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Prevention of Data Breach by Machine Learning Techniques
In today's data communication environment, network and system security is vital. Hackers and intruders can gain unauthorized access to networks and online services, resulting in some successful attempts to knock down networks and web services. With the progress of security systems, new threats and countermeasures to these assaults emerge. Intrusion Detection Systems are one of these choices (IDS). An Intrusion Detection System's primary goal is to protect resources from attacks. It analyses and anticipates user behavior before determining if it is an assault or a common occurrence. We use Rough Set Theory (RST) and Gradient Boosting to identify network breaches (using the boost library). When packets are intercepted from the network, RST is used to pre-process the data and reduce the dimensions. A gradient boosting model will be used to learn and evaluate the features chosen by RST. RST-Gradient boost model provides the greatest results and accuracy when compared to other scale-down strategies like regular scaler. 2022 IEEE. -
Prevention of Child Sexual Abuse : A Protection Motivation Theory-Based Intervention for Mothers of Preadolescents
Child sexual abuse (CSA) is a growing concern in the world. Prevention of CSA in India is challenging due to deep rooted traditional values and beliefs. Sex and related matters newlineare difficult topics for parents to discuss. Lack of parental awareness leads to increased newlinerisk for CSA. Maternal care is the most influential aspect of child rearing and they need information and skills to educate children on sexual abuse. The literature review was based on Bloom s taxonomy for academic writing. The need for systematic and evidencebased approach in primary prevention was identified. The aim of this study was to test the efficacy of Protection Motivation Theory (PMT)-based psycho education program in enhancing mothers knowledge, attitude and sense of parental competence among mothers. An interactive mixed-method design embedding quantitative and qualitative methods selected 72 mothers as participants from Kannur, Kerala. Mothers aged between 30-40 years who had preadolescent children (8-12 years) were assigned to control and experimental group. A facilitator s psycho education manual was developed embedding PMT constructs for the intervention. The quantitative results indicated significant differences between the groups for CSA knowledge and attitude. The impact of the intervention was moderate to high. The qualitative results indicated the benefits of intervention. Mothers have overcome communication blocks, misconceptions regarding CSA education are cleared, are aware of risks and warning signs and are confident to deal with CSA disclosure. The involvement of mothers in the prevention program was found to be effective in this study. The findings of this study have important implications for developing theory- based interventions for CSA prevention. The application of systematic evidence-based interventions promotes active engagement of participants for applying the learnt skills effectively. The culturally sensitive issues like CSA needs more contextual understanding of the problems to find effective solutions. -
Prevention and Mitigation of Intrusion Using an Efficient Ensemble Classification in Fog Computing
Cloud services in fog network is a platform that inherits software services to a network to handle cloud-specific problems. A significant component of the security paradigm that supports service quality is represented by intrusion detection systems (IDSs). This work develops an optimization environment to mitigate intrusion using RSLO classifier on a cloud-based fog networks. Here, a three-layer approach namely the cloud, end point, and fog layers is used as a trio to carry out all of the processing. In the cloud layer, three layers of processing are required for handling the dataset metrics which are data transformation metrics, feature selection metrics, and classification processes. With log transformation, data is transformed using KS correlation-based filter which is used to choose a feature. The classification using an ensemble methodology of RideNN classifiers which is a Rider Sea Lion Optimization (RSLO), a created classifier, is used to tune the ensemble classifier. Physical work is carried out at another layer called an end point layer. A trained ensemble classifier is used for intrusion detection in the fog layer. A greater precision, recall, and F-measure were obtained with an accuracy approximately 95%, with all benefits of the suggested RSLO-based ensemble strategy. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Preventing Data Leakage and Traffic Optimization in Software-Defined Programmable Networks
