measuring defects. In the second set of experiments, sensitivity to varying noise is tested. The results show that VMM helps prevent unstable sliding in the presence of Gaussian noise. In the third set of experiments, we compare convergence speed and convergence stability under different initial positions. It is verified that VMM exhibits the quadratic convergence. Finally, a set of artificial experiments is implemented, revealing that the proposed method is appropriate for use in automated manufacturing processes such as geometric inspection and allowance distribution. Note to Practitioners—Measuring defects usually occur when using a scanning device to obtain the measured points of a workpiece. Weakening the effect of measuring defects on matching results is critical to promoting manufacturing automation. This paper proposes a new method called variance-minimization matching (VMM) that considers measuring defects. In the first part of this paper, the modeling and theoretical analysis of VMM were introduced. In the second part of this paper, simulated experiments are performed to verify the feasibility of VMM in addressing uneven/open point distributions, measuring noise, and large initial positions. Next, artificial experiments employing VMM in geometric inspection and allowance distribution are presented. The proposed method also applies to other automated manufacturing processes, such as workpiece localization, deformation analysis, and complex parts repair. [ABSTRACT FROM AUTHOR]

Introduction: Leaves are important organs for photosynthesis in plants, and the restriction of leaf growth is among the earliest visible effects under abiotic stress such as nutrient deficiency. Rapidly and accurately monitoring plant leaf area is of great importance in understanding plant growth status in modern agricultural production. Method: In this paper, an image processing-based non-destructive monitoring device that includes an image acquisition device and image process deep learning net for acquiring Brassica napus (rapeseed) leaf area is proposed. A total of 1,080 rapeseed leaf image areas from five nutrient amendment treatments were continuously collected using the automatic leaf acquisition device and the commonly used area measurement methods (manual and stretching methods). Results: The average error rate of the manual method is 12.12%, the average error rate of the stretching method is 5.63%, and the average error rate of the splint method is 0.65%. The accuracy of the automatic leaf acquisition device was improved by 11.47% and 4.98% compared with the manual and stretching methods, respectively, and had the advantages of speed and automation. Experiments on the effects of the manual method, stretching method, and splinting method on the growth of rapeseed are conducted, and the growth rate of rapeseed leaves under the stretching method treatment is considerably greater than that of the normal treatment rapeseed. Discussion: The growth rate of leaves under the splinting method treatment was less than that of the normal rapeseed treatment. The mean intersection over union (mIoU) of the UNet-Attention model reached 90%, and the splint method had higher prediction accuracy with little influence on rapeseed. [ABSTRACT FROM AUTHOR]

The paper analyzes the modern methods of storing spent nuclear fuel and its processing, taking into account the finding of fuel in spent fuel assemblies. Currently, the most common methods involve storage in containers for fuel assemblies filled with a substance that has a high thermal conductivity. Therefore, experimental methods of researching the storage properties of spent fuel assemblies in containers are promising. In the work, research was carried out in the indicated directions with the help of the created experimental stand. A description of the stand itself and the sequence of conducting the experiment are given, as a result of which the necessary experimental data should be obtained. Namely, the heating regimes in the experimental heater were determined, which are close to the real processes of heating spent fuel assemblies loaded into the container. For this purpose, a laboratory autotransformer with a capacity of 4.6 kW was used. The next task was to determine the time required for the heater to go into constant operation. For this purpose, the concept of constant time of the heating process was introduced. FLIR ONE thermal imager was used to determine this parameter, as well as devices that allowed to determine the voltage on the laboratory autotransformer. This made it possible to determine the dependence of the change in the temperature of the heater on time and voltage, as well as the voltage of the heater, which simulates real heating modes. The paper presents the thermographic results of thermal imager measurement of the main areas of the stand. Taking into account that the power of the heater should be about 1.5 kW, the stand was made airtight with pressure control and taking into account the real conditions of storage of spent fuel assemblies, where there may be damage and cracks in the container. As a result of the conducted experimental studies, the optimal heating modes of the heater were determined. [ABSTRACT FROM AUTHOR]

