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The presence of joints in rocks significantly impacts the mechanical behavior and stability of a slope. A better comprehension of the relationship between jointed rock masses and slope stability has been made possible by recent advances in machine learning algorithms and numerical modelling. The purpose of this research is to predict the stability of slopes in the presence of different types of joints (parallel deterministic, cross jointed, Baecher, Veneziano, and Voronoi) with the help of classification-based machine learning algorithms. In order to achieve this goal, 40,290 different cases have been utilized, following numerical simulation using shear strength reduction (SSR) technique in RS2. Geomechanical properties, parameters defining slope geometry, structural properties of joints including properties of filling materials, and the influence of certain external factors have been considered. For these datasets, classification algorithms such as random forest, k-nearest neighbor, support vector machine, logistic regression, decision tree, and Naive Bayes have been utilized. Additionally, the synthetic minority oversampling technique (SMOTE) has been implemented in order to address imbalanced class problems. The results exhibit an encouraging level of accuracy, with random forest and decision tree both achieving 0.98 as an overall accuracy.

The selection of an efficient speckle filter for SAR imagery primarily depends upon a specific application of interest and statistical characteristics of the noise present in SAR datasets. The main goal of this study is to assess the performance of the two wavelet shrinkage-based filtering techniques (VISU shrink and SURE shrink) against two spatial adaptive filters (Enhanced Lee and Gamma MAP) and one non-local filter (NL-SAR) for the removal of speckle noise from high-resolution COSMO-SkyMed (CSK) SAR datasets. Before applying these filters to real CSK datasets, they are tested on synthetically generated speckled test datasets and benchmark simulated SAR datasets. Experimental analysis has been conducted on synthetically generated speckled datasets based on varying level of speckle noise introduced on test images. In case of benchmark datasets, numerous qualitative and quantitative measures are observed and evaluated. To find the best filter for real CSK data, a Pareto optimality concept has been used where the coefficient of variation is the parameter considered. From the findings, it is evident that VISU shrink-generated speckle filtering solution is non-dominated by all the other filtering solutions except NL-SAR-based speckle suppression in smooth areas. Considering the various user-defined situations of homogeneity and heterogeneity in the SAR scene, an overall performance index is formulated and VISU shrink performs the best in all user-defined conditions.

The active tilt-controlled narrow three-wheelers (3Ws) equipped with a closed cabin aim to offer a comfortable driving experience comparable to four-wheelers while maintaining the manoeuvrability of two-wheelers without compromising on speed. Based on this concept, this study explores a tilt control strategy for narrow 3Ws. While previous research has established a steady-state tilt angle considering a zero-track width, this study incorporates track width due to the multi-wheel axle configuration. This novel approach not only withstands unbalanced lateral acceleration but also saves significant tilting torque. Unnecessary tilting is minimised by introducing a tilt actuation system (TAS) based on a unique dynamic rollover index. Central to the original contribution is the stability margin (SM), a dynamic rollover-safety index considering longitudinal and lateral dynamics, surpassing the traditional rollover index load transfer ratio, particularly for delta 3Ws. This work proposes a desired SM threshold-dependent steady-state tilt angle, activating TAS only when necessary. This pioneering method optimises the desired SM threshold using goal programming. Additionally, this research addresses a critical oversight in previous studies by accounting for the influence of road slopes, ensuring consistent stability across diverse road conditions. It is crucial to note that the proposed rollover index-based tilting approach markedly outperforms the conventional methods, reinforcing its originality and potential for future vehicular design.

The issues like traffic congestion, parking space and vehicular emission can be reduced by adopting electric narrow tilting three-wheelers, which can also provide a cost-effective and safe mode of transport for low-income people. According to energy technology perspectives 2017, well-to-wheel global greenhouse gas emissions can be reduced up to 1.3 GtCO2-eq by 2060 by adopting electric mobility. This study presents a new and modified SDTC strategy and performance parameters that takes Road Bank Angle (RBA) into account so as to exhibit the adverse effects on rollover safety, ride comfort in terms of the perceived lateral acceleration and desired trajectory. Besides, this study identifies the importance of the RBA consideration in active tilt controlled vehicle for the scenario of parking on sloped surface. Simple electronic control architecture of the SDTC approach with real-time RBA consideration is proposed to address the limitations of SDTC and its supplementary advantages. This study evaluates the scenario of constant turn manoeuvre and vehicle parking on the banked roads. A multi-body model is used to capture the dynamic characteristics of the vehicle, whereas a characteristic of the Tilt Actuation System (TAS) and Active Steering (AS) system is incorporated in the form of a Transfer Function (TF) estimated using a system identification approach. The results indicate that the inclusion of a real-time RBA in the SDTC enables it to maintain steady-state torque and perceived lateral acceleration close to zero with the proposed controlled strategy, and it also keeps the vehicle upright on the sloped surface. It may be concluded that RBA compensation improves the ease of handling the vehicle while parking or riding on a sloped surface without significant control system alterations, which also makes it a viable alternative for physically disabled people.

