Soft Computing Systems

This paper presents a hybrid Local Unimodal Sampling (LUS)-Teaching Learning Based Optimization (TLBO) optimized Proportional-Derivative-fuzzy-Proportional-Integral-Derivative (PD-FPID) cascaded controller to study the load frequency control (LFC) issue in a three area interconnected thermal power system considering generation rate constraint (GRC). Initially hybrid LUS-TLBO optimized conventional PD-PID cascaded controller is used and the result acquired is matched with that of Bat Algorithm optimized conventional PD-PID cascaded controller. It is proved that the proposed LUS-TLBO based PD-PID cascaded controller is revealing better dynamic performance in all aspects i.e. in terms of settling time, undershoot and overshoot. Then the study is extended to inspect dynamic behaviour of the same power system employing a novel PD-FPID cascaded controller optimized by the proposed hybrid LUS-TLBO algorithm. It is again proved that the proposed LUS-TLBO optimized PD-FPID cascaded controller is performing better as compared to LUS-TLBO based conventional PD-PID cascaded controller. A step load disturbance of 1% is applied in area1 and integral time absolute error (ITAE) is chosen as objection function in designing the proposed controller. Again sensitivity analysis of the proposed PD-FPID cascaded controller is conducted by varying the system parameters and it is seen that the proposed cascaded controller is less sensitive to parametric variations, and therefore there is no need to reset the controller parameters for wide deviation in system parameters.

Abstract: This paper presents a hybrid Local Unimodal Sampling (LUS)-Teaching Learning Based Optimization (TLBO) optimized Proportional-Derivative-fuzzy-Proportional-Integral-Derivative (PD-FPID) cascaded controller to study the load frequency control (LFC) issue in a three area interconnected thermal power system considering generation rate constraint (GRC). Initially hybrid LUS-TLBO optimized conventional PD-PID cascaded controller is used and the result acquired is matched with that of Bat Algorithm optimized conventional PD-PID cascaded controller. It is proved that the proposed LUS-TLBO based PDPID cascaded controller is revealing better dynamic performance in all aspects i.e. in terms of settling time, undershoot and overshoot. Then the study is extended to inspect dynamic behaviour of the same power system employing a novel PD-FPID cascaded controller optimized by the proposed hybrid LUS-TLBO algorithm. It is again proved that the proposed LUS-TLBO optimized PD-FPID cascaded ...

In this study, a fuzzy proportional integral derivative controller (FPID) was adjusted using the differential evolution (DE) method to enhance the automated generation control (AGC) of a three-zone reheat-type power system. The objective function used in this study was an integral of the time-weighted absolute error (ITAE). In the optimization, the gain control parameters of the proportional integral (PI), the integral (I), and FPID were optimized and compared to improve the limitations drawn by the controller over a few parameters. To demonstrate that FPID controllers with IPFC produce better and more accurate optimization results than integral and PI controllers optimized by DE, the interline power flow control (IPFC) of a flexible AC transmission system (FACTS) device with suitable connections and control parameter optimization was used. Also, the particle swarm optimization (PSO) PID with IPFC was compared with the proposed DEFPID + IPFC, and better results were achieved by usin...

This study aims to design a soft sensor (SS) using the state-dependent parameter (SDP) method within the control loop. SSs estimate variables based on measured values of other variables, but measurement noise affects their performance. The advantage of the SDP method is its reliance on the system state for model parameter dependency, leading to a lower model order and a reduction in number of input variables. However, this introduces measurement noise into the SS outputs. The research focuses on developing a reliable SS that effectively handles measurement noise, improving accuracy and reliability within the control loop. The innovation of this article lies in enhancing the SDP soft sensor (SDPSS) using the dynamic data reconciliation (DDR) filter. The proposed approach's superiority stems from utilizing linear regression (LR) models instead of complex dynamic process models as redundant models in the DDR filter's development. The performance of the SDP method is evaluated by employing an actual industrial sulfur recovery unit (SRU) as a reference point for assessing the effectiveness of SSs. Quantitative results conclusively demonstrate that SDP-based SSs significantly enhance estimation accuracy compared with alternative soft sensing techniques. A simulated continuous stirred-tank reactor (CSTR) is also used to evaluate the effectiveness of the proposed approach in two scenarios: external disturbance elimination and setpoint tracking. The DDR-SDPSS's performance is compared with that of the statistical filter-based SDPSS, demonstrating improved variable monitoring, reduced susceptibility to fluctuations, and satisfactory performance across a wide range of measurement noise variances without the need for controller readjustment.

CBIR is the mainframe of Image Retrieval System. To understand query semantics and users expectations so as to communicate faithful results in terms of accuracy, Relevance Feedback is incorporated into CBIR System. This system allows users to progressively refine the search results, to access iteratively the results as “relevant/irrelevant” or even giving him/her the opportunity to specify a degree of relevance, the system creates a new query that better captures the user’s needs, hence raising the opportunity to get more relevant image results. In the watermark-based protocol, a unique watermark is directly embedded into the encrypted images by the cloud server before images are sent to the query user. Hence, when an illegal image copy is found, the unlawful query user who distributes the image can be traced by the watermark extraction. Feature vectors get protected by the secure hashing algorithm, auditing and alert generation are used at image users side for verification purpose....

Content Based Image Retrieval (CBIR) is the application through the integration of various traditional computer vision techniques to the image retrieval problem. CBIR usually contains high volume of personal and authenticated information which makes image privacy as a major concern. The proposed scheme for privacy allows the data owner to outsource the image database and the CBIR service to the cloud, without revealing the actual content of the database to the cloud server. The system uses only the index of the query image to prevent revealing the content of the image. Second, the image is encrypted using the session key generated between the client and the cloud server and then sent to the server for computation. Being the reduced information, it is computing stiff for the server to know the client's interest. The proposed architecture also uses a novel framework called Apache Spark which is considered to 100x faster than MapReduce in certain applications. Result shown Apache Spark is in-memory computations which helps a lot in the retrieval of similar images. Apache Spark framework has been used when the images are newly inserted into the Cloud storage at the point of which features are extracted from the image using transformation and action functionalities and stored in the feature database.

