Intrusion Detection System in Wireless Sensor Network Using Conditional Generative Adversarial Network

Wireless communication networks have much data to sense, process, and transmit. It tends to develop a security mechanism to care for these needs for such modern-day systems. An intrusion detection system (IDS) is a solution that has recently gained the researcher’s attention with the application of deep learning techniques in IDS. In this paper, we propose an IDS model that uses a deep learning algorithm, conditional generative adversarial network (CGAN), enabling unsupervised learning in the model and adding an eXtreme gradient boosting (XGBoost) classifier for faster comparison and visualization of results. The proposed method can reduce the need to deploy extra sensors to generate fake data to fool the intruder 1.2–2.6%, as the proposed system generates this fake data. The parameters were selected to give optimal results to our model without significant alterations and complications. The model learns from its dataset samples with the multiple-layer network for a refined training process. We aimed that the proposed model could improve the accuracy and thus, decrease the false detection rate and obtain good precision in the cases of both the datasets, NSL-KDD and the CICIDS2017, which can be used as a detector for cyber intrusions. The false alarm rate of the proposed model decreases by about 1.827%.

     

Performance Analysis of Machine Learning Algorithms for Classifying Hand Motion-Based EEG Brain Signals

Brain-computer interfaces (BCIs) records brain activity using electroencephalogram (EEG) headsets in the form of EEG signals; these signals can be recorded, processed and classified into different hand movements, which can be used to control other IoT devices. Classification of hand movements will be one step closer to applying these algorithms in real-life situations using EEG headsets. This paper uses different feature extraction techniques and sophisticated machine learning algorithms to classify hand movements from EEG brain signals to control prosthetic hands for amputated persons. To achieve good classification accuracy, denoising and feature extraction of EEG signals is a significant step. We saw a considerable increase in all the machine learning models when the moving average filter was applied to the raw EEG data. Feature extraction techniques like a fast fourier transform (FFT) and continuous wave transform (CWT) were used in this study; three types of features were extracted, i.e., FFT Features, CWT Coefficients and CWT scalogram images. We trained and compared different machine learning (ML) models like logistic regression, random forest, k-nearest neighbors (KNN), light gradient boosting machine (GBM) and XG boost on FFT and CWT features and deep learning (DL) models like VGG-16, DenseNet201 and ResNet50 trained on CWT scalogram images. XG Boost with FFT features gave the maximum accuracy of 88%.     

Investigation of machining characteristics in rotary ultrasonic machining of alumina ceramic

Alumina ceramic is well documented as a much-demanded advanced ceramic in the present competitive structure of manufacturing and industrial applications owing to its excellent and superior properties. The current article aimed to experimentally investigate the influence of several process variables, namely: spindle speed, feed rate, coolant pressure, and ultrasonic power, on considered machining characteristics of interest, i.e., chipping size and material removal rate in the rotary ultrasonic machining of alumina ceramic. Response surface methodology has been employed in the form of a central composite rotatable design to design the experiments. Variance analysis testing has also been performed with a view to observing the consequence of the considered parameters. The microstructure of machined rod samples was evaluated and analyzed using a scanning electron microscope. This analysis has revealed and confirmed the presence of plastic deformation that caused removal of material along with brittle fractures in rotary ultrasonic machining of alumina ceramic. The validity and competence of the developed mathematical model have been verified with test results. The multi-response optimization of machining responses (material removal rate and chipping size) has also been attempted by employing a desirability approach, and at an optimized parametric setting the obtained experimental values for material removal rate and chipping size were 0.4166?mm³/s and 0.5134?mm, respectively, with a combined desirability index value of 0.849.     

Provision of mental health services in women's health centers

Women's health centers are often associated with a comprehensive model of health care that treats the "whole woman." Using data from a nationwide study of 467 women's health centers, we explored how the ideal of comprehensive care was implemented with respect to mental health services. Specifically, we examined the rates of screening and treatment for a subset of mental health and behavioral and social problems in women's health centers and the structural, staffing, philosophical, and patient factors associated with the provision of services. Across 12 services, the overall rates of provision ranged from 7.7% for screening for dementing disorders to 27.6% for smoking cessation counseling and treatment. In a series of logistic regressions, center type (primary care) and having a mental health staff person were consistently associated with service provision; other important variables were having a high percentage of women using the center as their usual source of care and having a belief in women-centered care. Findings indicate that the majority of women using women's health centers do not receive services in a comprehensive care environment that includes key mental health services.     

Domain flexibility in retroviral proteases: structural implications for drug resistant mutations

Rigid body rotation of five domains and movements within their interfacial joints provide a rational context for understanding why HIV protease mutations that arise in drug resistant strains are often spatially removed from the drug or substrate binding sites. Domain motions associated with substrate binding in the retroviral HIV-1 and SIV proteases are identified and characterized. These motions are in addition to closure of the flaps and result from rotations of approximately 6-7 degrees at primarily hydrophobic interfaces. A crystal structure of unliganded SIV protease (incorporating the point mutation Ser 4 His to stabilize the protease against autolysis) was determined to 2.0 A resolution in a new space group, P3221. The structure is in the most "open" conformation of any retroviral protease so far examined, with six residues of the flaps disordered. Comparison of this and unliganded HIV structures, with their respective liganded structures by difference distance matrixes identifies five domains of the protease dimer that move as rigid bodies against one another: one terminal domain encompassing the N- and C-terminal beta sheet of the dimer, two core domains containing the catalytic aspartic acids, and two flap domains. The two core domains rotate toward each other on substrate binding, reshaping the binding pocket. We therefore show that, for enzymes, mutations at interdomain interfaces that favor the unliganded form of the target active site will increase the off-rate of the inhibitor, allowing the substrate greater access for catalysis. This offers a mechanism of resistance to competitive inhibitors, especially when the forward enzymatic reaction rate exceeds the rate of substrate dissociation.     

