Track-index-guided sustainable off-road operations using visual analytics, image intelligence and optimal delineation of track features

Visual-analytics-guided systems are replacing human efforts today. In many applications, movement in off-road terrain is required. Considering the need to negotiate various soft ground and desertic conditions, the beaten tracks of leading vehicles considered to be safe and suitable for guiding are used in such operations. During night, often, these tracks pass through low-contrast conditions posing difficulty in their identification. The maximization of track contrast is therefore desired. Many contrast enhancement techniques exist but their effectiveness varies as per the surrounding. Other than conventional techniques, the role of texture too becomes important for enhancing the differentiable track contrast. Gray-level co-occurrence matrix (GLCM)-based statistic measures are used here to evaluate the track texture. These measures are seen to improve the contrast of vehicle tracks significantly. A track-index-based technique is proposed to sort various images as per their effectiveness in increasing the track contrast. Different forms of track indices are proposed and compared. The proposed track index is seen as effective in sorting 88.8% of contrast images correctly. The proposed technique of creating and sorting images based on the contrast level is seen as a useful tool for improved fidelity in many difficult situations for making the off-road operations sustainable

Adaptive Technique for Contrast Enhancement of Leading Vehicle Tracks

During movement in various unpaved terrain conditions, the track impressions left over by the leading vehicles provide guiding and safe routes in the area. The delineation of these tracks captured by the images can extend immense support for guidance in real time. These tracks that look like edges in coarse-resolution images take the shape of elongated areas in fine-resolution images. In such a scenario, the high pass and edge detection filters give limited information to delineate these tracks passing through different surroundings. However, the distinct texture of these tracks assists in the delineation of these tracks from their surroundings. Gray level co-occurrence matrix (GLCM) representing the spatial relation of pixels is employed here to define the texture. The authors investigated the influence of different resolutions on the distinguishability of these tracks. The study revealed that texture plays an increasing role in distinguishing objects as the image resolution improves. The texture analysis extended to investigate the track impressions left over by the leading vehicle brings out an ample scope in delineating these tracks. The measures could improve the track contrast even better than conventional techniques. To select the most optimal contrast enhancement measure in a given scenario, authors proposed a quantified measure of track index. An investigation is made on the difference-based track index (TI) representing the mean contrast value of the track vis-à-vis off-track areas. The results show an increase in the quantified contrast from 7.83 per cent to 29.06 per cent. The proposed technique highlights the image with the highest track contrast in a given scenario. The study can lead to onboard decision-making for the rut following vehicles moving in low-contrast terrain

On the proficient use of GEV distribution: a case study of subtropical monsoon region in India

The paper deals with the probabilistic estimates of extreme maximum rainfall (Annual basis) in the Ranchi, Jharkhand (India). Extreme Value Distribution family models are tried to capture the uncertainty of data and finally Generalized Extreme Value (GEV) distribution model is found as the best fitted distribution model. The GEV model satisfied the selection criteria [Anderson-Darling test (A-D test or Goodness of fit test) and Normality test (Q-Q plot)], which are adopted under the present study. The return levels are estimated for 5, 10, 50, 100 and 200 years which are consistently increasing for long run in future

Toxicological manifestations in gills, liver, kidney and muscles of Channa punctatus exposed to mercuric chloride

Aquatic regimes are exposed to a variety of pollutants that are mainly released by anthropogenic activities. Mercuric chloride (HgCl2) pose serious hazards to freshwater fish resource for its toxicity and long persistence. It is also a threat to humans who consume fish as a food resource. This study aimed to determine the consequences of acute exposure to HgCl2 in the freshwater food fish Channa punctatus (Bloch, 1973). The acute study of 96 hours was composed of three groups (in triplicates), having ten fish in each group which includes group I (control), group II (0.112 mg/l of HgCl2) and group III (0.224 mg/l of HgCl2). Results showed induction in reactive oxygen species (ROS) level in erythrocytes of group III (22159 ± 258.036). The biomarkers of oxidative stress, glutathione reduced (GSH) and lipid peroxidase (LPO) showed significant (p < 0.05) decrement and increment in their activity, respectively, in gills, liver, kidney and muscle tissues of the fish treated with HgCl2. Further, micronuclei (MN) and nuclear abnormalities (NAs) were formed in the erythrocytes of the fish of groups II and III, revealing DNA damage, hence showing genotoxicity. Histopathological studies in sample tissues of HgCl2 treated group demonstrated irreversible tissue injuries and anomalies. Thus, the findings from the study demonstrate that biological stress is induced in fish because of acute exposure to HgCl2, leading to health impairmen

Dioxidobis(2-oxo-1,2-dihydropyridin-3-olato)­molybdenum(VI)

In the title compound, [Mo(C5H4NO2)2O2], the MoVI atom exhibits a distorted octa­hedral coordination geometry formed by two terminal oxo ligands and two monoanionic O,O-bidentate pyridinone ligands. The two terminal oxo ligands lie in a cis arrangement, the ketonic O atoms of the pyridinone ligands are coordinated trans to the oxo ligands and the deprotonated hydroxyl O atoms are located trans to each other. The crystal structure contains inter­molecular N—H⋯O hydrogen bonds, C—H⋯O contacts and face-to-face π–π stacking inter­actions with an inter­planar separation of 3.25 (1) Å

A New 3D 10-Connected Cd(II) Based MOF With Mixed Ligands: A Dual Photoluminescent Sensor for Nitroaroamatics and Ferric Ion

The precise unification of functional groups and photoluminescence properties can give rise to MOFs that can offer diverse applications like selective detection of nitroaromatic compounds (NACs) which are considered to be an important ingredient of explosive as well as cation and anion sensing. Hence, a new 3D metal-organic framework (MOF) [Cd2(btc)(bib)(HCOO)(H2O)·H2O]n (1) has been synthesized using mixed ligand strategy by solvothermal reaction of cadmium acetate with two ligands viz. 1,3,5-benzenetricarboxylic acid (H3btc) and 1,4-bis(2-methyl-imidazol-1-yl)butane (bib). The MOF 1 possesses highly 10-connected network which is based on {Cd4(btc)2(bib)4} molecular building block. The studies showed that 1 could be taken as the fluorescent sensor for sensitive recognition of NACs, in particular 2,4,6-trinitrophenol (TNP) with notable quenching (Ksv = 5.42 × 104 M−1) and LOD of 1.77 ppm. Additionally, 1 also displayed selective sensing for Fe3+ ions with Ksv = 6.05 × 103 M− 1 and LOD = 1.56 ppm. Also, this dual sensor displayed excellent reusability toward the detection of TNP and Fe3+ ion. Theoretical calculations have been performed to propose the probable mechanism for the sensing luminescence intensity. Calculations indicated that because of the charge transfer and weak interaction that is operating between NACs and MOF, the weakening in the photoluminescence intensity resulted