Association Rule Mining Frequent-Pattern-Based Intrusion Detection in Network

In the network security system, intrusion detection plays a significant role. The network security system detects the malicious actions in the network and also conforms the availability, integrity and confidentiality of data information resources. Intrusion identification system can easily detect the false positive alerts. If large number of false positive alerts are created then it makes intrusion detection system as difficult to differentiate the false positive alerts from genuine attacks. Many research works have been done. The issues in the existing algorithms are more memory space and need more time to execute the transactions of records. This paper proposes a novel framework of network security Intrusion Detection System (IDS) using Modified Frequent Pattern (MFP-Tree) via K-means algorithm. The accuracy rate of Modified Frequent Pattern Tree (MFPT)-K means method in finding the various attacks are Normal 94.89%, for DoS based attack 98.34%, for User to Root (U2R) attacks got 96.73%, Remote to Local (R2L) got 95.89% and Probe attack got 92.67% and is optimal when it is compared with other existing algorithms of K-Means and APRIORI.     

Hybrid Recommender System Using Systolic Tree for Pattern Mining

A recommender system is an approach performed by e-commerce for increasing smooth users’ experience. Sequential pattern mining is a technique of data mining used to identify the co-occurrence relationships by taking into account the order of transactions. This work will present the implementation of sequence pattern mining for recommender systems within the domain of e-commerce. This work will execute the Systolic tree algorithm for mining the frequent patterns to yield feasible rules for the recommender system. The feature selection's objective is to pick a feature subset having the least feature similarity as well as highest relevancy with the target class. This will mitigate the feature vector's dimensionality by eliminating redundant, irrelevant, or noisy data. This work presents a new hybrid recommender system based on optimized feature selection and systolic tree. The features were extracted using Term Frequency-Inverse Document Frequency (TF-IDF), feature selection with the utilization of River Formation Dynamics (RFD), and the Particle Swarm Optimization (PSO) algorithm. The systolic tree is used for pattern mining, and based on this, the recommendations are given. The proposed methods were evaluated using the MovieLens dataset, and the experimental outcomes confirmed the efficiency of the techniques. It was observed that the RFD feature selection with systolic tree frequent pattern mining with collaborative filtering, the precision of 0.89 was achieved.     

Biosynthesised silver and copper nanoformulation as foliar spray to control bird's eye spot disease in tea plantations

Tea leaves have economic importance in preparation of the popular beverage of the world “tea”. Bird’s eye spot disease of tea leaves creates significant revenue loss in tea trade of many tea plant cultivating countries. Management of this disease by silver (AgNps) and copper (CuNps) nanoparticles that are biosynthesised by efficient antagonists was studied. The biocontrol agents like Pseudomonas fluorescens, Trichoderma atroviride and Streptomyces sannanensis were evaluated for nanoparticle synthesis against Cercospora theae isolates namely KC10, MC24 and VC38. Initially, the freshly prepared extracellular AgNps showed high disease control (59.42 – 79.76%), but the stability of antagonistic property in stored nanoparticles were significantly high in CuNps (58.71 – 73.81%). Greenhouse studies on various treatments imposed also showed reduced disease incidence percentage of 13.4, 7.57 and 10.11% when treated with CuNps synthesized by P. fluorescens, T. atroviride and S. sannanensis respectively. Various treatment schedule in fields suggested the use of Bionanocopper@1.5 ppm for highest yield (3743 kg/ha) with 66.1% disease prevention. The results suggest the use of biosynthesised CuNps using Streptomyces sannanensis for controlling the tea plant pathogens causing foliar disease with higher stability in releasing the antagonistic activity during sporadic disease incidence of bird’s eye spot disease in tea plants.Inspec keywords: silver, copper, crops, plant diseases, nanoparticles, air pollution, agrochemicals, nanobiotechnologyOther keywords: biosynthesised silver, biosynthesised copper, nanoformulation, foliar spray, bird eye spot disease control, tea plantations, tea leaves, economic importance, revenue loss, tea trade, tea plant cultivating countries, silver nanoparticles, AgNps, copper nanoparticles, CuNps, biocontrol agents, nanoparticle synthesis, Cercospora theae isolates, KC10, MC24, VC38, greenhouse studies, antagonistic property, P. fluorescens, T. atroviride, S. sannanensis, fungicides, synthetic nanomaterials, bionanomaterials, disease prevention, green leaf yield, BionanoCu, tea plant pathogens, foliar disease     

Robust Estimation of GARMA Model Parameters with an Application to Cointegration among Interest Rates of Industrialized Countries

We review the literature on long memory ARFIMA and GARMA models andintroduce a new efficient estimator for GARMA models, which we show to berobust. Next we conduct a Monte Carlo study to demonstate the power of theDickie–Fuller test when the data are generated from a stationary GARMAprocess. We conclude with a brief discussion of cointegration in the contextof GARMA models with an application to international interest rates.     

