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On Isoclinism and Capability of Lie Superalgebras
No full textMany theorems and formulas of Lie superalgebras run quite parallel to Lie algebras, sometimes giving interesting results. So it is quite natural to extend the new concepts of Lie algebras immediately to Lie superalgebra case as the later type of algebras have wide applications in Physics, Mathematics and related theories. Isoclinism of Lie superalgebras and Schur multiplier has been defined and studied currently. The purpose of this thesis is to study more deeply the properties of isoclinism and the relation of Schur multiplier to capability. In this thesis it is shown that for finite dimensional Lie superalgebras of same dimension, the notion of isoclinism and isomorphism are equivalent. Furthermore, it is shown that covers of finite dimensional Lie superalgebras are isomorphic using the notion of isoclinism . For a Lie superalgebra L, the set of all superderivations of L whose image is contained in the center of L is known as central derivation of L and is denoted by SDerz(L). It is a subalgebra of superderivation algebra. This thesis presents the work on the central derivation of nilpotent Lie superalgebras which have nilindex 2. In particular, stem Lie superalgebras are characterized by their central derivations. Moreover, relation between SDerz(L) and stem Lie superalgebra is obtained for finite as well as infinite dimensional nilpotent Lie superalgebras with nilindex 2 and nonabelian finite dimensional nilpotent Lie superalgebra. In this thesis it is shown that distributive law holds for nonabelian tensor product of Lie superalgebras under certain direct sums. Thereby a rule for nonabelian exterior square of a Lie superalgebra is obtained. Capable Lie superalgebra is defined and then some characterization is given in this thesis. Specifically, it is proved that epicenter of a Lie superalgebra is equal to exterior square. All capable Lie superalgebras whose derived subalgebras have dimension at most one are classified. As an application to those results, it is shown that there exists at least one nonabelian nilpotent capable Lie superalgebra L of dimension a + b _ 3 where dim L = (a j b)
Synthesis and Study of Cu and Sn Based Nanostructured Metal Chalcogenides for Energy Storage and Photocatalytic Applications
No full textRapid growth of population and global economy lead to substantial depletion of fossil fuels, which generated two pressing concerns: first, energy crisis due to exhaustion of existing fossil fuel reservoirs and second, environmental pollution due to rapid increase in greenhouse gas emission. Hence, to save the future, it is a matter of urgency to develop sustainable, environmental friendly material for energy harvesting and energy storage from renewable sources such as solar energy, wind energy etc. Nanostructured metal chalcogenides (MCs), particularly, copper and tin based metal sulfides, being nontoxic and earth abundant, are found to be potential as well as sustainable materials for several energy related applications ranging from solar cells to supercapacitors, catalysis to thermoelectrics, and so on. Although substantial study have been carried out on copper, tin based binary and ternary metal sulfides and their nanocomposites, still underlying mechanism of formation of different phases and morphology with varying solvents, capping agents and sulfur sources are least understood. Understanding of the mechanism will help in the control synthesis of a particular phase with a particular morphology and is highly required for various applications. Moreover, evaluation of the energy storage properties of these compounds are least studied. In this thesis, several copper and tin based binary, doped binary, ternary and their nanocomposites have synthesized and studied by following hot injection as well as reflux method. Attempts have been made to understand the role of different phase formation by varying solvents, capping agents and sulfur sources. Mechanistic path is proposed for different phase formation in Cu-Sb-S ternary system with varying sulfur sources. Further, the energy storage and photocatalytic applications of these materials are evaluated.
The research work started with one of the simplest binary nano metal chalcogenide i.e. CuS, which present the synthesis and study of CuS with different morphology by varying the solvent, capping agent and reaction condition. It has been observed that by varying the capping agent the morphology of CuS significantly changed. By adding MPA, it is observed that the growth of nanoparticles cease to form 30-40 nm in size. However, addition of PVP as capping agent, biconcave shape submicron crystals of CuS were obtained. Without any capping agent, copper and sulfur precursor in ethylene glycol as solvent form nanosheets which aggregates to give nanoflowers. CuS nanoflowers show good electrochemical properties. Further to improve the properties we have synthesized nanocomposite with varying Ni:CuS ratio and their electrochemical properties were evaluated. It is observed that Ni:CuS with molar ratio of 0.6:1 provide optimum supercapacitance properties compared to other compositions.