Surface wear of conveyor belts is a matter of significant concern in the mining and mineral industry as they play a crucial role in the transportation of materials and bulk solids over long distances. Traditional intrusive techniques for assessing surface wear in belts often result in production stoppages for their own maintenance. In contrast, non-intrusive techniques like machine vision offer an advantage by enabling remote detection of wear patterns. This article explores a machine-vision-based technique specifically designed for assessing surface wear on cleated conveyor belts across the belt width and belt thickness. The approach exploits the unique design of an open-V cleated belt to logically section a given belt image into five distinct regions across the belt symmetry namely, the left edge, left cleat arms, middle, right cleat arm, and right edge regions. Belt image sectioning facilitates a detailed analysis of wear patterns in each of the five regions. The analysis conducted at four different stages of belt operation revealed non-uniform wear patterns across the belt surface. For belt thickness wear, the left edge region wore 9.7% more compared to the right edge region, while the left cleat arms experienced significantly higher wear (18.7%) than the right cleat arms. The left cleat arms have the highest overall wear (59.4%), whereas the right belt region demonstrates the lowest thickness wear (17%). Regarding width wear, the left cleat arms experience the most significant wear (34.5%) among the different belt regions, whereas the middle belt region shows negligible width wear (0.01%). Over a 12-month period, the entire belt experiences 41.2% thickness wear and 0.8% width wear. To validate the accuracy of the wear estimation method, the obtained measurements are compared with actual measurements. The obtained errors are marginal with a mean absolute percentage error of 0.52% for belt thickness and 0.05% for belt width, establishing the efficacy of the presented approach.

The habitation, distribution and conservation of endangered wildlife habitat were investigated in the southern part of the 'West Singhbhum' district, Jharkhand. The Geographical Information System (GIS) provides a powerful tool for investigating wildlife species habitat and their relationships with different socio-environmental conditions and development of wildlife conservation and management activities. A weight base wildlife suitability habitat (WSH) model is capable to develop indices of wildlife habitat suitability zone. Herein, the study provide the mining, rail, road, noise, forest cover and fire-risk area, availability of water, wild animal sighting (location), human settlement provide useful information for successful management of suitable wildlife habitat at the local scale. This is compared with predictive habitat suitability zones 90.06 km2(14.40%), and differences are found in areas near the vicinity. The 79.20% and 6.40% area has been identified as a moderately suitable (495.14 km2) and least suitable (40.01 km2) zone. The results highlight that distribution of habitat suitability that correlated with existing wildlife conservation plans which is highly matched and well spatially distributed. Conversely, where large expanses of the natural landscapes are available, relatively low levels of planning and management are needed to conserve wildlife.

Reclamation consists of modifying the disturbed land and returning it to a more natural state of hills, grasslands, forests and lakes for the benefit of future generations. This study analyzed the change of land use and land cover in the Noamundi block (West Singhbhum district, Jharkhand), India. This paper demonstrates the impact of mining on the natural environment in this area by using three images of the Landsat missions from 2003, 2011 and 2017 which were processed by the supervised image classification (8 classes). By comparing the classified images this paper retrieve the absolute and relative change of land use and land cover in the study area. An accuracy assessment is performed to describe the quality of the classification. The maximum increase of agricultural areas is detected with a decrease in forest areas.

Water is a most important natural resource and it occupies a very important role for the overall development of an area. The surface water bodies of the study area (i.e., Raniganj colliery area, West Bengal, India) are extracted from the satellite imagery. The drainage pattern of the study area also conforms to the dendritic pattern. The surface water body of the study area has been generated using the normalized difference water index (NDWI). The distribution of NDWI values is computed from the satellite imagery over the whole study area. Field water samples were collected from Damalia and Baktarnagar high school of Raniganj in Barddhaman district. Water has been collected as a field sample from mining area (abundant), and the samples are tested for the different parameters of the water. This cadastral-level sample data is very much useful for the proper planning and monitoring of the changes in the different environmental parameters at cadastral level that will include the mining/industrial zones within the study area and at the same time these digital databases would be used for sustainable environmental planning. Finally, the surface water map could be used for various purposes like location of well/tube well and irrigation by pump/deep tube well for sustainable agricultural purpose in cadastral/village label and management of subsurface water in this area for future prospect.

