Improving Indoor Localization Using Mobile UWB Sensor and Deep Neural Networks

Accurate localization in indoor environments with ultra-wideband (UWB) technology has long attracted much attention. However, due to the presence of multipath components or non-line of sight (NLOS) propagation of the radio signals, it has been converted to a critical challenge. Existing solutions use many fixed anchors in the indoor environment. Particularly, large areas require many anchor points and in the case of unexpected events that lead to the destruction of existing infrastructures, the fixed anchor points cannot be used. In this paper, a novel localization framework based on the transmitting signal from a mobile UWB sensor on the outside of the building and its received signal regarding the modified Saleh Valenzuela (SV) channel model is presented. After preprocessing the received signals, two new procedures to reduce the ranging error caused by multipath components are proposed. In the first procedure, two machine learning algorithms including multi-layer perceptron (MLP) and support vector machine (SVM) using the extracted features from the received UWB signal time and power vectors are implemented. Moreover, in the second procedure, two deep learning algorithms including MLP and convolutional neural networks (CNNs) using the received UWB signal time and power vectors are implemented to improve the performance of the indoor localization system. The simulation results show that the architecture designed for the convolutional neural network based on the hybrid dataset (the combination of the dataset related to received UWB signal time and power vectors) provides a mean absolute error (MAE) of about 3 cm

Fingerprinting the contribution of quarrying to fine‐grained bed sediment in a mountainous catchment, Iran

The contribution of quarrying in the context of multiple catchment sources of finegrained sediment has rarely been investigated. This study assessed the relative importance of quarrying as a sediment source alongside rangeland surface soils and channel banks in a mountainous catchment in northern Tehran, Iran, using fingerprinting. Eight geochemical tracers were measured on 24 potential sediment source samples and four fine‐grained sediment samples. Statistical analysis to select three different composite fingerprints for discriminating the potential sediment sources comprised: (a) the Kruskal–Wallis H test (KW‐H), (b) a combination of KW‐H and discriminant function analysis (DFA), and (c) a combination of KW‐H and principal components and classification analysis (PCCA). A Bayesian unmixing model was used to apportion sediment source contributions using the three composite fingerprints. Using the KW‐H composite signature, the respective relative contributions (with uncertainty ranges) from channel banks, rangeland surface soils, and quarrying were estimated as 28.4% (10.9–46.8), 15.1% (6.6–22.7), and 56.6% (38.3–74.2), compared with 35.4% (11.9–60.1), 13.4% (4.1–22.2), and 51.3% (26.5–74.3) using a composite signature selected using a combination of KW‐H and DFA, or 20.7% (3.9–41.7), 17.2% (4.4–29.9), and 61.4% (44–78.8) using a fingerprint selected using KW‐H and PCCA. The different composite signatures therefore all consistently suggested that quarrying is the dominant source of the fine‐grained sediment samples. Potential mitigation measures targeting this land use include closure to permit revegetation to reduce exposure of bare surfaces to sediment mobilization. Limitations and uncertainties associated with this preliminary investigation are briefly discussed

Investigating the importance of recreational roads as a sediment source in a mountainous catchment using a fingerprinting procedure with different multivariate statistical techniques and a Bayesian un-mixing model

Road construction associated with land development generally increases erosion and sediment yields. Construction of unpaved roads has the potential to alter hydro-sedimentological behavior and catchment sediment source dynamics and, to date, this has largely been investigated in forested environments. The objective of this study, therefore, was to assess the relative importance of unpaved recreational roads as a sediment source alongside hillslope surface soils and stream channel banks in a non-forested mountainous catchment in northern Tehran, Iran, using a fingerprinting procedure. Eleven geochemical tracers were measured on 27 samples collected to characterise the sediment sources and five suspended sediment samples collected at the study catchment outlet. The statistical analysis employed to select three different composite fingerprints for discriminating the sediment sources comprised: (1) the Kruskal–Wallis H test (KW-H), (2) a combination of KW-H and discriminant function analysis (DFA), and (3) a combination of KW-H and principal components & classification analysis (PCCA). A Bayesian un-mixing model was used to ascribe sediment source contributions using the three composite fingerprints. Using the KW-H composite signature, the respective relative contributions (with uncertainty ranges) from recreational roads, hillslope surface soils and channel banks were estimated as 64.5% (57.7–73.1), 1.1% (0.1–4.9), and 33.9% 24.9–41.0), compared to 55.3% (45.5–68.5), 1.9% (0.1–7.9)and 42.1% (27.8–52.4) using a composite signature selected using a combination of KW-H and DFA, or 82.0% (69.7–93.8), 8.2% (0.7–22.7) and 7.3% (0.7–21.0) using a fingerprint selected using KW-H and PCCA. The root mean square difference between the apportionment results using the fingerprints identified on the basis of the three different statistical approaches ranged from 5.5% to 25.7%, highlighting the sensitivity of source estimates to the tracers used. Regardless, the different composite signatures all suggested that unpaved recreational roads were the dominant source of the suspended sediment samples, underscoring the need for mitigation measures targeting these anthropogenic features of the catchment system, including closure to permit re-vegetation, surface ripping and/or mulching to improve infiltration or gravel re-surfacing to reduce exposure of bare surfaces to sediment mobilisation

