Recent advancement in low-cost cameras has facilitated surveillance in various developing towns in India.The video obtained from such surveillance are of low quality.Still counting vehicles from such videos are necess...Recent advancement in low-cost cameras has facilitated surveillance in various developing towns in India.The video obtained from such surveillance are of low quality.Still counting vehicles from such videos are necessity to avoid traf-fic congestion and allows drivers to plan their routes more precisely.On the other hand,detecting vehicles from such low quality videos are highly challenging with vision based methodologies.In this research a meticulous attempt is made to access low-quality videos to describe traffic in Salem town in India,which is mostly an un-attempted entity by most available sources.In this work profound Detection Transformer(DETR)model is used for object(vehicle)detection.Here vehicles are anticipated in a rush-hour traffic video using a set of loss functions that carry out bipartite coordinating among estimated and information acquired on real attributes.Every frame in the traffic footage has its date and time which is detected and retrieved using Tesseract Optical Character Recognition.The date and time extricated and perceived from the input image are incorporated with the length of the recognized objects acquired from the DETR model.This furnishes the vehicles report with timestamp.Transformer Timeseries Prediction Model(TTPM)is proposed to predict the density of the vehicle for future prediction,here the regular NLP layers have been removed and the encoding temporal layer has been modified.The proposed TTPM error rate outperforms the existing models with RMSE of 4.313 and MAE of 3.812.展开更多
The Internet of Things(IoT)is converting today’s physical world into a complex and sophisticated network of connected devices on an enormous scale.The existing malicious node detection mechanism in traditional approa...The Internet of Things(IoT)is converting today’s physical world into a complex and sophisticated network of connected devices on an enormous scale.The existing malicious node detection mechanism in traditional approaches lacks in transparency,availability,or traceability of the detection phase.To overcome these concerns,we provide a decentralized technique using blockchain technology.Despite the fact that blockchain technology is applicable to create that type of models,existing harmony set of instructions are susceptible to do violence to such as DoS and Sybil,making blockchain systems unfeasible.Here,a new Proof-of-Improved-Participation(PoIP)harmony instruction was suggested that benefits the participation rules to select honest peers for mining while limiting malicious peers.Under an evaluation the PoIP outperforms the Proof-of-Work(PoW)instructions are demonstrated,Proof of Stake(PoS)instructions in terms of energy consumption,accuracy,and bandwidth.To compare the three consensus protocols with respect to efficiency,we build a lightweight mining model andfind that PoIP consensus has greater efficiency than PoW and PoS.PoIP has 25%lower attack risk than existing consensus.As a consequence,our suggested methodology can provide the needed security with minimal attack risk and high accuracy,according to the analysis results.As a result,suggested consensus is more efficient than existing methods in terms of block generation time.Hence we suggest that suggested consensus is very suitable for IoT-based applications especially in healthcare.展开更多
Al-Cu alloy was deformed through equal channel angular pressing(ECAP) by routes A,Ba,Bc and C up to 5 passes.ECAP was done using a 90° die for three different conditions,namely 1) as received,2) solutionised at 7...Al-Cu alloy was deformed through equal channel angular pressing(ECAP) by routes A,Ba,Bc and C up to 5 passes.ECAP was done using a 90° die for three different conditions,namely 1) as received,2) solutionised at 768 K for 1 h and 3) solutionised at 768 K for 1 h + aged at 468 K for 5 h.The microstructure,microhardness and tensile strength were studied for all the three conditions and four routes.Significant improvement in hardness(HV 184 after five passes) and strength(602 MPa after three passes) was observed in solutionised and aged 2014 Al alloy deformed through route Bc.Microstructure evolution was reasonably equiaxed in route Bc with aspect ratio of 1.6.Solutionised and aged 2014 Al alloy deformed through route Bc was identified to have better microstructure and mechanical property than the other processing routes and conditions.展开更多
文摘Recent advancement in low-cost cameras has facilitated surveillance in various developing towns in India.The video obtained from such surveillance are of low quality.Still counting vehicles from such videos are necessity to avoid traf-fic congestion and allows drivers to plan their routes more precisely.On the other hand,detecting vehicles from such low quality videos are highly challenging with vision based methodologies.In this research a meticulous attempt is made to access low-quality videos to describe traffic in Salem town in India,which is mostly an un-attempted entity by most available sources.In this work profound Detection Transformer(DETR)model is used for object(vehicle)detection.Here vehicles are anticipated in a rush-hour traffic video using a set of loss functions that carry out bipartite coordinating among estimated and information acquired on real attributes.Every frame in the traffic footage has its date and time which is detected and retrieved using Tesseract Optical Character Recognition.The date and time extricated and perceived from the input image are incorporated with the length of the recognized objects acquired from the DETR model.This furnishes the vehicles report with timestamp.Transformer Timeseries Prediction Model(TTPM)is proposed to predict the density of the vehicle for future prediction,here the regular NLP layers have been removed and the encoding temporal layer has been modified.The proposed TTPM error rate outperforms the existing models with RMSE of 4.313 and MAE of 3.812.
文摘The Internet of Things(IoT)is converting today’s physical world into a complex and sophisticated network of connected devices on an enormous scale.The existing malicious node detection mechanism in traditional approaches lacks in transparency,availability,or traceability of the detection phase.To overcome these concerns,we provide a decentralized technique using blockchain technology.Despite the fact that blockchain technology is applicable to create that type of models,existing harmony set of instructions are susceptible to do violence to such as DoS and Sybil,making blockchain systems unfeasible.Here,a new Proof-of-Improved-Participation(PoIP)harmony instruction was suggested that benefits the participation rules to select honest peers for mining while limiting malicious peers.Under an evaluation the PoIP outperforms the Proof-of-Work(PoW)instructions are demonstrated,Proof of Stake(PoS)instructions in terms of energy consumption,accuracy,and bandwidth.To compare the three consensus protocols with respect to efficiency,we build a lightweight mining model andfind that PoIP consensus has greater efficiency than PoW and PoS.PoIP has 25%lower attack risk than existing consensus.As a consequence,our suggested methodology can provide the needed security with minimal attack risk and high accuracy,according to the analysis results.As a result,suggested consensus is more efficient than existing methods in terms of block generation time.Hence we suggest that suggested consensus is very suitable for IoT-based applications especially in healthcare.
文摘Al-Cu alloy was deformed through equal channel angular pressing(ECAP) by routes A,Ba,Bc and C up to 5 passes.ECAP was done using a 90° die for three different conditions,namely 1) as received,2) solutionised at 768 K for 1 h and 3) solutionised at 768 K for 1 h + aged at 468 K for 5 h.The microstructure,microhardness and tensile strength were studied for all the three conditions and four routes.Significant improvement in hardness(HV 184 after five passes) and strength(602 MPa after three passes) was observed in solutionised and aged 2014 Al alloy deformed through route Bc.Microstructure evolution was reasonably equiaxed in route Bc with aspect ratio of 1.6.Solutionised and aged 2014 Al alloy deformed through route Bc was identified to have better microstructure and mechanical property than the other processing routes and conditions.