Thermodynamic properties of alumina-saturated iron-carbon-bismuth alloys

Using direct and indirect equilibration methods, the solubilities of iron in molten bismuth and those of bismuth in molten iron-carbon alloys have been measured over the temperature range 1473-1873 K. The Henrian behaviour of bismuth in molten ferrous alloys allows the calculation of its activity coefficient, which in turn facilitates modelling as a function of temperature and carbon content, using the unified interaction parameter formalism developed by Pelton and Bale. The modelling results generate the expression: . A model has also been developed expressing bismuth content in molten iron-carbon alloys as a function of temperature and composition: .     

All that you can be: stereotyping of self and others in a military context

The authors tested the shifting standards model (M. Biernat, M. Manis, & T. E. Nelson, 1991) as it applies to sex- and race-based stereotyping of self and others in the military. U. S. Army officers attending a leadership training course made judgments of their own and their groupmates' leadership competence at 3 time points over a 9-week period. We examined the effects of officer sex and race on both subjective (rating) and objective/common-rule (ranking/Q-sort) evaluations. Stereotyping generally increased with time, and in accordance with the shifting standards model, pro-male judgment bias was more evident in rankings than in ratings, particularly for White targets. Self-judgments were also affected by sex-based shifting standards, particularly in workgroups containing a single ("solo") woman. Differential standard use on the basis of race was less apparent, a finding attributed to the Army's explicit invocation against the use of differential race-based standards.     

Analogues of capsaicin with agonist activity as novel analgesic agents: structure-activity studies. 4. Potent, orally active analgesics

Structural features of three regions of the capsaicin molecule necessary for agonist properties were delineated by a previously reported modular approach. These in vitro agonist effects were shown to correlate with analgesic potency in rodent models. Combination of optimal structural features from each of these regions of the capsaicin molecule have led to highly potent agonists (eg., 1b). Evaluation in vivo established that 1b had analgesic properties but poor oral activity, short duration of action, and excitatory side effects which precluded further development of this compound. Preliminary metabolism studies had shown that the phenol moiety of 1b was rapidly glucuronidated in vivo, providing a possible explanation for the poor pharmacokinetic profile. Subsequent specific modification of the phenol group led to compounds 2a-j, which retained in vitro potency. The in vivo profiles of two representatives of this series, 2a,h, were much improved over the "parent" phenol series, and they are candidates for development as analgesic agents.     

Roald Amundsen--a study of personality

Roald Amundsen is the most famous of the Norwegian polar explorers. His ancestors came from a group of islands south-east of the Oslofjord. From being fishermen and sailors, they progressed to becoming captains and shipowners in the course of two generations. Amundsen's father, Jens, stayed at sea until his ship went down with all the crew. Roald was 14 years of age at the time, the youngest of four competing brothers. Jens had left the close-knit local family community before that, and bought a flat in the capital, Oslo, so that his sons could get a better education. Roald's mother wanted him to study medicine. He did as she wished for a time, but was not at all interested. When his mother died, he abruptly left the university and went to sea, which had been the tradition in his family for decades. As a young boy he was an admirer of Sir John Franklin and his explorers of the Northwest Passage. Fridtjof Nansen became his ideal. The biographies about Roald Amundsen are very diverging--some hold him a hero, others reflect a strongly critical attitude. Here, the author tries to define his personality and places him firmly within the narcissistic domain. His tendency to seek the company of married women, but to take immediate flight when they really became interested reflects an Oedipus complex from before puberty. The tragic death of his father, the sea captain, may have been a supposition; puberty can be seen as a period of coping with ambivalence towards an earlier idealized father. His genius combined ambitious goals with a sharp eye for details as regards the equipment used in his expeditions. In his travels in the Arctic and the Antartic he was driven forward by the energy of the nation. His heroic death, trying to save his earlier "enemy", Nobile, was probably caused by an urge for self-destruction.     

CHL1 encodes a component of the low-affinity nitrate uptake system in Arabidopsis and shows cell type-specific expression in roots

The Arabidopsis CHL1 (AtNRT1) gene confers sensitivity to the herbicide chlorate and encodes a nitrate-regulated nitrate transporter. However, how CHL1 participates in nitrate uptake in plants is not yet clear. In this study, we examined the in vivo function of CHL1 with in vivo uptake measurements and in situ hybridization experiments. Under most conditions tested, the amount of nitrate uptake by a chl1 deletion mutant was found to be significantly less than that of the wild type. This uptake deficiency was reversed when a CHL1 cDNA clone driven by the cauliflower mosaic virus 35S promoter was expressed in transgenic chl1 plants. Furthermore, tissue-specific expression patterns showed that near the root tip, CHL1 mRNA is found primarily in the epidermis, but further from the root tip, the mRNA is found in the cortex or endodermis. These results are consistent with the involvement of CHL1 in nitrate uptake at different stages of root cell development. A functional analysis in Xenopus oocytes indicated that CHL1 is a low-affinity nitrate transporter with a K(m) value of approximately 8.5 mM for nitrate. This finding is consistent with the chlorate resistance phenotype of chl1 mutants. However, these results do not fit the current model of a single, constitutive component for the low-affinity uptake system. To reconcile this discrepancy and the complex uptake behavior observed, we propose a "two-gene" model for the low-affinity nitrate uptake system of Arabidopsis.