Sandeep Bhowmik

Meta-heuristic techniques are widely used to solve different complex real-life problems in recent scenarios. In this work, traditional key-generation mechanisms have been combined with meta-heuristic techniques to derive new key generation models in chaos-based image cryptography. Initially, one among the key-strings has been generated using the logistic map approach that is known for its ability to produce effective chaotic performance. In this paper, the chaotic effect of the key-string generated by the logistic map has further been enhanced by the application of differential evolution (DE), a population-based meta-heuristic optimization algorithm. This improved key sequence is used to produce chaotic a map which has been applied to images for diffusion operation. The confusion operation on the other hand is performed by the transposition process using another key-string produced by the application of another meta-heuristic technique, namely, Genetic Algorithm (GA). After thorough experimental works, the results have been compared with the state-of-the-art and it is observed that the approach proposed here provides strong cryptographic behavior in terms of information entropy, key sensitivity, robustness against noise, and hereby stands against all kinds of statistical and differential attacks including brute force.

The Job-Shop Scheduling Problem (JSSP) is a well-known and one of the challenging combinatorial optimization problems and falls in the NP-complete problem class. This paper presents an algorithm based on integrating Genetic Algorithms and Simulated Annealing methods to solve the Job Shop Scheduling problem. The procedure is an approximation algorithm for the optimization problem i.e. obtaining the minimum makespan in a job shop. The proposed algorithm is based on Genetic algorithm and simulated annealing. SA is an iterative well known improvement to combinatorial optimization problems. The procedure considers the acceptance of cost-increasing solutions with a nonzero probability to overcome the local minima. The problem studied in this research paper moves around the allocation of different operation to the machine and sequencing of those operations under some specific sequence constraint.

Evidently, information security is a sine qua non in the “modern life, With its sick hurry, its divided aims, Its heads o'ertaxed, its palsied hearts, ...”. To protect our data against unauthorized access, from the time immemorial the first choice has always been to use cryptography. With rapid growth in the arena of multimedia technology, since digital image has become an important medium of communication, extensive research is still a dynamic process in this field. We also have concentrated on image data encryption in this work. The effectiveness of the protection through encryption depends on the algorithm applied and as well as on the quality of the `key' used. If a `key' is badly designed or haphazardly selected, obviously the protection fails to provide proper security and improper access can be gained on the secured information. The first algorithm in cryptographic system design is the algorithm to generate `key'. It specifies the manner in which the `key' is to be chosen. This work focuses on a totally new approach towards the `key' generation for encryption algorithms. Here, Genetic Algorithm (GA), an important method of artificial intelligence has been applied to generate encryption `key', which plays a vital role in any type of encryption. In our work, a hybridized technique called BlowGA is also proposed which is a combination of Blowfish and GA. Blowfish Algorithm is a conventional method of encryption. Our experimental observations show that the newly-proposed hybridized method BlowGA outperforms both GA and Blowfish Algorithm.

We present measurements of the reduction of light output by plastic scintillators irradiated in the CMS detector during the 8 TeV run of the Large Hadron Collider and show that they indicate a strong dose rate effect. The damage for a given dose is larger for lower dose rate exposures. The results agree with previous measurements of dose rate effects, but are stronger due to the very low dose rates probed. We show that the scaling with dose rate is consistent with that expected from diffusion effects.

Written in a tutorial style, this comprehensive guide follows a structured approach explaining cloud techniques, models and platforms. Popular cloud services such as Amazon, Google and Microsoft Azure are explained in the text. The security risks and challenges of cloud computing are discussed in detail with useful examples. Emerging trends including mobile cloud computing and internet of things are discussed in the book for the benefit of the readers. Numerous review questions, multiple choice exercises and case studies facilitate enhanced understanding. This textbook is ideal for undergraduate and graduate students of computer science engineering, and information technology.

Event-shape variables, which are sensitive to perturbative and nonperturbative aspects of quantum chromodynamic (QCD) interactions, are studied in multijet events recorded in proton-proton collisions at sqrt(s) = 7 TeV. Events are selected with at least one jet with transverse momentum pt > 110 GeV and pseudorapidity abs(eta) < 2.4, in a data sample corresponding to integrated luminosities of up to 5 inverse femtobarns. The distributions of five event-shape variables in various leading jet pt ranges are compared to predictions from different QCD Monte Carlo event generators.

