Trustworthy Method Research Articles

Hybrid of the fuzzy logic controller with the harmony search algorithm to PWR in-core fuel management optimization

One of the important parts of the in-core fuel management is loading pattern optimization (LPO). The loading pattern optimization as a reasonable design of the in-core fuel management can improve both economic and safe aspects of the nuclear reactor. This work proposes the hybrid of fuzzy logic controller with harmony search algorithm (HS) for loading pattern optimization in a pressurized water reactor. The music improvisation process to find a pleasing harmony is inspiring the harmony search algorithm. In this work, the adjustment of the harmony search algorithm parameters such as the bandwidth and the pitch adjustment rate are increasing performance of the proposed algorithm which is done through a fuzzy logic controller. Hence, membership functions and fuzzy rules are designed to improve the performance of the HS algorithm and achieve optimal results. The objective of the method is finding an optimum core arrangement according to safety and economic aspects such as reduction of power peaking factor (PPF) and increase of effective multiplication factor (Keff). The proposed approach effectiveness has been tried in two cases, Michalewicz's bivariate function problem and NEACRP LWR core. The results show that by using fuzzy harmony search algorithm the value of the fitness function is improved by 15.35%. Finally, with regard to the new solutions proposed in this research it could be used as a trustworthy method for other optimization issues of engineering field.

Quantitative palaeobathymetric reconstructions based on foraminiferal proxies: a case study from the Neogene of south‐west Spain

AbstractQuantitative palaeobathymetric reconstructions based on foraminiferal proxies have been used in a wide variety of geological studies on tectonic, climatic and environmental changes in sedimentary basins. However, palaeo‐water‐depth estimates are frequently biased due to taphonomic processes (dissolution, transport) as well as local conditions (primary productivity, oxygen content, and organic matter fluxes). This study evaluated the level of reliability of three commonly used transfer equations based on planktic and benthic foraminiferal proxies that produce different palaeobathymetric results, using Neogene sediments from the Guadalquivir Basin, south‐west Spain. The most trustworthy method involves removing abundant infaunal benthic foraminifera before applying the palaeo‐water‐depth equation based on benthic foraminiferal water‐depth ranges and presence/absence of species. This new approach provides sound palaeobathymetric results that improve estimations of long and short‐term relative sea‐level changes with negligible influence of taphonomic as well as ecological factors. When using one equation based on planktic/benthic ratios (P/B ratios), removing all infaunal benthic foraminiferal species improves the accuracy of P/B ratios, which yields more accurate palaeodepth reconstructions despite the low level of trustworthiness of this equation for both long and short‐term relative sea‐level variations.

Geostatistical analysis for mapping soil salinity in the Lajas Valley Agricultural Reserve, southwestern Puerto Rico

Studies were conducted in the 1950s to evaluate the degree and spatial extent of soil salinity and sodicity in the Lajas Valley in southwestern Puerto Rico. Problem areas were identified and most of these were remediated with the establishment of irrigation and drainage infrastructure, resulting in a four-fold increase in agricultural production over a 10-year period. The area is now an important agricultural region (known as the Lajas Valley Agricultural Reserve). But soil salinity and sodicity are important concerns among farmers. In this paper we used published data and re-created the spatial distribution of soil salinity and sodicity using geostatistical analysis with Geographic Information Systems (GIS). An Ordinary Kriging method was applied to map the spatial distribution of soil salinity and to classify soils in four classes: (i) Normal, (ii) Saline, (iii) Saline-Sodic, and (iv) Sodic. The original hand-drawn maps were digitized using the Georeferencing Tool in ArcGIS, guided by a recent aerial photo of the Lajas Valley. Salinity and sodicity isopleths were created using Surface Generation to map the spatial distribution and to compare the newly created data to the original maps. The relative error in aerial estimate between the old and new maps for Normal, Saline, Saline-Sodic, and Sodic surface soils was between 1 and 5 percent. The new maps developed with geostatistical analysis can predict soil problem areas with a 94% coincidence compared with the hand-drawn maps. The highest proportion of soils classified as Normal was found in the upper soil layers and the proportion of soils affected by salt and sodium increased with depth. The combination of geostatistical analysis and GIS is a cost-effective and trustworthy method for analyzing similar datasets that would otherwise be costly and involve lengthy time commitments.