To further modify the electrochemical properties, we have incorporated a third element, Sb and synthesized various ternary compounds in Cu-Sb-S system. The effect of solvent, capping agent, sulfur sources and varying concentration of metal precursor on the formation of different phases and the electrochemical properties in these phases have been studied. By varying solvent, capping agent, sulfur source and concentration of metal precursor different phases such as CuSbS2, Cu3SbS3 and Cu3SbS4 are obtained. With equal moles of metal precursor, when elemental sulfur is used as sulfur precursor, nanoplates of pure CuSbS2 obtained, while thioacetamide is used as sulfur precursor, CuSbS2-Cu3SbS4 nanocomposite obtained with Cu3SbS4 nanoparticle decorated on the surface of CuSbS2 nanoplates. However, by changing the molar ratio of metal precursor to 3:1 with thioacetamide (TA) as sulfur precursor, Cu3SbS3-Cu3SbS4 nanocomposites are obtained. The ease of reduction of thioacetamide as compared to sulfur at high temperature in presence of oleylamine (OLA), promotes the oxidation of antimony from (III) to (V) state and the formation of Cu3SbS4 phase containing Sb(V). Moreover, it is observed that 25% enhancement of specific capacitance value of the CuSbS2-Cu3SbS4 nanocomposite as compared to the parent CuSbS2 nanoplates at a current density of 2 A/g. In summary, it is observed that both Ni-CuS and CuSbS2-Cu3SbS4 nanocomposite show enhanced electrochemical properties as compared to their parent binary or ternary compound.
After understanding the effect of sulfur sources on stabilization of various phases in Cu–based ternary metal chalcogenides, the work is further extended on Sn based metal chalcogenides. SnS is one of the simplest metal chalcogenide which we have focused to synthesize and study its photo catalytic activity for dye degradation. To enhance its properties and activity towards dye degradation we have further carried out doping and composite formation on SnS. In general, SnS and doped SnS has emerged as a promising energy material owing to its remarkable optical and electrical properties. Mn-substitution in SnS revealed a change in the size-cum-morphology of nanocrystals, while cuboid or plate shape nanocrystals were observed for SnS, Mn-substitution results in spherical shape. The optical band gap of Sn1−xMnxS shows a red-shift (by 0.15 eV) up to 10% Mn-concentration, however further substitution leads to contrasting effect. Mn-substitution in SnS enhances the photocatalytic activity on the degradation of Congo red dye in visible region. The scavenger study suggested that the photo generated hole, hydroxyl and super oxide radicals were the principal reacting species for the degradation of Congo red dye. Further, with small amount of Mn substitution at Sn site, a dilute magnetic semiconductorhas been developed. Sn1−xMnxS with x = 0.10 shows a weak-antiferromagnetic ordering at 28 K. Observation of enhanced photocatalytic activity of Mn doped SnS nanocrystals motivated us to study further SnS based nanocomposite and their applications in photocatalysis. Ag-SnS nanocomposite was synthesized via hot injection method. Different Ag-SnS nanocomposites were obtained by varying Ag and SnS concentration. It is observed that with increasing Ag concentration in the composite, the photocatalytic efficiency can be increased. Photocurrent measurement supported the observed increase in photocatalytic properties of Ag-SnS nanaocomposite with higher amount of Ag. The mechanistic study indicated that superoxide radicals and holes are the active species, which are largely responsible for the photocatalytic degradation of CR dye. So the photocatalytic activity of SnS could be enhanced by both doping with Mn and composite formation with silver metal
Development of Survivability Protocols in Wireless Personal Area Networks for IoT Applications
Get PDFInternet of Things (IoT) is a renascence of the Internet that gathers rapid momentum propelled by the evolutions in mobile and sensing devices, wireless communication and networking technologies, and cloud computing. The proliferation of IoT applications like healthcare monitoring services and others has accelerated the demand for wireless networks of tiny devices. Wireless sensor networks, enhanced communication technologies, distributed intelligence for smart objects, wireless radio frequency identification systems, and several other Wireless Personal Area Network (WPAN) technologies and communication solutions together enable the promising next-generation Internet, IoT. Many IoT applications are developed for continuous health monitoring and fitness supervision. IoT healthcare application would gather physiological parameters by using non-invasive wearable devices like wristbands, belts. Elderly care, smart homes, wearable technologies, personal assistance for belongings tracking are some of the practical use cases of Consumer IoT (CIoT), which brings consumer devices to the network. A healthcare monitoring application of the CIoT network is considered in this research that consists of many numbers of small body area networks, which are composed of six to nine different sensors and a master coordinator. The coordinator node collects and aggregates these packets to compose data chunks and transmits to the local processing and storage station. Many numbers of persons with such a system constitute the entire application network. The base station would be connected to the cloud and make the whole system remotely accessible.