This paper presents a new approach of steganography. The secret image is firstly perturbed by Stego-Key (SK) and again perturbed by a genetically generated, good, session based transposition operator (TO). In the next step this perturbed secret image is embedded within the host image by variable bit replacement using a hash function. At the time of extraction of secret image firstly perturbed image is extracted then by reverse engineering with the session based TO and SK the secret image is obtained.

With the increasing use of digital techniques for transmitting and storing images, the fundamental issue of protecting image data against unauthorized access, chaos-based encryption has enjoined a superb know-how to deal with the problem of fast and highly-secured image encryption. The effectiveness of the transposition cipher algorithm profusely depends on the trait of the key. If a key is badly designed or poorly selected, then the protection fails to provide proper security and improper access can be gained on the sensitive information. This work focuses on the application of a crucial Artificial Intelligence approach in block-based image transposition cipher generation. Here, Genetic Algorithm has been applied to search for effective keys to encrypt images through permutation of the pixel locations. This work also statistically analyses the effect of applying varied sizes of keys in block- based image transposition algorithm.

We theoretically investigate a two-dimensional decorated honeycomb lattice framework to realize a second-order topological magnon insulator (SOTMI) phase featuring distinct corner-localized modes. Our study emphasizes the pivotal role of spin-magnon mapping in characterizing bosonic topological properties, which exhibit differences from their fermionic counterparts. We employ a symmetry indicator topological invariant to identify and characterize this SOTMI phase, particularly for systems respecting time-reversal and ${\sf{C}}_6$ rotational symmetry. Using a spin model defined on a honeycomb lattice geometry, we demonstrate that introducing ``\textit{kekul\'e}'' type distortions yields a topological phase. In contrast, ``\textit{anti-kekul\'e}'' distortions result in a non-topological magnonic phase. The presence of kekul\'e distortions manifests in two distinct topologically protected bosonic corner modes - an \textit{intrinsic} and a \textit{pseudo}, based on the specific edge terminations. On the other hand, anti-kekul\'e distortions give rise to \SW{\textit{Tamm/Shockley}} type bond-localized boundary modes, which are non-topological and reliant on particular edge termination. We further investigate the effects of random out-of-plane exchange anisotropy disorder on the robustness of these bosonic corner modes. The distinction between SOTMIs and their fermionic counterparts arises due to the system-specific magnonic onsite energies, a crucial feature often overlooked in prior literature. Our study unveils exciting prospects for engineering higher-order topological phases in magnon systems and enhances our understanding of their unique behavior within decorated honeycomb lattices.

We present a noteworthy finding of high-temperature ferroelectric order in a fairly unexplored ${\mathrm{Gd}}_{2}{\mathrm{MnFeO}}_{6}$ compound, characterized by a disordered double-perovskite structure. This material exhibits a remarkable cryogenic refrigerant capacity alongside the ferroelectric order, making it a rare occurrence. Notably, the refrigerant capacity of this Gd-based double perovskite surpasses that of all previously reported counterparts. Around 92 K (${T}_{FE}$), we observe the presence of ferroelectric order, which is significantly higher in temperature compared to the magnetic order at 4 K (${T}_{N}$). The involvement of dominant short-range magnetic order below ${T}_{FE}$ ($\ensuremath{\gg}{T}_{N}$) leads to a notable magnetoelectric consequence. Raman studies further support our findings, revealing a steplike octahedral distortion of $(\mathrm{Mn}/\mathrm{Fe}){\mathrm{O}}_{6}$ at ${T}_{FE}$. This distortion aligns with a structural transition to a polar $Pna{2}_{1}$ structure at ${T}_{FE}$, consequently inducing the ferroelectric order. The high-temperature ferroelectric order associated with the linear magnetoelectric coupling and promising magnetic refrigeration capacity are in tune with the strong magnetic frustration and significant Jahn-Teller effect in ${\mathrm{Gd}}_{2}{\mathrm{MnFeO}}_{6}$.