Effect of Carbon Dioxide and Ammonia on Polymer Electrolyte Membrane Fuel Cell Stack Performance

Proton exchange membrane fuel cell (PEMFC) performance degrades when impurities are present in the anode fuel gas, referred to as catalyst poisoning. This paper investigates the effect of carbon dioxide and ammonia as impurities in the anode gas of the PEMFC, and found that the presence of CO₂ decreases the performance of the fuel cell by up to 10%. The performance loss depends on the CO₂ concentration and the exposure time. The voltage loss is recoverable on passing pure hydrogen gas, indicating that a permanent poisoning of the catalyst layer has not taken place. Exposure of the fuel cell to ammonia beyond 20 ppm, even for a short duration, causes permanent PEMFC failure, probably due to the deterioration of the membrane.     

Evidence for the improvement of thermostability of the maltogenic α‐amylase of Aspergillus niger by negative pressure

Thermostability of the enzymes is influenced by the different parameters and pressure also influences the biological activity of the enzymes. Recently reported maltogenic α‐amylase from Aspergillus niger acts optimally on starch at 40°C and it was unstable above 40°C at atmospheric pressure. Calcium could stabilize the maltogenic α‐amylase activity up to 50°C at atmospheric pressure. But, at negative pressure (−200 mbar) enzyme was stable at temperatures higher than 50°C either in the presence or absence of the substrate, starch making it adoptable for starch processing. Enzyme showed higher affinity to the starch at negative pressure compared to the atmospheric pressure and change in the surface roughness of the enzyme is almost similar to the native state at 70°C and negative pressure. These results suggest that thermolabile enzymes can be used at negative pressures for industrial applications.     

Biocomposite based electrode for effective removal of Cr (VI) heavy metal via capacitive deionization

Abstract

This study focuses on the fabrication of biocomposite electrode and removal of Cr (VI) ions from wastewater using a capacitive deionization (CDI) method. The activated carbon (AC) was synthesized from Bael fruit shell (BS). The synthesized AC surface has a macroporous and mesoporous structure with the large specific surface area (617.72?m² g^?1) and high adsorption capacity. The cyclic voltammetry and CDI were performed for the detection and for the removal of chromium (VI) ions, respectively. The lower level of detection of Cr (VI) by a modified electrode was found to be 10 ppt. SEM, BET, and FTIR analyses were performed to explore the surface properties of electrode materials. The removal efficiency was achieved 100% by using biocomposite electrode with an applied potential of 15?V. The highest percent removal mechanism consists of electrosorption and electroreduction due to the affinity between polyvinyl alcohol modified electrode and Cr (VI) ions, under electrochemically faradic process.     

Preparation and characterization of camptothecin-loaded alginate/poly[N-(2-hydroxypropyl) methacrylamide] hydrogel beads for anticancer treatment

Encapsulation of poor water-soluble drugs into a biocompatible polymeric matrix is a good strategy for in vitro drug delivery. Present study deals with the preparation and optimization of alginate/poly[N-(2-hydroxypropyl) methacrylamide] beads (SA/pHPMA) for the delivery of an anticancer drug such as camptothecin (CPT). Beads were prepared by ionotropic gelation technique using calcium chloride and optimized concentrations of 10?w/v% of sodium alginate beads and 10:10?w/v% of poly[N-(2-hydroxypropyl) methacrylamide]:sodium alginate (SA/pHPMA) beads were prepared. Twenty ppm of CPT was incorporated into the beads by the imbibition method. XRD, thermogravimetric analysis, and differential scanning calorimetry studies of the beads showed no free pHPMA and CPT indicating their uniform dispersion into the matrix. FTIR analysis showed weak interaction between CPT and polymers. In vitro release of CPT from SA/pHPMA beads showed slow and sustained release of 80% while SA beads showed 62% retaining the shape of the beads in phosphate-buffered saline at pH 7.4. The presence of CPT inside the prepared beads has the potential to be used as soft bandages for treatment of cancer.     

Impact of conditioning regimens and time on adhesion of a fiber post to root dentin using two resin cements

The aim of this study was to evaluate the influence of irrigation protocols on the bond strength of a glass fiber post bonded to dentin using two resin cements. In 200 root-filled teeth, post space was prepared and divided into five groups (n?=?40) based on the irrigation protocol: group 1 (3% sodium hypochlorite), group 2 (3% sodium hypochlorite – 17% Ethylene diamine tetraacetic acid), group 3 (a mixture of sodium hypochlorite and etidronic acid), group 4 (sodium hypochlorite – QMix), and group 5 (distilled water). Samples were subdivided into two subgroups (n?= 10) and fiber posts were cemented using subgroup A (Self-adhesive dual-cure resin cement; SEA) or B (dual-cure resin cement following an etch-and-rinse protocol, ER). Push-out bond strength was performed after 24 h and four months (n?= 10) and failure modes were categorized. Statistical analysis of data was carried out by appropriate analyses (p < 0.05). The irrigation protocol and the resin cement had a significant impact on push-out bond strength. Subgroup A group showed lower bond strength than B at both time periods when 3% NaOCl–17% EDTA and 1:1 mixture of 6% NaOCl + 18%EA protocols were used. Three percent NaOCl used in combination with 17% EDTA or QMix significantly decreased the push-out bond strength of ER at the end of four months (p < 0.05). In conclusion, dual-cure resin cements bonded with etch-and-rinse protocol showed highest bond strength when a mixture of NaOCl and etidronic acid was used as root canal irrigant. These values were differentially influenced by time.