Austenitic stainless steel 304 was deep drawn with different blank diameters under warm conditions using 20 t hydraulic press. A number of deep drawing experiments both at room temperature and at 150 ℃ were conducted...Austenitic stainless steel 304 was deep drawn with different blank diameters under warm conditions using 20 t hydraulic press. A number of deep drawing experiments both at room temperature and at 150 ℃ were conducted to study the metallography. Also, tensile test experiments were conducted on a universal testing machine up to 700 ℃ and the broken specimens were used to study the fractography of the material using scanning electron microscopy in various regions. The microstructure changes were observed at limiting draw ratio （LDR） when the cup is drawn at different temperatures. In austenitic stainless steel, martensite formation takes place that is not only affected by temperature, hut also influenced by the rate at which the material is deformed. In austenitic stainless steel 304, dynamic strain regime appears above 300 ℃ and it decreases the formability of material due to brittle fracture as studied in its fractography. From the metallographic studies, the maximum LDR of the material is observed at 150 ℃ before dynamic strain regime. It is also observed that at 150 ℃, grains are coarse in the drawn cups at LDR.展开更多
Rapid growth in the transfer of multimedia information over the Internet requires algorithms to retrieve a queried image from large image database repositories.The proposed content-based image retrieval(CBIR)uses Gaus...Rapid growth in the transfer of multimedia information over the Internet requires algorithms to retrieve a queried image from large image database repositories.The proposed content-based image retrieval(CBIR)uses Gaussian-Hermite moments as the low-level features.Later these features are compressed with principal component analysis.The compressed feature set is multiplied with the weight matrix array,which has the same size as the feature vector.Hybrid firefly and grey wolf optimization(FAGWO)is used to prevent the premature convergence of optimization in the firefly algorithm.The retrieval of images in CBIR is carried out in an OpenCV python environment with K-nearest neighbours and random forest algorithm classifiers.The fitness function for FAGWO is the accuracyof the classifier.The FAGWO algorithm derives the optimum weights from a randomlygenerated initial population.When these optimized weights are applied,the proposed algorithm shows better precision/recall and efficiency than other techniques such as exact legendre moments,Region-based image retrieval,K-means clustering and Color descriptor wavelet-based texture descriptor retrieval technique.In terms of optimization,hybrid FAGWO outperformed various optimization techniques(when used alone)like Particle Swarm Optmization,Genetic Algorithm,Grey-Wolf Optimization and FireFly algorithm.展开更多
A major problem in networking has always been energy consumption.Battery life is one parameter which could help improve Energy Efficiency.Existing research on wireless networking stresses on reducing signaling message...A major problem in networking has always been energy consumption.Battery life is one parameter which could help improve Energy Efficiency.Existing research on wireless networking stresses on reducing signaling messages or time required for data transfer for addressing energy consumption issues.Routing or Forwarding packets in a network between the network elements like routers,switches,wireless access points,etc.,is complex in conventional networks.With the advent of Software Defined Networking(SDN)for 5G network architectures,the distributed networking has embarked onto centralized networking,wherein the SDN Controller is responsible for decision making.The controller pushes its decision onto the network elements with the help of a control plane protocol termed OpenFlow.Decentralized networks have been largely in use because of their ease in physical and logically setting the administrative hierarchies.The centralized controller deals with the policy funding and the protocols used for routing procedures are designated by the decentralized controller.Ambience Awake is a location centered routing protocol deployed in the 5G network architecture with OpenFlow model.The Ambience Awake mechanism relies on the power consumption of the network elements during the packet transmission for unicast and multicast scenarios.The signalling load and the routing overhead witnessed an improvement of 30%during the routing procedure.The proposed routing mechanism run on the top of the decentralized SDN controller proves to be 19.59%more efficient than the existing routing solutions.展开更多
It is often very difficult for the patient to tell the difference between angina symptoms and heart attack symptoms, so it is very important to recognize the signs of heart attack and immedi-ately seek medical attenti...It is often very difficult for the patient to tell the difference between angina symptoms and heart attack symptoms, so it is very important to recognize the signs of heart attack and immedi-ately seek medical attention. A practical case of this type of remote consultation is examined in this paper. To deal with the huge amount of electrocardiogram (ECG) data for analysis, storage and transmission;an efficient ECG compression technique is needed to reduce the amount of data as much as possible while pre-serving the clinical significant signal for cardiac diagnosis. Here the ECG signal is analyzed for various parameters such as heart rate, QRS-width, etc. Then the various parameters and the compressed signal can be transmitted with less channel capacity. Comparison of various ECG compression techniques like TURNING POINT, AZTEC, CORTES, FFT and DCT it was found that DCT is the best suitable compression technique with compression ratio of about 100:1. In addition, different techniques are available for implementation of hardware components for signal pickup the virtual im-plementation with labview is also used for analysis of various cardiac parameters and to identify the abnormalities like Tachycardia, Bradycardia, AV Block, etc. Both hardware and virtual implementation are also detailed in this context.展开更多
基金Sponsored by Department of Science and Technology Government of India(SR/S3/MERC/0129/2012)
文摘Austenitic stainless steel 304 was deep drawn with different blank diameters under warm conditions using 20 t hydraulic press. A number of deep drawing experiments both at room temperature and at 150 ℃ were conducted to study the metallography. Also, tensile test experiments were conducted on a universal testing machine up to 700 ℃ and the broken specimens were used to study the fractography of the material using scanning electron microscopy in various regions. The microstructure changes were observed at limiting draw ratio （LDR） when the cup is drawn at different temperatures. In austenitic stainless steel, martensite formation takes place that is not only affected by temperature, hut also influenced by the rate at which the material is deformed. In austenitic stainless steel 304, dynamic strain regime appears above 300 ℃ and it decreases the formability of material due to brittle fracture as studied in its fractography. From the metallographic studies, the maximum LDR of the material is observed at 150 ℃ before dynamic strain regime. It is also observed that at 150 ℃, grains are coarse in the drawn cups at LDR.