In such IoT applications, network survivability is an important attribute to be considered. Survivability for a network topology has to be achieved through many approaches, such as reliable communication techniques, efficient utilization of energy resources, adaptive techniques to reduce undesired topology changes and performance degradation, and efficiency to get along the security issues and failures. Efficient communication protocol design and topology structure evaluation for undesirable changes are of utmost importance, which is tried through this research. Protocols are developed at different stack layers, mainly routing and MAC layers, to maintain network survivability at different levels such as node, link, path, and topology. Simulation experiments are implemented to analyze the proposals at different network topologies that pretend real IoT application scenarios. Further, a centralized network evaluation tool is developed to analyze the network performance and scrutinize the structural changes in the topology for improving the survivability of the network. Network survivability is an important attribute to be considered in IoT vii applications. Some researchers observe the network survivability as the topology coverage and the time to get the network disconnected. Further, the survivability of a network has to be maintained at different levels. Path survivability is the stability in the routing paths. Link survivability ensures the efficient usage of the channel between two peer nodes of a hop. Node survivability can be achieved by effectively utilizing the node’s energy and making it less congested with packet bursts. Algorithms at different layers of the protocol stack should jointly operate to maintain the survivability of the network. The thesis comprises four contributory chapters along with the introduction, literature survey, and conclusion
In the first contributory chapter, a protocol at the routing layer is designed that selects the next-hop node in the data forwarding path which maximizes the network survivability. The proposed routing protocol is a data forwarding technique that maintains the network survivability by choosing the path which has a higher survivability factor. It also tries to minimize the congestion at the nodes by including the network traffic information (congestion level of a node) from the physical layer as the route choosing factor. The routing choice decision-making process also includes the signal strength information of the previously received packets.
An algorithm that efficiently allocates the channel dynamically among the contending nodes is proposed as the next contribution, in which the nodes get priority in the contention resolution process whose corresponding receivers are having stronger survivability metrics. Survivability of links between the contending nodes and their receivers are also considered during the process of channel allocation. The application data rate of the sender and the service rate of the receiver are considered for improving the receiver’s node survivability. Link survivability metrics like channel strength indicator, link quality indicator, and path loss distance between the hops are used to decide the spell for accessing the medium. Information from other layers and the assistance of proposed survivable path routing protocol are used with cross-layer design for the efficient assignment of the channel access. The protocols have been evaluated in an IoT remote healthcare application with a cross-layer design of developed MAC and routing techniques.
The proposed survivability aware protocols are implemented in the protocol stack of Contiki-OS. Real-time communications are addressed where there are many nodes simultaneously transmit their application data frames towards the base station. Since the network layer routing protocol in Contiki is by definition made suitable for modifications, the proposal tries to maximize the survivability of the links between hops, to reduce the energy disparity in the nodes, and to avoid congestion at the relay nodes. Contiki provides an IEEE 802.15.4 compatible CSMA driver at the MAC layer. This CSMA protocol is used to adapt to the proposed channel allocation technique. The proposed survivability aware protocols are adapted with the protocol stack of the Contiki, which is a multi-tasking OS for networked, resource-constrained embedded systems and wireless personal area networks. The protocols are tested with hardware implementation on FIT IoT-Lab, which is an online viii testbed infrastructure for IoT-enabled wireless sensor networks.