Data blinding for the nEDM experiment at PSI

Psychological bias towards, or away from, prior measurements or theory predictions is an intrinsic threat to any data analysis. While various methods can be used to try to avoid such a bias, e.g. actively avoiding looking at the result, only data blinding is a traceable and trustworthy method that can circumvent the bias and convince a public audience that there is not even an accidental psychological bias. Data blinding is nowadays a standard practice in particle physics, but it is particularly difficult for experiments searching for the neutron electric dipole moment (nEDM), as several cross measurements, in particular of the magnetic field, create a self-consistent network into which it is hard to inject a false signal. We present an algorithm that modifies the data without influencing the experiment. Results of an automated analysis of the data are used to change the recorded spin state of a few neutrons within each measurement cycle. The flexible algorithm may be applied twice (or more) to the data, thus providing the option of sequentially applying various blinding offsets for separate analysis steps with independent teams. The subtle manner in which the data are modified allows one subsequently to adjust the algorithm and to produce a re-blinded data set without revealing the initial blinding offset. The method was designed for the 2015/2016 measurement campaign of the nEDM experiment at the Paul Scherrer Institute. However, it can be re-used with minor modification for the follow-up experiment n2EDM, and may be suitable for comparable projects elsewhere.

Trustworthy Image Fusion with Deep Learning for Wireless Applications

To fuse infrared and visible images in wireless applications, the extraction and transmission of characteristic information security is an important task. The fused image quality depends on the effectiveness of feature extraction and the transmission of image pair characteristics. However, most fusion approaches based on deep learning do not make effective use of the features for image fusion, which results in missing semantic content in the fused image. In this paper, a novel trustworthy image fusion method is proposed to address these issues, which applies convolutional neural networks for feature extraction and blockchain technology to protect sensitive information. The new method can effectively reduce the loss of feature information by making the output of the feature extraction network in each convolutional layer to be fed to the next layer along with the production of the previous layer, and in order to ensure the similarity between the fused image and the original image, the original input image feature map is used as the input of the reconstruction network in the image reconstruction network. Compared to other methods, the experimental results show that our proposed method can achieve better quality and satisfy human perception.

Standard error estimates for rotated estimates of canonical correlation analysis: an implementation of the infinitesimal jackknife method

In applications of canonical correlation analysis (CCA), rotation of the canonical loadings is recommended to facilitate the interpretation of canonical variates. Based on the COSAN modeling approach to CCA proposed by Gu et al. (Multivar Behav Res 54:192–223, 2019), we describe the infinitesimal jackknife (IJ) method in modified COSAN-CCA models to obtain the IJ estimates of standard errors for rotated CCA estimates. Specifically, given two CCA rotation strategies (i.e., concurrent and separate) and two types of rotation method (i.e., orthogonal and oblique), our descriptions of the modified COSAN-CCA models and IJ method cover four rotation strategy-method combinations: concurrent-orthogonal, concurrent-oblique, separate-orthogonal, and separate-oblique. Simulation studies are used to evaluate the IJ estimates of standard errors, and a real data example is analyzed for illustration. We conclude that the IJ method is a trustworthy method for standard error estimation for rotated CCA estimates.

An Approach for Power Loss Reduction in Radial Distribution Networks

The loss power of distribution systems is increasingly more and more due to the increase of demand load from industrial zones and households as well as extended grids. For solving the problem, a strategy that can be regarded as a simple and effective way to allocate capacitor banks to the distribution systems. In the paper, a marine predator optimization algorithm (MPOA) is applied for determining the best size of capacitors and the most advantageous buses for the capacitors. The effectiveness of MPOA is scrutinized on two distribution systems considering the number of different integrated capacitors. The solutions found from MPOA are coped with those of recently available algorithms. Through the comparisons with previous studies, a conclusion is drawn that MPOA is a trustworthy method. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium provided the original work is properly cited.

