Energy Management System for Microgrid System using Improved Grey Wolf Optimization Algorithm

An Energy Management System (EMS) is indispensable to monitor the power flow and load matching inside a microgrid during grid-connected mode (GCM) and islanded modes (IM) of operation. Many conventional optimization algorithms show poor reliability for real time optimization problem solving where an objective function is non-linear. An optimization technique is necessary to reduce the cost of energy obtained from the grid, generated inside the grid, and consumed by the load. This article presents, an optimization scheme based on the improved Grey wolf optimization (GWO) algorithm that considers replacement of wounded/injured wolves of one pack by strong wolves of other pack for an EMS in micro-grid. The GWO optimization algorithm's effectiveness is demonstrated forGCM and IM operation. The proposed GWO shows fast, lost cost and precise optimization of the real time EMS for the grid connected and islanded micro-grid system

Design of Hybrid Network Anomalies Detection System (H-NADS) Using IP Gray Space Analysis

In Network Security, there is a major issue to secure the public or private network from abnormal users. It is because each network is made up of users, services and computers with a specific behavior that is also called as heterogeneous system. To detect abnormal users, anomaly detection system (ADS) is used. In this paper, we present a novel and hybrid Anomaly Detection System with the uses of IP gray space analysis and dominant scanning port identification heuristics used to detect various anomalous users with their potential behaviors. This methodology is the combination of both statistical and rule based anomaly detection which detects five types of anomalies with their three types of potential behaviors and generates respective alarm messages to GUI.Network Security, Anomaly Detection, Suspicious Behaviors Detection

Identification of Identical Twins using Face Recognition with Results

Face recognition is a process used to identify or verify the person based on digital image from unique face of humans. Face recognition is based on individual and unique person identification. This process fully based on comparing the image with other person image for identification. Face Recognition is typically used in security systems and can be compared with other biometrics such as fingerprint or iris recognition systems. Here, the major problem is to identify twins. To overcome this problem we can use different facial recognition algorithms. The facial recognition algorithms should be able to identify the similar-looking individuals or identical Twins with accurate classification. In the proposed system, image of a person is given as a input then different features of image were extracted by using the Gabor and LBP algorithms. Extracted Features of both the images are compared and then classified using multi-SVM classifier. Based on classification method, the persons were identified to be identical twins or they were identified to be same person or not twins. After Identification, Performance of the process is measured

On Improving Reliability of SRAM-Based Physically Unclonable Functions

Physically unclonable functions (PUFs) have been touted for their inherent resistance to invasive attacks and low cost in providing a hardware root of trust for various security applications. SRAM PUFs in particular are popular in industry for key/ID generation. Due to intrinsic process variations, SRAM cells, ideally, tend to have the same start-up behavior. SRAM PUFs exploit this start-up behavior. Unfortunately, not all SRAM cells exhibit reliable start-up behavior due to noise susceptibility. Hence, design enhancements are needed for improving reliability. Some of the proposed enhancements in literature include fuzzy extraction, error-correcting codes and voting mechanisms. All enhancements involve a trade-off between area/power/performance overhead and PUF reliability. This paper presents a design enhancement technique for reliability that improves upon previous solutions. We present simulation results to quantify improvement in SRAM PUF reliability and efficiency. The proposed technique is shown to generate a 128-bit key in ≤0.2 μ\u27\u3eμμ s at an area estimate of 4538 μ\u27\u3eμμ m 2\u27\u3e22 with error rate as low as 10−6\u27\u3e10−610−6 for intrinsic error probability of 15%

Formulation and Evaluation of Anti-Ulcer Floating Tablet Using Swellable Polymers