A python-based centralized topology evaluation module is developed to analyze the performance by using the data collected from the mesh network deployment with Contiki-OS using the Collect-View plug-in of the Cooja simulation environment. The developed tool evaluates the network health based on the collected information from the deployed topology. The collected data contains the details about each node in the network, such as the IP address of the node, hop count from the gateway node, next-hop node towards the gateway, uplink and downlink packet delivery ratio, physical layer channel number, Tx/Rx airtime, etc. The global network structure is reconstructed by the proposed tool from this local information by using python libraries for networking and graph theory. Once the network structure is constructed, it is decomposed to different DODAGs, i.e., subtrees. Each subtree is grounded to the gateway node that is connected with the outside Internet backbone. The structure and characteristics of these subtrees may change over time. The tool evaluates the operational health of the subtrees and investigates any possible changes in the structure based on historical data for better functionality. The final chapter of the thesis presents the concluding remarks inferred from the proposals, along with the emphasis on the achievements and limitations. The future extents for improvements are outlined at the end
Adequacy Assessment of Power System and Capacity Credit Estimation with Renewable Source Integration
No full textEver increasing global population creates the serious issue of cumulative increase in demand for electrical power. To cope with the situation, many methods have been suggested in the past. These methods include expansion plan as well renewable integration in islanding and interconnection. In the era of green energy, instead of expansion planning of conventional generation, it is advisable to choose renewable integration. Among all the available renewable sources wind and solar are more popular.
Reliability estimation is a statistical calculation. This demands unavailability rates of generating units taking part in the evaluation process. The index for PV is determined using the plant configuration. Mostly three types of configuration are accessed and failure rate is determined. Wind energy conversion system converts wind energy into electrical energy. To anticipate the variability of wind speed in the adequacy assessment, wind speed is predicted using some of the popular methods; e.g. autoregressive moving average (ARMA) method, Weibull distribution and adaptive neuro-fuzzy inference system (ANFIS). In case of ARMA and Weibull distribution, mathematical models are developed and collected wind speed is fitted to them. The best fitting is determined by finding F-value in case of ARMA. Statistical error in case of Weibull distribution determines the fitting. The approach in case of ANFIS is little different. ANFIS divides the total data into two groups; training and checking data. ANFIS trains the input with the training data and checks the accuracy using the checking data. The comparative plots between the actual and predicted wind speed decides the suitable prediction technique among all the considered techniques. Power from wind turbine generator (WTG) is segregated into different categories to form multi-states. Multi output states are reduced to 2 states using Apportioning method to determine the unavailability rate. With the determination of failure rates, adequacy is estimated by finding the expected loss of load index.
Capacity value of a newly added generating unit is generally determined using reliability based methods. These methods are estimating capacity value considering additional load taken by the system, integrating a theoretical capacity or adding a practical capacity by maintaining the annual system risk. Unlike conventional, it is not that easy to include random renewable sources in the adequacy assessment as they rely on chaotic resources. Thus, to include renewable sources in the process of adequacy assessment, hourly generated power are considered as negative load and subtracted from the system load. x
The reliability based method of capacity credit estimation demands enormous data collection as well as recursive probabilistic calculation. Again repetitive calculation of capacity value of identical renewable sources may occur due to dependency of renewable generation on the random resource. Thus, a database is constructed with the reliability indices after adding sequential value of renewable sources to the system along with all the capacities values corresponding to each reliability based method. To calculate the capacity value, expected loss of loads (LOLEs) after adding the equivalent capacities are chosen as the target. To find the best match, the database is represented as a multidimensional tree and nearest neighbor search algorithm is used to search the query in the tree
Performance Analysis of Realtime Task Scheduling in Cloud System
Get PDFCloud computing is becoming an important computing paradigm due to its costefficiency, scalability, availability, and high resource utilization. Applications like financial transactions, healthcare, scientific workflows, video streaming, Internet of Things (IoT), etc. with their realtime nature, need provisioning of cloud resources to guarantee timeliness and high availability. The Cloud Service Providers (CSPs) must support sufficient cloud resources to satisfy the demand from these realtime applications. Meanwhile, the evergrowing demand from applications forces CSPs to deploy more and more cloud resources, which consumes a considerable amount of energy. The high energy consumption affects the environment and other metrics like execution cost, makespan, and reliability of the cloud system. Hence, it necessitates employing some techniques to reduce cloud systems’ energy consumption and make it energyefficient along with other performance metrics like reliability, execution cost, makespan, etc. Realtime task scheduling is one of the methods to achieve energyefficiency in the cloud system. Moreover, heterogeneous computing environments and application timing constraints add complexity to the realtime task scheduling. Therefore, the study of a cloud system’s performance is necessary for realtime applications to ensure Quality of Service (QoS), defined in terms of energy consumption, makespan, execution cost, reliability, etc.
