Improved Feature Selection Algorithm for Intrusion Detection Using Data Mining Approach

With the rapid growth of Internet applications, there are more and more intrusions into network systems. In this case, it is necessary to provide security for the network through effective intrusion detection and prevention methods. This can mainly be achieved by creating effective interruption detection systems using efficient algorithms that can identify abnormal activities in network traffic and safeguard network resources from unlawful attack by interlopers. Although many interruption recognition frameworks have been proposed before, existing network intrusion detection has limitations in terms of accuracy and detection time. To overcome these shortcomings, In this paper, we propose a new intrusion detection system by developing a new intelligent feature selection algorithm based on conditional random fields (CRF) to optimize the number of features. Furthermore, algorithms based on existing hierarchical methods (LA) In this paper, we propose another interrupt recognition framework, fostering a book. Compared with the existing methods, the interruption identification framework provides high precision and achieves the efficiency of attack detection. The main advantages of this system are reduced detection time, improved classification accuracy and lower false positive rate

A study on malassezia micro flora in the skin of healthy individuals in North Kerala, India

Background: Malassezia spp are accounted for approximately 60-90% of the total cutaneous fungal micro biota. An enhanced understanding of the distribution of Malassezia spp in healthy individuals is necessary to gain insight to involvement of these species in human skin disorders particularly in pityriasis versicolor. The aim of this study was to assess the Malassezia micro flora of healthy individuals and to identify species variation with different body sites, gender and age groups.Methods: A total of 120 apparently healthy men and 120 women without any skin diseases or who were not treated for Malassezia associated skin diseases were selected for the study. The specimens consisted of scrapings collected from chest, back and neck from each control subject totaling 720 sites.Results: The recovery rate of Malassezia was positive in case of 452 (62.78%) of 720 sites sampled, while the remaining 268 (37.22%) were found to be negative. Recovery rate of Malassezia was highest in chest with 83.33% positive cases, followed by the back with 73.33% and the neck 31.67%. M. globosa was identified as the common species (46.46%) followed by M. furfur (25%) and M. restricta (22.56%). No significant difference was present (P > 0.05) in distribution of species with different body sites, gender and age groups.Conclusions: The overall colonization rate of Malassezia spp in normal healthy individuals found in this study was 62.78%. M. globosa was identified as the common species (46.46%)

Neutrosophic Vague Binary G-subalgebra of G-algebra

Nowadays, human society is using artificial intelligence in a large manner so as to upgrade the present existing applicational criteria’s and tools. Logic is the underlying principle to these works. Algebra is inevitably inter-connected with logic. Hence its achievements to the scientific research outputs have to be addressed. For these reasons, nowadays, research on various algebraic structures are going on wide. Crisp set has also got developed in a parallel way in the forms as fuzzy, intuitionistic fuzzy, rough, vague, neutrosophic, plithogenic etc. Sets with one or more algebraic operations will form different new algebraic structures for giving assistance to these logics, which in turn acts to as, a support to artificial intelligence. BCH/BCI/BCK- are some algebras developed in the first phase of algebraic development output. After that, so many outputs got flashed out, individually and in combinations in no time. Q- algebra and QS –algebra are some of these and could be showed as such kind of productions. G- algebra is considered as an extension to QS – algebra. In this paper neutrosophic vague binary G – subalgebra of G – algebra is generated with example. Notions like, 0 – commutative G - subalgebra, minimal element, normal subset etc. are investigated. Conditions to define derivation and regular derivation for this novel concept are clearly presented with example. Constant of G – algebra can’t be treated as the identity element, generally. In this paper, it is well explained with example. Cosets for neutrosophic vague binary G – subalgebra of G - algebra is developed with proper explanation. Homomorphism for this new concept has been also got commented. Its kernel, monomorphism and isomorphism are also have discussed with proper attention

The incidence and risk factors for development of lower limb lymphedema after treatment for gynaecological cancers

Background: The development of postoperative lower limb lymphedema (LLL) is a disabling, yet usually overlooked sequele of most gynecological cancer treatment. It can lead to significant functional problems that negatively affect gynecological cancer survivors’ daily living, work, emotional state, and overall quality of life. The objective of this study is to calculate the incidence of lower limb lymphedema in patients undergoing surgery for gynecological cancer and to evaluate the risk factors for its development.Methods: Women with newly diagnosed carcinoma ovary, carcinoma endometrium and carcinoma cervix, who underwent surgery at a tertiary cancer centre from September 2016 were included in the study. The circumference of both lower limbs was measured at prefixed sites. The limb volume was calculated using the formula C2/pi. A baseline value was taken prior to surgery. The patients were followed up every 3 months and the limb volume were calculated at each visit. An increase in limb volume by >10% was defined as lymphedema.Results: The incidence of lymphedema after 1 year follow up was 43.5%. There was no significant association between known risk factors such as extent of lymphadenectomy (p value 0.633) number of pelvic or para aortic lymph nodes removed (p value 0.69 and 0.44 respectively) and type of adjuvant therapy (p value 0.455).Conclusions: The incidence of LLL according to the present study was 43.5%. There was no statistically significant association between development of LLL and risk factors like site and number of lymph nodes removed and type of adjuvant therapy

Key distinguishing characters (KDCs) of official (Boerhaavia diffusa L.) and commonly mistaken (Trianthema portulacastrum L.) sources of Mukkirattai of Siddha

