scholarly journals Neuromorphic Devices for Bionic Sensing and Perception

2021 ◽  
Vol 15 ◽  
Author(s):  
Mingyue Zeng ◽  
Yongli He ◽  
Chenxi Zhang ◽  
Qing Wan
Keyword(s):  
Artificial Intelligence ◽  
Real Time ◽  
Neural Systems ◽  
Biological Sensing ◽  
Neuromorphic Engineering ◽  
Personal Healthcare ◽  
Human Machine Interfaces ◽  
Challenges And Opportunities ◽  
Healthcare Monitoring ◽  
Made In

Neuromorphic devices that can emulate the bionic sensory and perceptual functions of neural systems have great applications in personal healthcare monitoring, neuro-prosthetics, and human–machine interfaces. In order to realize bionic sensing and perception, it’s crucial to prepare neuromorphic devices with the function of perceiving environment in real-time. Up to now, lots of efforts have been made in the incorporation of the bio-inspired sensing and neuromorphic engineering in the booming artificial intelligence industry. In this review, we first introduce neuromorphic devices based on diverse materials and mechanisms. Then we summarize the progress made in the emulation of biological sensing and perception systems. Finally, the challenges and opportunities in these fields are also discussed.

4 Brain computer interface for paralysis

2021 ◽  
Vol 92 (8) ◽  
pp. A1.4-A2
Author(s):  
Leigh R Hochberg
Keyword(s):  
Real Time ◽  
Closed Loop ◽  
Assistive Technologies ◽  
Computer Interfaces ◽  
Cord Injury ◽  
Challenges And Opportunities ◽  
Communication Devices ◽  
Intention To Move ◽  
The Brain ◽  
Made In

Intracortically-based Brain-Computer Interfaces (iBCIs) are poised to revolutionize our ability to restore lost neurologic functions. By recording high resolution neural activity from the brain, the intention to move ones hand can be detected and decoded in real- time, potentially providing people with motor neuron disease (ALS), stroke, or spinal cord injury with restored or maintained ability to control communication devices, assistive technologies, and their own limbs. iBCIs also are central to the development of closed-loop neuromodulation systems, with great potential to serve people with neuropsychiatric disorders. A multi-site pilot clinical trial of the investigational BrainGate system is assessing the feasibility of people with tetraplegia controlling a computer cursor and other devices simply by imagining the movement of their own arm or hand. This presentation will review some of the recent progress made in iBCIs, the information that can be decoded from ensembles of cortical or subcortical neurons in real-time, and the challenges and opportunities for restorative neurotechnologies in research and clinical practice.

Smart MM

2019 ◽  
pp. 225-251
Author(s):  
Meenakshi Tripathi ◽  
Saatvik Shah ◽  
Prashant Bahal ◽  
Harsh Sharma ◽  
Ritika Gupta
Keyword(s):  
Artificial Intelligence ◽  
Emotion Recognition ◽  
Real Time ◽  
Management System ◽  
Recommendation System ◽  
Information Gain ◽  
Recognition System ◽  
Media Management ◽  
User Friendly ◽  
Made In

Rapid advancements have been made in the field of artificial intelligence in recent years. This has resulted in its adoption in various technologies from medicine to search engines. Existing media management systems have however not yet fully leveraged the power of artificial intelligence (AI) to give users enhanced information apart from basic media metadata. This chapter proposes a smart movie management system which works majorly offline and uses AI to deliver optimum information to the users on four vital tasks. These tasks are multilevel phrase level review polarity, plot and review keywords, a content-based recommendation system, and an emotion recognition system. The complete system works in near-real time with a user-friendly presentation to maximize a user's information gain.

The Power of Matrix Factorization: Methods for Deconvoluting Genetic Heterogeneous Data at Expression Level

2021 ◽  
Vol 15 (8) ◽  
pp. 841-853
Author(s):  
Yuan Liu ◽  
Zhining Wen ◽  
Menglong Li
Keyword(s):  
Artificial Intelligence ◽  
Matrix Factorization ◽  
In Silico ◽  
Genetic Data ◽  
Heterogeneous Data ◽  
Expression Level ◽  
Mathematical Methods ◽  
Challenges And Opportunities ◽  
Factorization Methods ◽  
Genetic Profiles

Background:: The utilization of genetic data to investigate biological problems has recently become a vital approach. However, it is undeniable that the heterogeneity of original samples at the biological level is usually ignored when utilizing genetic data. Different cell-constitutions of a sample could differentiate the expression profile, and set considerable biases for downstream research. Matrix factorization (MF) which originated as a set of mathematical methods, has contributed massively to deconvoluting genetic profiles in silico, especially at the expression level. Objective: With the development of artificial intelligence algorithms and machine learning, the number of computational methods for solving heterogeneous problems is also rapidly abundant. However, a structural view from the angle of using MF to deconvolute genetic data is quite limited. This study was conducted to review the usages of MF methods on heterogeneous problems of genetic data on expression level. Methods: MF methods involved in deconvolution were reviewed according to their individual strengths. The demonstration is presented separately into three sections: application scenarios, method categories and summarization for tools. Specifically, application scenarios defined deconvoluting problem with applying scenarios. Method categories summarized MF algorithms contributed to different scenarios. Summarization for tools listed functions and developed web-servers over the latest decade. Additionally, challenges and opportunities of relative fields are discussed. Results and Conclusion: Based on the investigation, this study aims to present a relatively global picture to assist researchers to achieve a quicker access of deconvoluting genetic data in silico, further to help researchers in selecting suitable MF methods based on the different scenarios.

