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The growth of cloud in modern technology is drastic by provisioning services to various industries where data security is considered to be common issue that influences the intrusion detection system (IDS). IDS are considered as an essential factor to fulfill security requirements. Recently, there are diverse Machine Learning (ML) approaches that are used for modeling effectual IDS. Most IDS are based on ML techniques and categorized as supervised and unsupervised. However, IDS with supervised learning is based on labeled data. This is considered as a common drawback and it fails to identify the attack patterns. Similarly, unsupervised learning fails to provide satisfactory outcomes. Therefore, this work concentrates on semi-supervised learning model known as Fuzzy based semi-supervised approach through Latent Dirichlet Allocation (F-LDA) for intrusion detection in cloud system. This helps to resolve the aforementioned challenges. Initially, LDA gives better generalization ability for training the labeled data. Similarly, to handle the unlabelled data, Fuzzy model has been adopted for analyzing the dataset. Here, pre-processing has been carried out to eliminate data redundancy over network dataset. In order to validate the efficiency of F-LDA towards ID, this model is tested under NSL-KDD cup dataset is a common traffic dataset. Simulation is done in MATLAB environment and gives better accuracy while comparing with benchmark standard dataset. The proposed F-LDA gives better accuracy and promising outcomes than the prevailing approaches.

One of the main ITER objectives is to demonstrate the feasibility of the breeding blanket concepts that would lead to tritium self-sufficiency and the extraction of a high-grade heat for electricity production. India has developed the LLCB TBM to be tested in ITER for the validation of design concepts for tritium breeding blankets relevant DEMO and future power reactor. LLCB concept has the unique features of combination of both solid (lithium titanate as packed pebble bed) and liquid breeders (molten lead lithium). India specific IN-RAFMS is the structural material for TBM. The First Wall is actively cooled by high-pressure helium (He) gas [1]. It is important to validate the design of TBM to withstand various loads acting on it including accident analysis like LOCA, LOFA etc. Detailed thermal-hydraulic simulation studies including LOFA in helium and Pb-Li circuits of LLCB TBM have been performed using Finite Element using ANSYS. These analyses will provide important information about the temperature distribution in different materials used in TBM during steady state and transient condition. Thermal-hydraulic safety requirement has also been envisaged for the initiation the FPPS (Fusion Power Shutdown System) during LOFA. All these analysis will be presented in detail in this paper.

The term profitability represents to the ability of an organization to obtain sufficient profit. Profitability is connected to the efficiency of an organization to maximize the profit and wealth at reasonable rate. It is relative measure of the success of the organization in terms of the effective utilization of resources. Scientific study of current trade provides a platform to forecast the possible future trends of the profitability strategic managerial decisions like expansion of the business, rising of additional finance, issue related to bonus and dividend directly connected with profit. To analyze the profitability, the researcher used profitability ratios to determine the earning by considering the variables like EBIT, Gross contribution, Net sales, operating cash flow, ROA, Capital employed, Shareholders equity are considered in the study. An appropriate statistical tools like regression analysis has been employed to measure the relationship between profitability and productivity, which predict the growth of an organization in monetary value during the study period. The researcher made an attempt to measure the profitability of L&T a leading private infrastructure company in India. The researcher made an attempt to measure the profitability of L&T a leading private infrastructure company in India. The study has analyzed the profitability of L&T. Profit being a crucial measure to determine the performance in profitability, internal determinants of the firms, earning power has been ascertained in the study by applying a multiple regression model with EBIT as dependent variable and internal data inputs has independent variable s namely operating profit margin ratio, net profit margin ratio, return on capital employed, return on net worth ratio, return on total assets, operating cash flow to total asset, EBIT to total tangible asset, profit after tax to total tangible assets, EBIT to total assets, retained cash flow to capital employed, EBIT to capital employed, PAT to tangible portion of shareholders equity, interest coverage ratio.

Recent economic changes facilitated the Steel sector to ignore the Reserve quotation for PSU to get a wave from mandatory. The six major role players in Indian steel sector equally qualified to world class iron makers out of 36 in the world. In 2018, steel utility was about to grow at the rate of 5.7% year-on-year 9.2% Metric Tons. Our country anticipated to beat Japan to predominant in iron production at the earliest. But, few iron PSUs in India still struggle to sustain with Industry growth. With this aim, the financial performances of seven selected PSU companies are predicted through Altman’s Z- score.