First, an Energy and Cost Aware task scheduling (ECA) algorithm based on the TOPSIS analysis method is proposed to reduce energy consumption and execution cost. Here, a scoring value is calculated for a VM based on its energy consumption and execution cost to execute a task. Then, a VM with the best score in terms of energy usage and execution cost is selected. Next, a Learning Automata (LA)based scheduling (LAS) algorithm is proposed to minimize energy consumption and makespan. It is a reinforcementbased method where the action, i.e., assignment of a task to a VM, is penalized if it contributes to scheduling objective degradation and rewarded if the action is suitable to improve scheduling objective.The above process is continued for a fixed number of iterations, and the actions with the best reward value are added in the scheduling decision.
Then, a game theory based scheduling algorithm is proposed to enhance system performance where energy consumption and reliability are considered as the performance metrics. The biobjective scheduling algorithm is modeled as a noncooperative scheduling game, named Realtime Task Scheduling Game (RTSG). The solution or Nash Equilibrium of RTSG is presented using a Vickery auction mechanism. The proposed solution is compared with a cooperative game based solution and an auctionbased approach.
Finally, a faulttolerant scheduling algorithm is presented, taking into account energy consumption and reliability. First, an acceptance test mechanism is designed considering schedulability and response time failure to detect VM failure. A reliability and energyaware Faulttolerant scheduling algorithm, REO, is proposed using the PB concept and BB overlapping technique. The performance metrics used for comparison of algorithms include Success Ratio, makespan, and total energy consumption. The outcomes of the simulation results signify the usefulness and effectiveness of the proposed algorithms for studying realtime task scheduling performance
Study of Routing Protocols for Low Power Internet of Things (IoT) Devices
Get PDFInternet of Things (IoT) refers to the interconnection of everyday objects around us and sharing of information among them through the Internet. This information can be used in various applications starting from smart agriculture to smart healthcare and so on. IoT plays a critical role in controlling and automating the whole process making the computation and communication faster. The basic technology used in most of the IoT devices is wireless sensor networks. Every IoT device is embedded with sensors within it that enable it to sense, process the data, and communicate to other things. Thus, the underlying architecture of IoT demands the study and understanding of WSN for its efficient functioning. This thesis focuses on the study of routing protocols developed for IoT based applications. Routing protocols play a critical role in sending the information gathered from the sensors or objects to the required destination for further processing. The information after processing can be used in various applications for helping humans to improve their lifestyle. To start with the research, a Scalable Survival Path Routing (SSPR) protocol has been designed to meet the efficiency of a scalable wireless sensor network. The protocol uses weight based clustering technique to select cluster heads to route data from source to the destination via them in a WSN. This enables to design a scalable network and the protocol performance is increased for larger network. SSPR protocol has been simulated and analysed using NS2 simulator.
While moving towards the routing protocols for IoT, it was observed that the SSPR protocol does not satisfy all the requirements of IoT applications like it does not support Ipv6 packets, cannot be coded to IoT hardware devices and adaptable to all types of traffic patterns. So a composite routing technique named as Modified Routing Protocol for Low Power and Lossy Networks (MRPL) is proposed for such a network. The proposed protocol combines three metrics: Expected Transmission Count (ETX) of a link, Hop count (HC) between source and destination and Available Energy (AE) of a node to select a routing path from source to destination. The path selected for transmission would be the path with less number of packet transmissions, less number of intermediate hops and maximum available energy. ETX metric ensures that good quality links will be selected for data transmission, HC ensures that shortest path to the destination would be selected and available energy ensures that a node does not die out in the process of data transmission. Clustering is a proven solution to be an efficient method to enhance the scalability and v lifetime of any network, a Clustered Approach in RPL (CARPL) has been proposed. The proposed protocol uses a weight based clustering algorithm to perform well even in a larger network. The nodes in the network send their data to their respective cluster heads inside each cluster using one-hop communication. The cluster heads are responsible for aggregating these data and transmitting it to the destination using multi-hop communication. Using this method the scalability as well as the network lifetime is increased.