In this article, a higher-order degree of freedom (DOF) proportional-integral-derivative (PID) (3DOFPID) controller optimized with the meta-heuristic method of the water cycle algorithm (WCA) is proposed. Initially, WCA-tuned 3DOFPID is designed to the widely accepted power system model of two-area simple hydro-thermal (TASHT) system and the presented controller efficacy is revealed with other techniques discussed in the literature. Later, another interconnected power system model of two areas nonlinear realistic hydro thermal (TANRHT) system is considered for the investigative purpose by subjugating area-1 with step load perturbation (SLP) of 10%. The proposed controller is implemented to TANRHT without and with deliberating the integration of a geothermal power plant (GTPP). Dynamical responses of TANRHT reveal the efficacy of 3DOFPID over PID and 2DOFPID. Further, the impact of GTPP integration on the performance of the TANRHT system is demonstrated. Furthermore, the coordinated territorial strategy of superconducting magnetic energy storage (SMES) and unified power flow controller (UPFC) is enacted with GTPP-integrated TANRHT system for performance improvement. Finally, the sensitivity analysis is conducted to reveal the robustness of proposed secondary and territorial control strategies.

In our study, we introduce a novel hybrid ensemble model that synergistically combines LSTM, BiLSTM, CNN, GRU, and GloVe embeddings for the classification of gene mutations in cancer. This model was rigorously tested using Kaggle's Personalized Medicine: Redefining Cancer Treatment dataset, demonstrating exceptional performance across all evaluation metrics. Notably, our approach achieved a training accuracy of 80.6 %, precision of 81.6 %, recall of 80.6 %, and an F1 score of 83.1 %, alongside a significantly reduced Mean Squared Error (MSE) of 2.596. These results surpass those of advanced transformer models and their ensembles, showcasing our model's superior capability in handling the complexities of gene mutation classification. The accuracy and efficiency of gene mutation classification are paramount in the era of precision medicine, where tailored treatment plans based on individual genetic profiles can dramatically improve patient outcomes and save lives. Our model's remarkable performance highlights its potential in enhancing the precision of cancer diagnoses and treatments, thereby contributing significantly to the advancement of personalized healthcare.

Automatic generation control (AGC) plays a crucial role in modern power system to control the frequency with change in power demand. A novel fractional
order (FO) hybrid PID-fuzzy-PID (FO-hPID-FPID) controller is proposed in
this paper as the secondary controller for AGC of a three unequal area inter-connected nonlinear reheat thermal power system considering generation rate
constraint. This paper also deals with the implementation of FO fuzzy PID
(FOFPID) and FO PID (FOPID) controllers in addition to the proposed controller along with their counterpart integer order controllers to establish the
dominance of FO controllers over integer order controllers. Various parameters of the controllers are optimized by hybridizing two global optimization
techniques: particle swarm optimization and modified sine cosine algorithm
(MSCA) and the optimization techniques so obtained is called as hybrid PSOMSCA (hPSO-MSCA) technique. A step load perturbation of 0.01 p.u. is
injected in area-1, and the system response is investigated independently with
different controllers. It is revealed that the proposed FO-hPID-FPID delivers
superior performance than the other controllers. Sensitivity analysis for parametric variations is carried out, and random load test is performed to validate the robustness of the proposed controller. Further, it is observed that the
controllers deliver result in an ascending order of control performance as PID,
FOPID, FPID, FOFPID, hPID-FPID and FO-hPID-FPID controllers with
FO-hPID-FPID controller delivering the best result and the FO controllers
deliver better control performance than their integer order counterparts.

In order to enhance the control action, in this article multi degree of freedom PID controllers (MDFPID) like 2DOF-PID and 3DOF-PID controllers are suggested for frequency control in a multi-unit hydro-thermal interconnected system. The finest gains of the recommended MDFPID controllers are achieved with Grey Wolf Optimization (GWO) Technique considering a time based evaluative function. The dom-inating performance of the suggested control technique is validated by relating the outcomes with a pre-published journal results. The robust behavior of the MDFPID controller is also validated by abruptly amplifying the loading of the system. The system dynamic responses are analyzed in consideration with time response parameters like minimum undershoots, settling time and peak overshoots.  

The operation and control of the modern power system has become complex and difficult due to the incessant penetration of nonconventional energy sources integrated to the power grid and the structural variation of power system with continuing escalation of power demand in recent years. This entails the implementation of intelligent control strategy for satisfactory operation of the power system. Hence, a fractional order fuzzy proportional integral derivative (FOFPID) controller is suggested in this article for automatic generation control of two unequal area interconnected power system with diverse generating units such as thermal, hydro, diesel and wind power plants. The dynamic performance of the system is investigated by using proportional integral derivative (PID), fractional order PID (FOPID), fuzzy PID (FPID) and fractional order fuzzy PID (FOFPID) controllers separately. The parameters of these controllers are optimised by using ant lion optimiser algorithm with integral tim...

The continuous stirred-tank reactors have complex dynamic behavior. In the reactor, the residual concentration decreases during an exothermic chemical reaction. In this transition proper cooling is essential to stabilize the reaction, and to prevent reactor overheating. This paper presents the data-driven metaheuristic state-dependent parameter proportional-integration-plus (M-SDP-PIP) control as an alternative of gain-scheduled control for adjusting the coolant temperature of the reactor. In fact, the parameters of the discrete transfer function were identified in the non-minimal state space using state-dependent parameter which is a nonlinear method; and weighting matrixes of linear quadratic servomechanism cost function of the optimal controller were achieved by metaheuristic methods, genetic algorithm, and particle swarm optimization, according to the minimization of the integral absolute error index and energy consumption. The proposed controller was compared to gain-scheduled and non-gain-scheduled controllers in the closed-loop condition in terms of tracking performance. The results show particle swarm optimization algorithm converge to the same optimal solution as genetic algorithm using fewer number of function evaluation, so that proposed controller has more effective offset-free servo-regulatory performance than other control schemes. In addition, it is simpler and more comprehensible because it requires no auxiliary equations and models to determine and manage the control gain, as opposed to the gain-scheduled structure.