A soil quality index for evaluation of degradation under land use and soil erosion categories in a small mountainous catchment, Iran

Soil erosion and land use type have long been viewed as being particularly important drivers of soil degradation. The objectives of this study, therefore, were to select a new soil quality index (SQI) which varies significantly with land use/soil erosion,and to evaluate the new SQI using expert opinion. In total, 18 soil physical, chemical, and biochemical properties (indicators) were measured on 56 soil samples collected from four land use/soil erosion categories (rangeland/surface erosion, rangeland/subsurface erosion, cultivated land/surface erosion and dry-farming land/surface erosion). Principal component and classification analysis (PCCA)identified five PCs that explained 77.7% of the variation in soil properties with the biochemical PC varying significantly with land use/soil erosion. General discriminant analysis (GDA) selected urease and clay as the most sensitive properties distinguishing the land use/soil erosion categories.The GDA canonical scores for the new SQI were significantly correlated with expert opinion soil surface summed scores (for soil movement, surface litter, pedestalling, rills and flow pattern) derived using the U.S. Department of the Interior Bureau of Land Management (BLM) method. A forward stepwise general regression model revealed that the new SQI values were explained by soil movement, surface litter, and the summed values of the soil surface factors. Overall, this study confirmed that soil quality in the study area in Iran is controlle

A microfluidic approach to rapid sperm recovery from heterogeneous cell suspensions

The isolation of sperm cells from background cell populations and debris is an essential step in all assisted reproductive technologies. Conventional techniques for sperm recovery from testicular sperm extractions stagnate at the sample processing stage, where it can take several hours to identify viable sperm from a background of collateral cells such as white bloods cells (WBCs), red blood cells (RBCs), epithelial cells (ECs) and in some cases cancer cells. Manual identification of sperm from contaminating cells and debris is a tedious and time-consuming operation that can be suitably addressed through inertial microfluidics. Microfluidics has proven an effective technology for high-quality sperm selection based on motility. However, motility-based selection methods cannot cater for viable, non-motile sperm often present in testicular or epididymal sperm extractions and aspirations. This study demonstrates the use of a 3D printed inertial microfluidic device for the separation of sperm cells from a mixed suspension of WBCs, RBCs, ECs, and leukemic cancer cells. This technology presents a 36-fold time improvement for the recovery of sperm cells (> 96%) by separating sperm, RBCS, WBCs, ECs and cancer cells into tight bands in less than 5 min. Furthermore, microfluidic processing of sperm has no impact on sperm parameters; vitality, motility, morphology, or DNA fragmentation of sperm. Applying inertial microfluidics for non-motile sperm recovery can greatly improve the current processing procedure of testicular sperm extractions, simplifying the fertility outcomes for severe forms of male infertility that warrant the surgery

Comparison performance of visible-nir and near-infrared hyperspectral imaging for prediction of nutritional quality of goji berry (Lycium barbarum l.)

The potential of hyperspectral imaging for the prediction of the internal composition of goji berries was investigated. The prediction performances of models obtained in the Visible-Near Infrared (VIS-NIR) (400–1000 nm) and in the Near Infrared (NIR) (900–1700 nm) regions were compared. Analyzed constituents included Vitamin C, total antioxidant, phenols, anthocyanin, soluble solids content (SSC), and total acidity (TA). For vitamin C and AA, partial least square regression (PLSR) combined with different data pretreatments and wavelength selection resulted in a satisfactory prediction in the NIR region obtaining the R2pred value of 0.91. As for phenols, SSC, and TA, a better performance was obtained in the VIS-NIR region yielding the R2pred values of 0.62, 0.94, and 0.84, respectively. However, the prediction of total antioxidant and anthocyanin content did not give satisfactory results. Conclusively, hyperspectral imaging can be a useful tool for the prediction of the main constituents of the goji berry (Lycium barbarum L.)

