Improved detection of Probe Request Attacks : Using Neural Networks and Genetic Algorithm

The Media Access Control (MAC) layer of the wireless protocol, Institute of Electrical and Electronics Engineers (IEEE) 802.11, is based on the exchange of request and response messages. Probe Request Flooding Attacks (PRFA) are devised based on this design flaw to reduce network performance or prevent legitimate users from accessing network resources. The vulnerability is amplified due to clear beacon, probe request and probe response frames. The research is to detect PRFA of Wireless Local Area Networks (WLAN) using a Supervised Feedforward Neural Network (NN). The NN converged outstandingly with train, valid, test sample percentages 70, 15, 15 and hidden neurons 20. The effectiveness of an Intruder Detection System depends on its prediction accuracy. This paper presents optimisation of the NN using Genetic Algorithms (GA). GAs sought to maximise the performance of the model based on Linear Regression (R) and generated R > 0.95. Novelty of this research lies in the fact that the NN accepts user and attacker training data captured separately. Hence, security administrators do not have to perform the painstaking task of manually identifying individual frames for labelling prior training. The GA provides a reliable NN model and recognises the behaviour of the NN for diverse configurations

FoodNet: Recognizing Foods Using Ensemble of Deep Networks

In this work we propose a methodology for an automatic food classification system which recognizes the contents of the meal from the images of the food. We developed a multi-layered deep convolutional neural network (CNN) architecture that takes advantages of the features from other deep networks and improves the efficiency. Numerous classical handcrafted features and approaches are explored, among which CNNs are chosen as the best performing features. Networks are trained and fine-tuned using preprocessed images and the filter outputs are fused to achieve higher accuracy. Experimental results on the largest real-world food recognition database ETH Food-101 and newly contributed Indian food image database demonstrate the effectiveness of the proposed methodology as compared to many other benchmark deep learned CNN frameworks.Comment: 5 pages, 3 figures, 3 tables, IEEE Signal Processing Letter

Possibility of observing Leptonic CP violation with perturbed Democratic mixing patterns

The Daya Bay Collaboration has recently reported the precise measurement of $\theta_{13}\simeq 8.8^\circ \pm 0.8^\circ$ or $\theta_{13} \neq 0$ at 5.2 \sigma level. The observed non-zero $\theta_{13}$ can be accommodated by some general modifications to the Democratic mixing matrix. Using such matrices we study the possibility of observing non-zero CP violation in the leptonic sector.Comment: 12 pages, 3 figures, typos corrected, version to appear in MPL

Analysis of fMRI data based on prediction of neural response using MVPA

fMRI data is an emerging approach that shows all the information of the brain that is represented in the subject of the brain at a particular point in time. Multi-voxel pattern analysis (MVPA) is gaining interest in the neuro imaging because it allows Cognitive states to be modeled as distributed patterns of neural activity. The MVPA approach allows to several cognitive state of brain reading. In order to relate the neural actions to cognition in fMRI information Multi-voxel sample examination is used. The intend of this project is to construct a classification model. When the quantity of features(voxels) exceeds the total quantity of data scrutiny, it creates replica over fitting. For this reason it is significant to choose informative voxels previous to constructing a classification model. This project mostly deals with two methods that are MI and partial least square regression (PLS). By using these two techniques effective feature assortment is done. Based on the degree of association to the stimulus circumstances informative voxel index must be created. The proposed work is evaluated by determining the performance of standard classification algorithms. The results obtained from the proposed work which is based on PLS and MI method improves the classification accuracy

Issues and Challenges in Advertising on the Web

One of the big surprises of the 21st century has been the ability of all sorts of interesting Web applications to support themselves through advertising, rather than subscription. While radio and television have managed to use advertising as their primary revenue source, most media – newspapers and magazines, for example – have had to use a hybrid approach, combining revenue from advertising and subscriptions.  A venue for on-line advertising has been search, and much of the effectiveness of search advertising came from the “adwords” model of matching search queries to advertisements. This paper presents the algorithms for optimizing the way of matching search queries to advertisements is done. The algorithms discussed are of unusual type; they are greedy and they are on-line which are used to tackle the adwords problem.DOI:http://dx.doi.org/10.11591/ijece.v4i5.662