The first widely used communication infrastructure was the telephone network, often known as a connection-oriented or circuit-switched network. While making a phone call, these networks will first set up a connection, and then tear it down after the call has ended. The connection made during the call would not be used again. Thus, connectionless or packet-switched networks have been introduced, with an aim to send voice signals as data packets. When compared to conventional network architecture, SDN's separation of the data plane and control plane of networking devices makes the management of these devices directly programmable via a centralised controller. It uses a MAS-based distributed architecture to categorise network flows, and it's called the Traffic Classification Module. Each host or server's high-priority application traffic is isolated via Deep Packet Inspection (DPI). The time consumed for a packet to travel from one endpoint to another is referred to as the average packet delay, whereas the controller's reaction time is twice the average packet delay. Few works existed that utilised routing strategies to decrease the typical packet delay in SDN. To reduce the controller's response time, Software-Defined Networks (SDNs) need a routing algorithm that reduces the average packet delay. Each of the proposed modules and the whole combined SDN-MASTE framework were put through their paces in a series of experiments and emulation-based tests to see how well they performed. 2023 IEEE. -
Prevalence of hypertension and determination of its risk factors in korangrapady, udupi district, coastal Karnataka, India
Objective: Hypertension is a global public health problem that estimates about 4.5% of overall disease burden. It is a general health challenge in economically developing and developed countries. High blood pressure prevalence is increased from 11.2% to 28% (p<0.001) and 2342.2% in rural and urban area according to the study done in Delhi for about 20 years. It is one of the important risk factors of cardiovascular disease, which is associated with morbidity and mortality. The aim was to identify the significant correlates of hypertension in a rural village in south India. Methods: Data were collected through a door-to-door survey among the residents of the village. Data collected was related to demographics and anthropometric measures. Blood pressure was measured with the help of the medical supervisor. Data were analyzed using Chi-square test for comparison between attributes. The potential hazard factor of hypertension was found by performing binary logistic regression model. Result: Of 299 participants considered for the study, 50 were hypertensive contributing to the overall prevalence of 16.72% with 95% confidence interval of 0.12920.2137, in which females have the prevalence rate of 17.8% and males with the prevalence rate of 15.5%. The study outcome identified education level, occupation, and family history of hypertension is the predicted risk factors. Conclusion: The high blood pressure prevalence is low and comparable with the studies conducted in other rural regions of India. More studies are, however, required to decide the appropriation and determinants of hypertension in different parts of this region. 2018 The Authors. -
Prevalence of Cardiovascular Diseases in South Asians: Scrutinizing Traditional Risk Factors and Newly Recognized Risk Factors Sarcopenia and Osteopenia/Osteoporosis
One of the primary reasons for complications and death worldwide are cardiovascular diseases (CVDs), with a death toll of approximately 18 million per year. CVDs include cardiomyopathy, hypertension, ischemic heart disease, coronary heart disease, myocardial infarction, heart attack, hearth failure, etc. Over 80% of the CVD mortality is recorded from lower and middle-income countries. Records from the past decade have highlighted the increase of CVDs among the South Asian populations, and the prime purpose of the review is to jot down the reasons for the steep spike in CVDs. Studies analyzing the causative factors for the increase of CVDs in South Asians are still to be verified. Apart from known predisposing and lifestyle factors, other emerging risk factors associated with CVDs, namely the musculoskeletal diseases sarcopenia and osteopenia, should be tracked to tackle research gaps in upcoming analyses. This requires loads of scientific efforts. With proper monitoring, the raising alarm that the CVD burden generates can be reduced. This review discusses the already established signs and recognizes important clues to the emerging etiology of CVDs in the Asian population and prevention measures to keep it at bay. 2023 Elsevier Inc. -
Prevalence and Predictors of Restless Leg Syndrome in Adolescents and Young Adults of Bengaluru City, India: A Cross-Sectional Study