Carry Select Adder (CSLA) is an essentially utilized adder on account of its higher computational speed. CSLA is utilized in the space of incorporation frameworks. This paper proposes a CSLA design by carrying out the Logic Optimization Technique (ZFCLOT) using Zero Finding Logic contrasted with ordinary Zero Finding Logic (ZFC). This paper notices the different presentation measurements like area, power, delay, area delay product (ADP), power delay product (PDP) and effectiveness. Approval of the ZFCLOT put together CSLA is displayed with respect to Cadence stage utilizing 45 nm platform. The presented CSLA utilizing ZFCLOT has shown advanced execution measurements, explicitly, region and power improvement of 47.287% and 49.1%, separately contrasted with the current standard plans. [ABSTRACT FROM AUTHOR]

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With the development of science and technology, it brings more possibilities for artistic space design method innovation. The development of computer image data acquisition technology has realized the continuous extension of artistic space design and creation. Based on the computer image data collection technology, this paper realizes the innovative design of real and virtual environment in the exhibition of art space, centering on the interactive integration of the three elements of "human-objects-space." Through the experimental design, from the space, color data collection, display space moving line, and space function design scheme were the four aspects of exploration and analysis. Compared with traditional design methods, the following conclusions are drawn: first, in spatial data acquisition, the average error of area measurement is less than 3.63%, and the measurement accuracy can reach more than 91%. Second, the average accuracy of color detection of various materials in space can be maintained at 90%. Third, the spatial movement line designed in this paper is simple and clear, with appropriate length, so that visitors can achieve the best visiting effect with the smallest distance. Fourth, the overall design scheme is reasonable, the space is transparent and bright, and the tour route is clear. It can complete the functional zoning design of the art exhibition space in a short time, saving a lot of manpower and time. [ABSTRACT FROM AUTHOR]

This paper deals with the detection of small magnetization using a thin film magneto-impedance sensor with subjecting to strong normal field. The sensor was made by soft magnetic amorphous thin-film with uniaxial magnetic anisotropy in the width direction of the element. It was reported that the sensor has very high sensitivity, such as pico-tesla order, when it is driven by hundreds of MHz. In this paper, a sensitive measurement method aiming for detection of a small particle or a cluster of nano-particles, having low-remanence, is proposed. The point is the application of strong normal field in the measurement area including sensor element and particle. The normal strong field is applied in the normal direction of the sensor plane in the value almost hundreds of mT. Instead of such strong normal field, the sensor keeps high sensitivity, because of the demagnetizing force in the thickness direction. A theoretical estimation for clarifying an efficiency of the method, experimental results of sensor property and sensitivity with subjecting to the normal field, and also a confirmation of detection of a small particle using the proposed method is reported. As a special mention, detection fundamentals when a applied surface normal field has a distribution and also a particle would run through in the vicinity of sensor is discussed. [ABSTRACT FROM AUTHOR]

This paper proposes an improved solution for the calibration of multi-camera line structured light vision systems, which is aimed at the problem of discontinuity or even faults in the overlapping area of measurement in the coordinate system. First, the two-dimensional target is placed in different poses in the overlapping area of two adjacent cameras, to obtain the initial matching matrix of the adjacent camera coordinate system. Then, an optimization objective function is constructed to optimize the internal and external parameters of the camera based on the characteristics of the ring-shaped measurement field itself, to achieve the best matching of the overlapping area. The experimental results show that, compared to the traditional matching method, the method proposed in this paper reduces the matching error of adjacent cameras by about 66.2 % , the accumulated error is reduced by about 91.8 % , and the overall measurement accuracy is improved by 4.5 times. [ABSTRACT FROM AUTHOR]

