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Topic Review
Biography
Topic Review
Artificial Intelligence in Cancer Research
Integration of artificial intelligence (AI) into cancer research is currently addressing many of the challenges where medical experts fail to bring cancer to control and cure, and the outcomes are quite encouraging. AI offers many tools and platforms to facilitate more understanding and tackling of this life-threatening disease. AI-based systems can help pathologists in diagnosing cancer more accurately and consistently, reducing the case error rates. Predictive-AI models can estimate the likelihood for a person to get cancer by identifying the risk factors. Big data, together with AI, can enable medical experts to develop customized treatments for cancer patients. The side effects from this kind of customized therapy will be less severe in comparison with the generalized therapies.
643
09 Dec 2022
Topic Review
Windows 10 Version History (Version 2004)
The Windows 10 May 2020 Update (also known as version 2004 and codenamed "20H1") is the ninth major update to Windows 10. It carries the build number 10.0.19041.
642
17 Oct 2022
Topic Review
Update on Cyber Health Psychology
In recent years, there has been more and more talk of cyber health psychology and the implication that new technologies can have in the diagnosis, treatment, and rehabilitation of psychopathological issues in the field of mental health, ranging from post-traumatic stress disorder (PTSD) to addiction to substances of abuse.
642
25 Mar 2022
Topic Review
Community-Specific Overview of Knowledge Graph Research
Knowledge graphs (KGs) have rapidly emerged as an important area in AI over the last ten years. Building on a storied tradition of graphs in the AI community, a KG may be simply defined as a directed, labeled, multi-relational graph with some form of semantics. In part, this has been fueled by increased publication of structured datasets on the Web, and well-publicized successes of large-scale projects such as the Google Knowledge Graph and the Amazon Product Graph. However, another factor that is less discussed, but which has been equally instrumental in the success of KGs, is the cross-disciplinary nature of academic KG research. Arguably, because of the diversity of this research, a synthesis of how different KG research strands all tie together could serve a useful role in enabling more ‘moonshot’ research and large-scale collaborations.
642
01 Apr 2022
Topic Review
Time-Series Forecasting Models
The time-series forecasting method is a suitable pricing solution for Digital Signage Advertising (DSA), as it improves the pricing decision by modeling the changes in the environmental factors and audience attention level toward signage for optimal pricing. However, it is difficult to determine an optimal price forecasting model for DSA with the increasing number of available time-series forecasting models in recent years. Based on the 84 research articles reviewed, the data characteristics analysis in terms of linearity, stationarity, volatility, and dataset size is helpful in determining the optimal model for time-series price forecasting.
641
03 Nov 2021
Topic Review
The Crossroads of Computer Science and Physics
The intersection of computer science and physics has opened up exciting new opportunities for research and innovation. The principles of physics have inspired the development of new computational models, and the ability to simulate complex physical systems using computer algorithms has been a critical tool for physicists to test their theories and hypotheses. Conversely, computer science has also had a significant impact on physics, providing tools and techniques for simulations and data analysis that have enabled physicists to explore complex physical systems. Machine learning and AI techniques are also increasingly being used to tackle some of the most challenging problems in physics. Despite the many potential benefits of interdisciplinary research between computer science and physics, there are also significant challenges that must be addressed. The synergy between these two fields and how interdisciplinary research is shaping their future was described. The research discusses the challenges and opportunities of interdisciplinary research, future directions for research, and the countries and scientists at the forefront of this field. By addressing the challenges of interdisciplinary research, researchers can unlock the full potential of interdisciplinary research and shape the future of both computer science and physics.
641
22 May 2023
Topic Review
Deep Anomaly Detection for In-Vehicle Monitoring
Deep learning approaches to the detection of visual data instances that markedly digress from regular sequences have been mostly focusing on outdoor video-surveillance scenarios, mainly regarding abnormal behaviour and suspicious or abandoned object detection. However, with the increasing importance of public and shared transportation for urban mobility, it becomes imperative to provide autonomous intelligent systems capable of detecting abnormal behaviour that threatens passenger safety. In-vehicle monitoring becomes particularly relevant for Shared Autonomous Vehicles, which do not have a driver responsible for assuring the well-being and safety of passengers; such vehicles must be accompanied by reliable autonomous in-vehicle surveillance systems.
641
17 Oct 2022
Topic Review
Dengue Detection
The dengue virus (DENV) is a vector-borne flavivirus that infects around 390 million individuals each year with 2.5 billion being in danger. Having access to testing is paramount in preventing future infections and receiving adequate treatment. Currently, there are numerous conventional methods for DENV testing, such as NS1 based antigen testing, IgM/IgG antibody testing, and Polymerase Chain Reaction (PCR).
640
05 Jul 2021
Topic Review
Compression of Neural Networks
Researchers propose the value-locality-based compression (VELCRO) algorithm for neural networks. VELCRO is a method to compress general-purpose neural networks that are deployed for a small subset of focused specialized tasks.
640
08 Nov 2021
Topic Review
RTP Audio Video Profile
The RTP audio/video profile (RTP/AVP) is a profile for Real-time Transport Protocol (RTP) that specifies the technical parameters of audio and video streams. RTP specifies a general-purpose data format, but doesn't specify how encoded data should utilize the features of RTP (what payload type value to put in the RTP header, what sampling rate and clock rate [the rate at which the RTP timestamp increments] to use, etc.). An RTP profile specifies these details. The RTP audio/video profile specifies a mapping of specific audio and video codecs and their sampling rates to RTP payload types and clock rates, and how to encode each data format as an RTP data payload, as well as specifying how to describe these mappings using Session Description Protocol (SDP).
640
21 Oct 2022
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