Out-of-step protection of one or a group of synchronous generators is unreliable in a power system which has significant renewable power penetration. In this work, an innovative out-of-step protection algorithm using ...Out-of-step protection of one or a group of synchronous generators is unreliable in a power system which has significant renewable power penetration. In this work, an innovative out-of-step protection algorithm using wavelet transform and deep learning is presented to protect synchronous generators and transmission lines. The specific patterns are generated from both stable and unstable power swing, and three-phase fault using the wavelet transform technique. Data containing 27,008 continuous samples of 48 different features is used to train a two-layer feed-forward network. The proposed algorithm gives an automatic, setting free and highly accurate classification for the three-phase fault, stable power swing, and unstable power swing through pattern recognition within a half cycle. The proposed algorithm uses the Kundur 2-area system and a 29-bus electric network for testing under different swing center locations and levels of renewable power penetration. Hardware-in-the-loop (HIL) tests show the hardware compatibility of the developed out-of-step algorithm. The proposed algorithm is also compared with recently reported algorithms. The comparison and test results on different large-scale systems show that the proposed algorithm is simple, fast, accurate, and HIL tested, and not affected by changes in power system parameters.展开更多
This paper propose a computerized method of magnetic resonance imaging （MR/） of brain binarization for the uses of preprocessing of features extraction and brain ab- normality identification. One of the main problem...This paper propose a computerized method of magnetic resonance imaging （MR/） of brain binarization for the uses of preprocessing of features extraction and brain ab- normality identification. One of the main problems of MR/ binarization is that many pixels of brain part cannot be cor- rectly binarized due to extensive black background or large variation in contrast between background and foreground of MR/. We have proposed a binarization that uses mean, vari- ance, standard deviation and entropy to determine a thresh- old value followed by a non-gamut enhancement which can overcome the binarization problem of brain component. The proposed binarization technique is extensively tested with a variety of MR/and generates good binarization with im- proved accuracy and reduced error. A comparison is carried out among the obtained outcome with this innovative method with respect to other well-known methods.展开更多
Surat city, the commercial capital of Gujarat state, India is situated at latitude 21°06’ to 21°15’ N and longitude 72°45' to 72°54'E on the bank of river Tapi and is affected by flood on...Surat city, the commercial capital of Gujarat state, India is situated at latitude 21°06’ to 21°15’ N and longitude 72°45' to 72°54'E on the bank of river Tapi and is affected by flood once in every five years since last hundred years. Present study describes the application of HEC-RAS model with integration of GIS for delineation of flood plain. Digital Elevation Model (DEM) of Surat city is used as main input for flood inundation mapping. River section near Nehru Bridge is used as sample case to simulate flood flow. Discharges equal to food return period for 25 and 32 (worst flood year) have been used for investigation of flood scenario. Outcome of the research clearly indicates that most of the area of the Surat city is submerged for a depth of 2.5 to 4.0 m when the discharge released from Ukai dam equals to return period of 32 years (25768.09 Cumecs).展开更多
Over the last few years, the Internet of Things (IoT) has become an omnipresent term. The IoT expands the existing common concepts, anytime and anyplace to the connectivity for anything. The proliferation in IoT offer...Over the last few years, the Internet of Things (IoT) has become an omnipresent term. The IoT expands the existing common concepts, anytime and anyplace to the connectivity for anything. The proliferation in IoT offers opportunities but may also bear risks. A hitherto neglected aspect is the possible increase in power consumption as smart devices in IoT applications are expected to be reachable by other devices at all times. This implies that the device is consuming electrical energy even when it is not in use for its primary function. Many researchers’ communities have started addressing storage ability like cache memory of smart devices using the concept called—Named Data Networking (NDN) to achieve better energy efficient communication model. In NDN, memory or buffer overflow is the common challenge especially when internal memory of node exceeds its limit and data with highest degree of freshness may not be accommodated and entire scenarios behaves like a traditional network. In such case, Data Caching is not performed by intermediate nodes to guarantee highest degree of freshness. On the periodical updates sent from data producers, it is exceedingly demanded that data consumers must get up to date information at cost of lease energy. Consequently, there is challenge in maintaining tradeoff between freshness energy consumption during Publisher-Subscriber interaction. In our work, we proposed the architecture to overcome cache strategy issue by Smart Caching Algorithm for improvement in memory management and data freshness. The smart caching strategy updates the data at precise interval by keeping garbage data into consideration. It is also observed from experiment that data redundancy can be easily obtained by ignoring/dropping data packets for the information which is not of interest by other participating nodes in network, ultimately leading to optimizing tradeoff between freshness and energy required.展开更多
