Adaptive Constraint Solving for Information Flow Analysis

In program analysis, unknown properties for terms are typically represented symbolically as variables. Bound constraints on these variables can then specify multiple optimisation goals for computer programs and nd application in areas such as type theory, security, alias analysis and resource reasoning. Resolution of bound constraints is a problem steeped in graph theory; interdependencies between the variables is represented as a constraint graph. Additionally, constants are introduced into the system as concrete bounds over these variables and constants themselves are ordered over a lattice which is, once again, represented as a graph. Despite graph algorithms being central to bound constraint solving, most approaches to program optimisation that use bound constraint solving have treated their graph theoretic foundations as a black box. Little has been done to investigate the computational costs or design e cient graph algorithms for constraint resolution. Emerging examples of these lattices and bound constraint graphs, particularly from the domain of language-based security, are showing that these graphs and lattices are structurally diverse and could be arbitrarily large. Therefore, there is a pressing need to investigate the graph theoretic foundations of bound constraint solving. In this thesis, we investigate the computational costs of bound constraint solving from a graph theoretic perspective for Information Flow Analysis (IFA); IFA is a sub- eld of language-based security which veri es whether con dentiality and integrity of classified information is preserved as it is manipulated by a program. We present a novel framework based on graph decomposition for solving the (atomic) bound constraint problem for IFA. Our approach enables us to abstract away from connections between individual vertices to those between sets of vertices in both the constraint graph and an accompanying security lattice which defines ordering over constants. Thereby, we are able to achieve significant speedups compared to state-of-the-art graph algorithms applied to bound constraint solving. More importantly, our algorithms are highly adaptive in nature and seamlessly adapt to the structure of the constraint graph and the lattice. The computational costs of our approach is a function of the latent scope of decomposition in the constraint graph and the lattice; therefore, we enjoy the fastest runtime for every point in the structure-spectrum of these graphs and lattices. While the techniques in this dissertation are developed with IFA in mind, they can be extended to other application of the bound constraints problem, such as type inference and program analysis frameworks which use annotated type systems, where constants are ordered over a lattice

Design of Phase Locked Loop

In the optical communication in a backbone infra structure, flexibility means, for example, programmable bitrates requiring a PLL with robust operation over a wide range of frequency range. A wide range PLL could be used by different protocols and applications so that we maximize the reusability and reduce time to market. In this report we try to present an extended frequency CMOS monolithic VCO design. A negative feedback control algorithm is used to automatically adjust the VCO range according to control voltage. Based on this analog feedback control algorithm, the VCO achieves a wide range without any pre-register settings. Here we discuss about different component of PLL (Phase Lock Loop), mainly on Phase Frequency Detectors and VCO (voltage controlled oscillator). Here we proposed different architecture of Phase frequency detectors and also of VCOs and designed many architecture in mentor graphics

Do Names Echo Semantics? A Large-Scale Study of Identifiers Used in C++'s Named Casts

Developers relax restrictions on a type to reuse methods with other types. While type casts are prevalent, in weakly typed languages such as C++, they are also extremely permissive. If type conversions are performed without care, they can lead to software bugs. Therefore, there is a clear need to check whether a type conversion is essential and used adequately according to the developer's intent. In this paper, we propose a technique to judge the fidelity of type conversions from an explicit cast operation, using the identifiers in an assignment. We measure accord in the identifiers using entropy and use it to check if the semantics of the source expression in the cast match the semantics of the variable it is being assigned. We present the results of running our tool on 34 components of the Chromium project, which collectively account for 27MLOC. Our tool identified 1,368 cases of discord indicating potential anti-patterns in the usage of explicit casts. We performed a manual evaluation of a random-uniform sample of these cases. Our evaluation shows that our tool identified 25.6% cases representing incorrect implementations of named casts and 28.04% cases representing imprecise names of identifiers.Comment: The manuscript has 21 pages and it contains 22 Figures and a table. The preprint is submitted and currently under review at Journal of Systems and Software Elsevie

Transcend:Detecting Concept Drift in Malware Classification Models

Building machine learning models of malware behavior is widely accepted as a panacea towards effective malware classification. A crucial requirement for building sustainable learning models, though, is to train on a wide variety of malware samples. Unfortunately, malware evolves rapidly and it thus becomes hard—if not impossible—to generalize learning models to reflect future, previously-unseen behaviors. Consequently, most malware classifiers become unsustainable in the long run, becoming rapidly antiquated as malware continues to evolve. In this work, we propose Transcend, a framework to identify aging classification models in vivo during deployment, much before the machine learning model’s performance starts to degrade. This is a significant departure from conventional approaches that retrain aging models retrospectively when poor performance is observed. Our approach uses a statistical comparison of samples seen during deployment with those used to train the model, thereby building metrics for prediction quality. We show how Transcend can be used to identify concept drift based on two separate case studies on Android andWindows malware, raising a red flag before the model starts making consistently poor decisions due to out-of-date training

Internalization of Staphylococcus aureus in Lymphocytes Induces Oxidative Stress and DNA Fragmentation: Possible Ameliorative Role of Nanoconjugated Vancomycin

