Miracle-dz/UniFAR-FTUs huggingface dataset:
Cervical Proprioception Assessed through Targeted Head Repositioning: Validation of a Clinical Test Based on Optoelectronic Measures

Neck proprioception is commonly assessed with head repositioning tests. In such a test, an operator rotates the head of a blindfolded individual to a target position. After returning to the rest position, the participant actively repositions the head to the target. Joint Position Error (JPE) is the angular difference between the target angle (however oriented in a 3D space) and the actively reached positions (the smaller the difference, the better the proprioception). This study aimed to validate a head-to-target (HTT) repositioning test using an optoelectronic system for also measuring the components of the JPE in the horizontal, frontal, and sagittal planes. The head movements requested by the operator consisted of 30° left-right rotations and 25° flexion-extension. The operators or subjects could not obtain these movements without modest rotations in other planes. Two operators were involved. Twenty-six healthy participants (13 women) were recruited (mean (SD): 33.4 (6.3) years). The subjects’ JPE in the requested (intended) plane of motion (JPEint-component) was a few degrees only and smaller for flexion-extensions than for left-right rotations (right rotation: 5.39° (5.29°); left rotation: 5.03° (4.51°), extension: 1.79° (3.94°); flexion: 0.54° (4.35°)). Participants’ average error in unintended planes was around 1° or less. Inter-operator consistency and agreement were high. The smallest detectable change, at p < 0.05, for JPEint-component ranged between 4.5° and 6.98°. This method of optoelectronic measurement in HTT repositioning tests provides results with good metric properties, fostering application to clinical studies.
The Simulation Research of IR Decoy Countermeasure to the IR Missile Trace

The model of the movement and the radiation of the IR countermeasure decoy and the model of the movement of the target craft and the infrared missile are set up;The equivalent radiation energy centre of the target craft and the infrared missile is studied.When the infrared missile is tracking the equivalent radiation energy centre,the normal trace of the infrared missile tracking target craft and the countermeasure trace of the infrared missile from the infrared countermeasure decoy are simulated.
Information and Communication Technology Based Integrated Care for Older Adults: A Scoping Review

Background: Integrated care is an important initiative to respond positively to the ageing of society and information and communication technology(ICT) plays an important role in facilitating the integration of functional and normative health and social care. The scoping review aims to synthesize evidence on the experience and practice of ICT-based implementation of integrated care for older adults. Methods: This study followed the research framework developed by Arksey and O’malley for the scoping review and systematically searched for relevant studies published between 1 January 2000 and 30 March 2022 from nine electronic databases, three specialist journals, three key institutional websites, 11 integrated care project websites, google scholar and references of the studies to be included. Two reviewers independently screened and extracted data and used thematic analysis to sort out and summarize the core elements, hindrances and facilitators of ICT-based integrated care. Results: A total of 77 studies were included in this study, including 36 ICT-based practice models of integrated care with seven core elements of implementation including single entry point, comprehensive geriatric assessment, personalized care planning, multidisciplinary case conferences, coordinated care, case management and patient empowerment, which generally had a positive effect on improving quality of life, caregiver burden and primary care resource utilization for older adults, but effectiveness evaluations remained Heterogeneity exists. The barriers and facilitators to ICT-based implementation of integrated care were grouped into four themes: demand-side factors, provider factors, technology factors and system factors. Conclusion: The implementation of ICT-based integrated care for the elderly is expected to improve the health status of both the supply and demand of services, but there is still a need to strengthen the supply of human resources, team training and collaboration, ICT systems and financial support in order to promote the wider use of ICT in integrated care.
Participatory music making with people living with dementia

Disciplinary background A. Background in music psychology: The potential therapeutic effects of music are wide ranging (MacDonald et al., 2012). Music has been shown to stimulate the brain (Trimble & Hesdorffer, 2017), promote social connections, and provide a channel for communicating emotions and intentions, and expressing individual identity (Hargreaves et al., 2017). Disciplinary background B. Background in healthcare: People living with dementia can experience behavioural and psychological symptoms, often resulting in a lower quality of life for themselves and their caregivers (Cerejeira et al., 2012). In recent years there has been increased interest in music-based interventions that could alleviate some of these symptoms and improve quality of life. Abstract The main aim of my talk is to give an introduction to my research, which explores the experiences and perspectives of experienced music therapists and community musicians who engage in participatory music practices with people living with dementia. Through my research I aim to bring about a deeper understanding of the benefits of active participation in music for people living with dementia, and also shed light on the challenges and rewards it can bring for the community musicians and music therapists who work with them. Music has
SAKS: Sampling Adaptive Kernels From Subspace for Point Cloud Graph Convolution

