Security on the Abusive Social Network Sites- A Survey

To share business interests, the internet social network have become the common platform where users communicate through which My Space, Second Life and similar web2.0 sites can pose malicious security hazards. The social networking sites are viewed as a kind of online cocktail party in business view as a friendly comfortable place to establish contacts, associate buyers or sellers and raise personal or corporate file. To the maxim, cocktail party metaphor is not pure, obviously in the content of a load glass house for social network serves, the users are served in with care and endless visibility through a highly amplified bullhorn. The social network sites are accessed from the comfort and privacy by maximum users, there is a possibility of false sense of anonymity where the users natural defences can too devasted due to the lack of physical contact on social network site by which there is an endanger of disclosing the information of individuals which would never think of revealing to another at a cocktail partys

Video Based Emotion Recognition Using CNN and BRNN

Video-based Emotion recognition is rather challenging than vision task. It needs to model spatial information of each image frame as well as the temporal contextual correlations among sequential frames. For this purpose, we propose hierarchical deep network architecture to extract high-level spatial temporal features. Two classic neural networks, Convolutional neural network (CNN) and Bi-directional recurrent neural network (BRNN) are employed to capture facial textural characteristics in spatial domain and dynamic emotion changes in temporal domain. We endeavor to coordinate the two networks by optimizing each of them to boost the performance of the emotion recognition as well as to achieve greater accuracy as compared with baselines

Predictive Technique Of Security Data Breaches In Ai Powered Mobile Cloud Application Using Deep Random Forest Algorithm

With the rapid integration of artificial intelligence (AI) in mobile cloud applications, ensuring robust security mechanisms is vital to safeguard sensitive user data. The proliferation of AI technologies in mobile cloud applications has brought unprecedented efficiency and convenience, accompanied by an escalating risk of security breaches. As the threat landscape evolves, traditional security measures fall short in providing comprehensive protection. This research recognizes the critical need for a predictive approach to security data breaches in AI-powered mobile cloud applications. Existing security frameworks often lack the adaptability to detect and pre-emptively address emerging threats specific to AI-enhanced mobile cloud environments. This study employs the Deep Random Forest Algorithm, an advanced machine learning technique known for its ability to handle complex and dynamic datasets. The algorithm combines the power of deep learning with the versatility of random forest classifiers to predict security breaches in real-time. The results demonstrate the efficacy of the proposed Deep Random Forest Algorithm in predicting and mitigating security breaches in AI-powered mobile cloud applications. The model exhibits high accuracy and sensitivity, showcasing its potential to enhance the security posture of mobile cloud ecosystems

Semi Automated Text Categorization Using Demonstration Based Term Set

Abstract Manual Analysis of huge amount of textual data requires a tremendous amount of processing time and effort in reading the text and organizing them in required format. In the current scenario, the major problem is with text categorization because of the high dimensionality of feature space. Now-a-days there are many methods available to deal with text feature selection. This paper aims at such semi automated text categorization feature selection methodology to deal with a massive data using one of the phases of David Merrill's First principles of instruction (FPI). It uses a pre-defined category group by providing

Ethnic Differences in Survival after Breast Cancer in South East Asia

Background: The burden of breast cancer in Asia is escalating. We evaluated the impact of ethnicity on survival after breast cancer in the multi-ethnic region of South East Asia. Methodology/Principal Findings Using the Singapore-Malaysia hospital-based breast cancer registry, we analyzed the association between ethnicity and mortality following breast cancer in 5,264 patients diagnosed between 1990 and 2007 (Chinese: 71.6%, Malay: 18.4%, Indian: 10.0%). We compared survival rates between ethnic groups and calculated adjusted hazard ratios (HR) to estimate the independent effect of ethnicity on survival. Malays (n = 968) presented at a significantly younger age, with larger tumors, and at later stages than the Chinese and Indians. Malays were also more likely to have axillary lymph node metastasis at similar tumor sizes and to have hormone receptor negative and poorly differentiated tumors. Five year overall survival was highest in the Chinese women (75.8%; 95%CI: 74.4%–77.3%) followed by Indians (68.0%; 95%CI: 63.8%–72.2%), and Malays (58.5%; 95%CI: 55.2%–61.7%). Compared to the Chinese, Malay ethnicity was associated with significantly higher risk of all-cause mortality (HR: 1.34; 95%CI: 1.19–1.51), independent of age, stage, tumor characteristics and treatment. Indian ethnicity was not significantly associated with risk of mortality after breast cancer compared to the Chinese (HR: 1.14; 95%CI: 0.98–1.34). Conclusion: In South East Asia, Malay ethnicity is independently associated with poorer survival after breast cancer. Research into underlying reasons, potentially including variations in tumor biology, psychosocial factors, treatment responsiveness and lifestyle after diagnosis, is warranted

Unravelling the evolution of the Allatostatin-Type A, KISS and Galanin Peptide-Receptor gene families in Bilaterians: insights from Anopheles Mosquitoes

Allatostatin type A receptors (AST-ARs) are a group of G-protein coupled receptors activated by members of the FGL-amide (AST-A) peptide family that inhibit food intake and development in arthropods. Despite their physiological importance the evolution of the AST-A system is poorly described and relatively few receptors have been isolated and functionally characterised in insects. The present study provides a comprehensive analysis of the origin and comparative evolution of the AST-A system. To determine how evolution and feeding modified the function of AST-AR the duplicate receptors in Anopheles mosquitoes, were characterised. Phylogeny and gene synteny suggested that invertebrate AST-A receptors and peptide genes shared a common evolutionary origin with KISS/GAL receptors and ligands. AST-ARs and KISSR emerged from a common gene ancestor after the divergence of GALRs in the bilaterian genome. In arthropods, the AST-A system evolved through lineage-specific events and the maintenance of two receptors in the flies and mosquitoes (Diptera) was the result of a gene duplication event. Speciation of Anophelesmosquitoes affected receptor gene organisation and characterisation of AST-AR duplicates (GPRALS1 and 2) revealed that in common with other insects, the mosquito receptors were activated by insect AST-A peptides and the iCa(2+)-signalling pathway was stimulated. GPRALS1 and 2 were expressed mainly in mosquito midgut and ovaries and transcript abundance of both receptors was modified by feeding. A blood meal strongly up-regulated expression of both GPRALS in the midgut (p < 0.05) compared to glucose fed females. Based on the results we hypothesise that the AST-A system in insects shared a common origin with the vertebrate KISS system and may also share a common function as an integrator of metabolism and reproduction. Highlights: AST-A and KISS/GAL receptors and ligands shared common ancestry prior to the protostome-deuterostome divergence. Phylogeny and gene synteny revealed that AST-AR and KISSR emerged after GALR gene divergence. AST-AR genes were present in the hemichordates but were lost from the chordates. In protostomes, AST-ARs persisted and evolved through lineage-specific events and duplicated in the arthropod radiation. Diptera acquired and maintained functionally divergent duplicate AST-AR genes.Foundation for Science and Technology, Portugal (FCT) [PTDC/BIA-BCM/114395/2009]; European Regional Development Fund (ERDF) COMPETE - Operational Competitiveness Programme; Portuguese funds through FCT Foundation for Science and Technology [PEst-C/MAR/LA0015/2013, UID/Multi/04326/2013, PEst-OE/SAU/LA0018/2013]; FCT [SFRH/BPD/89811/2012, SFRH/BPD/80447/2011, SFRH/BPD/66742/2009]; auxiliary research contract FCT Pluriannual funds [PEst-C/MAR/LA0015/2013, UID/Multi/04326/2013]info:eu-repo/semantics/publishedVersio