Present study involves the formulation and evaluation of floating tablets Ranitidine hydrochloride by direct compression method by using HPMC K4M, HPMC K100M as a synthetic polymers and Gellan Gum (low acyl) as a natural polymer with addition of sodium bicarbonate and citric acid as effervescent agent. The physicochemical compatibility of the drug and the polymers was studied by infrared spectroscopy and differential scanning calorimetry. The results suggested that drug and the polymers were physicochemically compatible with each other. The effect of synthetic and natural polymers on the drug release and floating properties of tablet were investigated. Formulation was optimized on the basis of pre compression and post compression parameters, floating lag time, total floating time and in vitro drug release study was carried out. The floating lag time, dissolution studies indicated that formulation F11 with drug: polymer ratio 5:4 exhibited sustained release of drug and followed Korsemeyer Peppas kinetics. Natural polymer (Gellan Gum) showed better results for sustained drug release properties than synthetic polymer. The floating lag time was found to be increase significantly with increase in concentration of polymer and drug release was found to decrease with increase concentration of polymers

Preparation of guava jam blended with sapota

Jam is prepared from fruit pulp by boiling with sufficient quantity of sugar to a moderately thick consistency.  There are different types of fruit jams like strawberry jam, mango jam, pineapple jam, apple jam and mixed fruit jam.  Hence an attempt was made to find out the possibilities of mixing guava and sapota for making jam and utilizing a major potion of marketable surplus of guava.  Guava and Sapota pulp was blended in the ratios of 100:0, 90:10, 80:20, 70:30, and 60:40 respectively to prepare blended jams.  The treatment of T4, 60% guava pulp and 40% sapota pulp, showed significantly less titrable acidity (1.05%), higher TSS (74.2°Brix) and total sugar (67.28%).  Among the blended jams, the highest score for colour (8.64), flavor (8.88), consistency (8.97), taste (8.12), and overall acceptability (8.78) was judged in the treatment 60% guava pulp and 40% sapota pulp.  Treatment T4, 60% guava pulp and 40% sapota pulp was more in red color.   Keywords: guava, sapota, blending jam, chemical analysis, sensory evaluation, colour analysi

Discovery of Ranking Fraud for Mobile Apps Evidence Aggregation Based Ranking Fraud Detection (EA-RFD)

Ranking fraud within the mobile App market refers to dishonest or deceptive activities that have a purpose of bumping up the Apps within the quality list. Indeed, it becomes additional and additional frequent for App developers to use shady suggests that, like inflating their Apps? sales or posting phony App ratings, to commit ranking fraud. Whereas the importance of preventing ranking fraud has been well known, there's restricted understanding and analysis during this space. to the present finish, during this paper, we offer a holistic read of ranking fraud and propose a ranking fraud detection system for mobile Apps. Specifically, we tend to 1st propose to accurately find the ranking fraud by mining the active periods, specifically leading sessions, of mobile Apps. Such leading sessions will be leveraged for detective work the native anomaly rather than world anomaly of App rankings. Moreover, we tend to investigate 3 forms of evidences, i.e., ranking based mostly evidences, rating {based based mostly primarily based mostly} evidences and review based evidences, by modeling Apps? ranking, rating and review behaviors through applied mathematics hypotheses tests. Additionally, we tend to propose AN optimization based mostly aggregation methodology to integrate all the evidences for fraud detection. Finally, we tend to evaluate the projected system with real-world App knowledge collected from the iOS App Store for an extended fundamental measure. Within the experiments, we tend to validate the effectiveness of the projected system, and show the quantifiability of the detection algorithmic program furthermore as some regularity of ranking fraud activities

AREVIEW-IMPORTANCE OF NIDANPANCHAK IN PANDUROGA

Pandu is a disease entity descrbed in Ayurveda which has clinical features similar to that of various types of anemia, in whivh there develops a pale-yellow discoloration on skin. Pandu is a very commonprevalent disease in the society.Nutritional Iron deficiency is the mostcommon cause of Panduroga in India. Itaffects all age groups but the mostvulnerable are preschool-age children,pregnant women, and non-pregnantwomen of childbearing age. In IndiaMalnutrition, poverty, illiteracy, contributeto anaemia which can be correlated aspandu roga in Ayurveda. In Ayurvedapanduroga has been described in allSamhita in detail with nidan panchak inpresent study. Study deals with systemicreview of Panduroga from all the classicsof Ayurveda