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Recent Developments and Limitations in Recommender Systems: A Review 2022

Recommender systems are an indispensable and inseparable part of everyday online content offerings like music, movies, sports, and e-commerce. They help users by personalizing products, services, and content, cutting the time and effort required to browse through large amounts of online information. Despite the evolution of recommender systems, the extent to which they can be explored and extended is yet to be discovered. This paper conducts an extensive review of recent developments in recommender systems and presents a comprehensive analysis, highlighting their approaches and limitations. Based on the findings of the analysis, recommendations are provided on possible research avenues that look promising to investigate further. The primary objective of this study is to provide an entry point for researchers who intend to address the current limitations of recommender systems and develop new strategies. Based on the recent breakthroughs in recommender systems detailed in this study, it is possible to find various prospective research avenues, not limited to novel recommender systems but also new evaluation mechanisms and security measures.

Functional Brain Connectivity in Resting-State FMRI Analysis Using Machine Learning Algorithms: A Review 2023

Anatomically and functionally different brain regions in the human brain are identified in brain network analysis. Using magnetic resonance imaging, the fMRI indirectly measures variations in blood flow to infer brain activity (MRI). The sub-modality of fMRI known as resting-state fMRI (rs-fMRI) is an effective tool for assessing regional interactions that take place while a subject is not at rest. Dynamic functional connectivity (DFC) reveals the functional interaction between brain areas and the alterations that take place quickly. In order to estimate DFCs in rs-fMRI data, the first step was to determine the optimal window length and stride to use with the sliding window technique. After determining the proper window length and stride, the next step was to generate features using the sliding window technique. Due to the high dimensionality of the generated features, which were presented as column-wise data, the feature selection and dimensional reduction process was used as the next step to learn the discriminating features and reduce the dimensions. The final output of the data preprocessing phase is a dataset with 54 rows representing subjects in the CM&N dataset and h columns representing discriminating features. The number of columns h can vary based on the method of feature selection employed. Due to the fact that multiple feature selection techniques were tested in the data pre-processing section, 9 different feature selections were available for training the learning models. 11 distinct learning algorithms were utilized in the classification process. In 10-fold cross-validation, our implemented classification model achieved 96.33% accuracy. Using only rs-fMRI data on chess players, previous research achieved a maximum accuracy of 85.45%. This represents a significant improvement of 10.88% in accuracy. In addition, this represents an 8.33% improvement in accuracy compared to the 88% accuracy achieved by a method that combined rs-fMRI data with T1-weighted MRI data. By using only rs-fMRI data in our study, we were able to improve accuracy

Method and apparatus for consistent and highly available data storage using local and fabric attached non-volatile memory storage devices: A Review 2022

A server computer is configured to write a first copy of a block of data to a first namespace on a first non-volatile memory-based cache drive and a second copy of the block of data to a RAID controller for de-staging of the data to hard disk drives of a RAID array. Acknowledgment of hardening of the data on the hard disk drives initiates purging of the first copy of the block of data from the cache drive. High availability is enabled by writing a third copy of the block of data to a second server to store the block of data in a second namespace on a second non-volatile memory-based cache drive. Restoring of data after power loss accesses the data on the first non-volatile memory-based cache drive.

Integrated storage/processing devices, systems and methods for performing big data analytics: A Review 2015

Architectures and methods for performing big data analytics by providing an integrated storage/processing system containing non-volatile memory devices that form a large, non-volatile memory array and a graphics processing unit (GPU) configured for general purpose (GPGPU) computing. The non-volatile memory array is directly functionally coupled (local) with the GPU and optionally mounted on the same board (on-board) as the GPU.

Methods and apparatus for providing acceleration of virtual machines in virtual environments: A Review 2015

A host server computer system that includes a hypervisor within a virtual space architecture running at least one virtualization, acceleration and management server and at least one virtual machine, at least one virtual disk that is read from and written to by the virtual machine, a cache agent residing in the virtual machine, wherein the cache agent intercepts read or write commands made by the virtual machine to the virtual disk, and a solid state drive. The solid state drive includes a non-volatile memory storage device, a cache device and a memory device driver providing a cache primitives application programming interface to the cache agent and a control interface to the virtualization, acceleration and management server.

Data security and digital rights management system: A Review 2011

A system and method is described for enhancing data security in a broad range of electronic systems through encryption and decryption of addresses in physical memory to which data is written and from which data is read. It can be implemented through software, hardware, firmware or any combination thereof. Implementation in Digital Rights Management execution using the invention reduces cost, enhances performance, and provides additional transactional security.

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