A Study on Vehicle Trajectory Analysis

Successful developments of effective real-time traffic management and information systems demand high quality real time traffic information. In the era of intelligent transportation convergence, traffic monitoring requires traffic sensory technologies. The present analysis extracted data from Mobile Century experiment. The data obtained in the experiment was pre-processed. Based on the pre processed data experimental road map has generated. Individual vehicle tracking has done using trajectory analysis. Finally an attempt has been made for extracting association rules from mobile century dataset using Apriori algorithm

Estimation of the growth curve parameters in Macrobrachium rosenbergii

Growth is one of the most important characteristics of cultured species. The objective of this study was to determine the fitness of linear, log linear, polynomial, exponential and Logistic functions to the growth curves of Macrobrachium rosenbergii obtained by using weekly records of live weight, total length, head length, claw length, and last segment length from 20 to 192 days of age. The models were evaluated according to the coefficient of determination (R2), and error sum off square (ESS) and helps in formulating breeders in selective breeding programs. Twenty full-sib families consisting 400 PLs each were stocked in 20 different hapas and reared till 8 weeks after which a total of 1200 animals were transferred to earthen ponds and reared up to 192 days. The R2 values of the models ranged from 56 – 96 in case of overall body weight with logistic model being the highest. The R2 value for total length ranged from 62 to 90 with logistic model being the highest. In case of head length, the R2 value ranged between 55 and 95 with logistic model being the highest. The R2 value for claw length ranged from 44 to 94 with logistic model being the highest. For last segment length, R2 value ranged from 55 – 80 with polynomial model being the highest. However, the log linear model registered low ESS value followed by linear model for overall body weight while exponential model showed low ESS value followed by log linear model in case of head length. For total length the low ESS value was given by log linear model followed by logistic model and for claw length exponential model showed low ESS value followed by log linear model. In case of last segment length, linear model showed lowest ESS value followed by log linear model. Since, the model that shows highest R2 value with low ESS value is generally considered as the best fit model. Among the five models tested, logistic model, log linear model and linear models were found to be the best models for overall body weight, total length and head length respectively. For claw length and last segment length, log linear model was found to be the best model. These models can be used to predict growth rates in M. rosenbergii. However, further studies need to be conducted with more growth traits taken into consideratio

On Bivariate Pseudo-Logistic Distribution: Its Properties, Estimation and Applications

The literature has covered the features and uses of the traditional univariate and bivariate logistic distributions in great detail. It is reasonable to wonder, though, if logistic marginals and conditionals could exhibit a similar behavior. A phenomenon that is comparable to both bivariate exponential and bivariate normal distributions. In this study, we will concentrate on bivariate distributions where one family of conditionals is marginal and the other family is of logistic type. Pseudo-logistic distributions are the name for such distributions. Research on conditionally specified models has revealed, however, that only in cases where the variables are independent will logistic marginals and both conditionals be of the logistic form occur. We talk about the features of distributional aspects and how they are built using the original. Both the original and the new conditioning regimes are used in two different ways. Possible generalizations are also considered. We also provide an example of a Pseudo-logistic model application

Nitrile hydratase of Rhodococcus erythropolis: characterization of the enzyme and the use of whole cells for biotransformation of nitriles

The intracellular cobalt-type nitrile hydratase was purified from the bacterium Rhodococcuserythropolis. The pure enzyme consisted of two subunits of 29 and 30 kDa. The molecular weight of the native enzyme was estimated to be 65 kDa. At 25 °C the enzyme had a half-life of 25 h. The Michaelis–Menten constants K(m) and v(max) for the enzyme were 0.624 mM and 5.12 μmol/min/mg, respectively, using 3-cyanopyridine as the substrate. The enzyme-containing freely-suspended bacterial cells and the cells immobilized within alginate beads were evaluated for converting the various nitriles to amides. In a packed bed reactor, alginate beads (2 % alginate; 3 mm bead diameter) containing 200 mg/mL of cells, achieved a conversion of >90 % for benzonitrile and 4-cyanopyridine in 38 h (25 °C, pH 7.0) at a feed substrate concentration of 100 mM. The beads could be reused for up to six reaction cycles

FOURIER-TRANSFORM INFRARED SPECTROSCOPY STUDIES AND EVALUATION OF TOTAL PHENOLICS, FLAVONOIDS, AND ANTIOXIDANT ACTIVITY OF CLEOME GYNANDRA

Objective: The objective of this study was to evaluate the nature of chemical constituents, total phenolics, total flavonoids, and antioxidant activity of Cleome gynandra and their functional groups with the help of phytochemical, Fourier-transform infrared spectroscopy (FTIR) analysis, colorimetric assay, and 2,2-diphenyl-1-picrylhydrazyl (DPPH) free radical scavenging assay. Methods: C. gynandra of the Cleomaceae family is an annual herb. The dried leaves were powdered and extracted using Soxhlet apparatus by different solvents. Preliminary phytochemical analysis was carried out to identify the phytoconstituents present in the extract of C. gynandra, FTIR spectrum was scanned at the range of 4000-400 cm−1. The extracts were subjected to the colorimetric assay in triplicate manner to quantitative determination of total phenolic and total flavonoid content. Gallic acid and rutin used as standards to determine the total phenolic content and total flavonoid content. Antioxidant activity was evaluated using DPPH radical scavenging method. Results: Phytochemical analysis of the ethanolic extract of C. gynandra revealed the presence of alkaloids, phenolics, saponins, steroids, flavonoids, cardiac glycosides, and tannins. FTIR spectrum showed intense bands at 3679.18, 3616.63, 3317.34, 2943.67, 1634.01, 1360.20, 1036.71, and 778.04 cm−1 corresponding to N-H2, O-H stretch, aliphatic C-H stretch, C=O, C-H benzene, C-O stretch, and C-Cl. The total phenolic content was found to be 8.39 ± 0.0952 mg gallic acid equivalent/g and 66.76 ± 0.0333 mg rutin equivalent/g. The DPPH radical scavenging activity of ethanolic extract was showed more scavenging activity compared to ethyl acetate and n-hexane fractions. Conclusion: The present research work creates a platform to screen many bioactive chemical constituents present in C. gynandra to treat various diseases