Analysis of Cases inWhich a Biopsy Specimen Is Positive and an Excised Lesion Is Negative for Nonmelanoma Skin Cancer

Nonmelanoma skin cancers (NMSCs), including squamous cell carcinoma (SCC) and basal cell carcinoma (BCC), are the most common types of cancer with the fastest-growing treatment costs in the United States.1 Standard treatment requires biopsy for histologic confirmation, followed by excision. Oftentimes, no residual carcinoma is detected, implying spontaneous clearance at rates reported to vary from 24% to 76%.2- 5 These types of lesions have been investigated by others2- 5 and are not fully understood. Our study aims to determine the lesion and patient characteristics that would most strongly predict a histologically negative result for an excised lesion after a biopsy specimen had positive margins

Vortex fluidic mediated synthesis of polysulfone

Polysulfone (PSF) was prepared under high shear in a vortex fluidic device (VFD) operating in confined mode, and its properties compared with that prepared using batch processing. This involved reacting the pre-prepared disodium salt of bisphenol A (BPA) with a 4,4′-dihalodiphenylsulfone under anhydrous conditions. Scanning electron microscopy (SEM) established that in the thin film microfluidic platform, the PSF particles are sheet-like, for short reaction times, and fibrous for long reaction times, in contrast to spherical like particles for the polymer prepared using the conventional batch synthesis. The operating parameters of the VFD (rotational speed of the glass tube, its tilt angle and temperature) were systematically varied for establishing their effect on the molecular weight (Mw), glass transition temperature (Tg) and decomposition temperature, featuring gel permeation chromatography (GPC), differential scanning calorimetry (DSC) and thermal gravimetric analysis (TGA) respectively. The optimal VFD prepared PSF was obtained at 6000 rpm rotational speed, 45° tilt angle and 160 °C, for 1 h of processing with Mw ∼10000 g mol−1, Tg ∼158 °C and decomposition temperature ∼530 °C, which is comparable to the conventionally prepared PSF

Fingerprinting sub-basin spatial sediment sources in a large Iranian catchment under dry-land cultivation and rangeland farming: combining geochemical tracers and weathering indices

Study region: The Kamish River catchment (308 km2); a mountainous agricultural catchment under dry-land and rangeland farming located in Kermanshah province, in western Iran. Study focus: The main objective of this study was to apportion sub-basin spatial source relative contributions to target channel bed sediment samples using a composite fingerprinting procedure including a Bayesian un-mixing model. In total, thirty-four geochemical tracers, eleven elemental ratios and different weathering indices were measured or estimated for 43 tributary sediment samples collected to characterise three sub-basin spatial sediment sources and eleven target bed sediment samples collected at the outlet of the main basin. Statistical analysis was used to select three different composite signatures. New hydrological insights for the region: Using a composite signature based on KW-H and DFA, the respective relative contributions (with uncertainty ranges) from tributary sub-basins 1, 2 and 3 were estimated as 54.3% (47.8–62.0), 11.4% (4.2–18.7) and 34.3% (27.6–39.9), compared to 72.0% (61.6–82.7), 13.6% (9.0–18.5) and 14.2% (3.1–25.4) using a combination of KW-H and data mining, and 50.8% (42.8–59.9), 28.7% (20.2–37.3) and 20.3% (12.7–27.2) using a fingerprint selected by KW-H and PCCA. The root mean square difference between these source estimates highlighted sensitivity to the composite signatures. Evaluation of the un-mixing model predictions using virtual mixture tests confirmed agreement between modelled and known source proportions

Identification and characterization of the first fish parvalbumin-like protein data from a pathogenic fungal species, Trichophyton violaceum

Parvalbumins are the most important fish allergens, which are heat-stable, classified in the family of calcium-binding EF-hand proteins, and contain one magnesium binding site. The functional connection between calcium and parvalbumin gives fish the high-speed swimming ability because of high concentration of Ca2+-binding parvalbumin in fish white muscles. Although parvalbumins are widely studied and conceivably play crucial roles in the physiology and swimming pattern of fishes, still no report is available about their presence in microbes, such as pathogenic fungal species. We detected a DNA sequence in the genome of Trichophyton violaceum and used in silico and polymerase chain reaction (PCR) technique with a designed pair of primers to identify it as parvalbumin-coding gene. © 2020 The Author