Secondary controllers are implemented in the alternator control loop to take care of the swinging of frequency initiated due to inequality of load and demand. A fractional fuzzy-PID controller (FFPID) is projected in this work for frequency deviation control in unified system including EV aggregators and superconducting magnetic energy storage (SMES). EVs and SMES are given primacy because of their ecofriendly nature. Proper adjustment of gains of FFPID is also required to extract the best performance of the secondary controllers. Here a recent tuning process named as artificial rabbits optimization (ARO) is applied for proper tuning of projected controller. The implemented dual area power system includes time varying delay-based EV aggregators, SMES, and thermal generating units. The ARO technique is applied in the model to tune the controller constraints with abrupt increment of demand in one of the control areas. A time-based function is treated as fitness function to evaluate the system performance. The dominance property of the projected FFPID controller over conventional PID and FPID controller in terms of different response specifications like maximum positive deviation (overshoot), settling time and minimum negative deviation (undershoot). The robust nature of the projected controller is also confirmed by multiple analysis like random load deviations and system constraint alteration.

ABSTRACTIdentifying functional non-coding variants can enhance genome interpretation and inform novel genetic risk factors. We used whole genomes and peripheral white blood cell transcriptomes from 624 Sardinian individuals to identify non-coding variants that contribute to population, family, and individual differences in transcript abundance. We identified 21,183 independent expression quantitative trait loci (eQTLs) and 6,768 independent splicing quantitative trait loci (sQTLs) influencing 73 and 41% of all tested genes. When we compared Sardinian eQTLs to those previously identified in Europe, we identified differentiated eQTLs at genes involved in malarial resistance and multiple sclerosis, reflecting the long-term epidemiological history of the island’s population. Taking advantage of pedigree data for the population sample, we identify segregating patterns of outlier gene expression and allelic imbalance in 61 Sardinian trios. We identified 809 expression outliers (median z-s...

Promoters and enhancers are key cis-regulatory elements, but how they orchestrate to generate cell-type-specific transcriptomes remains elusive. We developed a simple and robust approach to globally determine 5’-ends of nascent RNAs (NET-CAGE) in diverse cells and tissues, thereby sensitively detecting unstable transcripts including enhancer-derived RNAs. We studied RNA synthesis and degradation at the transcription start site level, uncovering the impact of differential promoter usage on transcript stability. We quantified transcription from cis-regulatory elements without influence of RNA turnover, and identified enhancer-promoter pairs which were simultaneously activated upon cellular stimulation. By integrating NET-CAGE data with chromatin interaction maps, we revealed that cis-regulatory elements are topologically connected according to their cell-type specificity. We discovered new enhancers with high sensitivity, and delineated primary locations of transcription within super-...

This article proposed a Grasshopper optimization algorithm (GOA) based cascade controller i.e. fuzzy-PD with PI controller (FPD-PI) for the study of load frequency control. A three unequal-area interconnected power system employed with thermal units has been considered for the present study. Initially, the performance of the GOA technique is verified over the Ant-lion optimization technique with integral square error (ISE) as an objective function. Finally, the supremacy of the proposed FPD-PI controller is verified over other benchmark controllers namely PID and fuzzy-PID with GOA, after ensuring the superiority of integral time multiplied absolute error (ITAE) over ISE.

With almost no consensus promoter sequence in prokaryotes, recruitment of RNA polymerase (RNAP) to precise transcriptional start sites (TSSs) has remained an unsolved puzzle. Uncovering the underlying mechanism is critical for understanding the principle of gene regulation. We attempted to search the hidden code in ~16500 promoters, of twelve prokaryotes representing two kingdoms, in their structure and energetics. Twenty eight fundamental parameters of DNA structure including backbone angles, base pair axis, inter base pair and intra base pair parameters were used and information was extracted from X-ray crystallography (XRC) data. Three parameters (solvation energy, hydrogen bond energy and stacking energy) were selected for creating energetics profiles using in-house programs. DNA was found to be inherently designed to undergo a change in every parameter undertaken, from some distance upstream of TSSs to adopt a signature state at these locations in all prokaryotes. These signatu...

This paper deals with the design of Fuzzy Proportional Integral and Derivative FPID controller self tuned by Relative Rate Observer RRO method. The developed approach is applied to the Load-Frequency Control LFC of the Egyptian power system EPS as a single area with multi unit power system. The studied power system comprises three power plants; non-reheat, reheat and hydro generation plants. The proposed FPID controller is designed on an average point of four loading conditions of the EPS during summer and winter of 2008. The effectiveness of the proposed FPID self tuned by RRO (FPID-RRO) has been demonstrated by introducing the system nonlinearities using MATLAB-SIMULINK simulation program. Moreover, a comparison of the FPID with FPID-RRO controllers under different disturbances and parameter variations are presented to validate the FPID-RRO controller. The simulation results reflect and prove fast settling time and accurate tracking for the LFC of the Egyptian Power System.

This paper presents a detailed comparative analysis between Symmetrical and Asymmetrical Quasi Z-Source Cascaded Multilevel Inverter (QZS-CMI). The comparative analysis investigates for boost operation in both Symmetrical and Asymmetrical System. Analysis is done based on the achieved input current, capacitor voltage of the upper capacitor and parallel capacitor and the two inductors current of DC link (Quasi Z-Source network) which is combined with H-bridge. In Asymmetrical QZS-CMI, the input voltage for three DC sources are given in the ratio of 1:3:9, i. e. the system is designed for 27 level. Asymmetrical QZS-CMI is new system and proposed in this paper for comparative analysis with Symmetrical QZS-CMI. An advanced optimal Alternative Phase Opposition Disposition (APOD) technique is developed and implemented. Symmetrical system has high boosting capability of output voltage, reducing the switching losses, high voltage gain and lower spikes in switching voltage. The comparative study is done and results are verified with Experimental 250 W prototype model and also verified by using MATLAB/ Simulink.