GAMBARAN PENGETAHUAN IBU NIFAS TENTANG ADAPTASI PSIKOLOGIS PADA MASA NIFAS DI KLINIK PRATAMA AFIYAH PEKANBARU TAHUN 2019

Combination pills are tablets that are considered to be a trustworthy method of contraception. Contraceptive pills in Indonesia while its user is as much asgk 17.24% in 2017, among the 17.24% of users of contraceptive pills there are some users who experience side effects such as vomiting nausea 2.7%, not menstruation as much as 0.2% weight gain As much as 1.6% and headaches as much as 5.8% according to Kemenkes year 2018 initial Survey conducted in Puskesmas Rejosari Kota Pekanbaru Year 2019 There are 4422 people who consume KB pills, preliminary Survey There are 6 mothers who consume KB pill combination Experienced side effects like increased weight and embossed its black spots on the face. The purpose of this study is to know the description of KB acceptor behaviour against combination pill side effects. Quantitative research type with deskritif design. The population of mothers who consume KB pills in 2018 is 4422 people. Sampling techniques using sampling quota, samples used 30 mothers in the work area Puskesmas Rejosari who consume KB pill combinations that experience side effects. The results of the study obtained the majority of respondents had a positive behavior of 21 70% in the working area of Rejosari Puskesmas. Suggestions for respondents expected this research could add insight into the behavior or actions of the mother to the side effects experienced adding to this insight can be done in a way often follow the counseling about the KB that is held healthcare personnel In the Puskesmas, read a book on how to cope with the pill side effects combination and can also find info on the problems of side effects through social media.

The Place of Alternative Dispute Resolution (ADR) in Recovering Assets of 'White Collar Crimes' in Kenya

In a civil or criminal justice system, litigation has always been the first option whenever disputes arise. A good number of people have grown up believing or have at least been made to believe that litigation is the best and most trustworthy method of solving disputes. Even as they have progressed and developed critical thinking skills which allow them to gauge the efficacy or otherwise of litigation as the premier dispute resolution mechanism, they keep favoring it because of the unknown benefits of alternative dispute resolution mechanisms. Safe to take the risks with what is known rather than what is relatively unknown. Economic and financial crimes is one such field that has barely employed the use of alternative Dispute Resolution. Economic crimes refer to crimes of a financial nature and in our context, those that in one way or another affect the larger public as one. They involve the unlawful taking of public resources. Criminologists prefer to use the term white collar crimes because of the status and type of individuals who ordinarily commit them. Alternative dispute resolution in the country has over the last years gained notoriety and deservedly because of its potential to not only maintain relationships between disputing sides but the fact that it saves court resources which would otherwise have been spent pursuing the matters in court. The same has slowly found itself in the discourse around economic crimes and has even received the endorsement of the authorities mandated with the investigation and prosecution of such economic crimes. This paper seeks to assess the benefits of the use of alternative dispute resolution in dealing with economic crimes and as such, provide a reference point for those who remain skeptical about the wisdom of using non-litigation measures to deal with people who have been accused of fleecing the public.

Potentiality of municipal sludge for biological gas production at Soba Station South of Khartoum (Sudan)

Potentiality of municipal sludge for biological gas production at Soba Station South of Khartoum (Sudan)

Ecotoxicological responses of weed biochar on seed germination and seedling growth in acidic soil

Abstract Ecotoxicological measurement is vital for unbeaten soil-based/soil-less amendment with bioenergy by-products like biochar and the germination experiment is a trustworthy method for different types of biochar phytotoxicity investigation. An experiment was conducted to study the ecotoxicological responses of four weed biochar on seed germination and seedling growth in acidic soil at three different level of application in maize and black gram. The weed derived biochar were prepared at 600 °C followed by their characterization. With increase in biochar application rate the seed germination increased for both maize and black. The seedling growth parameter was significantly enhanced by low biochar application rate (5 t/ha) than high rate (10 t/ha). The Artemisia vulgaris (AVB) biochar performed better than all other biochar and it may be due to that the original biomass AV was medicinal in nature. The Bidens sp. (BB) and Neyraridia sp. (NB) biochar performed moderately and the worst performance observed by Chromolaena odorata (COB) biochar for both seed germination and seedling growth. At higher dose few seedling growth parameters were inhibited due to presence of toxic level elements selenium and chromium. The shoot/root ration (s/r) increased with augmentation in biochar application rate except NB for maize and irregular trend for black gram. Thus low cost biochar should be promoted for the welfare of agricultural production.