Modified Z-source Integrated PV/Grid/EV DC Charger/Inverter Modeling, Design, Control, and Implementation

Sun based Energy has been the most well known wellsprings of sustainable power source for private and semi business applications. Vacillations of sunlight based vitality gathered because of climatic conditions can be moderated through vitality stockpiling frameworks. Sun oriented vitality can likewise be utilized to charge electric vehicle batteries to lessen the reliance on the network. One of the prerequisites for a converter for such applications is to have a decreased number of changes organizes and give seclusion. Z-source inverter (ZSI) topology can expel various stages and accomplish voltage lift and DC-AC power transformation in a solitary stage. The utilization of latent parts additionally exhibits a chance to coordinate vitality stockpiling frameworks (ESS) into them. This paper presents demonstrating, plan and activity of an altered Z-source inverter (MZSI) incorporated with a split essential secluded battery charger for DC charging of electric vehicles (EV) batteries. Reenactment and exploratory outcomes have been displayed for the evidence of idea of the activity of the proposed converter. Index Terms—quasi-Zsource inverter (qZSI); Z-source-inverters; Active filter; energy storage; photovoltaic (PV) power generation; singlephase systems; transportation electrification; Solar energy; distributed power generation, invert

Deep Learning Convolutional Neural Networks for Content Based Image Retrieval

Content Based Image Retrieval (CBIR) has received an excellent deal of interest within the researchcommunity. A CBIR system operates on the visible features at low-level of a user's input image that makes it troublesome for the users to devise the input and additionally doesn't offer adequate retrieval results. In CBIR system, the study of the useful representation of features and appropriate similarity metrics is extremely necessary for improving the performance of retrieval task. Semantic gap has been the main issue which occurs between image pixels at low-level and semantics at high-level interpreted by humans. Among varied methods, machine learning (ML) has been explored as a feasible way to reduce the semantic gap. Inspired by the current success of deep learning methods for computer vision applications, in this paper, we aim to confront an advance deep learning method, known as Convolutional Neural Network (CNN), for studying feature representations and similarity measures. In this paper, we explored the applications of CNNs towards solving classification andretrieval problems. For retrieval of similar images, we agreed on using transfer learning to apply the deep architecture to our problem. Extracting the last-but-one fully connected layer from the retraining of proposed CNN model served as the feature vectors for each image, computing Euclidean distances between these feature vectors and that of our query image to return the closest matches in the datase

FABRICATION OF NANO CLAY INTERCALATED POLYMERIC MICROBEADS FOR CONTROLLED RELEASE OF CURCUMIN

Objective: The objective of this study was to formulate and evaluate the Curcumin (CUR) encapsulated sodium alginate (SA)/badam gum (BG)/kaolin (KA) microbeads for controlled drug release studies. Methods: The fabricated microbeads were characterized by fourier transform infrared spectroscopy (FTIR), differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), X-ray diffraction (X-RD), and scanning electron microscopy (SEM). Dynamic swelling studies and in vitro release kinetics were performed in simulated intestinal fluid (pH 7.4) and simulated gastric fluid (pH 1.2) at 37 °C. Results: FTIR confirms the formation of microbeads. DSC studies confirm the polymorphism of CUR in drug loaded microbeads which indicate the molecular level dispersion of the drug in the microbeads. SEM studies confirmed the microbeads are spherical in shape with wrinkled and rough surfaces. XRD studies reveal the molecular dispersion of CUR and the presence of KA in the developed microbeads. In vitro release studies and swelling studies depend on the pH of test media, which might be suitable for intestinal drug delivery. The % of drug release values fit into the Korsmeyer-Peppas equation and n values are obtained in the range of 0.577-0.664, which indicates that the developed microbeads follow the non-Fickian diffusion drug release mechanism. Conclusion: The results concluded that the CUR encapsulated microbeads are potentially good carriers for controlled drug release studies

Implementation of Dynamic Virtual Cloud Architecture for Privacy Data Storage

Nowadays rapidly developing technologies, cloud computing offers versatile services. However, cloud computing presents a challenge to secure information sharing. Customers can securely share their data with others and remotely store it in the cloud using cloud storage services. In recent times, cloud storage typically represents as the primary method of external data storage. The primary challenge is safeguarding the cloud-based data against attacks. Over the information network, the growth of private or semi-private information has increased. The search techniques have not been addressed by privacy safeguards. As there is no suitable audit system, the validity of the stored data has become in question. In addition, user authentication presents additional difficulties. Hence in order to solve these issues, Design and implementation of dynamic virtual cloud architecture for privacy data storage is presented. In this approach, third-party audits are presented accompanied a new, regenerative public audit methodology. A distributed KDC (Key Distribution Center) is employed to encrypt the data. Documents can be stored on a private server in plain word form, which compromise the protection of privacy. As a result, system security can be improved to make the documents safer and more effective. The main objective of this Virtual Cloud Architecture is to achieve data confidentiality, as well as authenticity.&nbsp