Mobile to Fuel Explosive Ecommerce Growthin india

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Priya Yadav ◽  
Pranjeet Das ◽  
Ravi Kumar Malhotra
Keyword(s):  
Developing Countries ◽  
Electronic Commerce ◽  
Rapid Development ◽  
Global Markets ◽  
Network Technology ◽  
Mobile Terminals ◽  
Doing Business ◽  
Is Security ◽  
Challenges And Opportunities ◽  
Made In

E-commerce is process of doing business through computer networks. Advances in wireless network technology and the continuously increasing number of users of mobile latter on make an ideal platform for offering various high utilityservices in just a snap of a finger to the mobile users and give pace to the rapid development of E-Commerce in India.E-commerce is considered an excellent alternative for companies to reach new customersbut the fact that has hindered the growth of e-commerce is security. Security is the challenge facing e-commerce today and there is still a lot of advancement made in the field of securityfor increasing the use of e-commerce in developing countries the B2B e-commerce is implemented for improving access to global markets for firms in developing countries. With the special characteristics and constraints of mobile terminals and wireless networks and the context, situations and circumstances that people use their hand-held terminalswhich will ultimately fuel explosive ecommerce growth in India This paper highlights the various key challenges and opportunities which Indian e-commerce industry may face in the upcoming years. And also discuss challenges in electronic commerce transactions.

scholarly journals BattleNet: Capturing Advantageous Battlefield in RTS Games (Student Abstract)

2020 ◽  
Vol 34 (10) ◽  
pp. 13849-13850
Author(s):  
Donghyeon Lee ◽  
Man-Je Kim ◽  
Chang Wook Ahn
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Real Time ◽  
Large Scale ◽  
Outcome Predictor ◽  
Short Term ◽  
Rts Game

In a real-time strategy (RTS) game, StarCraft II, players need to know the consequences before making a decision in combat. We propose a combat outcome predictor which utilizes terrain information as well as squad information. For training the model, we generated a StarCraft II combat dataset by simulating diverse and large-scale combat situations. The overall accuracy of our model was 89.7%. Our predictor can be integrated into the artificial intelligence agent for RTS games as a short-term decision-making module.

scholarly journals A Deterministic Rapid Intensification Aid

2011 ◽  
Vol 26 (4) ◽  
pp. 579-585 ◽  
Author(s):  
Charles R. Sampson ◽  
John Kaplan ◽  
John A. Knaff ◽  
Mark DeMaria ◽  
Chris A. Sisko
Keyword(s):  
Real Time ◽  
Arithmetic Mean ◽  
Forecast Errors ◽  
Rapid Intensification ◽  
Intensity Forecast ◽  
Probability Threshold ◽  
Forecast Time ◽  
National Hurricane Center ◽  
Made In

Abstract Rapid intensification (RI) is difficult to forecast, but some progress has been made in developing probabilistic guidance for predicting these events. One such method is the RI index. The RI index is a probabilistic text product available to National Hurricane Center (NHC) forecasters in real time. The RI index gives the probabilities of three intensification rates [25, 30, and 35 kt (24 h)−1; or 12.9, 15.4, and 18.0 m s−1 (24 h)−1] for the 24-h period commencing at the initial forecast time. In this study the authors attempt to develop a deterministic intensity forecast aid from the RI index and, then, implement it as part of a consensus intensity forecast (arithmetic mean of several deterministic intensity forecasts used in operations) that has been shown to generally have lower mean forecast errors than any of its members. The RI aid is constructed using the highest available RI index intensification rate available for probabilities at or above a given probability (i.e., a probability threshold). Results indicate that the higher the probability threshold is, the better the RI aid performs. The RI aid appears to outperform the consensus aids at about the 50% probability threshold. The RI aid also improves forecast errors of operational consensus aids starting with a probability threshold of 30% and reduces negative biases in the forecasts. The authors suggest a 40% threshold for producing the RI aid initially. The 40% threshold is available for approximately 8% of all verifying forecasts, produces approximately 4% reduction in mean forecast errors for the intensity consensus aids, and corrects the negative biases by approximately 15%–20%. In operations, the threshold could be moved up to maximize gains in skill (reducing availability) or moved down to maximize availability (reducing gains in skill).

scholarly journals Smart Wearable Sensors Based on Triboelectric Nanogenerator for Personal Healthcare Monitoring

Micromachines ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 352
Author(s):  
Ruonan Li ◽  
Xuelian Wei ◽  
Jiahui Xu ◽  
Junhuan Chen ◽  
Bin Li ◽  
...  
Keyword(s):  
Medical Care ◽  
Health Monitoring ◽  
Wearable Sensors ◽  
The Elderly ◽  
The Body ◽  
Assessment System ◽  
Triboelectric Nanogenerator ◽  
Personal Healthcare ◽  
Healthcare Monitoring ◽  
Smart Wearable

Accurate monitoring of motion and sleep states is critical for human health assessment, especially for a healthy life, early diagnosis of diseases, and medical care. In this work, a smart wearable sensor (SWS) based on a dual-channel triboelectric nanogenerator was presented for a real-time health monitoring system. The SWS can be worn on wrists, ankles, shoes, or other parts of the body and cloth, converting mechanical triggers into electrical output. By analyzing these signals, the SWS can precisely and constantly monitor and distinguish various motion states, including stepping, walking, running, and jumping. Based on the SWS, a fall-down alarm system and a sleep quality assessment system were constructed to provide personal healthcare monitoring and alert family members or doctors via communication devices. It is important for the healthy growth of the young and special patient groups, as well as for the health monitoring and medical care of the elderly and recovered patients. This work aimed to broaden the paths for remote biological movement status analysis and provide diversified perspectives for true-time and long-term health monitoring, simultaneously.

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