Project Area Research Articles

Neural network enabled fringe projection through scattering media

The projection of fringes plays an essential role in many applications, such as fringe projection profilometry and structured illumination microscopy. However, these capabilities are significantly constrained in environments affected by optical scattering. Although recent developments in wavefront shaping have effectively generated high-fidelity focal points and relatively simple structured images amidst scattering, the ability to project fringes that cover half of the projection area has not yet been achieved. To address this limitation, this study presents a fringe projector enabled by a neural network, capable of projecting fringes with variable periodicities and orientation angles through scattering media. We tested this projector on two types of scattering media: ground glass diffusers and multimode fibers. For these scattering media, the average Pearson’s correlation coefficients between the projected fringes and their designed configurations are 86.9% and 79.7%, respectively. These results demonstrate the effectiveness of the proposed neural network enabled fringe projector. This advancement is expected to broaden the scope of fringe-based imaging techniques, making it feasible to employ them in conditions previously hindered by scattering effects.

Botanical Observations in the Balimela Project Area, Orissa

This article deals with an account of the vegetation and flora of Balimela dam project area in Koraput district of Orissa. In all a total of about 200 species of flowering plants occurring in the submerging sites are enumerated.

Granular satellite data to assess the potential for nature based solutions at a national scale: a proof of concept with data from Rwanda and Lesotho

ABSTRACT Nature-based Solutions (NbS) form a substantial part of cost-efficient climate change mitigation options. However, public financial flows towards NbS have been limited. Among the factors impeding investments in NbS are challenges in reliable remote project identification and comparison. In this article, we demonstrate a technological solution to these challenges. Using cloud-based satellite data processing and the proliferation of open geospatial data, we developed a methodology to map NbS suitability based on a set of biophysical, pedological, hydrological and climatological criteria. To provide a proof of concept, we identify potential project areas for eight types of NbS in Rwanda and Lesotho. Building on these spatially-explicit NbS suitability data layers (accessible at https://wb-nbs.users.earthengine.app/view/ncs-potential), we develop marginal abatement cost curves for projects in Rwanda and Lesotho. We thus provide a proof of concept for remote identification and project comparison. These technological developments can help investors, such as multilateral donors or governments, alleviate additionality concerns that are implied by local project selection. Key Policy Insights Investment in climate change mitigation through Nature-based Solutions (NbS) is limited, in spite of the large, cost-efficient potential for achieving national and global goals. Remote project identification and comparison can help alleviate some of the impediments to international investment in NbS. Such remote identification and comparison of NbS projects is now possible because of breakthroughs in cloud-based satellite data processing technologies and increased availability of geospatial data. We present a proof of concept, establishing marginal abatement cost curves for climate change mitigation through NbS in Rwanda and Lesotho. Coupled with the institutional improvements necessary to create a reliable intergovernmental carbon credit market, these technological developments have the potential to boost international investment in NbS.

World Bank-Assisted Community-Based Development Project for High-Value Crop Production: Failures and Successes

The government of Punjab has recently implemented a World-Bank-assisted community-based development project for the enhancement of farm productivity in water deficit areas of the Punjab province for 11 years. This paper describes a case study from the Faisalabad division, wherein drip irrigation in conjunction with tunnel technology has improved crop and water productivity of fruits, vegetables and cash crops, optimizing farm incomes. Not only crop yields were optimized, but also there were savings on water (30-45%) and other inputs, reduced incidence of pests and diseases (15-20%), early spring production by 35 days and higher quality of produce, which substantially increased farm incomes (19-41%) along with some environmental benefits. A conservative estimate showed a reduction in unemployment by 5% in project areas. Despite these impressive achievements, a post-project survey showed that 93% of beneficiary farmers abandoned drip irrigation systems, soon after project closure. It emphasized that in the Thal area, only a 4% system rolled back, suggesting the better suitability of the high-efficiency irrigation system for water conservation and productivity enhancement in sandy areas. Post-project farmer-participatory rural appraisal (PRA) shows that drip irrigation was rolled back due to multiple constraints. For example, unsuitable/inefficient design, clogging of drippers/drip lines, non-availability of spare parts, poor response of troubleshooters and top-down approach of the project, prompting better planning and implementation, in the future, for similar projects.

