Feature Selection for Detecting ICMPv6-Based DDoS Attacks Using Binary Flower Pollination Algorithm

Internet Protocol version 6 (IPv6) is the latest version of IP that goal to host 3.4 × 10³⁸ unique IP addresses of devices in the network. IPv6 has introduced new features like Neighbour Discovery Protocol (NDP) and Address Auto-configuration Scheme. IPv6 needed several protocols like the Address Auto-configuration Scheme and Internet Control Message Protocol (ICMPv6). IPv6 is vulnerable to numerous attacks like Denial of Service (DoS) and Distributed Denial of Service (DDoS) which is one of the most dangerous attacks executed through ICMPv6 messages that impose security and financial implications. Therefore, an Intrusion Detection System (IDS) is a monitoring system of the security of a network that detects suspicious activities and deals with a massive amount of data comprised of repetitive and inappropriate features which affect the detection rate. A feature selection (FS) technique helps to reduce the computation time and complexity by selecting the optimum subset of features. This paper proposes a method for detecting DDoS flooding attacks (FA) based on ICMPv6 messages using a Binary Flower Pollination Algorithm (BFPA-FA). The proposed method (BFPA-FA) employs FS technology with a support vector machine (SVM) to identify the most relevant, influential features. Moreover, The ICMPv6-DDoS dataset was used to demonstrate the effectiveness of the proposed method through different attack scenarios. The results show that the proposed method BFPA-FA achieved the best accuracy rate (97.96%) for the ICMPv6 DDoS detection with a reduced number of features (9) to half the total (19) features. The proven proposed method BFPA-FA is effective in the ICMPv6 DDoS attacks via IDS.     

Novel method to transform ZnO nanorods into interlaced tattered nanosheets by changing the target inclination angle

ZnO nanoparticles were synthesized by liquid-phase pulse laser ablation of a Zn foil target immersed in deionized water. Nanosecond Q-switched Nd:YAG laser pulses of 532 nm were applied to the Zn foil target at a perpendicular and inclined (θ = 45°) angles. X-ray diffraction analysis revealed that both cases feature a ZnO nanostructure with a hexagonal wurtzite structure and that the particle size increases with the inclined target angle. Field emission scanning electron microscopy results of a colloidal drop cast on a glass substrate showed the ZnO has a nanorod structure in the case of a perpendicular target angle and an interlaced tattered nanosheet structure in the case of an inclined target angle. Photoluminescence spectra showed emission peaks in the UV, violet, blue, and green spectral regions, which correspond to excitonic and various defects resulting in an enhancement of emissions at inclined target angle.     

New design of CHP for hypermarket of higher energy efficiency,less-fugitive refrigerant emissions and a remarkable reduction in initial and operating cost

High initial cost of power plant, limited power capacity of the existing plant and the frequent black out of many districts due to the continuous increase in electrical demands, in addition to the adverse effect of the blackout on hypermarkets, especially on foodstuff such as meat, chicken, etc. strongly encourage the adoption of a regenerating process and the principle of combined heat and power. This work investigates the upgrading of the combined cooling heat and power system and improving the regenerating process adopted in the first design of an existing project. Linking between refrigeration and air-conditioning systems is proposed in scheme-II. A single-effect absorption chiller operating in the range of refrigeration scale (i.e. aqueous-ammonia refrigeration, not air-conditioning scale, LiBr–H₂O employed in scheme-I) will be adopted using pressurised hot water recovered from the generators. The chilled water system will be serving three categories in the following order, namely, refrigeration stores, cold stores and air-conditioning units, respectively. The chilled water output of the first category will be the input of the second one. This will enhance the overall system efficiency, reduce the generator load and lessen the fugitive refrigerant emissions, which mainly participate in ozone-depleting potential and global-warming potential. This is in addition to the dramatic reduction in initial and operating cost, which can be estimated to be 50% and 79.6%, respectively.     