Two-parameter estimator for the inverse Gaussian regression model

The inverse Gaussian regression model (IGRM) is frequently applied in the situations, when the response variable is positively skewed and well fitted to the inverse Gaussian distribution. The maximum likelihood estimator (MLE) is generally used to estimate the unknown regression coefficients of the IGRM. The performance of the MLE method is better if the explanatory variables are uncorrelated with each other. But the presence of multicollinearity generally inflates the variance and standard error of the MLE resulting the loss of efficiency of estimates. So, for the estimation of unknown regression coefficients of the IGRM, the MLE is not a trustworthy method. To combat multicollinearity, we propose two parameter estimators (TPE) for the IGRM to improve the efficiency of estimates. Moreover, mean squared error criterion is taken into account to compare the performance of TPE with other biased estimators and MLE using Monte Carlo simulation study and a real example. Based on the results of Monte Carlo simulation study and a real example, we may suggest that the TPE based on Asar and Genç method for the IGRM is better than the other competitive estimators.

Trustworthy Method for Person Identification in IIoT Environments by Means of Facial Dynamics

In industrial Internet of Things (IIoT) environments, dependability of a complex manufacturing process in which human operators play a key role can be improved by identity recognition/authentication of whoever is involved in various stages of a production process, according to where and when he/she is supposed to be. To this aim, we propose an approach that exploits the dynamic appearance and the time-dependent local features characterizing the face of an individual during speech utterance with regard to their spatial and temporal components. The proposed method models these dynamic facial patterns captured from edge Internet of Things devices by means of the Local Binary Pattern on Three Orthogonal Planes descriptor, which effectively extract both face's local features and movement at the fog level of the architecture. A deep feedforward network available in the cloud is trained and optimized to match the extracted features to a reference database. The achieved results highlight state-of-the-art performances of the proposed method with regard to robustness and trustworthiness of identification, especially for challenging IIoT scenarios.

Comparative Analysis of Proposed Artificial Neural Network (ANN) Algorithm With Other Techniques

The mortality rate among women is increasing progressively due to cancer. Generally, women around 45 years old are vulnerable from this disease. Early detection is hope for patients to survive otherwise it may reach to unrecoverable stage. Currently, there are numerous techniques available for diagnosis of such a disease out of which mammography is the most trustworthy method for detecting early cancer stage. The analysis of these mammogram images are difficult to analyze due to low contrast and nonuniform background. The mammogram images are scanned and digitized for processing that further reduces the contrast between Region of Interest and background. Presence of noise, glands and muscles leads to background contrast variations. Boundaries of suspected tumor area are fuzzy & improper. Aim of paper is to develop robust edge detection technique which works optimally on mammogram images to segment tumor area. Output results of proposed technique on different mammogram images of MIAS database are presented and compared with existing techniques in terms of both Qualitative & Quantitative parameters.

Detection of Copy Number Alterations by Shallow Whole-Genome Sequencing of Formalin-Fixed, Paraffin-Embedded Tumor Tissue.