Purpose: Women's empowerment remains a key development challenge in Kenya. The purpose of this study is to attempt to understand the status of women's empowerment and the key contributors to their disempowerment in Kenya's aquaculture sector. Design/methodology/approach: A cross-sectional survey was conducted on 534 male and female fish farmers from 300 households drawn from six counties in Kenya (Kakamega, Kisumu, Kisii, Kiambu, Meru and Nyeri). The Abbreviated Women's Empowerment in Agriculture Index (A-WEAI) was adapted to Abbreviated Women's Empowerment in Fisheries and Aquaculture Index (A-WEFI) to suit the aquaculture and fisheries sub-sector. The adapted A-WEFI was then used to estimate and the status of women's and men's using five domains of empowerment (5DE) and a gender parity index (GPI). Data were analysed using descriptive statistics, Cramer's V and sensitivity analysis as test statistics. Findings: About 86% of the men and 80% of the women were classified as empowered. The mean score of the 5DE was 0.93 and 0.95 for women and men, respectively. In addition, 82% of the households achieved gender parity, suggesting that for such households, empowerment of men was no greater than that of women. Overall, the results suggest no major differences between the empowerment of women and men. Findings suggest areas of improvement in empowerment: when observed separately, women report lack of agency in production, resource, time-use and allocation and leadership. Originality/value: This paper adapts the A-WEAI to the fisheries and aquaculture context, in bid to bridge the gap in standard women's empowerment measurement methods in this area. Also, there are limited empirical studies on the multifaceted empowerment of women in aquaculture in Kenya. The findings are meant to serve as a point of reference for policymakers, as they develop gender-responsive intervention programmes, and in implementing gender mainstreaming in Kenya. [ABSTRACT FROM AUTHOR]

When evaluating an area's seismic risk or resilience, it is necessary to use the spatial correlation to analyze the ground motion parameters of multiple sites together in an earthquake. These two large earthquakes in Türkiye provided the possibility for spatial correlation analysis of ground motion intensity measurements in this area. Based on the strong motion records provided by The Disaster and Emergency Management Authority of Türkiye (AFAD), this study uses the local ground motion prediction equation in Türkiye to give spatial correlation analysis of Intensity Measurements. This study gives an exponential model based on a semivariogram and compares it with the correlation model obtained from previous studies. [ABSTRACT FROM AUTHOR]

This paper presents a system integration of a sense-based user interface (SUI) platform, comprised of flexible pressure and humidity sensor arrays with a commercial inertial measurement unit (IMU), to analyze behavioral patterns of young children. The pressure sensors utilize a sensor array created using flexible inkjet printing, with each sensor using a piezoresistive sensing layer. The humidity sensors employ an interdigitated capacitive sensor based on a polyimide humidity-sensitive layer and are also manufactured using the flexible inkjet printing technique. To achieve a wide measurement area, both the pressure and humidity sensors are expanded into 5 × 5 and 5 × 10 sensor arrays, respectively. Also, commercial IMU, including accelerometer/gyroscope sensors, is employed. Finally, the SUI platform is in the form of a cuboidal block model, with an IMU and circuits embedded within the block. Multilayered pressure and humidity sensor arrays are installed on the external surface of the block. Collected data from each sensor are visualized through heatmaps and 3D motion representation to create a platform that integrates fine-grained behavior as well as global behavior information of young children. This research would provide a foundation for the development of SUI technology, especially aimed at individuals who have difficulty with conventional forms of input–output devices. [ABSTRACT FROM AUTHOR]

The paper presents new approaches and principles for identifying the conditions of stability disturbance based on detecting dangerous disturbances in the early stages using information about changes in regime parameters and their Rate of Change. As a mode parameter, the mutual voltage angle between the controlled 500 kV substation and its Rate of Change was selected in the study. It is suggested to take the values of the mentioned parameters from the Wide Area Measurements System (WAMS). The relevance of the research is due to the need to improve the efficiency and eliminate the drawbacks of existing revealing devices of regime automatics, which will reduce the number of accidents due to disturbances of the power system stability. The proposed principle of predicting stability violation is based on using the provision of Lyapunov’s stability theory, according to which the assessment of stability is carried out by the total system energy consisting of kinetic and potential. In contrast to the existing principles of detecting stability violation, where the exit from the stability area is determined by the main parameter (potential energy), the prediction principle allows evaluating stability by its rate of change (kinetic energy), which provides the early detection of stability disturbance. Calculations were performed on modeling power surges in the North-South interconnection of the Kazakhstan Unified Energy System in the «DigSILENT Power Factory» software on the model, which was verified by real perturbations in the power system according to the WAMS data. The calculations confirmed the effectiveness of the proposed principles and the possibility of using WAMS data for detecting emergency power surges on transit power networks in the initial stage. [ABSTRACT FROM AUTHOR]

