Volume 9 | Issue 5 |

 Abstract

In contemporary world, a man or women is engaged with different worldly duties in their profession, work, commitments, family maintenance etc. Smart medicine has emerged to contribute the evolution of healthcare and medical services by applying machine learning together with advanced computing techniques like cloud computing to computer-aided diagnosis and treatments. Depression is another name for mental illness. It can lead to severe health complications and increase the risk of stroke, and sometimes death. Machine learning is mainly focusing on Mind and then Matter. Main motive of this project is to give the analysis and prediction of depression because 21% people are affected in this psychological disease across the nation. In this paper, we collected the datasets which contains patient records and histories with medication process. We analyzed the hypothesis from the records, to point out which are all the major factors to affect the man or women. Besides we are highlighting the factors with grades in different geographical structures like Family problem, Physical illness, Lust or desire not obtained so far. We are introducing ensemble learning method for predicting the disease level for the particular node. Ensemble learning is the process by which multiple models, such as classifiers or experts, are strategically generated and combined to solve a particular computational intelligence problem. We compute a unified medicine framework based on the depression identification parameters using

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

AN EFFICIENT MEDICAL FRAMEWORK FOR DEPRESSION RISK PREDICTION USING ENSEMBLED LEARNING

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

To create some outstanding new ideas of innovation during Pandemic, this paper reveals an augmented study of modified robust fuzzy clustering approach to detect the unusual outliers. Outlier Detection, an unsupervised learning used to detect complex dataset to identify perpetual outliers using membership function to tolerate the uncertainty. The first stage aims to estimate auto-detection of noise reduction, incorrect data points and so on as perpetual outliers. The second stage aims to determine the characterization of utilized input parameters of unending outliers using FCM (Fuzzy C-means Clustering) method to find FOF(Fuzzy Objective Function). This method enhances accuracy, efficacy over similarity measure and performance efficiency that assessed over some UCI repository datasets. Experimental results and statistical evaluation shows effectiveness of detecting perpetual outliers.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Outliers, fuzzy, clustering, Fitness, Perpetual, FOF, Characterization

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Physical infrastructure is one of the major assets of a city for economic and sustainable development. Globally Physical Infrastructure is facing threat due to the lack of Infrastructure resources within the city and its proximity. This paper envisages factors of land use implications, and the process of physical infrastructure development that would reflect the current contemporary challenges. The need and necessity of various types of infrastructure has been rapidly increasing beyond their core functions, which demands the involvement of stake holder participation to promote orderly decisions on infrastructure development policies. An empirical analysis is conducted on time series annual data from 1991 to 2011 for water supply and sanitation of kavali town. The availability of infrastructure facilities is inadequate and requires improvement for the future. The results suggest that public physical infrastructure provision certainly improves the socio-economic conditions by contributing towards growth in the ULB. This paper also suggests and proposes new innovative techniques for improvement of facilities by considering the norms and guidelines framed by the public authorities.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Land-use Analysis, Physical Infrastructure, urbanization, ULB and sanitation

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The recent rapid growth in big data, networking, and machine learning is due to exponential advances in processing, storage, and network technologies. As the world becomes more digitalized, there is a greater need for comprehensive and sophisticated security technologies and strategies to address the increasingly complex nature of cyber-attacks. This paper examines how machine learning, big data is being used in cyber security, both in defence and offense, with a focus on cyber-attacks against machine learning models. Machine learning can be used to carry out cyber-attacks, such as smart botnets, sophisticated spear fishing, and evasive malware. In the field of defence, big data analytics refers to the ability to collect large volumes of digital data in order to analyse, visualize, and derive knowledge that can help predict and prevent cyber-attacks. It gives us a stronger cyber defence stance when combined with security technologies. They allow businesses to identify patterns of behaviour that indicate network threats. Machine learning is used in cyber security for threat identification and prevention, malware detection and classification, and network risk rating, among other things.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Cyber Security; Machine Learning; Malware; Threats Detection and Classification; Network Risk Scoring, Big Data Analytics

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

AN ANALYSIS OF WOMEN ENTREPRENEURS IN DAKSHINA DISTRICT, KARNATAKA

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Time banks are innovative community program which attracted significant interest from the public and voluntary sectors especially in the west. Time banking is the thought where individuals volunteer time for a help and that time is recorded and kept in a record and can be utilized to acquire administrations when a volunteer requires. The paper examines the concept of time-banking and its utility in the Indian context. Timebank is a reciprocal service exchange and promotes equality and dignity of labor. Time bank is based on the notion that every work is equal and everyone has something to offer. Time-banking aims to build community and reciprocity through the exchange of time-based currency. India has rich history of volunteerism and community building and the model of time banking can help to build the social capital in the country. Time banking as concept is based on the foundation of co-production and social exchange.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

time banking, co-production, community, reciprocity, volunteers,social capital

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Corporate social responsibility (CSR) is a type of international private business self-regulation that aims to contribute to societal goals of a philanthropic, activist, or charitable nature by engaging in or supporting volunteering or ethically-oriented practices. The purpose of corporate social responsibility is to give back to the community, take part in phhropic causes, and provide positive social value. The impact of Corporate Social Responsibility (CSR) on firm performance is an important issue in organizational research and has been discussed for decades. Only lately, scholars turned their attention towards aspects on an individual level, like the relation between CSR and work satisfaction or work engagement.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Impact of corporate social responsibility on employee motivation.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Dielectric constant, Dielectric loss, frequency, Moisture content.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

competitive marketplace

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Solid lipid nanoparticles (SLN) are one of the most rapidly evolving nanotechnology formulations, with numerous applications in fields such as drug delivery, clinical medicine, research, and a variety of other sciences. SLN are nanometer-sized spherical particles that are dissolved in water or aqueous surfactant solution and treated with lipophilic or hydrophilic drugs. Also improving the solubility and bioavailability of poorly soluble drugs can be done with biodegradable and bio acceptable polymers that can also resolve the harmful effects of traditional drug carriers. The different development strategies and their assessment were the subject of this review report. The major applications of SLNs, primarily targeted drug delivery, are discussed, as are the analytical methods used in SLN evaluations.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Keywords: solid lipid nanoparticles, methods of preparation, evaluation, applications.

  License

Creative Commons Attribution 4.0 and The Open Definition