In this paper, we propose a new, simple, and effective Self-supervised Spatio-temporal Transformers (SPARTAN) approach to Group Activity Recognition (GAR) using unlabeled video data. Given video, create local global views with varying spatial patch sizes frame rates. The proposed self-supervised objective aims match the features of these contrasting representing same be consistent variations in spatiotemporal domains. To best our knowledge, mechanism is one first works alleviate weakly...

Home automation and environmental control is a key ingredient of smart homes. While systems for home exist, there are few that interact with individuals suffering from paralysis, paresis, weakness limited range motion common sequels resulting severe injuries such as stroke, brain injury, spinal cord injury many chronic (guillian barre syndrome) degenerative (amyotrophic lateral sclerosis) conditions. To address this problem, we present the design, implementation, evaluation Inviz, low-cost...

Quadriplegia and paraplegia are disabilities that result from injuries to the spinal cord neuromuscular disorders such as cerebral palsy. Patients suffering quadriplegia have varied levels of impaired motor movements, hence, performing quotidian tasks like controlling home appliances is challenging for quadriplegics. The use hand eye gestures perform these a plausible remedy, but available solutions often assume considerable limb movement, not fit long-term use, may be applicable...

Quantum computing-specifically Shor's algorithm [1]-presents an existential threat to some standard cryptographic algorithms. In preparation, post-quantum cryptography (PQC) algorithms have been in development and are nearing mathematical cryptanalytic maturity. Standardization efforts through the National Institute of Standards Technology (NIST) PQC standardization process chosen one PKE/KEM (i.e., CRYSTALS-Kyber) three digital signature CRYSTALS-Dilithium, Falcon, SPHINCS+). CRYSTALS-Kyber...

This paper introduces a novel approach to Social Group Activity Recognition (SoGAR) using Self-supervised Transformers network that can effectively utilize unlabeled video data. To extract spatio-temporal information, we created local and global views with varying frame rates. Our self-supervised objective ensures features extracted from contrasting of the same were consistent across domains. proposed is efficient in transformer-based encoders alleviate weakly supervised setting group...

Upper extremity mobility impairment is a common sequel of Spinal Cord Injury (SCI), brain injury, strokes, and degenerative diseases such as Guillain-Barre ALS. Existing assistive technology solutions that provide access user input devices are intrusive expensive, require physical contact can have deleterious effects skin friction injury for paralyzed users who reduced sensitivity. To address this problem, in paper, we present the design, implementation, evaluation non-contact proximity...

Safe Community Awareness and Alerting Network (SCALE) is a community government/academic/industry partnership effort that aims to deploy, actuate evaluate techniques support multiple heterogeneous IoT technologies in real world communities. SCALE2, an extension of SCALE, engages multi-tier multi-network approach drive data flow from devices the cloud platforms. While are used gather data, most analytics executed cloud. Managing utilizing these networks, big challenge calls for integrated...

In this work, we recover the private key material of FrodoKEM exchange mechanism as submitted to NIST Post Quantum Cryptography (PQC) standardization process.

Recent efforts to integrate Internet Of Things (IoT) technologies into Smart City constructs have proven successful through proof-of-concept deployments in multiple cities. To facilitate additional deployments, standardization and dissemination of best practices for these is critical. that effort, this work seeks establish a framework set IoT hardware, software, wireless radio components are flexible address several use cases easily replicable new deployments. Moreover, the aims be...

Individuals with mobility impairments represent a large portion of the population. These are often sequels strokes, spinal cord injury, or diseases, such as amyotrophic lateral sclerosis and Guillain-Barré syndrome. Many these diagnoses manifest in upper-extremity impairment, which may prohibit make difficult actuating devices within home. While solutions exist for smart-home automation control, few approachable by those impairments. To address this issue, we designed Inviz, touchless...

Upper-Extremity motor impairment affects millions of Americans due to cerebrovascular incidents, spinal cord injuries, or brain trauma. Current therapy practices used assist these individuals in regaining functionality often require extensive time at rehabilitation facilities with potentially prohibitive travel financial costs. This work presents a mobile low-cost field programmable gate array (FPGA)-smart system that can be home environments. The prototype is table instrumented capacitive...

Purpose: We investigate the enhancement in terahertz (THz) images of freshly excised breast tumors upon treatment with an optical clearance agent. The hyperspectral imaging and spectral classifications are used to quantitatively demonstrate image enhancement. Glycerol solution 60% concentration is applied tumor specimens for various time durations effectiveness on Approach: THz reflection spectroscopy utilized obtain absorption coefficient index refraction untreated glycerol-treated tissues...

Introduction This paper explores the feasibility of using touchless textile sensors as an input to environmental control for individuals with upper-extremity mobility impairments. These are capacitive embedded into clothing and act proximity sensors. Methods We present results from five spinal cord injury they perform gestures that mimic alphanumeric gesture set. The used controlling appliances in a home setting. Our setup included custom visualization provides feedback individual on how...

The pervasive instrumentation of the physical world with sensors and actuators provides an unprecedented level information granularity that is useful in decision-making processes. As municipalities public sector at large begin to leverage Internet Things (IoT) for civic solutions, there exist greater necessity impetus maintain a certain standardization platform data architecture. Ideally, these standards should be place well ahead legislation which encourages adoption. For this reason, it...

This work presents a prototype of an FPGA-based hand motion recognition system using capacitive sensor array (CSA). The is being developed as tool to evaluate upper-limb motor skills for assistive or rehabilitative applications. A light-weight gesture segmentation algorithm was that uses summation and moving average filtering quantized sensing data segment motions. time-series motions are then recognized through recurrent classifier based on long short-term memory (LSTM) neural networks....

This demonstration presents Inviz, a low-cost gesture recognition system that uses flexible textile-based capacitive sensors. Gestures are recognized using proximity-based movement detection sensor arrays can be built into the environment or placed on to body integrated clothing. Inviz provides an innovative interface home automation systems simplify environmental control for individuals with limited-mobility resulting from paralysis, paresis, and degenerative diseases. Proximity-based...

This paper proposes a rehabilitation assitant system equipped with capacitor sensor array (CSA) for persons exhibiting upper-extremity motor impairments. The CSA utilizes mutual capacitance to quantize patients' hand motions on activity board. board is an accelerometer detect the slope of board, since different inclinations may affect quality post trauma. A microcontroller - Texas Instruments MSP430FR2633 used measure capacitance. secondary ATmega 328P Arduino firmware retrieve capacitive...

This work presents a mobile FPGA-smart rehabilitation system that can be used at home. The prototype is table instrumented with capacitive sensor array (CSA) to track the upper-extremity motions of user through proximity or touch. In addition, inertial measurement units (IMUs) are placed on affected upper limb and combined CSA data our fusion signal processing architecture. Motions classified evaluated using multi-task convolutional recurrent neural networks. achieves real-time execution...

Semantic Artificial Intelligence possesses attributes that are particularly beneficial for deep learning tasks in medical imaging. By infusing semantic context into the fundamental classification process, richness of data images can be enhanced, leading to a potential increase reliability outcomes. In this research, we explore use AI distinguishing different tissue types within breast tumors have been excised and imaged using pulsed terahertz (THz) technology, which is cutting-edge method...