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This paper aims to reduce and eliminate the abnormal peaks which, because of the reflection in the process of laser detection, make it easier to proceed with further analysis.

To solve the above problem, an abnormal data correction algorithm based on histogram, K-Means clustering and improved robust locally weighted scatter plot smoothing (LOWESS) is put forward. The proposed algorithm does section leveling for shear plant first and then applies histogram to define the abnormal fluctuation data between the neighboring points and utilizes a K-Means clustering to eliminate the abnormal data. After that, the improved robust LOWESS method, which is based on Euclidean distance, is used to remove the noise interference and finally obtain the waveform characteristics for next data processing.

The experiment result of liner tool mark laser test data correction demonstrates the accuracy and reliability of the proposed algorithm.

The study enables the following points: the detection signal automatic leveling; abnormal data identification and demarcation using K-Means clustering and histogram; and data smoothing using LOWESS.

Radiometric calibration is a method that estimates the reflection of the target from the measured input radiation. The purpose of this study is to radiometrically calibrate three spectral bands of Sentinel-2A, including green, red and infrared. For this purpose, Landsat-8 OLI data are used. Because they have bands with the same wavelength range and they have the same structure. As a result, Landsat-8 OLI is appropriate for relative radiometric calibration.

The method used in this study is radiometric calibration uncorrected data from a sensor with corrected data from another sensor. Also, another aim of this study is a comparison between radiometric correction data and data that, in addition to radiometric correction, has been sharpened with panchromatic data. In this method, both of them have been used for radiometric calibration. Calibration coefficients have been obtained using the first-order polynomial equation.

This study showed that the corrected data has more valid answers than corrected and sharpened data. This method studied three land-cover types, including soil, water and vegetation, which it obtained the most accurate coefficients of calibration for soil class because R-square in all three bands was above 88%, and the root mean square error in all three bands was below 0.01. In the case of water and vegetation classes, only results of red and infrared bands were suitable.

For validating this method, the radiometric correction module of SNAP software was used. According to the results, the coefficient of radiometric calibration of the Landsat-8 sensor was very close to the coefficients obtained from the corrected data by SNAP.

Purpose: The main purpose of the study is to understand the factors that facilitate correction behavior among individuals. In this study the authors examine the impact of self-perceived media literacy (SPML) and reflection on participants’ correction behavior.

Methods: Data for the study were collected from Amazon's MTurk using an online survey. Data were collected after a certificate of exemption was received by the Institutional Review Board in a research university in the United States (US) Qualtrics software was used to collect data. The total number of participants was 797.

Findings: The findings show that although both SPML and reflection are positively associated with rumor refutation, higher SPML alone is not enough. Reflective judgment is critical for individuals to take part in this behavior online, such that individuals with higher reflective judgment indicated that they refute rumors online, irrespective of their SPML score.

Originality: The authors tested the relationship of multiple variables with participants correction behavior. Although research shows the importance of social correction, there is not much knowledge about what facilitates actual misinformation correction.

Automation is no longer an option; it is no longer “if” but “when” and “how”. This book has been written for senior librarians who recognise this, for their line managers to whom the detailed work has been delegated, and for the junior staff, library and clerical, who need to know not only how to operate a system, but why it works as it does.

The air data system of an aircraft includes, amongst other items, the airspeed indicator, altimeter and machmeter all of which derive their readings from measurement of air pressures. The instruments are designed on the assumption that they will be fed with pressures from the undisturbed free‐stream in which the aircraft is flying; this is not generally the case. In flight the aircraft disturbs the air mass and in doing so causes a pressure field around itself which produces the forces necessary for lift and control. The pressure sensors which detect the airstream pressures may be located within the aircraft pressure field and the pressures transmitted to the instruments may not correspond to the free‐stream pressures; if this is so then the instrument indications will be in error.

SUPERCHARGED aero engines are more or less a post‐war invasion into the practical side of aero‐engine design. The problem of power boosting for internal combustion engines, especially aero engines, has for several years engaged the attention of engine designers, with the result that to‐day quite a number of engines are produced with superchargers as an integral part of the standard equipment. Various types of superchargers have been tried, such as the reciprocating pump, Roots Blower, exhaust‐driven turbo compressor, and the gear‐driven centrifugal form of blower. The last‐named is the type most commonly used in this country at the present time.

The purpose of this paper is to propose a new conceptual framework for big data analytics (BDA) in the healthcare sector for the European Mediterranean region. The objective of this new conceptual framework is to improve the health conditions in a dynamic region characterized by the appearance of new diseases.

This study presents a new conceptual framework that could be employed in the European Mediterranean healthcare sector. Practically, this study can enhance medical services, taking smart decisions based on accurate data for healthcare and, finally, reducing the medical treatment costs, thanks to data quality control.