MRPL and CARPL has been analysed using COOJA simulator in Contiki OS as this simulator supports the features required for IoT like it supports Ipv6 packets, RPL for low power and lossy networks standardized by Internet Engineering Task Force (IETF) and also it supports the code to run inside IoT specific devices like sky motes. It is observed that our proposed protocols outperform the existing approaches in performance metrics like packet delivery ratio, network latency, throughput, and energy consumption
Nonlinear Structural Analysis of SMA Bonded Curved Skew Sandwich Composite Panel Under Hygro-Thermo- Mechanical Loading
No full textThe present dissertation proposes a nonlinear mathematical model for the analysis of smart sandwich composite panel structural responses (deflection, frequency, transient and buckling/post-buckling) with and without skew angle including the effect of hygro-thermomechanical loading. In this context, the model has been developed using an equivalent higher-order single layer theory considering the effect of shear deformation and throughthickness stretching effect. Additionally, the model includes the large geometrical deformation of the shallow shell structure (due to combined loading) through Green’s strain in Lagrangian reference frame. Further, to enhance the final performances of the structure against the loading and the environmental conditions, the shape memory alloy fibre has been introduced as the smart material. The material nonlinearity of the functional alloy due to the change in temperature environment has also been incorporated via the marching technique.
The linear and nonlinear finite element solutions of the deflection, eigenvalue and dynamic responses including the buckling load parameter are computed via the in-house computer code (MATLAB). The nonlinear solutions are evaluated through the direct iterative technique in association with the isoparametric finite element steps, whereas the constant acceleration integration method (Newmark’s) for the computation of dynamic responses. In addition, the volume fractions and the pre-strain effect of the smart material due to the variation in ambient condition have been incorporated to show the corresponding improvement of the sandwich components. The numerical model consistency and their accuracy in terms of available published benchmark solutions (numerical/analytical/experimental) for the individual and the combined cases are verified.
In addition, a few experimental tests have been carried out to show the comparison of the bending (linear/nonlinear), eigenvalue and dynamic cases of the in-house fabricated (hand lay-up technique) sandwich structural component (different numbers of face sheet layers and unlike core thicknesses) under the ambient conditions to ensure the model accuracy.
Finally, the influential input parameters which are affecting the structural stiffness and the relevant design aspect including the configurational efficacy have been explored using the present equivalent single-layer higher-order nonlinear (geometry and material) sandwich model. Also, a few recommendations are provided suitably based on the obtained output for the future reference relevant to the applicability of functional material and sandwich construction
Monocular Vision Aided Autonomous UAV Navigation in Indoor Environments
No full textIn recent years, Unmanned Aerial Vehicles (UAV), popularly known as drones, have swiftly gained popularity in various sectors such as disaster hit environments, military and industrial applications, agriculture, etc. Vision-based pose estimation of UAV has recently been very popular among the computer vision community. In this doctoral research, an attempt has been made to navigate UAV autonomously in GPS-denied indoor environments with the feed from a monocular camera only. Understanding the 3D perspective of a scene is imperative in improving the precision of intelligent autonomous systems. However, with only one camera (monocular vision) feed, the difficulty in understanding becomes compounded. This research focuses on estimating 3D primitives using only the visual data captured with a monocular static camera and without any additional sensors. The primitives thus estimated are used for safe navigation of UAV in the presence of static obstacles in indoor environments. A monocular vision assisted optical flow method is proposed to measure the depth of a UAV from an impending frontal obstacle. The approach follows the fundamental principle of perspective vision that the size of an object relative to its field of view (FoV), increases as the center of projection moves closer towards the object. This involves modeling the depth followed by its realization through scale-invariant visual features. Noisy depth measurements arising due to the external wind, or the turbulence in the UAV, are rectified by employing a constant velocity based Kalman filter model. Rigorous experiments with scale-invariant features reveal an overall accuracy of 89.6% with varying obstacles, in both indoor and outdoor environments. However, this method requires frequent command updates to keep the UAV on safe path. A two-stage deep neural network (DNN) model is developed to predict the instantaneous optimal trajectory of the UAV from an input RGB image. In the first stage, the depth map and surface normal of the image are predicted using a fully convolutional deep architecture. The network is trained separately for both the tasks while keeping the architecture same. In the second stage, the predicted depth and surface normal are jointly processed through another trained DNN classifier model to predict the optimal trajectory of the UAV. The suggested architecture, compared to the counterparts, uses fewer training samples and model parameters. Instantaneous optimal trajectories also help to overcome the issue of low frequency command updates, which is a drawback of the previous method.
