varunr14/newsummary huggingface dataset:
Online induction machine faults diagnosis is a concern to guarantee the overall production process efficiency . Nowadays the industry demands the integration of smart wireless sensors networks to improve the fault detection in order to reduce cost maintenance and power consumption . Induction motors can develop one or more faults at the same time that can produce sever damages . The origin of most recurrent faults in rotary machines is in the components stator rotor bearing and others . This work presents a novel methodology for the online faults diagnosis in induction motors . This technique uses the smart WSN to obtain the machine condition based on the motor stator current analysis . The implementation of the proposed smart sensor methodology allows the system to perform online fault detection in a fully automated way . Simulation results presented show the efficiency of the proposed method to detect simple and multiple faults in induction machine . It provides detailed analysis to address challenges in designing and deploying WSNs in industrial environments and its reliability . 


Summary: A new method has been proposed for online faults diagnosis in induction motors based on smart WSN combined with motor current signature analysis using FFT. The proposed method is novel as it is important to install low cost sensors and detection mechanisms along with induction machines to achieve short detection time and an automated way of reporting the fault. The system can distinguish a faulty motor from a healthy motor with a probability of 99 with less than 5 of false alarm. Simulation results presented show the efficiency of the proposed method to detect faults in induction machine.
In this paper we propose GeoRank a geographic routing approach for the IPv6 enabled large scale low power and lossy networks . We discuss the main drawbacks of the RPL for P2P communication in large scale 6LoWPAN networks . Then we address such drawbacks by proposing a routing protocol named GeoRank which integrates RPL protocol with the position based routing protocol GOAFR . The results obtained with simulations show that GeoRank finds shorter routes than RPL in high link density conditions and than GOAFR in low link density conditions . Thus GeoRank shows to be adaptive to variable link densities found in large scale networks . Further GeoRank avoids the use of DAO control messages required in RPL while being more scalable in terms of memory usage than storing mode RPL . 


Summary: We combine RPL and GOAFR protocols for IPv6 enabled large scale wireless networks. Main drawbacks of the RPL protocol for P2P communication are discussed. A routing protocol GeoRank is proposed and its scalability is compared to RPL. Simulations were performed on networks extracted from real street maps. GeoRank is adaptive to variable link densities found in large scale networks.
This paper presents a novel methodology for improving efficiency and power consumption of networks on chip NoCs . The proposed approach applies queue length considerations of a modified version of RED algorithm. Moreover a stochastic learning automata based algorithm has been used to optimize the threshold values required in RED algorithm. Furthermore a new architecture has been provided for dynamic flow control of virtual channels. The proposed method contributes to reduction in queue blockages and power consumption in addition to determining an appropriate size for virtual channels. The proposed algorithm was evaluated under various synthetic traffic patterns for different injection rates and trace driven SPLASH 2 benchmark suite. The experimental results demonstrate that the algorithm reduces latency and power consumption by 23 and 52 respectively compared to the conventional NoC. Further compared to Express Virtual Channels EVC scheme it showed 13 and 36 improvement in latency and power consumption respectively. 


Summary: We suggest a new flow control mechanism for improving power and latency. We present a novel methodology to improve the buffer space utilization. Our method reduces queue blockages to determine a proper size for virtual channels. We apply queue length considerations of a modified version of RED algorithm. We utilize learning automata to adapt the threshold values of RED algorithm.
Wireless sensor networks comprise nodes with limited power supply. The dense deployment of nodes on a terrain for monitoring the environment causes contention in wireless channels that leads to interference and high energy consumption. The topology of the network changes frequently because of failure of nodes addition of new nodes and channel fading. Topology control is an important technique for reducing energy consumption interference and maintaining connectivity in the network. This paper provides a survey on state scheduling based topology control techniques for unattended wireless sensor networks. Topology control algorithms for both flat and hierarchical networks are discussed. The algorithms are further categorized according to the key parameters used for state scheduling. The advantages disadvantages and results of the algorithms are tabulated. In addition we highlight future research directions in designing state scheduling based topology control algorithms. 


