Blast vibration monitoring in opencast mines

In this report the blast vibration monitoring techniques is studied. Ground vibration induced by blasting practices in mines has become a serious environmental issue in today’s scenario. Various factors influence the blast vibration being produced from the blasting practices such as the pattern of blasting, drilling pattern, quality and quantity of explosives being used, delay pattern etc. Also the vibration which is being generated by the blasting practices is comprised of two types of waves, body and surface waves. Some of the after blast features are also required to be studied in order to determine the safe blasting practices. Three types of adverse effects are generally associated with the blasting practices, Air blast, Fly rock and Ground vibration, However the amplitude, frequency and duration of the ground vibration is determined by the non-controllable(local geology, rock characteristic and distances of the structure from blast site) and controllable parameters(Charge weight, Delay interval, Type of explosive ,Direction of blast progression, Coupling, confinement, Spatial distribution of charges, Burden, spacing and specification and specific charge). For the purpose of determination of the safe Charge per Delay a number of researchers have given various theories and equations. The feasibility of the CMRI equation is studied in this report. Also there are various equipment’s available globally for measuring the ground vibration and air blast. In the present study Minimate Blaster specification has been studied in detail. All the blasting operations were obtained at different- different distances. According graphs were plotted for the data’s available from the blasting practices and the safe Charge per Delay and Peak Particle Velocity is determined for the mine in accordance with the DGMS regulations

Activity report analysis with automatic single or multispan answer extraction

In the era of loT (Internet of Things) we are surrounded by a plethora of Al enabled devices that can transcribe images, video, audio, and sensors signals into text descriptions. When such transcriptions are captured in activity reports for monitoring, life logging and anomaly detection applications, a user would typically request a summary or ask targeted questions about certain sections of the report they are interested in. Depending on the context and the type of question asked, a question answering (QA) system would need to automatically determine whether the answer covers single-span or multi-span text components. Currently available QA datasets primarily focus on single span responses only (such as SQuAD[4]) or contain a low proportion of examples with multiple span answers (such as DROP[3]). To investigate automatic selection of single/multi-span answers in the use case described, we created a new smart home environment dataset comprised of questions paired with single-span or multi-span answers depending on the question and context queried. In addition, we propose a RoBERTa[6]-based multiple span extraction question answering (MSEQA) model returning the appropriate answer span for a given question. Our experiments show that the proposed model outperforms state-of-the-art QA models on our dataset while providing comparable performance on published individual single/multi-span task datasets

Knowledge Graph Reasoning Based on Attention GCN

We propose a novel technique to enhance Knowledge Graph Reasoning by combining Graph Convolution Neural Network (GCN) with the Attention Mechanism. This approach utilizes the Attention Mechanism to examine the relationships between entities and their neighboring nodes, which helps to develop detailed feature vectors for each entity. The GCN uses shared parameters to effectively represent the characteristics of adjacent entities. We first learn the similarity of entities for node representation learning. By integrating the attributes of the entities and their interactions, this method generates extensive implicit feature vectors for each entity, improving performance in tasks including entity classification and link prediction, outperforming traditional neural network models. To conclude, this work provides crucial methodological support for a range of applications, such as search engines, question-answering systems, recommendation systems, and data integration tasks

Thermal analysis of various duct cross sections using altair hyperworks software

In this work thermal analysis and comparison of various duct cross sections is done computationally using Altair Hyperworks Software. Simple Analytical results were obtained for conduction and convection through the ducts which can be used to build up thermal circuit. The inner surface of all ducts is maintained at constant temperature and ambient air is at certain temperature that is less than inner surface temperature of pipe. Due to temperature difference heat will flow from higher temperature to lower temperature. Due to temperature difference heat will flow from higher temperature to lower temperature. The material of pipe provides conductive resistance and air provides convective resistance. Hence this is a mix mode of heat transfer. The heat transfer takes place in one dimension only and properties are considered to be isotropic. The ducts are assumed to be made of aluminium having known thermal conductivity and density. The surroundings of ducts have known convective heat transfer coefficient and temperature. The results are obtained on hyperview which are for heat flux, temperature gradient and grid temperature. The different characteristics can be obtained by varying the material of the ducts. Keywords: Ducts, Altair Hyperwork