Quasi-Z-source inverter has the ability to provide boost and DC-AC conversion of the input voltage in a single stage. The impedance network of the quasi-Z-source inverters offers unique advantages such as lower component ratings, constant DC current from source and capability to handle wide input voltage. Cascaded multilevel inverters are preferred as they are transformerless and modular and provide lower harmonics. The advantages of both are combined in five-level quasi-Z-source cascaded multilevel inverter, and the various modulation strategies applied to it are investigated in this paper. This paper focuses on phase-shifted pulse width modulation with simple boost, maximum boost and maximum constant boost control, phase-shifted pulse width amplitude modulation and hybrid pulse width modulation. Simulation of single-phase five-level quasi-Z-source cascaded multilevel inverter with the above-mentioned strategies has been carried out in MATLAB/Simulink. A hardware prototype of the five-level qZS-CMI has been developed. The PS-PWAM pulses have been implemented through FPGA/ Spartan 3E, and the results are validated.

Brushless DC motor has permanent magnets in the rotor side that rotates around fixed armature. The current rotates in armature continuously as it is electronically commutated. The motor's efficiency will otherwise reduce due to commutation angle errors. The novelty of the work is to reduce commutation errors that are obtained based on commutation point phase shift and the dc-link current difference. Based on these relationship analysis is made under ideal, advanced and delayed commutations. The self-compensation method of commutation instant deviation delays the commutation angle by 10º thus reducing the impact caused by commutation ripple thereby improving dynamic response and control. The dc-link current difference decrease gradually and phase deviation converges to correct the commutation angle. The proposed correction method can achieve ideal commutation effect thereby attaining fast convergence speed, current and torque.

A novel feature extraction algorithm using Otsu’s Threshold (OT-features) on scrambled images and the Instantaneous Clustering (IC-CBIR) approach is proposed for Content-Based Image Retrieval in cloud computing. Images are stored in the cloud in an encrypted or scrambled form to preserve the privacy content of the images. The proposed method extracts the features from the scrambled images using the Otsu’s threshold. Initially, the Otsu’s threshold is estimated from the scrambled image and based on this threshold the image is divided into two classes in the first iteration. Again, the new threshold values are estimated from two classes. The difference between the new threshold and the previous threshold gives two features. This process is repeated for number of iteration to obtain the complete OT-features of the scrambled image. This paper also proposes an instantaneous clustering approach (IC-CBIR) where the image is moved into a cluster as soon as the image is uploaded by the image owner. Therefore while retrieving the images, the images near to a particular cluster are matched instead of matching with a complete set of image features in the dataset which reduces the search time. The performance of the proposed algorithm is being tested using four different types of the dataset such as Corel 10K, Misc, Oxford flower, and INRIA Holidays dataset. The experimental evaluation reveals that the proposed method outperforms better than the traditional CBIR algorithm on encrypted images in terms of precision, time of search and time of index construction.

https://www.isecure-journal.com/article_118099.html

Storage requirements for visual data have been increasing in recent years, following the emergence of many highly interactive multimedia services and applications for mobile devices in both personal and corporate scenarios. This has been a key driving factor for the adoption of cloud-based data outsourcing solutions. However, outsourcing data storage to the Cloud also leads to new security challenges that must be carefully addressed, especially regarding privacy. In this paper we propose a secure framework for outsourced privacy-preserving storage and retrieval in large shared image repositories. Our proposal is based on IES-CBIR, a novel Image Encryption Scheme that exhibits Content-Based Image Retrieval properties. The framework enables both encrypted storage and searching using Content-Based Image Retrieval queries while preserving privacy against honest-but-curious cloud administrators. We have built a prototype of the proposed framework, formally analyzed and proven its security properties, and experimentally evaluated its performance and retrieval precision. Our results show that IES-CBIR is provably secure, allows more efficient operations than existing proposals, both in terms of time and space complexity, and paves the way for new practical application scenarios.

In this paper, a new single-phase seven-level quasi-Z-source (qZs) inverter with reduced switch count for multistring photovoltaic applications is proposed, which is capable of supplying both direct current (dc) and alternating current (ac) loads simultaneously. The proposed configuration is derived from a combination of qZs networks and asymmetrical seven-level inverter. The front-end qZs converter boosts the input voltage obtained from the dc sources to the desired value, whereas the asymmetrical seven-level inverter performs dc-ac conversion with reduced switch count and provides better efficiency. The steady-state performance of the model is evaluated in both continuous conduction mode (CCM) and discontinuous conduction mode (DCM) of operation. In addition, the dynamic performance of the model is tested for the load as well as input voltage changes. A simple proportional-integral (PI) controller is implemented in FPGA Spartan-6 Processor using Xilinx system generator blocks. An experimental prototype is also developed to validate the feasibility of the proposed topology. Finally, a brief comparative assessment is formulated with other topologies to show the merits of the proposed structure.