Boerhaavia diffusa L. has been used extensively in Siddha system of medicine and is often confused with Trianthema portulacastrum L. due to morphological similarities. This particular study compares, analyses and identifies the key distinguishing features of the two whole plant drugs based on pharmacognostical and phytochemical aspects. The samples were studied for macroscopy, microscopy, physicochemical analysis, preliminary phytochemical analysis and HPTLC following standard procedures. Macroscopic studies showed few notable differences in macro-microscopy of root, stem, leaves and flowers of both the plants. Microscopically root, stem, leaf and petiole of both the plants showed differences in layers of cork, presence of crystals and medullary rays (in root), the thickness of cuticle, cortex and arrangement of vascular bundles (stem), presence of characteristic type of trichomes (leaf) and shape of the petiole. Powder microscopy showed differences in epidermis, crystal types and shape of pollen. Preliminary phytochemical analysis showed the presence of phenol, saponins and coumarins in B. diffusa and was not detected in T. portulacastrum. There were significant differences in the values of quantitative microscopy, physicochemical parameters and HPTLC of both the whole plant samples. The finding of this study will be helpful for the correct identification of the plant

Intrinsic Functional Connectivity of the Brain in Adults with a Single Cerebral Hemisphere

A reliable set of functional brain networks is found in healthy people and thought to underlie our cognition, emotion, and behavior. Here, we investigated these networks by quantifying intrinsic functional connectivity in six individuals who had undergone surgical removal of one hemisphere. Hemispherectomy subjects and healthy controls were scanned with identical parameters on the same scanner and compared to a large normative sample (n = 1,482). Surprisingly, hemispherectomy subjects and controls all showed strong and equivalent intrahemispheric connectivity between brain regions typically assigned to the same functional network. Connectivity between parts of different networks, however, was markedly increased for almost all hemispherectomy participants and across all networks. These results support the hypothesis of a shared set of functional networks that underlie cognition and suggest that between-network interactions may characterize functional reorganization in hemispherectomy

Evaluation of the impact of high-resolution winds on the coastal waves

This study discusses the impact of high-resolution winds on the coastal waves and analyses the effectiveness of the high-resolution winds in recreating the fine-scale features along the coastal regions during the pre-monsoon season (March–May). The influence of the diurnal variation of winds on waves is studied for the Tamil Nadu coastal region using wind fields from weather research and forecast (WRF) (3 km) and European Centre for Medium-Range Weather Forecasts (ECMWF) (27.5 km). The improvement in the coastal forecast is then quantified with wave rider buoy observations. The high-resolution wind fields simulated fine-scale features like land–sea breeze events and showed good agreement with observation results. The error in the wave height and period is reduced by 8% and 46%, respectively, with the use of high-resolution forcing winds WRF over ECMWF, although the overestimation of wave energy on high frequencies due to overestimated WRF winds remains as a challenge in forecasting. The analysis also shows the importance of accurate wave forecast during a short-duration sudden wind (~12 m/s) occurrence in southern Tamil Nadu near Rameswaram during the pre-monsoon period. Low pressure forms over Tamil Nadu due to the land surface heating, resulting in a sudden increase of winds. High winds and steep waves which cause damage to the property of the coastal community near Rameswaram also were well simulated in the high-resolution forecast system with WRF winds

CMFRI Marine Fisheries Policy Series No-6; Non-Detriment Findings (NDF) for the export of Shark and Ray species listed in Appendix II of the CITES and harvested from Indian waters

This document entitled “Guidance on National Plan of Action for Sharks in India” is intended as a guidance to the NPOA-Sharks, and seeks to (1) present an overview of the current status of India’s shark fishery, (2) assess the current management measures and their effectiveness, (3) identify the knowledge gaps that need to be addressed in NPOA-Sharks and (4) suggest a theme-based action plan for NPOA-Sharks

Course Manual on Marine Fisheries & Mariculture Prepared for the Training programme for B.F.Sc students of Central Agricultural University (CAU), Tripura

The undergraduate Fisheries Science students are required to know about the inland and marine fisheries. The students from landlocked area are getting rare opportunity to understand the marine fisheries and mariculture activities. Hence, based on the request of the Central Agricultural University (CAU), Tripura as a part of their academic activities, the Director, ICAR-CMFRI, has kindly approved a 10 days in-plant training for B.F.Sc. final year students at the ICAR-Central Marine Fisheries Research Institute (CMFRI), Mandapam Regional Centre. The training was organized in collaboration with Agricultural Technology Information Centre (ATIC), ICAR-CMFRI, Kochi. A total of 27 B.F.Sc students and a faculty of Central Agricultural University (CAU), Tripura participated in the training programme during 17th to 26th January, 2020. The training emphasized on the skill development of students through hands on training on mariculture activities and field visits to fish landing centres. A course manual was prepared covering the major topics on marine capture fisheries and mariculture. I congratulate all those who have put in their sincere efforts to bring out this manual

Stem cell therapy in animal models of central nervous system (CNS) diseases: therapeutic role, challenges and perspectives

ABSTRACT Many human diseases relating to central nervous system (CNS) are mimicked in animal models to evaluate the efficacy of stem cell therapy. The therapeutic role of stem cells in animal models of CNS diseases include replacement of diseased or degenerated neuron, oligodendrocytes or astrocytes with healthy ones, secretion of neurotrophic factors and delivery of therapeutics/genes. Scaffolds can be utilized for delivering stem cells in brain. Sustained delivery of stem cells, lineage specific differentiation, and enhanced neuronal network integration are the hallmarks of scaffold mediated stem cell delivery in CNS diseases. This review discusses the therapeutic role, challenges and future perspectives of stem cell therapy in animal models of CNS diseases