Staphylococcus aureus is the most frequently isolated pathogen causing bloodstream infections, skin and soft tissue infections and pneumonia. Lymphocyte is an important immune cell. The aim of the present paper was to test the ameliorative role of nanoconjugated vancomycin against Vancomycin-sensitive Staphylococcus aureus (VSSA) and vancomycin-resistant Staphylococcus aureus (VRSA) infection-induced oxidative stress in lymphocytes. VSSA and VRSA infections were developed in Swiss mice by intraperitoneal injection of 5 × 106 CFU/mL bacterial solutions. Nanoconjugated vancomycin was adminstrated to VSSA- and VRSA-infected mice at its effective dose for 10 days. Vancomycin was adminstrated to VSSA- and VRSA-infected mice at a similar dose, respectively, for 10 days. Vancomycin and nanoconjugated vancomycin were adminstrated to normal mice at their effective doses for 10 days. The result of this study reveals that in vivo VSSA and VRSA infection significantly increases the level of lipid peroxidation, protein oxidation, oxidized glutathione level, nitrite generation, nitrite release, and DNA damage and decreases the level of reduced glutathione, antioxidant enzyme status, and glutathione-dependent enzymes as compared to control group, which were increased or decreased significantly near to normal in nanoconjugated vancomycin-treated group. These findings suggest the potential use and beneficial role of nanoconjugated vancomycin against VSSA and VRSA infection-induced oxidative stress in lymphocytes

Profile driven schemes for energy-sensitive cache hierarchy

With the advent of mobile and handheld devices, power consumption in embedded systems has become a key design issue. Of the components that consume significant amounts of power in an embedded system, cache memories have been reported to consume in excess of 40% of the total power in typical high end embedded processors. Therefore, cache memories are an obvious target of many low-power optimizations. Recently, it has been shown that cache requirements of the applications vary widely and a significant amount of energy spent in cache accesses can be saved by tuning the cache parameters according to the needs of the application. However, tuning the cache memory to suit the needs of the application entails identification of optimal cache configurations in the first place. With the large set of configurations to choose from, this process is prohibitively time consuming if done through exhaustive cache hierarchy simulations. Therefore, there exists a need for tools that can rapidly identify optimal cache configurations to tune the cache parameters for any given application.MASTER OF ENGINEERING (SCE

Performance Enhancement of Photovoltaic Integrated Unified Power Quality Conditioner for Power Quality Improvement

A drastic improvement in the conventional grid towards an efficient and advanced grid solutions are noticed after rise in demand in power quality by the domestic and commercial consumers. In the mean time, shortage of conventional sources of electricity and high demand for electricity including transmission and distribution losses are reported by many countries. Therefore researchers are finding efficient solutions for integration of renewable energy sources to the present grid. Among the various type of renewable energy sources, photovoltaic (PV) systems are more reliable for the proper grid integration due to its low installation costs. However, proliferations in the distribution systems are present because of voltage disturbances in the grid and various non linear loads connected to the grid. Aforementioned perturbations gives rise to power quality issues related to voltage and current such as voltage sags, voltage swells, voltage unbalance and current harmonics etc. Therefore power conditioners and various custom power devices are developed in order to compensate the power quality issues and improve the power quality. Previously distribution static compensators are widely used for grid connected PV systems for the elimination of current quality issues by neglecting the situations of grid voltage disturbances. For the compensation of voltage and current quality issues in a grid integrated PV system, unified power quality conditioners (UPQC) are developed and controlled sophisticatedly in this thesis to achieve the desired power quality standard. Integration of PV system to single phase grid through UPQC has been developed for its performance analysis and improvement of power quality. Presence of grid disturbances and harmonic rich currents due to nonlinear loads in a single phase grid connected PV systems are compensated effectively. A notch filter based control algorithm is developed and implemented for the PV-UPQC system. A detail stability analysis has been discussed of the controller with the system. The performance of the proposed controller is compared with SRF and UVT controller, both in simulation and experimentally to validate its efficiency. The design and development of three phase PV tied UPQC is presented to achieve the required power quality standard. The analysis on the performance of proposed system has been carried out in comparison with simple SRF controller and UVTG controller. Development of resonant controller for PV tied UPQC for making the system robustagainst grid disturbances has been discussed and experimentally validated with dSPACE1103 processor. Generation of accurate compensating signal for the inverters of PV-UPQC is highly important as various type of disturbances arise unexpectedly in the distribution system. Therefore utilization of conventional PI controllers by the controller of the system may not reach the expected solution. Therefore an advanced optimization algorithm is proposed by overcoming the demerits of conventional optimizations. The proposed JAYA (means victory) optimization algorithm is utilized to find the best controller gains. As the shunt and series inverter of PV-UPQC are employed for different control purpose, two different objective functions are designed for the algorithm. Performance of the system is analyzed for the proposed controller with JAYA optimization in comparison with conventional teaching learning based algorithm (TLBO), Particle swarm optimization algorithm. The proposed JAYA based controllers along with other conventional optimization methods are implemented in real-time for PV-UPQC system to validate the efficiency. A new PV tied UPQC topology with an improved LCL filter at shunt inverter part is proposed, which provides better compensation to current quality issues. This chapter also proposes a novel model reference tracker (MRT) control law to improve power quality and elimination of current harmonics, voltage sag/swells and unbalance. It has feature to regulate tracking error between model reference signal and actual measured signal. Therefore, proposed model reference approach provides robustness and flexibility for various operating conditions. In addition, integral plus sliding mode controller (SMCi) has been used for better control of DC-Link voltage to deal with severe change in power system conditions. Performance and efficiency of present topology with novel controller is analyzed along with conventional controllers through laboratory developed prototype, controlled by DS1103 dsp processor. A new topology for Photovoltaic fed open unified power quality conditioner has been proposed focusing on the requirement of voltage sensitive loads. It has incorporated the advantages of open UPQC and grid connected PV systems by providing a possible solution towards the demand of different power quality levels at end user. Adaptive notch filter based instantaneous symmetric components (ANF-ISC) controller scheme has been utilized for the control of series compensator. An adaptive logarithmic absolute algorithm has been implemented for shunt part of proposed system. The proposed controllers are verified on a developed prototype of proposed system in the laboratory. The system performance is found satisfactory under various grid conditions