This paper studies the composition in portrait paintings and develops an algorithm to improve the composition of portrait photographs based on example portrait paintings. A study of portrait paintings shows that the placement of the face and the figure is pose-related. Based on this observation, this paper develops an algorithm to improve the composition of a portrait photograph by learning the placement of the face and the figure from an example portrait painting. This example portrait painting is selected based on the similarity of its figure pose to that of the input photograph. This similarity measure is modeled as a graph matching problem. Finally, space cropping is performed using an optimization function to assign a similar location for each body part of the figure in the photograph with that of the figure in the example portrait painting. The experimental results demonstrate the effectiveness of the proposed method. A user study shows that the proposed pose-based composition improvement is preferred more than rule-based methods and learning-based methods. [ABSTRACT FROM AUTHOR]

The automated measurement mode in the lidar measurement system (LMS) has advantages unmatched by other measurement equipment in measuring the surface of large components. Before starting the automatic measurement mode, it is necessary to plan the measurement guide points for the measurement area. The rationality of the measurement points planning will directly affect the quality of the measurement data and the measurement efficiency. This paper proposes a planning method for measurement points on the outer surface of components based on lidar automatic measurement technology. First, the geometric features to be measured are discretized into spatial point cloud data. Second, the edge points of the point clouds are extracted and indented to meet the measurement requirements, which improves the measurement accuracy of the edge areas. Finally, by planning the path of the measurement points, the laser beam of the lidar can traverse the points of the measurement features with the shortest paths. Through the analysis of two cases, the method proposed in this paper will provide a huge advantage for the LMS: (1) The edge points of all features can be identified and indented in a short time to ensure the measurement accuracy of the edge areas of each measurement feature. (2) Through the measurement path planning, the repetitive measurement path of the lidar can be significantly reduced, improving the measurement efficiency. The method proposed in this paper has important guiding significance for the subsequent measurement station planning and constructing large-scale spatial measurement fields of the LMS. [ABSTRACT FROM AUTHOR]

Accurately evaluating the fault type and location is important for ensuring the reliability of the power distribution network. A mushrooming number of distributed generations (DGs) connected to the distribution system brings challenges to traditional fault classification and location methods. Novel AI-based methods are mostly based on wide area measurement with the assistance of intelligent devices, whose economic cost is somewhat high. This paper develops a super-resolution (SR) and graph neural network (GNN) based method for fault classification and location in the power distribution network. It can accurately evaluate the fault type and location only by obtaining the measurements of some key buses in the distribution network, which reduces the construction cost of the distribution system. The IEEE 37 Bus system is used for testing the proposed method and verifying its effectiveness. In addition, further experiments show that the proposed method has a certain anti-noise capability and is robust to fault resistance change, distribution network reconfiguration, and distributed power access. [ABSTRACT FROM AUTHOR]

Measuring the vibrating states of an artificial structure is an important approach to monitor the stability of the structure. However, the existing radar vibration measurement methods do not have enough azimuth resolution for measuring the vibrations in a relatively large scene, which contains multiple buildings or a large building. For such application scene, this paper proposes a vibration measurement method based on multiple-input multiple-output imaging radar system, which can achieve high azimuth resolution. Features of the proposed method are threefold: first of all, by utilizing the ability of quickly acquiring imaging data, the proposed method can achieve vibration measurement for the entire area simultaneously; second, in order to detect the positions of vibrating objects and decrease the time of vibration parameter estimation part, this paper proposes vibration similarity index to quantify the similarity between the detected signal and ideal vibration signal; at last, due to the limitations of the hardware performance, this paper adopts multiple signal classification least-squares estimation method to estimate the vibrating frequency and amplitude. To evaluate the performance of the proposed method, ideal point target simulation and vibrating calibrator experiment have been conducted, and the results show that the positions and the vibrating parameters of the vibrating objects fit well with the reference values. In addition, car experiment and bridge experiment have been carried out to verify the ability of the proposed method to measure the vibration of real artificial structures, which cannot be seen as point targets. [ABSTRACT FROM AUTHOR]