Greening airports: A methodological framework for site assessment and assessing solar PV potential

Due to energy intensiveness and carbon emissions, the aviation sector is under continuous environmental pressure. In this regard, airports have shown keen interest in solar photovoltaic (PV) technology to decarbonize their energy consumption. Implementing onsite solar projects in the airport is challenging due to various technical and safety aspects. Improper siting of solar PV arrays may adversely affect the safety of the passengers. This paper aims to develop a methodological framework for site assessment and potential estimation of PV projects in airport locations. The developed methodology is applied as a case study to seven Indian airports: Madurai, Goa, Raipur, Ahmedabad, Lucknow, Amritsar, and Dehradun. It was understood that the suitable area for solar PV projects on airport land depends on airspace restrictions, built area, and glare occurrence. On average, 30–40 % of the airport land is observed to be built area; hence, it is unavailable for land-based solar PV systems. Among the studied airports, the highest value of technical potential is observed for Raipur airport (21 MW). These conservative estimates provide baseline information for airport planning and development projects. This study is expected to be a reference material for energy specialists, airport stakeholders, and policymakers.

Impact evaluation of a cash-plus programme for children with disabilities in the Xiengkhouang Province in Lao PDR: study protocol for a non-randomised controlled trial

IntroductionMore than 170 countries have implemented disability-targeted social protection programmes, although few have been rigorously evaluated. Consequently, a non-randomised controlled trial is being conducted of a pilot ‘cash-plus’ programme implemented...

Estimation of Mechanical Properties of Aluminum Alloy Based on Indentation Curve and Projection Area of Contact Zone

Estimation of Mechanical Properties of Aluminum Alloy Based on Indentation Curve and Projection Area of Contact Zone

A Land Cover Change Detection Approach to Assess the Effectiveness of Conservation Projects: A Study Case on the EU-Funded LIFE Projects in São Miguel Island, Azores (2002–2021)

A Land Cover Change Detection Approach to Assess the Effectiveness of Conservation Projects: A Study Case on the EU-Funded LIFE Projects in São Miguel Island, Azores (2002–2021)

Influence of molecular descriptors of plant volatilomics on fumigant action against the three major stored product beetle pests.

Plant volatilomics such as essential oils (EOs) and volatile phytochemicals (PCs) are known as potential natural sources for the development of biofumigants as an alternative to conventional fumigant pesticides. This present work was aimed to evaluate the fumigant toxic effect of five selected EOs (cinnamon, garlic, lemon, orange, andpeppermint) and PCs (citronellol, limonene, linalool, piperitone, andterpineol) against the Callosobruchus maculatus, Sitophilus oryzae, and Tribolium castaneum adults. Furthermore, for the estimation of the relationship between molecular descriptors and fumigant toxicity of plant volatiles, quantitative structural activity relationship (QSAR) models were developed using principal component analysis and multiple linear regression. Amongst the tested EOs, garlic EO was found to be the most toxic fumigant. The PCs toxicity analysis revealed that terpineol, limonene, linalool, and piperitone as potential fumigants to C. maculatus (< 20 µL/L air of LC50), limonene and piperitone as potential fumigants to T. castaneum (14.35 and 154.11 µL/L air of LC50, respectively), and linalool and piperitone as potential fumigants to S. oryzae (192.27 and 69.10 µL/L air of LC50, respectively). QSAR analysis demonstrated the role of various molecular descriptors of EOs and PCs on the fumigant toxicity in insect pest species. In specific, dipole and Randic index influence the toxicity in C. maculatus, molecular weight and maximal projection area influence the toxicity in S. oryzae, and boiling point and Dreiding energy influence the toxicity in T. castaneum. The present findings may provide insight of a new strategy to select effective EOs and/or PCs against stored product insect pests.

Research on the new method for visualizing bendability testing of fabrics in multiple directions

PurposeThe current bending test method can only test the bending performance of fabric in one direction at a time. It is not possible to directly observe the bending morphology of fabrics in different directions, and it is necessary to cut samples and repeat the test several times, which takes more time. For this situation, a multidirectional visualization of the fabric bending test method is proposed, using which multiple results can be obtained at one time and the fabric bending can be visualized.Design/methodology/approachAbout 17 fabrics are tested using a self-designed device. The fabrics are cut into special triangles and multiple sets of results in three directions are obtained at once using the device. The experimental specimens are photographed from the above and the transverse elongation length, bending projection area and circumference are extracted after image processing.FindingsThe results show that the correlation coefficients of transverse elongation, bending projected area and circumference are good with the bending length measured by the cantilever method. In which, all three indicators are positively correlated with the bending length. This indicates the good feasibility of the new method.Originality/valueThis method can get the bending index of fabrics in three directions, with five samples in each direction at one time. Meanwhile, it can also visualize the flexural differences between different fabrics and directions of the same fabric. It can provide more efficient testing means for the textile testing field, and the testing efficiency is 15 times of the existing method, which has better theoretical significance and practical values.