INTRODUCTION: Restless leg syndrome (RLS) is a sensorimotor disease characterized by an urge to move the legs, often caused by uncomfortable and unpleasant sensations in the legs. It affects the quality of sleep which in turn affects scholastic performance in children and predisposes them to cardiovascular diseases in the long run. Hence, the primary aim of this study was to assess the prevalence and predictors of RLS, poor sleep quality, and excessive daytime sleepiness (EDS). METHODS: This was a cross-sectional observational study conducted between September 2017 and March 2020 in Bengaluru, India, including all consenting PreUniversity College, Degree College, and Higher Secondary school students. After parental consent and assent (if applicable) was obtained, a semi-structured standardized pilot-tested questionnaire consisting of the RLS diagnostic criteria, Pittsburgh Sleep Quality Index (PSQI), Epworth sleepiness scale, and questions on sleep hygiene was administered. The prevalence was expressed as proportions and 95% confidence intervals (95% CI). Regression analysis was done to determine the predictors. RESULTS: The overall prevalence (95% CI; frequency) of students with RLS, poor sleep quality, and EDS in our study population was 8.36% (7.54, 9.24; n = 1,544/4,211), 36.67% (35.21, 38.14; n = 1,544/4,211), and 39.87% (38.39, 41.37; n = 1,679/4,211), respectively. PSQI and Epworth score were the significant predictors of RLS. Age, Epworth score, knowledge score, and the number of unacceptable sleep habits were the significant predictors of sleep quality. Female gender, PSQI, RLS, knowledge score, and the number of unacceptable sleep habits were the significant predictors of EDS. CONCLUSIONS: The prevalence of RLS, those with poor sleep quality and EDS among adolescents and young adults was higher when compared to the historical data of general population in the same city. 2022 S. Karger AG, Basel. -
Prevalence and predictors of diabetes among adults in rural Dharwad, India: A cross-sectional study
Objective: Diabetes is a long life chronic non-communicable disease and emerging fast as one of the most serious health problems in developed and developing countries, also influences the risk of developing macrovascular complication including heart disease and stroke which are the leading causes of global death. This study aims to find the potential risk factors associated to diabetes among different community (Government, Private employees, and Businessmen) of adults 20 years and above. Methods: A cross-sectional study followed and conducted door-to-door survey using World Health Organization STEP Surveillance (WHO STEPS) questionnaire to collect the information of sociodemographic, anthropometric and behavioral characteristics. Multiple logistic regression is used to determine the risk factors of diabetes among study population. Data was pre-processed and used Chi-square test and t-test to find the comparison between the attributes. Results: Overall prevalence of diabetes is found to be 49.1% in which prevalence more in females with 51.7% than in males with 46.8%, the education, health examination, and waist circumference were found to be the potential risk factors. The total study subjects include 1083 in which male is 611 and female is 472. Conclusion: The current study reflects the importance of Diabetes disease among the study population in rural Dharwad and this study can be utilized to control and prevent diabetes. Its an early call for the females of the study population to take care and practice healthy food in day today life and the outcome of the study says that the education should be given prime importance in everyones life. 2018 The Authors. -
Preterm birth prediction using cuckoo search-based fuzzy min-max neural network
In the latest history, a Decision making and prediction system has been investigated vigorously for several decades and has got a lift. Together with preterm birth study, the decision support system has been explored in different areas. Using fuzzy, neural network and cuckoo search algorithm, the medical decision support system is improved for the forecast of preterm birth in this document. A two-module pattern categorization and rule extraction system has been highlighted by this study, where in the former module emphasises an altered fuzzy min-max (FMM) neural-network-based pattern classifier, whereas the subsequent module emphasises oppositional cuckoo search based rule extractor. With the theory of opposition, this paper examines altered cuckoo search algorithm. Using Pre Term Birth (PTB) datasets, the empirical analysis is executed and applied using MATLAB. Performance assessment matrix occupied is the precision and our suggested method is compared with the active methods. It is examined that our suggested method has attained improved precision value (85.6 %) when compared to FMM (77.36 %) which illustrates the efficiency of the suggested method from the results. 2013 Praise Worthy Prize S.r.l. - All rights reserved. -
Pressure ulcer risk assessment device /
Patent Number: 202141043299, Applicant: Vijayalakshmi A.
A pressure ulcer is a localized injury to the skin or underlying tissue as a result of unrelieved pressure which can be intrinsic or extrinsic in nature. Prevention of pressure ulcer is a prime requisite for any immobile patients as it can worsen the health situations and can even lead to mortality. In the context of Indian scenario, this issue is quite ignored either due to the lack of awareness of its implications or because of the absence of adequate preventive measures. Pressure ulcer often called as bed sores is a common issue prevalent in the immobile bed ridden, especially the old age people and the vulnerable patients with chronic medical conditions. -
Pressure ulcer risk assessment device /
Patent Number: 202141043299, Applicant: Vijayalakshmi A.
