An Improved Intrusion Prevention Sytem for WLAN

The volatile growth in wireless networks over the last few years resembles the rapid growth of the Internet within the last decade. The current IPS presents a less security. Unfortunately, our work combined with the work of others show that each of these mechanisms are completely futile. As a result, organizations with deployed wireless networks are vulnerable to illegal use of, and access to, their internal communications

Healthy mind and conceiving (Saumansya Garbhajananam) - A Critical Analysation with Ayurvedic prospective.

Soumanasya Garbhjananam (piece of mind) causes production of Garbha. As per Acharya Charaka’s guideline, this is a one type of Adravya Chikitsa not mere the placebo effect in the current era as many gynecologists also opine the same aspect with Charaka by means not having any deformity relates to male/female infertility. Thus the topic has keenly reviewed with other substantial approaches to prove the concept of Soumanasya Garbhajananam. The legacy of Charaka has been interpreted with special reference to Shareera Sthana of Charaka Samhita as well as Yonivyapat in Chikitsa Sthana. To evaluate this concept on the basic principle of Karyakarana Siddhant Vada has been enumerated on the parallel lines of current sexual enjoyment era. Day today practice it is also evident the concept of Soumanasya Garbhajananam. It is a matter of further research to calibrate the Soumanasya Bhava which it differs from individual to individual

Need of Boosted GMM in Speech Emotion Recognition System Implemented Using Gaussian Mixture Model

Speech feeling recognition is a vital issue that affects the human machine interaction. Automatic recognition of human feeling in speech aims at recognizing the underlying spirit of a speaker from the speech signal. Gaussian mixture models (GMMs) and therefore the minimum error rate classifier (i.e., theorem optimum classifier) is widespread and effective tools for speech feeling recognition. Typically, GMMs are wont to model the class-conditional distributions of acoustic options and their parameters are calculable by the expectation maximization (EM) algorithmic rule supported a coaching information set. During this paper, we have a tendency to introduce a boosting algorithmic rule for faithfully and accurately estimating the class-conditional GMMs. The ensuing algorithmic rule is known as the Boosted-GMM algorithmic rule. Our speech feeling recognition experiments show that the feeling recognition rates are effectively and considerably boosted by the Boosted-GMM algorithmic rule as compared to the EM-GMM algorithmic rule. During this interaction, human beings have some feelings that they want to convey to their communication partner with whom they are communicating, and then their communication partner may be the human or machine. This work dependent on the emotion recognition of the human beings from their speech signal. Emotion recognition from the speaker’s speech is very difficult because of the following reasons: Because of the existence of the different sentences, speakers, speaking styles, speaking rates accosting variability was introduced. The same utterance may show different emotions. Therefore, it is very difficult to differentiate these portions of utterance. Another problem is that emotion expression is depending on the speaker and his or her culture and environment. As the culture and environment gets change the speaking style also gets change, which is another challenge in front of the speech emotion recognition system.Human beings normally used their essential potentials to make communication better between themselves as well as between human and machine. During this interaction, human beings have some feelings that they want to convey to their communication partner with whom they are communicating, and then their communication partner may be the human or machine. This dissertation work dependent on the emotion recognition of the human beings from their speech signal. In this chapter introduction of the speech emotion recognition based on the problem overview and need of the system is provided. Emotional speech recognition aims at automatically identifying the emotional or physical state of a human being from his or her voice. Although feeling detection from speech could be a comparatively new field of analysis, it is several potential applications. In human-computer or human-human interaction systems, feeling recognition systems might give users with improved services by being adaptative to their emotions. The body of labor on sleuthing feeling in speech is sort of restricted. Currently, researchers area unit still debating what options influence the popularity of feeling in speech. There is conjointly appreciable uncertainty on the simplest algorithmic program for classifying feeling, and those emotions to category along.

Development and Ergonomic Evaluation of Manual Weeder

Rosana G. Moreira, Editor-in-Chief; Texas A&M UniversityThis is a paper from International Commission of Agricultural Engineering (CIGR, Commission Internationale du Genie Rural) E-Journal Volume 9 (2007): Development and Ergonomic Evaluation of Manual Weeder. Manuscript PM 07 022. Vol. IX. October, 2007

OPTIMIZATION OF SURFACE ROUGHNESS AND CONE ANGLE IN AWJ MACHINING OF AIRCRAFT MATERIAL USING RSM: Received: 14th October 2021; Revised: 29th December 2021, 11th February 2022, 15th February 2022; Accepted: 17th February 2022

Abrasive water jet machining (AWJM) of aircraft material is a difficult process using conventional machines. Machined parts of Inconel 718, a nickel-based alloy (aircraft material) are widely used in the aerospace industries. However, these alloys are expensive and difficult to machine. The objective of this article is to optimize AWJM process parameters. Response Surface Methodology (RSM) is planned with travel speed, abrasive flow rate, and stand-off distance as inputs. The response models of surface finish and cone angle show the correlation coefficient `R2` of 96.94% and 96.67%, respectively. 3D surface plot with analysis of variance (ANOVA) is presented to distinguish significant AWJM parameters. The work revealed that travel speed is a significant factor for surface finish and cone angle. Multi-response optimization results in the best optimal values of traverse speed; abrasive flow rate and standoff distance are 200 mm/min, 460 g/min, and 4 mm respectively. This research outcome showed more than 90 % of accuracy for both the responses. This article is helpful to the AWJM centers to select optimal machining parameters for achieving the desirability in the machining of Inconel 718. The obtained novel results confirmed that such a technique can be implemented to identify optimal parameters in the machining of different materials

A Secure Multi-Path Communication through Dynamic Path Identifiers to Prevent Denial-of-Service Flooding Attacks

Denial of service is characterized by the explicit attempt of the attackers to prevent legitimate user services. With the distributed denial-of-service multiple machines are deployed machines in the network. The denial of service affects the packet stream with the key resources rendering the legitimate clients to provide the ultimate access to the arbitrary damage. In DDoS environment the attacks are distributed with the largescale attempt the malicious users for the enormous number of network packets. The proposed model uses the weighted adaptive cache clustering (WACC) model for the denial of service flooding attacks in the network. The proposed WACC model uses the adaptive model in the estimation of the attack scenario in the network. The proposed WACC model exhibits the reduced False positive Rate, throughput and response rate. The proposed WACC model achieves the maximal delay of 35.41 ms while the conventional TEV achieves the maximal packet delay of 38.15ms and EMC provides the 42.69ms. The estimation expressed that the proposed WACC model achieves a higher throughput value of 88.35%. The analysis concluded that the proposed WACC model achieves improved performance for the prevention of denial-of-services flooding attack