In this paper, a new configuration of seven-level quasi Z-source (qZs)-based isolated inverter is introduced in the family of Z-source-based multilevel inverters (MLIs). The proposed topology is an upgrade of qZs inverter and asymmetrical seven-level inverter with significant advantages of high boost gain, reduced device count, and higher efficiency. In addition, the front-end qZs converter provides wide input voltage regulation for eco-friendly photovoltaic (PV) as well as fuel cell-based standalone/grid-connected applications. The use of high-frequency transformer blocks the leakage current from PV panels to the local load/grid, and the seven-level inverter produces high quality sinusoidal output waveform, which reduces the filter size. Therefore, the working principle of the proposed configuration is tested in simulation, and an experimental verification is performed to validate the effectiveness of the model. A proportional-integral (PI) controller is designed in field-programmable gate array (FPGA) using Xilinx blocks, and the dynamic response of the model is evaluated for changes in input voltage and step changes in load. Moreover, a brief comparative assessment of proposed configuration with existing sevenlevel qZs-MLI is also presented. KEYWORDS isolated quasi-Z source inverter, multilevel inverter, pulse-width modulation, shoot-through 1 | INTRODUCTION Recent advancements in Z-source-based converters have witnessed tremendous growth in terms of usage in potential applications such as eco-friendly photovoltaic (PV)/fuel cell-based generations to meet the increasing power demands, flexible alternating current transmission system (FACTS) devices, energy storage, and electric vehicles and wind energy conversion systems. 1 Z-source-based converters have emerged as a viable alternative among other converters because of the obvious advantages of wide output voltage regulation with inherent buck-boost capability. This improves the overall efficiency in single-stage conversion compared with the dc-dc converter-based two-stage conversion. The Z-source List of symbols and abbreviations: B, boost factor; C 1 , C 2 , capacitances of the qZs network; CHB, cascaded H-bridge; D 0 , shoot-through duty cycle; I L , average inductor current; I C , average capacitor current; L 1 , L 2 , inductances of the qZs network; M, modulation index; MLI, multilevel inverter; N P , number of turns of transformer primary winding; N S1 , N S2 , number of turns of transformer secondary windings; PV, photovoltaic; PWM, pulse-width modulation; V DC , dc-link voltage; V PV , pv voltage; i PV , pv current; TBV, total blocking voltage; T, switching period; qZSI, quasi z-source inverter; ZSI, z-source inverter

In this paper, a single-phase multistring <strong>seven-level Quasi-</strong>Z-source based Asymmetrical Inverter suitable for grid-connected photovoltaic (PV) system is presented.<strong> </strong>This topology is <strong>an upgrade of quasi-</strong>Z-source dc-dc (qZs) network and Asymmetrical multilevel inverter (AMLI). The AMLI generates higher number of levels with reduced switch count and number of sources when compared to symmetrical cascaded based MLI. The qZs network acts as an intermediate stage between the low-voltage PV array and AMLI, to enhance the output voltage gain of the inverter. The steady state performance the topology is verified through MATLAB simulation and experimentation. A laboratory prototype model is developed for a capacity of 200W to validate the theoretical studies. Finally, a <strong>c</strong>omparative assessment of the proposed with the existing topologies is presented.

In this study, a fuzzy proportional integral derivative controller (FPID) was adjusted using the differential evolution (DE) method to enhance the automated generation control (AGC) of a three-zone reheat-type power system. The objective function used in this study was an integral of the time-weighted absolute error (ITAE). In the optimization, the gain control parameters of the proportional integral (PI), the integral (I), and FPID were optimized and compared to improve the limitations drawn by the controller over a few parameters. To demonstrate that FPID controllers with IPFC produce better and more accurate optimization results than integral and PI controllers optimized by DE, the interline power flow control (IPFC) of a flexible AC transmission system (FACTS) device with suitable connections and control parameter optimization was used. Also, the particle swarm optimization (PSO) PID with IPFC was compared with the proposed DEFPID + IPFC, and better results were achieved by usin...

A power system’s nonlinearity and complexity increase from time to time due to increases of power demand. Therefore, properly designed power system controlsare required. Without these, system instability will cause equipment failures, and possibly even cascading events and blackouts. To cope with this, intelligent controllers using soft computing are necessary for real time operation. In this paper, the reheat type three-area thermal power system is considered, and the output scaling factors, gain parameters of fuzzy membership functions, and parameters of fuzzy-proportional integral derivative (FPID) controllers are optimized using a differential evolution (DE) optimization techniqueand integral time multiplied absolute error (ITAE) as objective functions. To improve the limitations of the controller and to enhance stability of the system, high voltage direct current (HVDC) technology is advantageous due to its quickresponse capabilities. In this paper, a HVDC is connected in paral...

Enhancers are important noncoding elements, but they have been traditionally hard to characterize experimentally. Only a few mammalian enhancers have been validated, making it difficult to train statistical models for their identification properly. Instead, postulated patterns of genomic features have been used heuristically for identification. The development of massively parallel assays allows for the characterization of large numbers of enhancers for the first time. Here, we developed a framework that uses Drosophila STARR-seq data to create shape-matching filters based on enhancer-associated meta-profiles of epigenetic features. We combined these features with supervised machine learning algorithms (e.g., support vector machines) to predict enhancers. We demonstrated that our model could be applied to predict enhancers in mammalian species (i.e., mouse and human). We comprehensively validated the predictions using a combination of in vivo and in vitro approaches, involving trans...

A microcontroller based pulse width modulation implementation for multilevel quasi Z source inverter is proposed in this paper. The component design of quasi z source inverter (qZSI) is first considered with continuous and discontinuous mode of operations. The low switching frequency operation of multilevel quasi Z source inverter is proposed in this paper. The detailed modelling for qZSI is then established for effective implementation of PIC microcontroller (PIC 16F877A) for generating the switching signals. A prototype of five level quasi z-source inverter have been developed and the control signal to the gate drivers have been applied by properly adjusting the shoot through and non shoot through switching states. The hardware result shows the effective implementation of the proposed scheme.

Application of Data Mining tasks over health care has gained much importance nowadays. Most of the Association Rule Mining techniques attempts to extract only the positive recurrent itemsets and pay less attention towards the negative items. The paper is all about medical assistance, which concentrates on retrieving both positive and negative recurrent itemsets in a efficient way by compressing the overall data available. Stemming methods help in this compression of data to half of its size in order to reduce and save memory space. To analyze data, the clustering technique is applied, especially the k-means clustering is used, as it is found to be more effective, easy and less time consuming method when compared to other clustering flavours.