Permeability prediction and construction of 3D geological model: application of neural networks and stochastic approaches in an Iranian gas reservoir

Determination of petrophysical parameters by using available data has a specific importance in exploration and production studies for oil and gas industries. Modeling of corrected permeability as a petrophysical parameter can help in decision making processes. The objective of this study is to construct a comprehensive and quantitative characterization of a carbonate gas reservoir in marine gas field. Artificial neural network is applied for prediction of permeability in accordance with other petrophysical parameters at well location. Correlation coefficient for this method is 84 %. In the study, the geological reservoir model is developed in two steps: First, the structure skeleton of the field is constructed, and then, reservoir property is distributed within it by applying new stochastic methods. Permeability is modeled by three techniques: kriging, sequential Gaussian simulation (SGS) and collocated co-simulation using modeled effective porosity as 3D secondary variable. This paper enhances the characterization of the reservoir by improving the modeling of permeability through a new algorithm called collocated co-simulation. Kriging is very simple in modeling the reservoir permeability, and also, original distribution of the data changes considerably in this model. In addition, the SGS model is noisy and heterogeneous, but it retains the original distribution of the data. However, the addition of a 3D secondary variable in third method resulted in a much more reliable model of permeability.     

Vasopeptidase inhibitors: incorporation of geminal and spirocyclic substituted azepinones in mercaptoacyl dipeptides

A series of 7-(di)alkyl and spirocyclic substituted azepinones were generated and incorporated as conformationally restricted dipeptide surrogates in mercaptoacyl dipeptides. Clear structure-activity relationships with respect to both angiotensin-converting enzyme (ACE) and neutral endopeptidase (NEP) activity in vitro were observed. The best in this series, compound 1g, a geminally dimethylated C-7-substituted azepinone, demonstrated excellent blood pressure lowering in animal models. Compound 1g (BMS-189921) is characterized by a good duration of activity and excellent oral efficacy in models relevant to ACE or NEP inhibition, and its activity is comparable to that of the clinically efficacious agent omapatrilat. Consequently this inhibitor has been advanced clinically for the treatment of hypertension and congestive heart failure.     

Input Selection of Wavelet-Coupled Neural Network Models for Rainfall-Runoff Modelling

Water Resources Management - The use of wavelet-coupled data-driven models is increasing in the field of hydrological modelling. However, wavelet-coupled artificial neural network (ANN) models...     

Improving the Summer Power Generation of a Hydropower Reservoir Using the Modified Multi-Step Ahead Time-Varying Hedging Rule

This paper aims to improve summer power generation of the Yeywa Hydropower Reservoir in Myanmar using the modified multi-step ahead time-varying hedging (TVH) rule as a case study. The results of the TVH rules were compared with the standard operation policy (SOP) rule, the binary standard operation policy (BSOP) rule, the discrete hedging (DH) rule, the standard hedging (SH) rule, the one-point hedging (OPH) rule, and the two-point hedging (TPH) rule. The Multi-Objective Genetic Algorithm (MOGA) was utilized to drive the optimal Pareto fronts for the hedging rules. The results demonstrated that the TVH rules had higher performance than the other rules and showed improvements in power generation not only during the summer period but also over the entire period.

     

Effect of Fe2+ and Fe0 Applied Photo‐Fenton Processes on Sludge Disintegration

The disintegration of waste active sludge was investigated by photo‐Fenton processes. A batch study was conducted to evaluate parameters, such as Fe²⁺ and Fe⁰ ions and H₂O₂, governing the activated sludge integration by the photo‐Fenton process. Under optimum conditions, the concentration of soluble chemical oxygen demand (SCOD) with the classical Fenton process (CFP) increased very rapidly in the first five minutes due to the sufficient presence of reaction components in the medium, and then the rate of increase declined. In the modified Fenton process (FTP), the SCOD concentration increased more slowly as metallic iron powder must first be dissolved. The photo‐Fenton process proved to be a feasible and efficient process for the disintegration of waste sludge.