Summary: We survey the state scheduling based topology control protocols suitable for unattended wireless sensor networks. We categorize the protocols based on the parameters used for state scheduling. Advantages drawbacks and results of existing methods are tabulated. We delineate future research issues in design of state scheduling based topology control protocols.
Mobility currently evolves far beyond owning a car or using public transit services . Passenger transport can be managed by mobility providers by combining and extending various mobility services either directly or by using available mobility service platforms . This paper evaluates the capabilities and technical features of existing mobility service platforms with a special focus on electric mobility . Based upon this evaluation criteria are presented which future platforms should address . As part of this work a marketplace approach is developed which addresses the identified criteria . Potential marketplace architectures are presented which are deemed to establish marketplace interconnectivity . The developed marketplace approach and the proposed architectures contribute to the vision of an interconnected service ecosystem for mobility services . 


Summary: Current electric mobility service marketplaces are proprietary and closed systems. Data exchange among marketplaces is not possible because no common protocol exists. Roaming provides easy service access and extends the end customers operation area. The access at foreign services can be achieved via interconnectivity and roaming. The selected architecture is critical for the success of interconnectivity.
Smart Grid makes use of Information and Communications Technology infrastructures for the management of the generation transmission and consumption of electrical energy to increase the efficiency of remote control and automation systems . One of the most widely accepted standards for power system communication is IEC 61850 which defines services and protocols with different requirements that need to be fulfilled with traffic engineering techniques . In this paper we discuss the implementation of a novel management framework to meet these requirements through control and monitoring tools that provide a global view of the network . With this purpose we provide an overview of relevant Software Defined Networking related approaches and we describe an architecture based on OpenFlow that establishes different types of flows according to their needs and the network status . We present the implementation of the architecture and evaluate its capabilities using the Mininet network emulator . 


Summary: We describe the IEC 61850 communication model and provide an SDN based framework. This framework mainly uses the OpenFlow sFlow and OVSDB protocols. It controls an IEC 61850 network including resource analysis and management. It integrates traffic engineering techniques such as QoS or traffic filtering.
This paper proposes two architectures including an Opportunistic Large Array Concentric Routing Algorithm with Geographic Relay Nodes OLACRA GRN architecture and an Opportunistic Large Array Concentric Routing Algorithm with Relay Nodes OLACRA RN architecture. First the OLACRA GRN architecture with the geographic information of relay nodes reduces node energy consumption and finds the optimum number of relay nodes to forward the data an analysis of the characteristics of the energy model is also presented. Besides the OLACRA RN architecture without the geographic information of relay nodes is proposed which can find the number layer of concentric circles in the sensing field. The optimal number layer of concentric circles is calculated according to the distance between the sink and field boundary. Simulation results show that our proposed OLACRA GRN and OLACRA RN architectures can effectively reduce node energy consumption more than Opportunistic Large Array Concentric Routing Algorithm OLACRA architecture. 


Summary: The optimal number layer of concentric circles is calculated by the distance. We calculate the optimum number of relay nodes to forward the data. Analysis of the characteristics of the energy model. Our proposed architectures can effectively reduce energy consumption of nodes.
This study examines a multicore processor based on a system on chip and configured by a Tensilica Xtensa LX2 . The multicore processor is a heterogeneous configurable dual core processor . In this study one core was used as the host to control the processor chip and the other was used as a slave to extend digital signal processing applications . Each core not only owned its local memory but also shared common data memory . In addition the proposed multicore processors had a virtual memory . This additional memory supported the processor by enabling it to easily manage complex programs it also allowed the two cores to access data from the unified data memory of different tasks . For bus management a bus arbitration mechanism was added to handle the cores and to distribute the priority of asynchronous access requests . The benefits of the proposed structure include avoiding hardwired memory and reducing interface handshaking . To verify the proposed processor it was simulated on the model level using a Petri net graph and on the system level using ARM SoC designer tools . In the performance simulation we found that the lowest latency to cost ratios were achieved using a 32 bit bus interface and a 4 entry data queue . 