Storage requirements for visual data have been increasing in recent years, following the emergence of many highly interactive multimedia services and applications for mobile devices in both personal and corporate scenarios. This has been a key driving factor for the adoption of cloud-based data outsourcing solutions. However, outsourcing data storage to the Cloud also leads to new security challenges that must be carefully addressed, especially regarding privacy. In this paper we propose a secure framework for outsourced privacy-preserving storage and retrieval in large shared image repositories. Our proposal is based on IES-CBIR, a novel Image Encryption Scheme that exhibits Content-Based Image Retrieval properties. The framework enables both encrypted storage and searching using Content-Based Image Retrieval queries while preserving privacy against honest-but-curious cloud administrators. We have built a prototype of the proposed framework, formally analyzed and proven its security properties, and experimentally evaluated its performance and retrieval precision. Our results show that IES-CBIR is provably secure, allows more efficient operations than existing proposals, both in terms of time and space complexity, and paves the way for new practical application scenarios.

Due to varying structure, random load demands, nonlinearities, parameters ambiguity, steadily escalating size and intricacy of the interconnected power system (IPS), automatic generation control (AGC) is treated as one of the biggest crucial issues in IPS. Hence, expert, intelligent and robust control scheme is indispensable for stable operation of IPS and supply of electricity under sudden load demand disturbances. In vision of this, in this work, a novel cascade fuzzy-proportional integral derivative incorporating filter (PIDN)-fractional order PIDN (FPIDN-FOPIDN) controller is offered as an expert control strategy to deal effectively with AGC issue of IPS. Imperialist competitive algorithm is prolifically utilized for optimizing the controller parameters. Initially, a two area non-reheat thermal IPS is studied in detail and next to attest the efficacy of the technique, the study is extended to realistic two-area multi-source thermalhydro-gas and reheat thermal three-area systems. The prominent benefit of cascade FPIDN-FOPIDN strategy comprises its great lethargy to large load demands and its supremacy over various latest intelligent classical/fuzzy controllers. The control strategy beats several techniques concerning significant lesser settling time, oscillations, over/under shoots and different performance index values. Finally, a robustness investigation is performed in order to validate the robustness of the controller.

To enhance the performance and dynamics of a direct current (DC) motor drive, this paper proposes a new alternative based on recently introduced powerful symbiotic organisms search (SOS) algorithm for tuning proportional integral parameters. While imitating the symbiotic behavior that is seen among organisms in an ecosystem, SOS has important features such that it does not require tuning parameters, and its implementation is very easy with efficient three phases. After obtaining the optimized values of K p-K i pair within the accurately prepared simulation software, they are used in real time. By managing the DC motor speed-controlled system with DSP of TMS320F28335, several simulations and experimental results confirming the performance of our proposal are presented along with comparisons against those of particle swarm optimization (PSO), genetic algorithm (GA), and Ziegler-Nichols (Z-N) tuning method. Results explicitly show that SOS is the pioneer in yielding better tracking performance and load disturbance rejection capability of the concerned drive system, which is followed by PSO, GA, and Z-N method, respectively. This has been achieved due to the fact that the gains obtained by SOS are more performant than those obtained by other applied methods.

In this study, a fuzzy proportional integral derivative controller (FPID) was adjusted using the differential evolution (DE) method to enhance the automated generation control (AGC) of a three-zone reheat-type power system. The objective function used in this study was an integral of the time-weighted absolute error (ITAE). In the optimization, the gain control parameters of the proportional integral (PI), the integral (I), and FPID were optimized and compared to improve the limitations drawn by the controller over a few parameters. To demonstrate that FPID controllers with IPFC produce better and more accurate optimization results than integral and PI controllers optimized by DE, the interline power flow control (IPFC) of a flexible AC transmission system (FACTS) device with suitable connections and control parameter optimization was used. Also, the particle swarm optimization (PSO) PID with IPFC was compared with the proposed DEFPID + IPFC, and better results were achieved by usin...

Automatic generation control (AGC) also known as load frequency control plays a vital role in interconnected power system for frequency regulation. Electric vehicles (EVs) with battery as the storage device can participate in frequency regulation service. In practice, a large number of EVs are aggregated as a single unit called EV aggregator for participation in frequency regulation service in AGC system. Participation of EV aggregators in AGC system for frequency regulation will be encouraged in near future because EVs have less environmental pollution than the conventional vehicles. However, participation of EV aggregators in AGC system may introduce time delay which degrades the dynamic performance of the power system and even may lead to system instability. Further, generation rate constraint (GRC) and governor dead band (GDB) of synchronous generator introduce nonlinearity in the system, which adversely affects its dynamic performance. Hence, selection of an appropriate control strategy is essential for performance enrichment of the power system. In this work, a PID-fuzzy-PID (PID-FPID) controller optimally designed by hybridizing particle swarm optimization (PSO) and modified sine cosine algorithm (MSCA) is proposed and a novel attempt is made to improve the frequency stability of a two-equal-area interconnected thermal power system with GDB and GRC incorporating an EV aggregators with time-varying delay in each area. Integral time absolute error has been chosen as the objective function to optimally design the controller parameters. Dynamic performance of the system is also investigated with proportional-integral-derivative (PID) controller optimally designed by PSO, sine cosine algorithm (SCA), MSCA, and hybrid PSO-MSCA. The efficacy and supremacy of the proposed hybrid PSO-MSCA-based PID-FPID control strategy is established by contrasting the results with the others. Finally, the robustness of the proposed control strategy is validated by (i) including two EV aggregators with time-varying delay in each area, (ii) applying a large disturbance of 0.4 p.u. in area-1, and (iii) applying a random load in area-1.