We investigate a probabilistic model for routeing in a multihop ad hoc communication network, where each user sends a message to the base station. Messages travel in hops via other users, used as relays. Their trajectories are chosen at random according to a Gibbs distribution, which favors trajectories with low interference, measured in terms of signal-to-interference ratio. This model was introduced in our earlier paper, where we expressed, in the limit of a high density of users, the typical distribution of the family of trajectories in terms of a law of large numbers. In this paper, we derive its qualitative properties. We analytically identify the emerging typical scenarios in three extreme regimes. We analyze the typical number of hops and the typical length of a hop and the deviation of the trajectory from the straight line, regime 1 in the limit of a large communication area and large distances and regime 2 in the limit of a strong interference weight. In both the regimes, the typical trajectory approaches a straight line quickly, in regime 1 with equal hop lengths. Interestingly, in regime 2, the typical length of a hop diverges logarithmically in the distance of the transmitter to the base station. We further analyze (regime 3) local and global repulsive effects of a densely populated subarea on the trajectories. [ABSTRACT FROM AUTHOR]

This paper deals with determination of uncertainty and individual contributions to the measurement uncertainty on the CMM SIOS NNM-1 instrument fitted with the touch-probe scanning system Gannen XP. Manufacturer SIOS designates this machine as nano-CMM. Two non-simulation methods to determine the measurement uncertainty, the substitution and multi-position methods are addressed in detail [Sramek, Jankovych 2018]. Ruby balls with various nominal diameters are used as the measured objects. One simulation method to determine the measurement uncertainty, the Monte Carlo method, is also addressed in this paper. The paper also summarizes and specifies calculation methods to determine the measurement uncertainty, and provides results of representative sets of measurements, including determination of the expanded measurement uncertainty. This paper contains novel conclusions in the area of uncertainty measurement of nano-CMMs. [ABSTRACT FROM AUTHOR]

In this paper, we provide a novel framework to assess the vulnerability/robustness of a network with respect to pair-wise nodes’ connectivity. In particular, we consider attackers that aim, at the same time, at dealing the maximum possible damage to the network in terms of the residual connectivity after the attack and at keeping the cost of the attack (e.g., the number of attacked nodes) at a minimum. Differently from the previous literature, we consider the attacker perspective using a multiobjective formulation and, rather than making hypotheses on the mindset of the attacker in terms of a particular tradeoff between the objectives, we consider the entire Pareto front of nondominated solutions. Based on that, we define novel global and local robustness/vulnerability indicators and we show that such indices can be the base for the implementation of effective protection strategies. Specifically, we propose two different problem formulations and we assess their performances. We conclude this paper by analyzing, as case studies, the IEEE118 power network and the U.S. Airline Network as it was in 1997, comparing the proposed approach against centrality measures. [ABSTRACT FROM AUTHOR]

State estimation has a special role in the real-time control and monitoring of smart distribution networks. State estimation process is typically based on network topology and measurements sent from meters. Employing an accurate state estimation algorithm as well as transferring high volumes of measurements are serious challenges in large scale grids. In this paper, compressive sensing is used to reduce the measurement data volume, before transmission, to alleviate problems such as lack of storage space, interference and delay. In this paper, a modified extended Kalman filter algorithm is proposed which estimates states from compressed data directly without applying the reconstruction procedure. The main differences between the proposed method and EKF are the network dynamic modeling approach and the states correction mechanism. The IEEE 33-node distribution network with two DGs is employed to illustrate the effective performance of the proposed method. Results show that the states of the test feeder are accurately estimated even with only 50% compressed measurements. [ABSTRACT FROM AUTHOR]

With the development of smart meters and other intelligent electronic devices, more and more data‐driven fault location methods based on wide area measurement are emerging. However, these diagnostic methods for dealing with the whole tested system often appear complex. This paper presents an innovative subsystems‐based fault location strategy in distribution grid by the sparsity promoted Bayesian learning algorithm. To avoid taking measurement for the whole distribution system, the fault‐included subsystem is selected according to the distribution characteristics of negative sequence voltage. Then the data for fault location is measured by allocating meters in subsystem, which can reduce the number of required meters. For accurately estimating the fault location, a sparse prior is proposed for the Bayesian learning, which could improve the accuracy of the fault location algorithm by about 4%. The performance is tested on a 12.66‐kV, 69‐bus distribution system in response to various fault scenarios. The results show that the accuracy of the proposed method for the fault section location can reach 90%. It also verifies the robustness and accuracy for fault line location, faced different fault types, fault resistance, noise, etc. [ABSTRACT FROM AUTHOR]