Summary: Multicore processor based on SoC configured by Tensilica Xtensa LX2 was examined. One core used as the host to control the processor chip. Other used as slave that is an extension of digital signal processing applications. Lowest latency to cost ratios by a 32 bit bus interface and 4 entry data queue.
The emerging IEEE 802.22 based Wireless Regional Area Network is the first wireless standard based on the Cognitive Radio technology . WRAN is designed to offer wireless access services in a large coverage area by allowing Secondary Users to opportunistically exploit the under utilized licensed portion of spectrum that is primarily allocated for TV services . To enable efficient WRAN communications the operation of a WRAN system should address two types of coexistence problem incumbent co existence and self coexistence . In this paper we investigate the self coexistence problem in a multi cell WRAN system that adopts an exclusive spectrum sharing policy . Specifically we present an adaptive channel allocation scheme based on a cooperative max min weighted fair allocation strategy . The proposed scheme is based on a centralized sensing mechanism that identifies the available spectrum opportunities for the WRAN cells . Our scheme dynamically allocates the available spectrum to the WRAN cells based on their expected traffic loads such that the total number of simultaneously admitted SU transmissions in the WRAN system is maximized . The expected traffic load is accurately estimated using a sample mean estimator based on previously monitored traffic in each cell . Simulation results indicate that our scheme is quite robust to traffic estimation error . Compared to reference spectrum allocation schemes simulation results indicate that the proposed scheme effectively exploits the available spectrum opportunities by increasing the total number of served SU transmissions which consequently results in a significant enhancement in the overall WRAN system performance . 


Summary: We investigate the self coexistence problem in a multi cell WRAN system. We propose an adaptive traffic aware exclusive channel allocation scheme. The proposed scheme is based on a cooperative max min weighted fair mechanism. Compared to other schemes results reveal that our scheme provides significant performance gain.
The Internet of Things has plenty of applications including Smart Grid . IoT enables smooth and efficient utilization of SG . It is assumed as the prevalent illustration of IoT at the moment . IP based communication technologies are used for setting SG communication network but they are challenged by huge volume of delay sensitive data and control information between consumers and utility providers . It is also challenged by numerous security attacks due to resource constraints in smart meters . Sundry schemes proposed for addressing these problems are inappropriate due to high communication computation overhead and latency . In this paper we propose a hybrid Diffie Hellman based lightweight authentication scheme using AES and RSA for session key generation . To ensure message integrity the advantages of hash based message authentication code are exploited . The scheme provides mutual authentication thwarting replay and man in the middle attacks and achieves message integrity while reducing overall communication and computation overheads . 


Summary: Designed an authentication scheme for IoT based smart grid communication. Analyzed the scheme using automated tool ProVerif. The proposed scheme is more lightweight and secure than existing schemes.
This paper presents a reconfigurable fault tolerant routing for Networks on Chip organized into hierarchical units . In case of link faults or failure of switches the proposed approach enables the online adaptation of routing locally within each unit while deadlock freedom is globally ensured in the network . Experimental results of our approach for a 16 16 network show a speedup by a factor of almost four for routing reconfiguration compared to the state of the art approach . Evaluation with transient faults shows that a dedicated reconfiguration unit enables successful reconfiguration of routing tables even in case of high error probabilities . 


Summary: Adding logical hierarchy to networks on chip enables table based routing without excessive chip area overhead. For a 256 node network the routing table occupies only less than 20 of the switches area. Thanks to the hierarchical network organization double data throughput is achieved compared to a flat network of same size. Table based routing can be used to implement fault tolerant routing by reconfiguring table entries. The article shows how table entries can be computed efficiently and how the reconfiguration process can be organized to function reliably even in presence of transmission errors. With proper choice of logical hierarchy the reconfiguration process takes less than one third of the time required by Ariadne the state of the art approach for non hierarchical networks. The additional hardware overhead for fault tolerant routing table reconfiguration amounts to only 6 of the chip area of a network switch.
Government agencies and many non governmental organizations often need to publish sensitive data that contain information about individuals . The sensitive data or private data is an important source of information for the agencies like government and non governmental organization for research and allocation of public funds medical research and trend analysis . The important problem here is publishing data without revealing the sensitive information of individuals . This sensitive or private information of any individual is essential to several data repositories like medical data census data voter registration data social network data and customer data . In this paper a personalized anonymization approach is proposed which preserves the privacy while the sensitive data is published . The main contributions of this paper are three folds the definition of the data collection and publication process the privacy framework model and personalized anonymization approach . The experimental analysis is presented at the end it shows this approach performs better over the distinct l diversity measure probabilistic l diversity measure and k anonymity with t closeness measure . 