In routine clinical practice, tumor tissue is stored in formalin-fixed, paraffin-embedded blocks. However, the use of formalin-fixed, paraffin-embedded tissue for genome analysis is challenged by poorer DNA quality and quantity. Although several studies have reported genome-wide massive parallel sequencing applied on formalin-fixed, paraffin-embedded samples for mutation analysis, copy number analysis is not yet commonly performed. To evaluate the use of formalin-fixed, paraffin-embedded tissue for copy number alteration detection using shallow whole-genome sequencing, more generally referred to as copy number variation sequencing. We selected samples from 21 patients, covering a range of different tumor entities. The performance of copy number detection was compared across 3 setups: array comparative genomic hybridization in combination with fresh material; copy number variation sequencing on fresh material; and copy number variation sequencing on formalin-fixed, paraffin-embedded material. Very similar copy number profiles between paired samples were obtained. Although formalin-fixed, paraffin-embedded profiles often displayed more noise, detected copy numbers seemed equally reliable if the tumor fraction was at least 20%. Copy number variation sequencing of formalin-fixed, paraffin-embedded material represents a trustworthy method. It is very likely that copy number variation sequencing of routinely obtained biopsy material will become important for individual patient care and research. Moreover, the basic technology needed for copy number variation sequencing is present in most molecular diagnostics laboratories.

FT-IR spectral features of DNA as markers for the detection of liver preservation using irradiation

Food preservation, inhibition of foodborne-pathogenic microorganisms, as well as prolonging the shelf life of food products are all achieved through the application of irradiation technology in food preservation. In terms of food safety and for strengthening worldwide trade of irradiated foods, the presence of a trustworthy method for identification of irradiated foodstuff is currently the focus of attention. Since DNA has a documented high sensitivity to ionizing radiation, this work introduces a method for the detection of gamma-irradiated (3 kGy) calf liver through measurements of Fourier-transform infrared (FT-IR) spectra of their extracted DNA. Results show characteristic FT-IR bands that yield significant differences between irradiated and control calf liver samples. The guanine nucleoside band at 1491 cm−1 provides the most significant characterization.

Validation of the echocardiographic assessment of epicardial adipose tissue thickness at the Rindfleisch fold for the prediction of coronary artery disease

Background and AimEchocardiography is a promising technique for the assessment of epicardial adipose tissue (EAT). Increased EAT thickness is associated with different cardiac diseases, including; coronary artery disease (CAD). Since several different echocardiographic approaches have been proposed to measure EAT, the identification of a standardized method is needed. We propose the assessment of EAT maximal thickness at the Rindfleisch fold, the reproducibility of this measurement and its correlation with EAT thickness and volume assessed at cardiac magnetic resonance (CMR). Finally, we will test the predictive role of this measurement on the presence of significant CAD. Methods and ResultsIn 1061 patients undergoing echocardiography, EAT thickness was measured at the level of the Rindfleisch fold. In 70 patients, we tested the relationship between echo-EAT thickness and EAT thickness and volume assessed at CMR. In 499 patients with suspected CAD, undergoing coronary artery angiography, we tested the predictive value of EAT on the presence of significant CAD.Echo-EAT thickness measurements had an excellent reliability as indicated by the inter-observer (ICC:0.97; 95% C.I. 0.96 to 0.98) and intra-observer (ICC:0.99; 95% C.I. 0.98 to 0.99) reliability rates. Echo-EAT thickness significantly correlated with CMR-EAT thickness and volume (p < 0.001). An EAT thickness value >10 mm discriminated patients with significant CAD at coronary angiography (p < 0.001). At multivariable analysis, including demographic data and cardiovascular risk factors, EAT thickness was an independent predictor of significant CAD and showed an additive predictive value over common atherosclerotic risk factors. ConclusionsEchocardiographic assessment of EAT thickness at the level of the Rindfleisch fold represents a simple and trustworthy method. An increased EAT thickness shows an additive predictive value on CAD over common atherosclerotic risk factors, thus suggesting its potential clinical use for CAD risk stratification.