A pressure ulcer is a localized injury to the skin or underlying tissue as a result of unrelieved pressure which can be intrinsic or extrinsic in nature. Prevention of pressure ulcer is a prime requisite for any immobile patients as it can worsen the health situations and can even lead to mortality. In the context of Indian scenario, this issue is quite ignored either due to the lack of awareness of its implications or because of the absence of adequate preventive measures. Pressure ulcer often called as bed sores is a common issue prevalent in the immobile bed ridden, especially the old age people and the vulnerable patients with chronic medical conditions. -
Presence or absence of Dunning-Kruger effect: Differences in narcissism, general self-efficacy and decision-making styles in young adults
The Dunning-Kruger effect is a cognitive bias in which individuals who are unskilled in certain domains overestimate their ability and are unaware of it. Past studies have focused on establishing the effect but have not looked into associated factors. This study aimed to see if the Dunning-Kruger effect has any influence on an individuals narcissism, general self-efficacy and decision making styles especially in young adults in the Indian population. The Dunning- Kruger effect was established using scores from the Cognitive Reflection Task and the Rationality scale from Rational Experiential Inventory, keeping the Unskilled and Unaware phrase under consideration, while establishing cut-offs. The participants were also divided into three groups - the group that was able to estimate their performance, the group that over-estimated their performance and the group that underestimated their performance. The dependent variables were measured using the NPI-16, General Self-Efficacy Scale and Flinders Decision-Making Styles Questionnaire. The Kruskal-Wallis H results showed that there is a significant difference between the group with Dunning-Kruger effect, without Dunning-Kruger effect and the group that underestimated their performance with reference to Narcissism, General Self-Efficacy, Vigilance and Hypervigilance decision-making styles. The Mann-Whitney U results further indicated a significant difference in Narcissism and Vigilance, between the groups that overestimated their performance and the group that accurately estimated their performance. However, there was no correlation between the CRT discrepancy scores of the individuals with Dunning-Kruger effect and the dependent variables. 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature. -
Presence of red giant population in the foreground stellar substructure of the Small Magellanic Cloud
The eastern region of the Small Magellanic Cloud (SMC) is found to have a foreground stellar substructure, which is identified as a distance bimodality (?12 kpc apart) in the previous studies using red clump (RC) stars. Interestingly, studies of red giant branch (RGB) stars in the eastern SMC indicate a bimodal radial velocity (RV) distribution. In this study, we investigate the connection between these two bimodal distributions to better understand the nature and origin of the foreground stellar substructure in the eastern SMC. We use the Gaia Early Data Release 3 astrometric data and archival RV data of RGB stars for this study. We find a bimodal RV distribution of RGB stars (separated by ?35-45 km s-1) in the eastern and south-western (SW) outer regions. The observed proper motion values of the lower and higher RV RGB components in the eastern regions are similar to those of the foreground and main-body RC stars, respectively. This suggests that the two RGB populations in the eastern region are separated by a similar distance to those of the RC stars, and the RGB stars in the lower RV component are part of the foreground substructure. Based on the differences in the distance and RV of the two components, we estimate an approximate time of formation of this substructure as 307 65 Myr ago. This is comparable with the values predicted by simulations for the recent epoch of tidal interaction between the Magellanic Clouds. Comparison of the observed properties of RGB stars, in the outer SW region, with N-body simulations shows that the higher RV component in the SW region is at a farther distance than the main body, indicating the presence of a stellar counter-bridge in the SW region of the SMC. 2021 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society. -
Preprocessing Big Data using Partitioning Method for Efficient Analysis
Big data collection is the process of gathering unprocessed and unstructured data from disparate sources. As data deluge, the large volume of data collected and integrated consist missing values, outliers, and redundant records. This makes the big dataset insignificant for processing and mining knowledge. Also, it unnecessarily consumes large amount of valuable storage for storing redundant data and meaningless data. The result obtained after applying mining techniques in this insignificant data lead to wrong inferences. This makes it inevitable to preprocess data in order to store and process big dataset effectively and draw correct inferences. When data is preprocessed before analytics the storage consumption is less and computation and communication complexity is reduced. The analytics result is of high quality and the needed time for processing is considerably reduced. Preprocessing data is inevitable for applying any analytics algorithm to obtain valuable pattern. The quality of knowledge mined from large volume of big data depends on the quality of input data used for processing. The major steps in big data preprocessing include data integration from disparate sources, missing value imputation, outlier detection and treatment, and handling redundant data. The process of integration includes steps such as extraction, transformation, and loading. The data extraction step gathers useful data used for analytics and the transformation process organize the collected data in structured format suitable for analytics. The role of load process is to store transformed data into secured storage so that data can be obtained and processed effectively in future. This work provides preprocessing techniques for big data that deals with missing values and outliers and results in obtaining quality data partitions. 2023 IEEE. -