The previous methods do not work well inside long corridor environments. Hence, an optical flow based vanishing point method is proposed to navigate a UAV safely inside indoor corridor environments. The proposed algorithm makes sure that the UAV avoids the side wall as well as the frontal wall at the end of the corridor. The knowledge of the vanishing point location alongside a formulated mechanism governs the necessary set of commands to safely navigate the UAV avoiding any collision with the side walls. Furthermore, the relative Euclidean distance scale expansion of matched scale-invariant keypoints in a pair of frames is taken into account to estimate the depth of a frontal obstacle; usually a wall at the end of the corridor. Exhaustive experiments in different corridors reveal the efficacy of the proposed scheme. A DNN based monocular vision assisted algorithm is proposed to safely localize a UAV in indoor corridor environments. Always, the aim is to navigate the UAV through a corridor in the forward direction by keeping it at the center with no orientation either to the left or right side. The algorithm makes use of the RGB image, captured from the UAV front camera, and passes it through trained DNN models to predict the position of the UAV with respect to the central bisector line (CBL) of the corridor. If the UAV is disoriented, an appropriate command is generated to rectify the pose. A new corridor dataset, named NitrUAVCorridorV1, that contains images as captured by the UAV front camera when the UAV is at all possible locations of a variety of corridors, is also proposed. As per our knowledge, we are the first ones to propose such a dataset to navigate a UAV inside corridor environments. The performance of all the proposed methods is experimentally validated in real-world indoor environments. Also, the results are compared qualitatively as well as quantitatively with the respective counterparts
Performance Improvement of Five Phase Induction Motor Drive System with Different Converter Configurations
No full textThe environment friendly transportation system has been drawing great attention worldwide, with a prospect of keeping climatic changes in check and minimizing the air pollution to an acceptable extent. Thus, advancement in electric based technologies for machineries used for propulsion has been a topic of great interest in variety of conveyance system, which includes hybrid vehicles, aircrafts and ships. Also, this progression is applicable to machineries to generators for power generation using renewable sources.
These types of applications are not well suited for the conventional machineries, which are based on three-phase suitability. Besides, due to the scenario of source and load system being isolated from the main power network in such applications, it is not a regulation anymore to restrict the number of phases in such machineries to only three. Moreover, the multi-phase machines propose a number of advantages as compared to the conventional three-phase type. The merits majorly include multi-phase drive’s power converter switch rating requirement is now reduced. Also, with higher number of phases its fault tolerant capability is highly increased.
The research on multi-phase drives and their application in real-world has developed at a good pace from past two decades. From all the old as well as modern machine drives available, the application of induction motor drives is still way long ahead from its competitors. Thus, research on multi-phase induction motor drives have been in the limelight in recent years. Specially, the five-phase induction motor drive system has drawn great attention and interest.
The converter arena in machine drives section is a major component to be dealt with. The conventional converter configurations used for three-phase drives can also be implemented for higher phase configuration with necessary modifications. However, since topological advancement in converter design sector has gone to a higher level, different advanced configuration with specific suitability to such multi-phase drive application is also a topic to be looked upon. Thus, two different converter configurations have been dealt with, in this thesis, i.e. Multi-level inverter (MLI) and Z-source inverter (ZSI), with more emphasis on the latter one. The MLI configuration obviously provides greater flexibility in supplying individual phases of multi-phase drive, however, their controlling complexity also increases with it. Also, the cost of using such configurations is on a higher side. The ZSI, nevertheless, iv
is more useful in voltage sensitive applications where there are high chances of voltage disturbances from the supply side. The additional control function of voltage control for ZSI can also be integrated with control structure of machine in drive system.
With the advent of modern and sophisticated processors, the control structure for multi-phase drive is now easier to design and implement. Out of different control techniques already in use for conventional three-phase induction motor system, such as scalar control, FOC (field oriented control), DTC (direct torque control), adaptive control technique, etc., DTC as such or in modified structure is still in large a highly preferable choice. Henceforth, DTC is primarily used in this work for designing the inherent control structure of five-phase induction motor. Furthermore, for voltage control of quasi Z-Source Inverter (qZSI), a duty cycle generation method is devised using a non-linear control function technique, known as dynamic evolution control (DEC). This duty cycle is further integrated with DTC for designing the complete control algorithm for qZSI fed five-phase induction motor drive system operating under conditions of supply voltage disturbance in the form of sag and voltage interruption.