Under both static and dynamic weather circumstances, maximum power point tracking (MPPT) is a fundamental and mandatory need for photovoltaic (PV) systems. In static weather conditions, irradiation will remain constant throughout the day, and in dynamic conditions, solar irradiation may vary which is mostly the actual scenario in everyone’s daily life. Commonly Hill climbing (HC), incremental conductance (INC), and perturb and observe (P&O) are commonly used maximum power point tracking (MPPT) technologies. These MPPT methods give an accurate output when the weather condition is static but fails during dynamic weather situations, as because in dynamic weather condition P-V curve deals with more than one number of maxima, out of these one is global maxima and the rest of them is called local maxima. MPPT needs to track the global maxima to give maximum output power to the consumer. The global maximum point (GMP) has been proposed to be tracked using particle swarm optimization (PSO). This work uses the PSO algorithm to evince the dominance of a control approach for a single-phase inverter with a grid-connected PV system in a partially shaded environment. The system consists of 4 parallel connected PV arrays when there is only partial shading, a Boost Converter, and an LCL filter, which is connected to a singlephase grid via a single-phase inverter. Here, for inner current control, the PR controller has been utilized instead of the PI controller, and the PI controller is used for outer voltage control. The primary benefit of utilizing a PR controller is that it has 0% steady-state error while tracking a sinusoidal reference current.

To optimize the usage of solar energy, it is an utmost need to run the photovoltaic (PV) panels at their maximum power point (MPP), which may be done by applying maximum power point tracking (MPPT) techniques. However, during partial shading situation p-v curve will have many peaks which makes tracking more challenging. The global MPPT point cannot be properly tracked using conventional MPPT control methods. In this study, a novel MPPT control method called the grey wolf algorithm (GWA) is described, and a levy distribution is derived to improve the convergence of the GWA. This study uses the GWA to examine the system having a single-phase inverter control connected in a partially shaded PV along with single-phase grid-connected system. The system comprises four parallel-connected PV arrays that are partially shaded, a boost converter, an RC filter, and a single-phase inverter connected with the grid. Here, proportional resonant (PR) control is used for inner current control along with Proportional Integral (PI) controller for outer voltage controller. The PR controller can able to track the sinusoidal reference current with zero steady-state error. The overall system is simulated in MATLAB Simulink environment and the simulation result shows that the PR controller can successfully able to track the sinusoidal reference inverter current and reduce the overall harmonics.

Maximum power point tracking (MPPT) methods may be employed to operate a photovoltaic (PV) system at its maximum power point (MPP), which is necessary to get the utmost electricity out of it. Due to partial shading conditions, the operating point tends to oscillate. Because of several peaks in the P-V curve, due to partial shading of PV, rises the complexity of the MPPT process. In this study, a novel MPPT control method called the Flower Pollination (FP) algorithm is described, and a levy distribution is inferred to improve the convergence of the FP. The research utilizes the FP algorithm to demonstrate the effectiveness of a control approach for a single-phase inverter with a grid-connected PV system in a partially shaded situation. The system comprises four parallel-connected PV arrays that are partially shaded, a Boost Converter, an LCL filter, and a single-phase inverter that connects to the single-phase grid. For inner current control in this study, the PR controller has been utilized instead of the PI controller, and the PI controller is used for outer voltage control. The PR controller's ability to follow the sinusoidal reference current with zero steady-state error is its main benefit. The MATLAB Simulink environment is used to test and validate the controller's performance.

Maximum power point tracking (MPPT) methods can be used to operate photovoltaic panels (PV) at their maximum power point (MPP), which is important to maximize the use of solar energy. Tracking is made more difficult by the parallelly connected PV array's P-V curve, which exhibits several peaks when partially shaded due to a variety of environmental conditions. Conventional MPPT control techniques cannot be used to accurately track the global MPPT point. The cuckoo search (CS) Algorithm, a revolutionary MPPT control technique, is discussed in this paper, and a levy flight is developed to enhance the CS Algorithm's convergence. In this work, a single-phase grid-connected PV system is partially shadowed, and the performance of a single-phase inverter control technique is investigated. The system consists of a boost converter, an RC filter, a single-phase inverter that links to the single-phase grid, and four partially shaded parallel-connected PV arrays. Here, dq control is mainly used instead of PI control for inner current control along with PI controller for outer voltage controller. In MATLAB, the entire system is simulated, and the results demonstrate that the dq controller can successfully monitor sinusoidal reference inverter current and lower overall harmonics.