Maternal and perinatal outcome of pregnancy in women with one previous caesarean section-a study at a tertiary care centre

Background: Increasing rates of primary caesarean section has led to an increased proportion of obstetric population with history of prior caesarean delivery. There is growing concern by obstetrician for optimizing the management of these high risk cases. The present study was undertaken to evaluate obstetric and fetal outcome of patients presenting at term with history of one previous LSCS.Methods: This was a prospective hospital based observational study conducted at Vani Vilas Hospital and Bowring and Lady Curzon Hospital, Department of OBG, BMC and RI, Bangalore. The study included 300 patients who had undergone previous one LSCS with term pregnancy.Results: Majority of patients, that is 186 (62%) were in the age group of 21 to 25 years. Out of 300 patients, 94 (31.33%) patients went for repeat LSCS without trial. 206 (68.67%) patients were included in the trial of labour group, out of which 109 (52.9%) patients had successful vaginal delivery. 97 (47.1%) patients went for repeat LSCS in trial group due to various indications, commonest being scar tenderness.Conclusions: Delivery of patients with previous caesarean section should always be conducted in a well-equipped hospital where facilities for immediate intervention are available if necessity arises. These patients should be counselled antenatally regarding institutional delivery, encouraging trial of labour after caesarean section in select group of patients with close fetal and maternal monitoring for early detection of complications and its management reduces maternal and perinatal mortality and morbidity

CBDC: EMPIRICAL STUDY ON DETERMINANTS OF CBDC USAGE PURPOSE AMONG CONSUMERS

Abstract The initiative from the government of India in making India into a digitally vibrant nation is highly admirable. India economic growth over the decade is raising at higher rate, it due to adoption of digitalization in every part of economy from banking, business, and international payment. Banks are updating according to needs and demands of the consumers providing amenable services at finger tips of the consumers. From small vendor to high business transitions are carry forward with the help of digital transition or digital currency. The primary objective of the study is determining CBDC usage purpose among consumers. The study used convenient sampling method and covered 160 banking consumers using digital banking. The findings of the study show Determinants of CBDC Usage Purpose among Consumers have been segregated into two dominant dimensions namely Payment Terminal and Financial Statibility Factor which dealing with cost of using online banking, usage of the same at all branches both nationally and internationally and security of the banking. The second factor is Usage and Payment Efficiency Factor which deals with usage of the digital banking, efficiency of the payment over the geographical location and ability of use the same without internet connections. Consumer Perception on CBDC have been segregated into two dominant dimensions namely Expectancy and Performance Factor which deals with expectancy of the consumers over usage of CBDC, knowledge on using digital currency and trust over the banking while using digital currency. A positive and significant impact of Consumer Perception on CBDC on Determinants of CBDC Usage Purpose among Consumers has been identified

Intervention of Talent Management Impact on the HR Practices among the Employees Working in the Software Industries.

Recruitment of applicants with highly valued talents, provision of continual learning and development opportunities, reward of important team members, and encouragement of advancement within the organization are all common and best practices in talent management (more on these practices below). Numerous examples exist of Indian businesses successfully keeping key employees on staff. Such organizations use alternative methods of talent management. In majority of these situations, such Indian organizations have a heritage of at least hundred years. Some startups and family-run enterprises are also successful in the talent acquisition and retention arena. This case study looks at how one Indian company's talent management practices led to the retention of a key employee. The case, which is based on research on the methods used by several Indian companies to manage their employees' talents, stresses the value of teamwork. The concept of collegiality in the context of talent management has received little attention. This case note is an attempt to spark conversations on how organizations might improve their talent management practices via the use of collaborative strategies. The term "talent management" refers to a company's approach to finding and keeping the best possible staff. Motivated workers who are also strategically aligned have a greater chance of advancing in their current positions and eventually taking on leadership responsibilities. YES, Bank staff in the Indian cities of Hyderabad, Bangalore, and Chennai participated in the researc