Sol-gel Synthesis and Characterisation of NanocrystallineYttrium Aluminum Garnet Nanopowder

The synthesis of  yttrium aluminum garnet (YAG) (Y3 Al5O12) nanopowder was carried outby sol-gel method. Y(NO3)3.6H2O, Al(NO3)3.9H2O in the presence of citric acid as complexing agent were used as starting materials. YAG nanopowder was characterised by FTIR, TGA, andXRD. To get phase-pure nanocrystalline YAG powder at relatively lower temperature, calcinationat various temperatures was studied and calcination temperature was optimised. Particle size,estimated by XRD using Scherrer's equation, was found to be 28Œ35 nm which was further confirmed by transmission electron microscopy. The particle morphology was studied by SEM.Defence Science Journal, 2008, 58(4), pp.545-549, DOI:http://dx.doi.org/10.14429/dsj.58.167

A decision model for a strategic closed-loop supply chain to reclaim End-of-Life Vehicles

Closed-loop supply chain strategies for End-of-Life (EOL) products and their logistics operations have received greater attention in recent years from supply chain research community. These strategies include warranty–based acquisition, quantity–based acquisition, quality–based acquisition, centrally coordinated logistics operations and third-party logistics (3PL) operations. The proposed research integrates two important aspects of an automobile's closed-loop supply chain strategy. The first aspect is optimal transportation planning for raw material parts, newly manufactured and EOL products in a closed-loop supply chain, using demand, collection rate and capacity of associated facilities in the network as functional parameters. We formulated a mixed integer mathematical model for the closed-loop supply chain network with a multi-echelon inventory, multi-period planning and multi-product scenario, which are used to compute the maximum contribution margin generated through different strategies. The second aspect pertains to using the output of the proposed model in first stage to handle the sequential form of a cooperative game. The proposed two–phase decision model analyzes the realization times and delivery limits of different products as an indicator of swapping different strategies. We analyze three instances to understand and validate the applicability of the model. In these scenarios, sensitivity analysis has been performed to demonstrate the robustness of the proposed model. We present managerial insights, leading to flexibility in decision making. It is observed that the demand, collection rate and capacity of network facilities create highly sensitive trilogy for the contribution margin of proposed network. The outcome of this research firstly confers optimal amounts of mass flows in the closed loop supply chain network from a state of the end product (new products, recycled products and non–recycled used products) to a state of the raw material (ferrous metal, non-ferrous metal and shredder fluff). Secondly, authors culminated a confound dichotomy among all reintegration strategies (conveyance, acquisition and cannibalization) by distinct enumeration and quantification (regarding realization times and delivery limits) of each one to forge a robust planning horizon for original equipment manufacturer

Evaluation of Nutritional value of Mollugo cerviana Ser. growing wild in Bikaner District of Rajasthan

Plants of arid and semiarid zones are good source of phytochemically important compounds. Mollugo cerviana is a common wild plant of Bikaner and surrounding areas and it has been evaluated for the nutritive contents from root, shoot and fruits. The results obtained by AOAC (1995) method shows that the plant is rich in nutritive contents

Strategic design for inventory and production planning in closed-loop hybrid systems

This research studies inventory and production planning in a closed-loop system while considering both manufacturing and remanufacturing. We studied five inventory and production planning models under the continuous and periodic review systems using a discrete event simulation. Under the above review policies, different demand and return rates, as well as manufacturing and remanufacturing lead times, are considered. The total recoverable and serviceable inventory costs and production order variance are considered as the main performance indicators. From the total inventory cost viewpoint, our findings reveal the trade-off between stochastic demand, stochastic lead times, and review periods. It was found that the periodic review system outperforms the continuous review system for higher values of the review period and return to demand rate ratio. Furthermore, remanufacturing demonstrates an appreciable contribution to low order variance in periodic review systems for high values of return to demand ratio and lead times