This research proposes a new conceptual framework for BDA in the healthcare sector that could be integrated in the European Mediterranean region. This framework introduces the big data quality (BDQ) module to filter and clean data that are provided from different European data sources. The BDQ module acts in a loop mode where bad data are redirected to their data source (e.g. European Centre for Disease Prevention and Control, university hospitals) to be corrected to improve the overall data quality in the proposed framework. Finally, clean data are directed to the BDA to take quick efficient decisions involving all the concerned stakeholders.

This study proposes a new conceptual framework for executives in the healthcare sector to improve the decision-making process, decrease operational costs, enhance management performance and save human lives.

This study focused on big data management and BDQ in the European Mediterranean healthcare sector as a broadly considered fundamental condition for the quality of medical services and conditions.

To assess the impacts of climate change on stream flow and evaluation of reservoir performances, reliability, resilience and vulnerability (RRV) indices are contemplated. Precipitation, temperature (Tmax, Tmin), relative humidity and solar radiation are the hydrological and meteorological data which have been used extensively. Climate data like RCP2.6, RCP4.5 and RCP8.5 were evaluated for the base period 1976–2005 and future climate scenario for 2021–2050 and 2051–2080 as per the convenience.

The hydrologic engineering center hydrologic modeling system (HEC-HMS) model was used to simulate the current and future inflow volume into the reservoir. The model performance resulted as 0.76 Nash-Sutcliffe efficiency (NSE), 0.78 R2 and −3.17 D and during calibration the results obtained were 0.8 NSE, 0.82 R2 and 2.1 D. The projected climate scenario illustrates an increasing trend for both maximum and minimum temperature though a decreasing trend was documented for precipitation. The average time base reliability of the reservoirs was less than 50% without reservoir condition and greater than 50% for other conditions but volumetric reliability and resilience varies between 50% and 100% for all conditions. The vulnerability result of reservoirs may face shortage of flow ranging from 5.7% to 33.8%.

Evaluating reservoir simulation and hydropower generation for different climate scenarios by HEC-ResSim model, the energy generated for upper dam ranges from 349.4 MWhr to 331.2 MWhr and 4045.82 MWhr and 3946.74 MWhr for short and long-term future scenario, respectively. RCP for Tmax and Tmin goes on increasing whereas precipitation and inflow to reservoir decreases owing to increase in evapotranspiration. Under diverse climatic conditions power production goes on varying simultaneously.

This paper is original and all the references are properly cited.

Budgeting data curation tasks in research projects is difficult. In this paper, we investigate the time spent on data curation, more specifically on cleaning and documenting quantitative data for data sharing. We develop recommendations on cost factors in research data management.

We make use of a pilot study conducted at the GESIS Data Archive for the Social Sciences in Germany between December 2016 and September 2017. During this period, data curators at GESIS - Leibniz Institute for the Social Sciences documented their working hours while cleaning and documenting data from ten quantitative survey studies. We analyse recorded times and discuss with the data curators involved in this work to identify and examine important cost factors in data curation, that is aspects that increase hours spent and factors that lead to a reduction of their work.

We identify two major drivers of time spent on data curation: The size of the data and personal information contained in the data. Learning effects can occur when data are similar, that is when they contain same variables. Important interdependencies exist between individual tasks in data curation and in connection with certain data characteristics.

The different tasks of data curation, time spent on them and interdependencies between individual steps in curation have so far not been analysed.

The purpose of this paper is to evaluate innovations in intellectual property rights (IPR) databases, techniques and software tools, with an emphasis on selected new developments and their contribution towards achieving advantages for IPR management (IPRM) and wider social benefits. Several industry buzzwords are addressed, such as IPR-linked open data (IPR LOD) databases, blockchain and IPR-related techniques, acknowledged for their contribution in moving towards artificial intelligence (AI) in IPRM.

The evaluation, following an original framework developed by the authors, is based on a literature review, web analysis and interviews carried out with some of the top experts from IPR-savvy multinational companies.

The paper presents the patent databases landscape, classifying patent offices according to the format of data provided and depicting the state-of-art in the IPR LOD. An examination of existing IPR tools shows that they are not yet fully developed, with limited usability for IPRM. After reviewing the techniques, it is clear that the current state-of-the-art is insufficient to fully address AI in IPR. Uses of blockchain in IPR show that they are yet to be fully exploited on a larger scale.

A critical analysis of IPR tools, techniques and blockchain allows for the state-of-art to be assessed, and for their current and potential value with regard to the development of the economy and wider society to be considered. The paper also provides a novel classification of patent offices and an original IPR-linked open data landscape.