Storage requirements for visual data have been increasing in recent years, following the emergence of many highly interactive multimedia services and applications for mobile devices in both personal and corporate scenarios. This has been a key driving factor for the adoption of cloud-based data outsourcing solutions. However, outsourcing data storage to the Cloud also leads to new security challenges that must be carefully addressed, especially regarding privacy. In this paper we propose a secure framework for outsourced privacy-preserving storage and retrieval in large shared image repositories. Our proposal is based on IES-CBIR, a novel Image Encryption Scheme that exhibits Content-Based Image Retrieval properties. The framework enables both encrypted storage and searching using Content-Based Image Retrieval queries while preserving privacy against honest-but-curious cloud administrators. We have built a prototype of the proposed framework, formally analyzed and proven its security properties, and experimentally evaluated its performance and retrieval precision. Our results show that IES-CBIR is provably secure, allows more efficient operations than existing proposals, both in terms of time and space complexity, and paves the way for new practical application scenarios.

This article presents automatic generation control (AGC) of an interconnected multi area thermal system. The control areas are provided with single reheat turbine and generation rate constraints of 3%/min. A maiden attempt has been made to apply a Proportional derivative-Proportional integral derivative (PD-PID) cascade controller in AGC. Controller gains are optimized simultaneously using more recent and powerful evolutionary computational technique Bat algorithm (BA). Performance of classical controllers such as Proportional Integral (PI) and Proportional Integral Derivative (PID) controller are investigated and compared with PD-PID cascade controller. Investigations reveal that PI, and PID provide more or less same response where as PD-PID cascade controller provides much better response than the later. Dynamic analysis has also been carried out for the controllers in presence of random load pattern, which reveals the superior performance of the PD-PID cascade controller. Sensitivity analysis reveals that the BA optimized PD-PID Cascade controller parameters obtained at nominal condition of loading, size and position of disturbance and system parameter (Inertia constant, H) are robust and need not be reset with wide changes in system loading, size, position of disturbance and system parameters. The system dynamic performances are studied with 1% step load perturbation in Area1.

Gene regulatory regions contain short and degenerated DNA sites recognized by transcription factors (TFs). When such regions harbor SNPs, the DNA motifs where TFs bind may be affected, thereby altering the transcriptional regulation of the target genes. Such regulatory SNPs have been implicated as causal variants in GWAS studies. In this study, we describe the application of the programs Var-tools designed to predict regulatory variants, and present four case studies to illustrate their usage and applications. In brief, Var-tools facilitate i) obtaining variation information, ii) interconversion of variation file formats, iii) retrieval of sequences surrounding variants, and iv) calculating the change on predicted TF affinity scores between alleles, using motif scanning approaches. Notably, the tools support the analysis of haplotypes. The tools are included within the well-maintained suite Regulatory Sequence Analysis Tools (RSAT, http://rsat.eu), and accessible through a web inter...

This paper presents a new control method for Quasi-Z-Source cascade multilevel inverter based on Grid connected Single phase photovoltaic power system. The control system enables the voltage boost of a PV string to a higher level and produces a balanced DClink voltage in H-bridge inverters. A novel Space vector modulation for QZS-CMI is presented to control the shoot through states independently and synthesize a staircase output voltage waveform. The system achieves independent Maximum power point tracking for separate PV arrays, independent DC-link voltage and the grid injected power control at unity power factor. A Fuzzy logic control scheme is developed to PV array voltage control loop, it adjusts the sum of pv arrays to track its reference value with reduced transients.. The system demonstrates stable output voltage with reduced total harmonic distortion. The proposed system components are modeled and simulated through software tool using MATLAB/SIMULINK.

In this study, a fuzzy proportional integral derivative controller (FPID) was adjusted using the differential evolution (DE) method to enhance the automated generation control (AGC) of a three-zone reheat-type power system. The objective function used in this study was an integral of the time-weighted absolute error (ITAE). In the optimization, the gain control parameters of the proportional integral (PI), the integral (I), and FPID were optimized and compared to improve the limitations drawn by the controller over a few parameters. To demonstrate that FPID controllers with IPFC produce better and more accurate optimization results than integral and PI controllers optimized by DE, the interline power flow control (IPFC) of a flexible AC transmission system (FACTS) device with suitable connections and control parameter optimization was used. Also, the particle swarm optimization (PSO) PID with IPFC was compared with the proposed DEFPID + IPFC, and better results were achieved by usin...

A power system’s nonlinearity and complexity increase from time to time due to increases of power demand. Therefore, properly designed power system controlsare required. Without these, system instability will cause equipment failures, and possibly even cascading events and blackouts. To cope with this, intelligent controllers using soft computing are necessary for real time operation. In this paper, the reheat type three-area thermal power system is considered, and the output scaling factors, gain parameters of fuzzy membership functions, and parameters of fuzzy-proportional integral derivative (FPID) controllers are optimized using a differential evolution (DE) optimization techniqueand integral time multiplied absolute error (ITAE) as objective functions. To improve the limitations of the controller and to enhance stability of the system, high voltage direct current (HVDC) technology is advantageous due to its quickresponse capabilities. In this paper, a HVDC is connected in paral...

Quasi-Z-Source Cascaded H-bridge Multilevel inverters (qZS-CHB-MLI) have attracted much interest in recent research works due to its rewarding advantages when compared with traditional voltage source inverters and Z-source Inverters. The qZS-CHB-MLI has limited output voltage boosting capability, and requires more number of switches as the number of levels increases. This increases the volume and cost of the qZS-CHB-MLI with limited voltage boosting capability. In order to surmount these problems, a new Voltage-Lift Quasi-Z-Source Modified Cascaded H-Bridge Multilevel Inverter (VL-qZS-M-CHB-MLI) is presented in this paper. The proposed topology utilizes lower number of switches for generating seven level output voltage as compared with traditional qZS-CHB-MLI for the same voltage level. The presence of voltage-lift cell in the proposed topology significantly increases the voltage boosting capability, providing boosted output voltage with reduced Total Harmonic Distortion (THD). The ...