Preprocessed text compression method for Malayalam text files
The increasing importance of Unicode for text files implies an increase in storage space required for data and the time for the transmission of data, with a corresponding need for compression of data. Conventional compressors fair purely on UTF-8 texts, where each character can span multiple bytes. Malayalam which is one among the four major languages of the Dravidian family, is represented by using Unicode characters. The contribution of this paper is a reversible transformation mapping of the input to reduce the actual size of the input file before a general purpose compression method. After the preprocessing, LZW compression achieves more compression to Malayalam text files containing any characters including ASCII characters. This method can be extended to any native language files containing mostly the characters of only one script. BEIESP. -
Preparation, characterization, and evaluation of corrosion inhibition efficiency of sodium lauryl sulfate modified chitosan for mild steel in the acid pickling process
The polar head and a hydrophobic long alkyl chain end of surfactants show effective adsorption on the metal surfaces and metal/solution interfaces. The present study deals with the investigation of corrosion inhibition efficiency of chitosan modified with an anionic surfactant, namely sodium lauryl sulfate. The modified chitosan was characterized using spectral techniques such as ATR- FTIR and NMR, thermal analytical methods that include TGA and DSC. The surface charge and particle size distribution were analyzed using Zeta potential analyzer. The corrosion inhibition efficiency of the water-soluble modified chitosan was evaluated using gravimetric and electrochemical methods. A maximum corrosion inhibition efficiency of 96.44% for 6 h of immersion period at 303 K was obtained. The adsorption process obeyed Langmuir isotherm. The adsorption mechanism involved both physisorption and chemisorption. Tafel and impedance studies showed results in agreement with the gravimetric method. Tafel plot indicates the inhibitor controlled both cathodic hydrogen evolution and anodic metal dissolution reactions. AC impedance study supports the increase in surface coverage of the metal surface by the inhibitor, forming a protective film. Further evidence comes from the surface characterization of the inhibited metal surface by contact angle measurement, SEM, EDAX spectra, and atomic force microscopic studies. DFT and Monte Carlo simulation studies showed a proper alignment with the experiment results. 2020 Elsevier B.V. -
Preparation, characterization, and electrochemical properties of PEO/PVDF blend films
This paper reports the electrochemical properties of PEO, PEO/PVDF10, and PEO/PVDF30 blend films, The XRD spectra reveal the structural properties of the blend and, FTIR spectra provide the chemical interaction between the blends, and observed FESEM images of PEO/PVDF blend film shows the porous with spherulite grain structure and AFM images gives the surface topology. The thermal stability, melting point, and decomposes of the polymer blend film were examined through TGA, DTA, and DSC. CV curve shows the proper oxidation and redox reaction involved in the blend film, these results provide the prepared polymer blend film is a good candidate for used to the separator in energy storage applications. 2022 Elsevier B.V. -
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Preparation for parenthood programme: Experiences from southern India
Parenting skills are critically important to ensure that children are brought up in a safe environment. Recent evidence shows that studies of parenting skills are still at a preliminary stage in low-and middle-income countries. These need to involve family practitioners and religious groups who often play a major role in preparing young people in India. There are organized programmes available in the country for Christian adults to prepare themselves for marriage and family life through various church initiatives and activities. In order to develop a programme which can be used to prepare young parents for responsibilities of parenthood, a needs assessment was carried out among 70 young adults who attended a marriage preparation course in Bangalore, India. All the participants belonged to the Christian faith. Participants consisted of 53% men and 47% women whose average age for deciding to get married was 26.8 years. All of them expressed a need for such a preparatory programme for parenthood. They considered they needed to know about normal child development, behavioural management of children, to develop adequate skills in handling children at different ages, and deal with their own past issues with their own parents when they were being parented. The results suggest that the development of a preparatory programme for young adults to support them in the role of parenthood must take their views and needs into account. 2014 Institute of Psychiatry. -
Preparation for parenthood programme: Experiences form Southern India /
Internatinoal Review of Psychiatry, Vol.26, Issue 4, pp.423-429, ISSN No: 0954-0261.