The analysis of real social, biological and technological networks has attracted a lot of attention as technological advances have given us a wealth of empirical data. For, analysis and investigation time varying grap...The analysis of real social, biological and technological networks has attracted a lot of attention as technological advances have given us a wealth of empirical data. For, analysis and investigation time varying graphs are used to understand the relationship, contact duration, repeated occurrence of contact. It is under exploring in intermittently connected networks. Now, by extending the same concept in intermittent networks, the efficiency of the routing protocol can be improved. This paper discusses about the temporal characterizing algorithm. Such characterization can help in accurately understanding dynamic behaviors and taking appropriate routing decisions. Therefore, the present research provokes exploring different possibilities of utilizing the same time varying network analyses and designing an Adaptive Routing protocol using temporal distance metric. The adaptive routing protocol is implemented using ONE simulator and is compared with the Epidemic and PropHET for delivery ratio, overhead and the number of dropped messages. The result reveals that Adaptive routing performs better than Epidemic and PropHET for real and synthetic datasets.展开更多
Pleurotus sajorcaju(P.sajorcaju),an edible and non-toxic mushroom,was evaluated as antioxidant,antitumor,an-ti-inflammatory and antihypertensive activities.P.sajorcaju is a good source of carbohydrates,dietary fiber,e...Pleurotus sajorcaju(P.sajorcaju),an edible and non-toxic mushroom,was evaluated as antioxidant,antitumor,an-ti-inflammatory and antihypertensive activities.P.sajorcaju is a good source of carbohydrates,dietary fiber,essential amino acids,minerals,vitamin B,folic acid and steroids.Anti-inflammatory,immunomodulatory and analgesic activities of aqueous and methanolic extracts of mycelium of P.sajorcaju were investigated(data is not shown).This finding suggests that extracts of P.sajorcaju can be used against inflammatory and autoimmune disease.So,P.sajorcaju examined for its antiarthritic activity.Plant was collected and separately extracted with water and methanol.For antiarthritic activity 500 and 1 000 mg·kg-1 of both extracts were prepared and ad-ministered by oral route.Body weight,paw edema(inflammation),hematological parameter,spleen weight,radiological and histologi-cal analysis of bone damage were assessed in rats with Freund's adjuvant induced paw inflammation.Both extracts showed significant and dose-dependent anti-inflammatory and anti-arthritic effects compared to control group.展开更多
文摘Out-of-step protection of one or a group of synchronous generators is unreliable in a power system which has significant renewable power penetration. In this work, an innovative out-of-step protection algorithm using wavelet transform and deep learning is presented to protect synchronous generators and transmission lines. The specific patterns are generated from both stable and unstable power swing, and three-phase fault using the wavelet transform technique. Data containing 27,008 continuous samples of 48 different features is used to train a two-layer feed-forward network. The proposed algorithm gives an automatic, setting free and highly accurate classification for the three-phase fault, stable power swing, and unstable power swing through pattern recognition within a half cycle. The proposed algorithm uses the Kundur 2-area system and a 29-bus electric network for testing under different swing center locations and levels of renewable power penetration. Hardware-in-the-loop (HIL) tests show the hardware compatibility of the developed out-of-step algorithm. The proposed algorithm is also compared with recently reported algorithms. The comparison and test results on different large-scale systems show that the proposed algorithm is simple, fast, accurate, and HIL tested, and not affected by changes in power system parameters.
文摘This paper propose a computerized method of magnetic resonance imaging （MR/） of brain binarization for the uses of preprocessing of features extraction and brain ab- normality identification. One of the main problems of MR/ binarization is that many pixels of brain part cannot be cor- rectly binarized due to extensive black background or large variation in contrast between background and foreground of MR/. We have proposed a binarization that uses mean, vari- ance, standard deviation and entropy to determine a thresh- old value followed by a non-gamut enhancement which can overcome the binarization problem of brain component. The proposed binarization technique is extensively tested with a variety of MR/and generates good binarization with im- proved accuracy and reduced error. A comparison is carried out among the obtained outcome with this innovative method with respect to other well-known methods.