Summary: It prevents homogeneity skewness similarity and background knowledge attacks. The privacy is ensured while publishing sensitive data. Only fewer partitioning need to be done for a stronger privacy requirement. It gives better efficiency over the previous approaches.
Botnets continue to be used by attackers to perform various malicious activities on the Internet . Over the past years many botnet detection techniques have been proposed however most of them can not detect botnets in an early stage of their lifecycle or they often depend on a specific command and control protocol . In this paper we propose BotGrab a general botnet detection system that considers both malicious activities and the history of coordinated group activities in the network to identify bot infected hosts . BotGrab tracks suspected hosts participating in some coordinated group activities and calculates a negative reputation score for each of them based on the history of their participation in these activities . A suspected host will be identified as being bot infected if it has a high negative reputation score or performs some malicious activities while having a low negative reputation score . We demonstrate the effectiveness of BotGrab to detect various botnets including HTTP IRC and P2P based botnets using a testbed network consisting of some bot infected hosts . 


Summary: A novel negative reputation system is proposed to detect bot infected hosts. It considers both malicious activities and history of coordinated group activities. A proposed online incremental clustering technique facilitates the online learning. The negative reputation threshold can adjust the sensitivity of the system. It can successfully detect various botnets with a high DR and a low FAR.
This paper focuses on the design of a novel low power twelve transistor static random access memory cell . In the proposed structure two voltage sources are used one connected with the bit line and the other one connected with the bitbar line in order to reduce the swing voltage at the output nodes of the bit and the bitbar lines respectively . Reduction in swing voltage reduces the dynamic power dissipation when the SRAM cell is in working mode . Low threshold voltage transmission gate and two high threshold voltage sleep transistors are used for applying the charge recycling technique . The charge recycling technique reduces leakage current when the transistors change its state from sleep to active and active to sleep modes . Reduction in leakage current causes the reduction in static power dissipation . Stability of the proposed SRAM has also improved due to the reduction in swing voltage . Simulation results of power dissipation access time current leakage stability and power delay product of the proposed SRAM cell have been determined and compared with those of some other existing models of SRAM cell . Simulation has been done in 45nm CMOS environment . Microwind 3.1 is used for schematic design and layout design purpose . 


Summary: A novel low power 12T MTCMOS based SRAM cell is proposed. Charge recycling technique used for reducing the current leakage during transition mode. Use voltage sources to reduce the dynamic power dissipation. Improving the stability of SRAM cell.
Traffic accidents are a fact of life . While accidents are sometimes unavoidable studies show that the long response time required for emergency responders to arrive is a primary reason behind increased fatalities in serious accidents . One way to reduce this response time is to reduce the amount of time it takes to report an accident . Smartphones are ubiquitous and with network connectivity are perfect devices to immediately inform relevant authorities about the occurrence of an accident . This paper presents the development of a system that uses smartphones to automatically detect and report car accidents in a timely manner . Data is continuously collected from the smartphone s accelerometer and analyzed using Dynamic Time Warping and the Hidden Markov Models to determine the severity of the accident reduce false positives and to notify first responders of the accident location and owner s medical information . In addition accidents can be viewed on the smartphone over the Internet offering instant and reliable access to the information concerning the accident . By implementing this application and adding a notification system the response time required to notify emergency responders of traffic accidents can potentially reduce the response time which may help in reducing fatalities . 


Summary: Use smartphones with their built in smart sensors to automatically detect report car accidents. Reporting is done as soon as an accident happens. Data is continuously collected from the smartphone s accelerometer. Data is intelligently analyzed using Hidden Markov Models HMM and Dynamic Time Warping DTW . Data analysis determines the severity of the accident and reduces false positives. Once the accident is confirmed an SMS is sent to the police medical services family members. The SMS includes the accident s location severity and owner s medical information. The application will notify the emergency responders within seconds of the accident. The application will help reduce the response time and perhaps help in reducing fatalities.
In this study a novel single image based dehazing framework is proposed to remove haze artifacts from images through local atmospheric light estimation . We use a novel strategy based on a physical model where the extreme intensity of each RGB pixel is used to define an initial atmospheric veil . Across bilateral filter is applied to each veil to achieve both local smoothness and edge preservation . A transmission map and a reflection component of each RGB channel are constructed from the physical atmospheric scattering model . The proposed approach avoids adverse effects caused by the error in estimating the global atmospheric light . Experimental results on outdoor hazy images demonstrate that the proposed method produces image output with satisfactory visual quality and color fidelity . Our comparative study demonstrates a higher performance of our method over several state of the art methods . 


Summary: A novel strategy is proposed based on the minimum and maximum of each RGB pixel. The concept of local atmosphere light veil is defined in this study. The reflection component of the scene is calculated accurately with imaging physical model. The proposed method yields even better results than the state of the art techniques.