Effects of changing water content of clay-content rocks on field cutter consumption rate of roadheaders: a case study of porous ignimbrites

The changing formation characteristics during excavation can cause a higher cutter consumption rate (CCR) of mechanical excavators than theoretically estimated before the project begins. This study investigates the adhesive potential of clay-content porous ignimbrites in increasing water content and their effects on the CCR of roadheaders. For this purpose, the actual field CCR data of roadheaders were recorded for ten cold storage caverns (CSC) projects during the excavation in dry and wet conditions. Then, laboratory tests were carried out on the rock samples collected from project areas. CCRs of roadheaders were theoretically estimated based on the Cerchar abrasivity index of rocks using three different empirical models. The laboratory test results showed that increasing water content reduces the abrasivity and strength of the rocks. The theoretically estimated results also showed that CCR is to be less under saturated conditions. However, actual field data revealed higher CCRs for all CSC projects in wet conditions. Therefore, the adhesion potential of rocks in different water contents was analyzed, and positive relationships were obtained between the field CCR in wet conditions and the adhesion potentials of excavated rocks with 15%, 20%, and 25% water content. New equations were developed to estimate the CCR of roadheaders, especially in excavating rocks that have an adhesive potential to cutters, such as clay-content rocks. It has been concluded that for an accurate CCR estimation, more than theoretical calculations will be required, and changing formation conditions should also be analyzed in detail.

Empowering Farmers to Enhance Water Use Efficiency: Innovative Practices in SSPC

The Sardar Sarovar project, featuring a gravity dam on the Narmada River in Gujarat, stands as one of the largest in terms of concrete volume globally. This study investigates the project's extensive canal network and its impact on agricultural productivity in the command area. Covering a vast expanse across multiple states, the project's irrigation allocation and water management strategies are examined. Special attention is given to addressing soil degradation issues, particularly salinity, and implementing farmer-centered interventions to enhance water use efficiency. Methodologies include land rejuvenation efforts, reclamation of salt-affected land, participatory irrigation management, and promoting improved agricultural practices. Results indicate successful mitigation of soil degradation and increased crop yields through strategic interventions like cotton-castor relay cropping which has demonstrated a 1.5-fold increase in income compared to sole cropping. Intercropping with isabgul/ajwain, and implementing deficit irrigation have resulted in a substantial 43% increase in overall yield, particularly in cumin cultivation. Farmers have also embraced innovative water-saving techniques, such as alternative furrow irrigation and strategic timing of irrigation during critical growth stages, resulting in water savings of 30-35%. However, challenges remain in achieving widespread adoption of participatory irrigation management practices. The study concludes with insights into the necessity of sustained social engineering efforts and community engagement for long-term water resource management and agricultural sustainability in the project area.

Machine learning based tool for the efficient estimation of geometric features of aggregated aerosol particles

While significant progress has been made in developing models for the formation and transport of aerosol aggregates, there is still a need for a simple, versatile tool capable of estimating intrinsic properties of aggregated particles. Scalar friction factor is an important parameter used extensively in the field of aerosol science. The scalar friction factor for non-spherical particles can be computed with the information on two geometric parameters, hydrodynamic radius (Rh) and orientationally averaged projected area (PA), depending on the momentum transfer regime. Although the existing methods for the estimation of these descriptors are efficient, many applications involve frequent estimation of these geometric descriptors, which can be time-consuming. We propose a Machine Learning (ML) based tool that can predict these descriptors using Fractal Dimension, pre-exponential factor, number of monomers and anisotropy factors as the input. An extensive database comprising fractal parameters, anisotropy factors, Rh, and PA is developed for testing and training the ML models. Five ML methods were assessed, with random forest (RF) identified as the most effective. The RF model demonstrated high accuracy in the testing phase, with R-squared value of 0.9875 for Rh and 0.9979 for PA, and average errors of 3.17% and 1.21% for Rh and PA, respectively. The predicted Rh and PA values were then used to estimate other relevant 3-dimensional properties such as mobility diameter, shape factor, and aerodynamic diameter, with the results indicating high accuracy of the prediction tool. Python-based tool offers ease of use, and can be easily integrated with other numerical codes.