Disjunctive Representation of Triangular Bipolar Neutrosophic Numbers, De-Bipolarization Technique and Application in Multi-Criteria Decision-Making Problems

This research paper adds to the theory of the generalized neutrosophic number from a distinctive frame of reference. It is universally known that the concept of a neutrosophic number is generally associated with and strongly related to the concept of positive, indeterminacy and non-belongingness membership functions. Currently, all membership functions always lie within the range of 0 to 1. However, we have generated bipolar concept in this paper where the membership contains both positive and negative parts within the range −1 to 0 and 0 to 1. We describe different structures of generalized triangular bipolar neutrosophic numbers, such as category-1, category-2, and category-3, in relation to the membership functions containing dependency or independency with each other. Researchers from different fields always want to observe the co-relationship and interdependence between fuzzy numbers and crisp numbers. In this platform, we also created the perception of de-bipolarization for a triangular bipolar rneutrosophic number with the help of well-known techniques so that any bipolar neutrosophic fuzzy number of any type can be smoothly converted into a real number instantly. Creating a problem using bipolar neutrosophic perception is a more reliable, accurate, and trustworthy method than others. In this paper, we have also taken into account a multi-criteria decision-making problem (MCDM) for different users in the bipolar neutrosophic domain.

Effects of age and wear on the stiffness and friction properties of an SUV tyre

Accurate tyre models are essential for all full vehicle simulation models. Tyre models are usually parameterised based on measurements on new tyres. This article performs a sensitivity analysis, based on experimental data, to determine the effects of age and wear on a 235/55R19 tyre’s stiffness characteristics as well as the effect of wear on the tyre’s longitudinal friction characteristics. A well-researched and documented method was used to artificially age the tyres. Static tests were performed periodically on the tyre to monitor the changes in stiffness characteristics. Tyres were also subjected to accelerated wear by performing repeated side force versus slip angle and longitudinal force versus slip tests on a coarse concrete surface. The results indicate that the vertical and longitudinal force versus displacement characteristics have small but convincing dependencies on the age and wear. While the aging process was a trustworthy method, the wear process created irregular lateral and circumferential wear which impacted results. Overall the effects of age and wear did not exhibit substantial enough influence on the tyre stiffness to merit a full tyre model update. However, the wear did have a significant effect, in the order of 10%, on the longitudinal friction of the tyre.

Graphene Nanobuds: A New Second-Generation Phosgene Sensor with Ultralow Detection Limit in Aqueous Solution.

Selective and sensitive detection of highly toxic chemicals by a suitable, fast, inexpensive, and trustworthy method is vital due to its serious health threats to humankind and breach of public security caused by unexpected terrorist attacks and industrial accidents. Phosgene or carbonyl dichloride is widely employed in many chemical industries and pharmaceuticals, and in pesticide production, which is extremely toxic by severe (short-term) inhalation exposure. Because of the non-existence of a phosgene sensor in aqueous solution and the immense emphasis gained by nanomaterials, especially carbonaceous materials, augmented attention has been given to the development of a fluorophore-functionalized carbon-based method to detect this noxious substance. In this study, surfactant free 1,8-diaminonaphthalene (DAN)-functionalized graphene quantum dots (DAN-GQDs) were prepared to detect phosgene in aqueous solution. The FESEM (field emission scanning electron microscopy) and HRTEM (high-resolution transmission electron microscopy) analyses confirm the as-prepared DAN-GQD morphology as nanobuds (NBs) with an average diameter of ca. 35-40 nm. The crystalline nature, elemental composition, and chemical state of DAN-GQDs were analyzed by standard physiochemical techniques. The edge-termination at the carboxyl functional group of GQDs with DAN was examined by XPS, Raman, FT-IR, and 1H NMR spectroscopy analyses. The aqueous solution of DAN-GQDs (4.89 × 10-9 M) exhibits a strong emission peak at 423 nm upon excitation at 328 nm. The addition of the phosgene molecule (0 → 88 μL) quenches the initial fluorescence intensity of DAN-GQDs (ΦF 53.6 → 34.6%) through the formation of a stable six-membered cyclized product. The DAN-GQDs displayed excellent selectivity and sensitivity for phosgene ( Ka = 3.84 × 102 M-1 and LoD (limit of detection) = 2.26 ppb) over other competing toxic pollutants in water. The time-resolved fluorescence analysis confirms that the quenching of DAN-GQDs follows nonradiative relaxation of excited electrons. Furthermore, bioimaging experiments of phosgene in living human breast cancer (HeLa) cells and cell viability test successfully demonstrated the practicability of DAN-GQDs.