文摘Rapid growth in the transfer of multimedia information over the Internet requires algorithms to retrieve a queried image from large image database repositories.The proposed content-based image retrieval(CBIR)uses Gaussian-Hermite moments as the low-level features.Later these features are compressed with principal component analysis.The compressed feature set is multiplied with the weight matrix array,which has the same size as the feature vector.Hybrid firefly and grey wolf optimization(FAGWO)is used to prevent the premature convergence of optimization in the firefly algorithm.The retrieval of images in CBIR is carried out in an OpenCV python environment with K-nearest neighbours and random forest algorithm classifiers.The fitness function for FAGWO is the accuracyof the classifier.The FAGWO algorithm derives the optimum weights from a randomlygenerated initial population.When these optimized weights are applied,the proposed algorithm shows better precision/recall and efficiency than other techniques such as exact legendre moments,Region-based image retrieval,K-means clustering and Color descriptor wavelet-based texture descriptor retrieval technique.In terms of optimization,hybrid FAGWO outperformed various optimization techniques(when used alone)like Particle Swarm Optmization,Genetic Algorithm,Grey-Wolf Optimization and FireFly algorithm.
文摘A major problem in networking has always been energy consumption.Battery life is one parameter which could help improve Energy Efficiency.Existing research on wireless networking stresses on reducing signaling messages or time required for data transfer for addressing energy consumption issues.Routing or Forwarding packets in a network between the network elements like routers,switches,wireless access points,etc.,is complex in conventional networks.With the advent of Software Defined Networking(SDN)for 5G network architectures,the distributed networking has embarked onto centralized networking,wherein the SDN Controller is responsible for decision making.The controller pushes its decision onto the network elements with the help of a control plane protocol termed OpenFlow.Decentralized networks have been largely in use because of their ease in physical and logically setting the administrative hierarchies.The centralized controller deals with the policy funding and the protocols used for routing procedures are designated by the decentralized controller.Ambience Awake is a location centered routing protocol deployed in the 5G network architecture with OpenFlow model.The Ambience Awake mechanism relies on the power consumption of the network elements during the packet transmission for unicast and multicast scenarios.The signalling load and the routing overhead witnessed an improvement of 30%during the routing procedure.The proposed routing mechanism run on the top of the decentralized SDN controller proves to be 19.59%more efficient than the existing routing solutions.
文摘It is often very difficult for the patient to tell the difference between angina symptoms and heart attack symptoms, so it is very important to recognize the signs of heart attack and immedi-ately seek medical attention. A practical case of this type of remote consultation is examined in this paper. To deal with the huge amount of electrocardiogram (ECG) data for analysis, storage and transmission;an efficient ECG compression technique is needed to reduce the amount of data as much as possible while pre-serving the clinical significant signal for cardiac diagnosis. Here the ECG signal is analyzed for various parameters such as heart rate, QRS-width, etc. Then the various parameters and the compressed signal can be transmitted with less channel capacity. Comparison of various ECG compression techniques like TURNING POINT, AZTEC, CORTES, FFT and DCT it was found that DCT is the best suitable compression technique with compression ratio of about 100:1. In addition, different techniques are available for implementation of hardware components for signal pickup the virtual im-plementation with labview is also used for analysis of various cardiac parameters and to identify the abnormalities like Tachycardia, Bradycardia, AV Block, etc. Both hardware and virtual implementation are also detailed in this context.