Background/Objectives: Quasi-Z-source based multilevel inverters have attracted much interest in recent research works due to its valuable merits when evaluated with conventional voltage source inverters and Z-source Inverters. The objectives of this research work is to provide lower power rating of power devices, continuous input current, higher boosted output voltage and reduced current stress for dc source. Methods/Statistical analysis: A new quasi-Z-source Cascaded H-Bridge multilevel inverter with voltage-lift cell (VL-qZS-CHB-MLI) is analysed in this research paper. The performance of the VL-qZS-CHB-MLI is verified through simulation results obtained using multicarrier PD-PWM technique with simple boost control strategy. Shoot-through states are introduced in generated pulses by utilizing the simple boost control technique. Extended boost operation of the proposed topology is provided by the shoot-through states. Findings: In this new proposed topology, the presence of voltage-lift cell significantly strengthens the boost capability for the equal shoot-through duty ratio as in traditional qZS-CHB-MLI. The proposed topology involves lower shoot-through duty ratio as in the qZS-CHB-MLI for achieving the same boost gain. This advantage of the proposed topology makes possible the larger improvement in the output voltage. Application/Improvements: The proposed topology can be popularly utilized for high-power applications requiring good quality boosted output and low voltage stress. Also, the proposed topology offered abundant merits over traditional Cascaded H-Bridge (CHB) multilevel inverter in distributed power generation applications like PV power system and wind energy system.

The PID controller is a popular controller that is widely used in various industrial applications. On the other hand, the control problems in microgrids (MGs) are so challenging, because of natural disturbances such as wind speed changes, load variation, and changes in other sources. This paper proposes an input-output scaling factor tuning of interval type-2 fuzzy (IT2F) PID controller using a multi-objective optimization technique. The suggested controller is applied to an MG frequency regulation problem. In the introduced controller the effect of variations of renewable energies (REs) and other disturbances are taken into account, and the robustness is investigated. In the multi-objective scheme, some factors such as least overshoot, and minimum settling/rising time are considered. The simulations show that by considering the suitable adjustment the desired regulation accuracy is achieved, such that the frequency trajectory shows the desired overshoot, and settling/rising time.

Storage requirements for visual data have been increasing in recent years, following the emergence of many new highly interactive multimedia services and applications for both personal and corporate use. This has been a key driving factor for the adoption of cloud-based data outsourcing solutions. However, outsourcing data storage to the Cloud also leads to new challenges that must be carefully addressed, especially regarding privacy. In this paper we propose a secure framework for outsourced privacy-preserving storage and retrieval in large image repositories. Our proposal is based on IES-CBIR, a novel Image Encryption Scheme that displays Content-Based Image Retrieval properties. Our solution enables both encrypted storage and searching using CBIR queries while preserving privacy. We have built a prototype of the proposed framework, formally analyzed and proven its security properties, and experimentally evaluated its performance and precision. Our results show that IES-CBIR is provably secure, allows more efficient operations than existing proposals, both in terms of time and space complexity, and enables more reliable practical application scenarios.

Due to varying structure, random load demands, nonlinearities, parameters ambiguity, steadily escalating size and intricacy of the interconnected power system (IPS), automatic generation control (AGC) is treated as one of the biggest crucial issues in IPS. Hence, expert, intelligent and robust control scheme is indispensable for stable operation of IPS and supply of electricity under sudden load demand disturbances. In vision of this, in this work, a novel cascade fuzzy-proportional integral derivative incorporating filter (PIDN)-fractional order PIDN (FPIDN-FOPIDN) controller is offered as an expert control strategy to deal effectively with AGC issue of IPS. Imperialist competitive algorithm is prolifically utilized for optimizing the controller parameters. Initially, a two area non-reheat thermal IPS is studied in detail and next to attest the efficacy of the technique, the study is extended to realistic two-area multi-source thermalhydro-gas and reheat thermal three-area systems. The prominent benefit of cascade FPIDN-FOPIDN strategy comprises its great lethargy to large load demands and its supremacy over various latest intelligent classical/fuzzy controllers. The control strategy beats several techniques concerning significant lesser settling time, oscillations, over/under shoots and different performance index values. Finally, a robustness investigation is performed in order to validate the robustness of the controller.

In this paper presents the controlling the power of using quasi-Z source inverter for renewable source application. The proposed quasi z source is single stage DC to AC converter it delivered buck-boost operation with respect to input. These buck-boost converter is highly suitable compare to the normal dc to dc converter for photovoltaic applications. The proposed single stage converter are reliable and suitable for renewable energy source application. The source impedance quasi network offers high gain compare to the exciting system and reduced the total harmonic level. The quasi-z source followed by single phase H bridge converter uses to convert DC to AC with high reliability output. A proposed system-built Simulink and the hardware made for the open loop control. The conventional voltage and current source inverter have its own limitation of the output voltage low compare to the input source in the voltage source inverter, it is just opposite in the current source inverter. These limitations overcome by designed novel modified z source inverter was developed and controlled pulse using unipolar and bipolar concept. The output of the inverter after filter, it produces the less harmonics result 7.6% on fifth harmonics level compare with conventional inverter.

This paper presents a new control method for Quasi-Z-Source cascade multilevel inverter based on Grid connected Single phase photovoltaic power system. The control system enables the voltage boost of a PV string to a higher level and produces a balanced DClink voltage in H-bridge inverters. A novel Space vector modulation for QZS-CMI is presented to control the shoot through states independently and synthesize a staircase output voltage waveform. The system achieves independent Maximum power point tracking for separate PV arrays, independent DC-link voltage and the grid injected power control at unity power factor. A Fuzzy logic control scheme is developed to PV array voltage control loop, it adjusts the sum of pv arrays to track its reference value with reduced transients.. The system demonstrates stable output voltage with reduced total harmonic distortion. The proposed system components are modeled and simulated through software tool using MATLAB/SIMULINK.