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New technical trends in data science

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New technical trends in data science Transparency and Traceability Consumers who are increasingly aware that their personal information is valuable, are demanding control. Many are recognizing the increasing risk of securing and managing personal data. Beyond that, governments are implementing strict legislation to ensure they do. Transparency and traceability are critical elements to support these digital ethics and privacy needs. Democratization of Technology Democratization of technology refers to the process by which access to technology rapidly continues to become more accessible to more people. Human Augmentation Human augmentation explores how technology can be used to deliver cognitive and physical improvements as an integral part of the human experience. This augmentation is leveraging technology to increase human capabilities both physically and cognitively. Companies like Boston Dynamics have already developed a wide variety of human augmenting devi...
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CLOUD COMPUTING THREATS THREATS of cloud computing- The cloud computing is a prominent and revolutionizing technology with virtually shared resources, Service and utility based computing. The characteristics of cloud computing may cause a lot of problems and threats in the security scope. The few are • Abuse and immoral use of cloud computing • Insecurity of interfaces and APIS • Loss or leakage of data • Malicious elements • Hijacking of accounts/ Maintenance • Technology sharing issues • Risk of exposing company’s confidential data • Data Breaches • Multitenancy some of them are explained- I.  Network Availability: The value of cloud computing in a particular environment can only be realized when your network connectivity and bandwidth meet the minimum requirement which are: According to the need of the customer the cloud should be available, i.e. every time the customer asks for it, the customer should be provided with his requirement . II.  Cloud ...
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AI :Use in Biomedical field Understanding the relationship between symptoms and diagnosis is important for the diagnostic process. A health knowledge graph is a representation of the connections between symptoms and diseases and can help with diagnosis prediction tasks. Chen and Agrawal et al present results evaluating health knowledge graphs and looking at what features are important for accurate diagnosis prediction. They identify major sources of error including unmeasured confounders and sample size and discuss new methods of robust medical knowledge extraction from electronic health records. Diagnosing a disease is not always straightforward; some disease states require multiple tests and longitudinal evaluation before a diagnosis is established. Artificial intelligence may play a role in helping diagnose a disease state sooner by learning predictive patterns that humans may miss. For example, Alzheimer’s disease is a neurodegenerative disorder marked with progr...
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Speech Recognization Speech recognition is the ability of a machine or a program to identify words and phrases in spoken language and convert them to a machine-readable format. Research is done for comparing best between Convolutional neural network (CNN) and Basic neural network. Some datasets collected from internet. After elimination of noise, cleaned audio data is fed to CNN and Basic NN and trained through different layers. Finally, the trained model is checked for accuracy, validation accuracy. Trained data is tested with test data to check the accuracy and efficiency of Model.  Introduction: Speech recognition is playing a major role in most of the fields such as smart phones, TVs, voice call routing, voice dialing, search keywords, simple data entry. While entering data in datasheets we can use ASR for that we are using microphones to dictate the word. Computer takes lots of time to enter data in particular cell. This problem can be reduced using more and mor...
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Augmenting the android app permission system using dynamic analysis                                               Android’s app ecosystem relies heavily on third-party libraries as they facilitate code development and provide a steady stream of revenue for developers. However, while Android has moved towards a more fine-grained runtime permission system, users currently lack the required resources for deciding whether a specific permission request is actually intended for the app itself or is requested by possibly dangerous third-party libraries. In this paper we present Reaper, a novel dynamic analysis system that traces the permissions requested by apps in real time and distinguishes those requested by the app’s core functionality from those requested by third-party libraries linked with the app. Our study on over 5K popular apps demonstrates the large ...
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                                              ML in cyber security Machine learning techniques have been applied in many areas of science due to their unique properties like adaptability, scalability, and potential to rapidly adjust to new and unknown challenges. Cyber security is a fast growing field demanding a great deal of attention because of remarkable progresses in social networks, cloud and web technologies, online banking, mobile environment, smart grid, etc. Diverse machine learning methods have been successfully deployed to address such wide-ranging problems in computer security. This paper discusses and highlights different applications of machine learning in cyber security. This study covers phishing detection, network intrusion detection, testing security properties of protocols, authentication with keystroke dynamics, cryptography, human i...
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                                                                Cloud Computing--            Cloud computing provides the capability to use  storage resources on a metered basis and reduce the investments in an organizations computing infrastructure. Service models of cloud computing can be categorized as Software as a service (SaaS) The software as a service mock up allows providing software application as a service to the users. The software is deployed on the host service and it is accessed through internet. The few examples of SaaS applications are billing and invoicing systems help desk applications, human resources applications and customer relationship management. The end users are not required to manage the software upgrades and patches which is done auto...
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