In this work, along with voltage control function of DEC method, it’s another controlling aspect is also explored, which is in respect to the source current. An attempt is made to counteract the THD content of source current along with voltage control by adapting to a proposed current controlled DEC method for qZSI fed five-phase induction motor drive system.
The proposed work for five-phase induction motor drive system, which includes analysis based on different converters at front-end such as MLI and qZSI, and also the proposed controllers are precisely described by mathematical and diagrammatic descriptions. The practicality of the proposed configurations is authenticated by their simulation and real-time results
Hardware Security: Hardware Trojan Detection, Test and Debug Security Infrastructure IP
No full textThis dissertation consists of two parts. The first part focuses on pre-silicon detection of hardware Trojans and second part presents a Test and Debug Security Infrastructure IP (TDS-IP) which address the several address hardware security issues like counterfeiting and debug security. The SoC design house integrates IP cores from 3rd party IP (Intellectual Property) core vendors (3PIP) into system on chip (SoC) devices. Different service providers and consultants will take part in SoC design process. 3PIP core sourced from an untrusted company may have HT (Hardware Trojan) and also in-house adversary can insert HT in RTL (Register Transfer Logic) code, synthesized netlist, scan inserted netlist and post layout netlist. Several HT detection schemes proposed in the past are standalone methods, which are not enough for SoC design house to detect HT. The past techniques are able to detect HT in 3PIP, RTL code and fabrication. In the first part of this dissertation, we propose a secure design flow for HT detection which uses several stages of ASIC (Application Specific Integrated Circuit) design flow to isolate the HT in different phases of chip design. The proposed scheme can be easily adopted into design flow by SoC integrator/ODM (Original Design Manufacturer) companies. The proposed work use all stages of chip design flow from functional verification, synthesis, formal verification, timing and power analysis in a coordinated way to find suspicious sections in the design. AES and microprocessor (PIC16F84) benchmarks from trust-hub are used to validate the proposed framework. The detailed analysis of proposed technique is presented and the proposed secure design flow is able to detect malicious inclusions in benchmarks successfully. The proposed technique detects HT and also gives concrete proof on their malicious activity. The major requirement for the success of this HT detection scheme is trusted team of security verification engineers.
In the second part of this dissertation, we propose a novel security infrastructure IP for test and debug (TDS-IP) which includes a novel anti-counterfeiting solution called secure split test and security framework for three major test protocols: JTAG (Joint Test Action Group), IEEE 1500 and IEEE 1687 (IJTAG(Internal JTAG))). Earlier access control based JTAG security techniques are further enhanced to support Over the Air (OTA) firmware update. The Physical unclonable function (PUF) based security techniques are proposed for IEEE 1500 core testing standard and IEEE IJTAG. In a novel security scheme proposed for IEEE 1500 based core based testing, PUF challenge response pairs are more secured than earlier techniques as PUF data is not shared with offshore OSAT (Outsourced Assembly and Test) centre. IJTAG viii (Internal JTAG or IEEE 1687) is a standard defined to streamline the access to on-chip instrumentation which is useful in debug and diagnosis. The PUF based security framework for IJTAG cluster the on-chip instruments according to requirement and place the security checks at entry points of clusters safeguard the on-chip instruments against scan based side channel attacks and IP piracy. Secure split test (SST) techniques proposed in the past does not support functional testing and we propose a novel SST scheme which support functional testing to mitigate the counterfeits coming out from the untrusted foundries and OSAT centres. Finally the novel anti-counterfeiting and debug security techniques are stitched together to create the Test and Debug Security Infrastructure IP (TDS-IP). The reliability issues connected with PUF responses is addressed in TDS-IP. The workflow to use and integrate the TDS-IP with openmsp430 microprocessor core is presented. In summary, contributions of this dissertation are as follows: -
• To design the novel secure split test (SST) technique which support both structural testing and functional testing with RMA analysis (Return Material Authorization) capability to prevent counterfeiting.
• To design the security framework to detect the HT at pre-silicon stage without adding an extra tool into ASIC design flow.
• Development of Security IP which includes novel SST technique as anti-counterfeiting solution and secure test/debug structure