文摘Surat city, the commercial capital of Gujarat state, India is situated at latitude 21°06’ to 21°15’ N and longitude 72°45' to 72°54'E on the bank of river Tapi and is affected by flood once in every five years since last hundred years. Present study describes the application of HEC-RAS model with integration of GIS for delineation of flood plain. Digital Elevation Model (DEM) of Surat city is used as main input for flood inundation mapping. River section near Nehru Bridge is used as sample case to simulate flood flow. Discharges equal to food return period for 25 and 32 (worst flood year) have been used for investigation of flood scenario. Outcome of the research clearly indicates that most of the area of the Surat city is submerged for a depth of 2.5 to 4.0 m when the discharge released from Ukai dam equals to return period of 32 years (25768.09 Cumecs).
文摘Over the last few years, the Internet of Things (IoT) has become an omnipresent term. The IoT expands the existing common concepts, anytime and anyplace to the connectivity for anything. The proliferation in IoT offers opportunities but may also bear risks. A hitherto neglected aspect is the possible increase in power consumption as smart devices in IoT applications are expected to be reachable by other devices at all times. This implies that the device is consuming electrical energy even when it is not in use for its primary function. Many researchers’ communities have started addressing storage ability like cache memory of smart devices using the concept called—Named Data Networking (NDN) to achieve better energy efficient communication model. In NDN, memory or buffer overflow is the common challenge especially when internal memory of node exceeds its limit and data with highest degree of freshness may not be accommodated and entire scenarios behaves like a traditional network. In such case, Data Caching is not performed by intermediate nodes to guarantee highest degree of freshness. On the periodical updates sent from data producers, it is exceedingly demanded that data consumers must get up to date information at cost of lease energy. Consequently, there is challenge in maintaining tradeoff between freshness energy consumption during Publisher-Subscriber interaction. In our work, we proposed the architecture to overcome cache strategy issue by Smart Caching Algorithm for improvement in memory management and data freshness. The smart caching strategy updates the data at precise interval by keeping garbage data into consideration. It is also observed from experiment that data redundancy can be easily obtained by ignoring/dropping data packets for the information which is not of interest by other participating nodes in network, ultimately leading to optimizing tradeoff between freshness and energy required.
文摘The analysis of real social, biological and technological networks has attracted a lot of attention as technological advances have given us a wealth of empirical data. For, analysis and investigation time varying graphs are used to understand the relationship, contact duration, repeated occurrence of contact. It is under exploring in intermittently connected networks. Now, by extending the same concept in intermittent networks, the efficiency of the routing protocol can be improved. This paper discusses about the temporal characterizing algorithm. Such characterization can help in accurately understanding dynamic behaviors and taking appropriate routing decisions. Therefore, the present research provokes exploring different possibilities of utilizing the same time varying network analyses and designing an Adaptive Routing protocol using temporal distance metric. The adaptive routing protocol is implemented using ONE simulator and is compared with the Epidemic and PropHET for delivery ratio, overhead and the number of dropped messages. The result reveals that Adaptive routing performs better than Epidemic and PropHET for real and synthetic datasets.
基金supported by the Department of Pharmacology, S.K. Patel College of Pharmaceutical Education and Research,Ganpat University,Gujarat,India
文摘Pleurotus sajorcaju(P.sajorcaju),an edible and non-toxic mushroom,was evaluated as antioxidant,antitumor,an-ti-inflammatory and antihypertensive activities.P.sajorcaju is a good source of carbohydrates,dietary fiber,essential amino acids,minerals,vitamin B,folic acid and steroids.Anti-inflammatory,immunomodulatory and analgesic activities of aqueous and methanolic extracts of mycelium of P.sajorcaju were investigated(data is not shown).This finding suggests that extracts of P.sajorcaju can be used against inflammatory and autoimmune disease.So,P.sajorcaju examined for its antiarthritic activity.Plant was collected and separately extracted with water and methanol.For antiarthritic activity 500 and 1 000 mg·kg-1 of both extracts were prepared and ad-ministered by oral route.Body weight,paw edema(inflammation),hematological parameter,spleen weight,radiological and histologi-cal analysis of bone damage were assessed in rats with Freund's adjuvant induced paw inflammation.Both extracts showed significant and dose-dependent anti-inflammatory and anti-arthritic effects compared to control group.