Event-shape variables, which are sensitive to perturbative and nonperturbative aspects of quantum chromodynamic (QCD) interactions, are studied in multijet events recorded in proton-proton collisions at $$\sqrt{s}=7$$ TeV. Events are selected with at least one jet with transverse momentum $$p_T> 110$$ GeV and pseudorapidity $$|\eta | < 2.4$$ , in a data sample corresponding to integrated luminosities of up to 5 fb $$^{-1}$$ . The distributions of five event-shape variables in various leading jet $$p_T$$ ranges are compared to predictions from different QCD Monte Carlo event generators.

Written in a tutorial style, this comprehensive guide follows a structured approach explaining cloud techniques, models and platforms. Popular cloud services such as Amazon, Google and Microsoft Azure are explained in the text. The security risks and challenges of cloud computing are discussed in detail with useful examples. Emerging trends including mobile cloud computing and internet of things are discussed in the book for the benefit of the readers. Numerous review questions, multiple choice exercises and case studies facilitate enhanced understanding. This textbook is ideal for undergraduate and graduate students of computer science engineering, and information technology.

Flavor changing neutral current (FCNC) interactions in top quark are highly suppressed in the Standard Model.Therefore, any measurable branching ratio for top FCNC decays would be an indication of new physics.In this article, searches for FCNC interactions in top quark production and decay by the ATLAS and CMS experiments at the LHC are presented.Searches in t → qH, t → qγ and t → qZ decays, and in top quark production in qg → t or q → tg are summarized.None of the FCNC searches yielded positive results and exclusion limits on branching ratios, coupling strengths and cross-sections are obtained.

The CMS Level-1 trigger architecture underwent a full upgrade in 2016 in order to maintain and improve the trigger performance in the challenging experimental environment of Run II.It uses very high bandwidth processors with complex, programmable algorithms which increase the efficiency of identifying physics objects while reducing rates.It has successfully delivered very high performance at the high luminosity and associated pile-up condition.

The High-Luminosity LHC will open an unprecedented window on the weak-scale nature of the universe, providing high-precision measurements of the standard model as well as searches for new physics beyond the standard model. The Compact Muon Solenoid (CMS) experiment is planning to replace entirely its trigger and data acquisition system to achieve this ambitious physics program. Efficiently collecting those datasets will be a challenging task, given the harsh environment of 200 proton-proton interactions per LHC bunch crossing. The new Level-1 trigger architecture for the HL-LHC will improve performance with respect to Phase I through the addition of tracking information and updates of the trigger electronics, which will allow to run a simplified particle-flow (PF) event reconstruction on the first trigger level (L1). In this proceedings, we present the development of an algorithm, which is one of many developed algorithms, to select events containing hadronic tau decays on L1 during LHC Phase II. The algorithm is inspired by the “hadrons-plus-strips” (HPS) algorithm, which has been used for the reconstruction of hadronic taus in offline analyses performed by CMS during LHC Runs 1 and 2. It takes advantage of the capability of the upgraded trigger to perform tracking and PF event reconstruction on L1 and is referred to as the HPS@L1 algorithm. The performance of the algorithm is studied in terms of efficiency and rate expected for a single hadronic tau and for a tau pair (di-tau) trigger, using simulated events. For a tau isolation selection that yields a plateau efficiency of 85\% per tau, the algorithm achieves a tau $p_T$ threshold of about 20 GeV for the di-tau trigger, which is lower than the $p_T$ threshold (32 GeV) achieved by the di-tau trigger (using calorimeter-only information) used by CMS during LHC Phase I (with luminosity $2\times10^{34}\rm{cm^{-2}s^{-1}}$).