Visualization of the rolling motion of spheres connected with a rubber band using an image processing technique

The traditional physics laboratory has adopted a photogate and polarized light to measure rotation motion in a fixed system, but they are not applicable to rolling objects. Computer vision has played an increasingly important role in image analysis. The popularization of mobile phones, cameras and computers makes it possible to measure the rotation of an object in a simple but nonintrusive way in a physics laboratory. A ‘tracker’ has been used to analyze the rotation motion of large objects, such as vehicle wheels, by recognizing the position of a marker. However, it is still challenging to precisely recognize the marker in a small object via simple algorithms in a physics laboratory. In this paper, we introduce a facile image processing technique to visualize the rotation and spin motion of spheres by marking it with two red and green semi-spheres. A basic formula of projection was derived to analyze the expression of spin angles with the projection area of the semi-sphere. The precision and suitability of the image processing technique was proven to be effective through comparison with the photogate measurement technique. The image processing technique has also been used to analyze the rotation and spin motion of two spheres bonded with a rubber band. It provides not only the trajectory of sphere centers, but the evolution of spin angles, orbit diameter and orbit angles of spheres. By analyzing the relationship between spin angles and orbit diameter, it is clear that the rubber band experienced typical transformations between three different phases (twist, coil and supercoil) until the energy was exhausted. The method offers valuable insights into rotational dynamics, showcasing its potential for practical applications in the physics laboratory and in educational contexts.

Detachment of particulate structures from a fiber array due to stretching and simultaneous gas flow

The main cause of high pressure drop and increased energy consumption in a filtration process is the clogging of particulate material in the upstream layers of a depth filter. To alleviate this issue, stress can be introduced into the particulate structure through stretching, which promotes rearrangement and detachment of particle structures, allowing for transfer of some of the clogged particulate material from the upstream layers to downstream void regions. This study aims to extend previous findings from experiments with single fibers to the level of an array. The goal is to analyze the introduction of a multiple stress state by performing stretching experiments with a particle-structure on a fiber array.The stretching tests investigate the influence of different process parameters such as stretching velocity and air flow velocity during stretching on the rearrangement and detachment behavior of a separated particle structures from the fiber array. Rearrangement and detachment of the particle structure are a direct consequences of the stress induced by stretching. The experiments showed a significant increase in relative free projection area of fiber interspaces (RFPI) of up to 160% and thus a large-scale removal of particle material from the fiber interspaces when the flow velocity was increased from 0.05 m/s to 0.8 m/s. Surprisingly, the radial rearrangement of the compact particle structures during stretching resulted in a clogging and blockage of the interfiber spaces (negative RFPI in the range of minimum -54% after the first stretching cycle) and not in a total release of the interfiber spaces. The size of the particle structures in the experiments decreased by about 331 μm with the number of stretching cycles, indirectly confirming the presence of residual structures. Preliminary experiments also confirmed an increased influence on the rearrangement and detachment (removed pariticulater material of about 30%) of particle structures by further increasing the fiber distance of 27 μm and thus introducing a biaxial stretching into the particle structure.

Effective Technique for Face Recognition System Using CNN in Attendance Applications

Face recognition is a personal identification system that uses individual characteristics of a person to recognize the person's identity. The software which is used for face recognition is MATLAB. The project area is image processing. Different types of ordinal measures are derived from magnitude and phase components of Gabor images. Two orientations and two wavelengths are used. Gabor filters are used in the pre-processing step. Array of Gabor filters is called as filter bank. Convolutional Neural Network (CNN) is used for face recognition, which outperforms the traditional techniques. It has three layers in which Convolution Layer is used for feature extraction. Pooling Layer is used, which crops the particular part of the image containing the object and then resizes it, because classification requires fixed size of an image. SoftMax Layer is used to normalize the un-normalized vectors and make the predictions into the probabilistic forms. Loss function is used to figure out the error. Finally, the face of a student is recognized by using CNN.