Aim : The purpose of the study is to compare the regional micro-push-out bond strength of custom-made resin post and a prefabricated resin post luted using self-etch adhesive and/or etch and rinse adhesive system at various regions. Materials and Methods : Forty freshly extracted human maxillary central incisors were selected for this study; 1.5-2-mm coronal to the cemento-enamel junction was removed with a diamond disk using a slow speed handpiece under cooling water. Working lengths were established, root canals were sequentially enlarged upto the apex until ISO size 50-K-file and obturated using gutta-percha and AH plus sealer by cold lateral compaction. Post spaces were prepared to a depth of 10 mm using paeso-reamer upto size #3. After preparation, each specimen was embedded in chemically cured acrylic resin. The roots were randomly assigned to four groups: Group I: Custom-made resin post+Self-etch adhesive, Group II: Glass FRC post+Self-etch adhesive, Group III: Custom-made resin post+Etch and Rinse adhesive, Group IV: Glass FRC post+Etch and Rinse adhesive. Fabrication of custom-made resin post was done. All the posts were cemented using a dual cure resin luting cement. Each root was sectioned perpendicular to the long axis using a microtome and subjected to micro-push-out bond strength. Results: The micro-push-out bond strength in the coronal region, in Group I 13.5+-1.66 MPa, Group II 12.08+-0.8 MPa, Group III 11.15+-1.06 MPa, Group IV 11.81+-1.11 MPa. In the middle third region: Group I 11.43+-0.740 MPa, Group II 10.584+-0.504 MPa, Group III 10.0582+-0.830 MPa, Group IV 10.35+-0772 MPa. In the apical third: Group I 10.38+-0.878 MPa, Group II 9.59+-1.06 MPa, Group III 9.34+-0.73o MPa, Group IV 8.77+-1.02 MPa. Conclusion : Within the limitations of the study, amongst all the four groups tested, custom-made resin post luted with self-etch system (CMPR-SE) showed higher micro-push-out bond strength values in all regions when compared to the other groups

Monomer of 7-methacryloyloxy-4-methylcoumarin (MAOMC) was synthesized and characterized by FTIR, 1H-NMR and 13C-NMR spectroscopy. Copolymers of MAOMC with butoxyethylmethacrylate (BOEMA) at different feed compositions were prepared by free radical solution polymerization at (70 ± 1) °C in ethylmethylketone (EMK) using benzyl peroxide (BPO) as an initiator. The copolymers were characterized by FTIR and 1H-NMR spectroscopy. Thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC) of the copolymers showed moderate thermal stability and higher Tg values. Gel permeation chromatography (GPC) was used to find out the molecular weights of the different copolymers. Antibacterial activities of the copolymers were also investigated against the selected pathogenic bacteria’s. The antibacterial activity of the copolymer increases as the MAOMC content increases in the copolymer. This shows that coumarin moiety plays a very important role in the antibacterial activity.

In future, the smart grid power transmission could be the most usable system for power transmission, however it also introduces many security problems. To overcome the security problem, the authors have used an encryption scheme which is introduced by an information network in the communication medium. In this paper, the information network can be integrated into the smart grid power transmission. In between the two systems of communication, the previous packets can be taken as re-transmission sequences. Here the re-transmitted packet is marked as \"1\" and the non retransmitted packet can be marked as \"0\". At the time of communication, the re-transmission sequences can be generated at both sides to update the encryption key. In this paper, the smart grid is built by using ZigBee protocol for wireless communication of the information network. The encryption system is designed based on this platform. The result shows that the re-transmission and packet loss can be very low and it is impossible for the attacker to track the updation of the encryption key.

Automatic License Plate Recognition (ALPR) systems are important in Intelligent Transportation Services (ITS) as they help ensure effective law enforcement and security. These systems play a significant role in border surveillance, ensuring safeguards, and handling vehicle-related crime. The most effective approach for implementing ALPR systems utilizes deep learning via a convolutional neural network (CNN). A CNN works on an input image by assigning significance to various features of the image and differentiating them from each other. CNNs are popular for license plate character recognition. However, little has been reported on the results of these systems with regard to unusual varieties of license plates or their success at night. We present an efficient ALPR system that uses a CNN for character recognition. A combination of pre-processing and morphological operations was applied to enhance input image quality, which aids system efficiency. The system has various features, such as the ability to recognize multi-line, skewed, and multi-font license plates. It also works efficiently in night mode and can be used for different vehicle types. An overall accuracy of 98.13% was achieved using the proposed CNN technique.

LITERATURE REVIEW Yang Jiao [1] proposed the planning and implementation of Distributed system-based webserver which aimed to extend the performance of the server. [...]as against the previous works, the scheme can further improve the security and prediction models. [...]the tasks are classified into heavy, medium, or light tasks. [...]the mapping of tasks to the convenient virtual machine group is done. The objective is to establish a dynamic load balancing algorithm and study response time, performance time, waiting time, scalability, power consumption, speed of virtual machines.