This review is on the various techniques and methodologies applied to sensor based monitoring of the quality and control of defects in an advanced joining process named friction stir welding (FSW). This study is aimed to come up with Industry 4.0 automation of the same, which will help in exchanging data efficiently for a sustainable growth in the industrial sector. The implementation of sensors into the existing FSW machine channelizes the information about the process in real time, and subsequently helps in controlling the process anomaly, and thereby ensures product quality and precision. Important aspects of FSW viz. its process parameters, weld zones, and defects have been discussed from the monitoring and control point of view. In this context, the applicability of various sensors such as force, torque, current, power, temperature, vibration, acoustic emission, and imaging to acquire information about the process have been discussed. In addition to the sensing systems, processing techniques have also been discussed. A case study has also been presented to introduce the readers with the behavior of some of the signals, and semantic utilization of the processing techniques in FSW. Towards the end, a roadmap for implementing the idea of Industry 4.0 in FSW has been proposed.

Hyperspectral imaging is one of the promising remote sensing techniques. This technique records the spatial and spectral information of the object under study. Consequently, it has been gaining momentum in a number of Earth observing applications. The aim of this paper is to present the current trends of hyperspectral sensing from different platforms and instruments for various applications. For Earth observation, mobile platforms are discussed which include spaceborne, airborne, ground-based sensing, unmanned aerial system, and underwater vehicle-based. Under these different sensing platforms, hyperspectral imaging instruments are presented that have been developed by various public and private organizations in the past with some specific goals.

Traffic congestion, pollution due to vehicular emissions and fuel energy crises are the major problems that have inspired research for the design of efficient and smaller vehicles as a regular mode of transport with a significantly lower carbon footprint. With an increased dependency on certain countries for fuel energy, electric mobility has been encouraged by policy makers so that national interests are not compromised. At the same time, enhanced standards of living have resulted in a demand for safer and comfortable transport. All of these factors have led to a need for a mode of transport that is efficient, compact, safe and comfortable. Electric three-wheelers are seen as one of the promising options that fits all of these requirements. Due to their high propensity to rollover during cornering, however, the use of three-wheeled vehicles (3Ws) is limited to low-speed applications for cheap transport. Recent developments in the field of rollover mitigation through active tilt control mechanisms indicate that the future mode of transport will be more exciting than the existing one. This paper is a review mainly focused on the recent technological developments in active-tilt-controlled three-wheeled vehicles. This paper gives a detailed review of the methodologies chosen, control strategies adopted, types of vehicle chosen for test/simulation, mathematical models applied, key findings and future work proposed to address the dynamics-related issues of tilting 3Ws.

Friction Stir Welding (FSW) is a relatively new technology in welding. The ultimate aim of any welding process is to achieve a defect-free weld. Several defects during FSW can be attributed to various factors and are required to be examined and eliminated if required. The exact severity of a surface defect in FSW cannot be determined by a 2D image, which does not provide any information about the depth of the defect. Thus, this paper aims towards the comprehensive analysis of degradation caused over the weld strength due to surface defect, based on its 3D reconstructed depth map obtained from 3D Optical Microscope. This research work proposed a novel algorithm to determine certain 3D geometrical features like effective length, effective width, average depth and effective volume for giving the severity of surface defects with a precision of around micrometres scale. The depth data were also used to determine the surface textural features like average roughness and RMS roughness. The results obtained by this technique were also experimentally verified by the conventional surface roughness tester machine.