A Digital Image Method for Calculating the Working Chamber Volume of a Combined Profile Scroll Compressor

Background:: The efficient and accurate calculation of working chamber volume can greatly contribute to the optimized design efficiency of the combined profile scroll compressor, but current papers and patents lack research on the method of calculating the working chamber volume of a combined profile scroll compressor. Objective:: A method of using digital image processing is proposed to efficiently calculate the working chamber volume of a combined scroll compressor. Methods:: This method discretizes and reconstructs the scroll profile that forms the working chamber into a coordinate sequence with equal involute angle intervals. By calculating the relationship between the coordinate sequence and the rotation angle, a general coordinate sequence that forms the working chamber profile is obtained. The real-time changes in the projection image of the working chamber during all the suction, compression and discharge processes can be accurately depicted. The digital image is processed to obtain the actual projection area of the working chamber, and thus, the volume of the working chamber is accurately calculated. Results:: The digital image method can accurately calculate the volume change of the working chamber of the combined profile scroll compressor by selecting the appropriate involute angle interval and digital image size, with a mean relative error of less than 1%. At the beginning of suction and the end of discharge, the calculated volume has been found to have poor accuracy, with a maximum relative error higher than 10%. Conclusion:: The digital image method has been found to have high accuracy, greatly reduce the difficulty of the analysis of the working chamber volume, and promote the design optimization of the combined profile scroll compressor, thus broadening the idea for the calculation method of the working chamber volume of the scroll compressor.

A UAV-Based Single-Lens Stereoscopic Photography Method for Phenotyping the Architecture Traits of Orchard Trees

This article addresses the challenges of measuring the 3D architecture traits, such as height and volume, of fruit tree canopies, constituting information that is essential for assessing tree growth and informing orchard management. The traditional methods are time-consuming, prompting the need for efficient alternatives. Recent advancements in unmanned aerial vehicle (UAV) technology, particularly using Light Detection and Ranging (LiDAR) and RGB cameras, have emerged as promising solutions. LiDAR offers precise 3D data but is costly and computationally intensive. RGB and photogrammetry techniques like Structure from Motion and Multi-View Stereo (SfM-MVS) can be a cost-effective alternative to LiDAR, but the computational demands still exist. This paper introduces an innovative approach using UAV-based single-lens stereoscopic photography to overcome these limitations. This method utilizes color variations in canopies and a dual-image-input network to generate a detailed canopy height map (CHM). Additionally, a block structure similarity method is presented to enhance height estimation accuracy in single-lens UAV photography. As a result, the average rates of growth in canopy height (CH), canopy volume (CV), canopy width (CW), and canopy project area (CPA) were 3.296%, 9.067%, 2.772%, and 5.541%, respectively. The r2 values of CH, CV, CW, and CPA were 0.9039, 0.9081, 0.9228, and 0.9303, respectively. In addition, compared to the commonly used SFM-MVS approach, the proposed method reduces the time cost of canopy reconstruction by 95.2% and of the cost of images needed for canopy reconstruction by 88.2%. This approach allows growers and researchers to utilize UAV-based approaches in actual orchard environments without incurring high computation costs.

New method for calculating the windward area of irregular fragments

Average windward area is an important index for calculating the trajectory, velocity attenuation and terminal effect of explosive fragments. In order to solve the problems that existing theoretical method cannot calculate windward area of irregular fragment and experiment method is not convenient for automatic calculation and has low accuracy, a Monte Carlo subdivision projection simulation algorithm is proposed. The average windward area of arbitrary shaped fragments can be obtained with coordinate translation, random rotation, plane projection, convex-hull triangulation, concave boundary searching and sorting with maximum edge length constraint, subdivision area calculation, and averaging by thousands of cycles. Results show that projection area obtained by the subdivision projection algorithm is basically the same as that obtained by software method of computer aided design. Moreover, the maximum calculation error of the algorithm is less than 7%, and its accuracy is much higher than that of the equivalent ellipsoid method. The average windward area calculated by the Monte Carlo subdivision projection simulation algorithm is consistent with theoretical formula for prefabricated fragments, and the error is less than 3%. The convergence and accuracy of the Monte Carlo subdivision projection algorithm are better than those of the icosahedral uniform orientation method.

A new method of calculating crown projection area and its comparative accuracy with conventional calculations for asymmetric tree crowns

A new method of calculating crown projection area and its comparative accuracy with conventional calculations for asymmetric tree crowns