Particle size distribution of coarse aggregates through mechanical sieving gives results in terms of cumulative mass percent. But digital image processing generated size distribution of particles, while being fast and accurate, is often expressed in terms of area function or number of particles. In this paper, a mass model is developed which converts the image obtained size distribution to mass-wise distribution, making it readily comparable to mechanical sieving data. The concept of weight/particleratio is introduced for mass reconstruction from 2D images of particle aggregates. Using this mass model, the effects of several particle shape parameters (such as major axis, minor axis, and equivalent diameter) on sieve-size of the particles is studied. It is shown that the sieve-size of a particle strongly depend upon the shape parameters, 91% of its variation being explained by major axis, minor axis, bounding box length and equivalent diameter. Furthermore, minor axis gives an overall accurate estimate of particle sieve-size, error in mean size (D-50) being just 0.4%. However, sieve-size of smaller particles (<20mm) strongly depends upon the length of the smaller arm of the bounding box enclosing them and sieve-sizes of larger particles (>20mm) are highly correlated to their equivalent diameters. Multiple linear regression analysis has been used to generate overall mass-wise particle size distribution, considering the influences of all these shape parameters on particle sieve-size. Multiple linear regression generated overall mass-wise particle size distribution shows a strong correlation with sieve generated data. The adjusted R-square value of the regression analysis is found to be 99 percent (w.r.t cumulative frequency). The method proposed in this paper provides a time-efficient way of producing accurate (up to 99%) mass-wise PSD using digital image processing and it can be used effectively to replace the mechanical sieving.

Mapping of land use/land cover (LU/LC) is an important activity of land management and monitoring, but mining activity has an effect on land, environment and local society. The analysis of land changes map is prepared using high resolution imagery and provide mining information. The rate of deforestation and forest fragmentation has also decreased due to mining activity. This has resulted in over exploitation of natural resources due to mining activities like deforestation, cultivation of marginal lands, mining and industrialization in meeting the increasing demand for food, fuel and fiber. Geo-spatial technology has led to the hosts of undesirable effects on the ecosystem. The risk buffer zone is manipulated based on environmental concern and field verification. Mining operations involve in mineral extraction from the earth’s crust, tends to make a notable impact on the environment, landscape and also biological communities of the earth in the mining area. LU/LC change detection and its impact over space and time (2007–2011). Risk buffer zone demarcation in colliery area and finally environmental impact assessment in the mining area.

The effect of slope angle for external overburden dump in response to average and heavy rainfall has been analyzed using a two dimensional finite difference method of transient water flow through unsaturated–saturated soil. The external dump stability is evaluated for five geomaterial types on the basis of globally accepted safety factor analysis technique, based on shear strength reduction approach using finite difference method. The results obtained from the finite difference method of analysis indicate that the external dump with more than 30° slope angle is greatly influenced by the rainfall under the studied conditions for geomaterial 3, 4 and 5, whereas dumps with geomaterial 1 and 2 remain safe. The analysis shows that major slope failure is out of preview for the studied rainfall conditions.

Cadastral is the method of registering land, designed to ensure the rights of individuals and the state of their property. Every activity in general, and developmental project activity in particular, is in some form or the other associated with land. Therefore, for planning purpose all land-associated information should be available in the form of a computer database, which can be easily accessed, manipulated by decision makers while formulating and executing a work. Such a database system is called Land information system. Cadastral applications will include cadastral index maps and land registration data in a digital format. Automation linkages will be created and developed between textual data (legal land registration data) and parcel maps. The final goal is to generate digital maps which will facilitate land management and planning and in particular land registration and the issuance of land titles in order to promote security of land tenure and reduce land disputes. Therefore land administration systems are not ‘just handling only geographic information’ as they represent a lawfully meaningful relationship amongst people, between people and land. As the land administration activity on the one hand deals with huge amounts of data, which moreover are of a very dynamic in nature, and on the other hand requires a continuous maintenance process, the role of information technology is of strategic importance. So the present study develops a case study of land information system using cadastral techniques of Tirat and Chalbalpur rural region of Raniganj in Barddhaman district which contains cadastral information.

Friction stir welding (FSW) is a new entrant in welding technology and getting a defect-free weld is the final objective. But different defects are generated due to various reasons and needs to be analyzed to eliminate them. The aim of the research work is to identify and classify different kinds of surface defects generally encountered during the FSW process using digital image processing techniques. The defects on the surface of the weld are identified using image pyramid and image reconstruction algorithms. Further, using these algorithms the defects can be classified into voids, grooves, cracks, key-hole and flash with the help of unique features of each kind of defect. Vertical intensity plot and the area plot of the defect blobs are represented for the proper localization and analysis of severity of defects.

Denudation of spoil dump due to heavy rain is a major problem for many Indian mines specially the Iron ore mines located at high altitudes. An attempt is made here to determine the extent of soil erosion effect on the dumps due to rain water flow on the dump surfaces. Computerised techniques are used to determine flow lines along which flow of the surface runoff would possibly take place. These flow are responsible for carrying down waste material to the base of the spoil dump. Volume estimate of the erosion is also carried out here using standard techniques.