Convolution on 3D point clouds has been extensively explored in geometric deep learning, but it is far from perfect. Convolution operations on point clouds with the fixed kernel indistinguishably capture correspondences between feature pairs, thereby raising an inherent drawback of limited distinctive feature learning. This paper proposes a novel approach to Sampling Adaptive Kernels from Subspace (SAKS) for graph convolution. It adaptively constructs convolution kernels for different feature correspondences according to the unique coordinate representations under the learned subspace. Associating the subspace design with the deep network is a novel concept, providing different viewpoints on feature learning. Specifically, incomplete orthogonal bases are learned at each convolution layer to span a linear subspace in an elaborately designed manner. Subsequently, adaptive kernels are sampled from the learned subspace via unique coordinates parameterized by feature pairs. Unlike existing adaptive convolution methods in a bruteforce manner, the low-rank property of the subspace reduces the computational complexity of this method. Moreover, we theoretically prove that the proposed SAKS derives the principal components of the kernel distribution, which is similar to principal component analysis under some prior assumptions. Extensive experimental results on point cloud classification and segmentation tasks show that SAKS outperforms state-of-the-arts on various benchmark datasets.
Semi-Analytical Finite-Element Analysis for Free and Forced Wave Propagation Using COMSOL and LiveLink for Matlab

The Semi-Analytical Finite-Element (SAFE) method represents one of the most established numerical approaches for predicting the propagation of elastic waves in one-dimensional structures of arbitrary cross-sections. Its implementation in the commercial finite-element software COMSOL Multiphysics has been proposed in recent years; however, it is limited to only the free wave propagation for computing dispersion curves. To overcome this limitation, this paper proposes an extension of this approach that combines COMSOL and its Livelink for Matlab tool. This enables the extraction from COMSOL of the assembled mass and stiffness SAFE matrices to solve problems of both free and forced wave propagation in the Matlab environment. The resulting customised software takes advantage of both the potential of commercial FE software and the power of Matlab without worrying about compatibility issues. A model of a simply supported plate strip and that of a more complex geometry are implemented to validate, respectively, the SAFE matrix extraction procedure and the implemented forced response formulation. The results agree well with corresponding analytical and numerical results validating the proposed implementation of the SAFE method.
Optimized Novel DC to DC Converter for PV Fed Grid Tied EV Charging Station

The use of Electric Vehicles (EVs) has been increasing in a wider range owing to the increase in population and energy demand.Nowadays, the Solar, which is one of the RES (Renewable Energy sources),assists in EV charging and is gaining higher importance. Moreover, the main function involved in an EV system is the battery charging, and many different types of issues like battery life time, interruptible power supply and poor energy management occur in conventional types of charging. Hence, in the proposed paper, a novel EV charging station is introduced and it involves an optimized DC-DC Bi-directional Boost-Zeta converter. In this work, the EV battery attains energy directly from the PV panel and the additional energy produced by PV is transferred to the grid. The proposed converter functions in boost mode and aids in improving the PV output; the resulting DC-link voltage is regulated and maintained constant using an optimization algorithm known as Firefly Algorithm (FFA). Further, through a single phase VSI, the DC link voltage is given to the grid. In order to attain grid synchronization, a PI controller is employed. Whenever, there is less sunshine, the energy from the grid is fed to the EV battery, thereby supplies continuous power to the EV, even in the absence of solar energy and during this condition, the DC-DC converter functions in Zeta mode. Then, for analysing the performance of the proposed work, it is implemented in MATLAB/Simulink and from an analysis, it is identified that the proposed EV charging station possess a less THD of 3.1%, better switching losses and reactive power compensation.
Efficient and Accurate Cloud-Assisted Medical Pre-Diagnosis With Privacy Preservation

The emergence of cloud computing enables various healthcare institutions to outsource pre-diagnostic models and provide timely and convenient services for patients. However, healthcare institutions and patients have serious concerns about potential privacy leakage as cloud servers cannot be fully trusted. In this paper, a privacy-preserving cloud-assisted medical pre-diagnosis scheme, named NAIAD, is proposed, where patients can securely query the outsourced model and obtain their pre-diagnostic results. Specifically, the pre-diagnostic model is constructed on <inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="huang-ieq1-3263974.gif"/></alternatives></inline-formula>-Nearest Neighbor (<inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="huang-ieq2-3263974.gif"/></alternatives></inline-formula>NN), and Mahalanobis Distance (MD) is chosen as the similarity metric to achieve high accuracy. Accordingly, a secure MD-based comparison method (SMDC) is designed based on a matrix encryption technique. The method is a basic module of NAIAD that enables cloud servers to compare encrypted medical records and achieve privacy-preserving <inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="huang-ieq3-3263974.gif"/></alternatives></inline-formula>NN-based pre-diagnosis with linear complexity. To further improve the computational efficiency, medical records are first clustered and encrypted to construct a hierarchical index tree, then patients can query the tree to speed up the query process. Detailed security analysis indicates NAIAD can resist closeness-same-pattern chosen-plaintext attack, and extensive experiments on real-world and synthetic databases demonstrate NAIAD has high query efficiency and pre-diagnosis accuracy.
Classification of Chromosomes to Diagnose Chromosomal Abnormalities using CNN

Karyotyping is a crucial screening test for genetic illnesses. However, as it is currently practiced, it requires considerable manual effort and experience to interpret results, which renders it time-consuming and costly. Automating karyotyping is important and popular, as it allows for less time-intensive procedures. It can also be used to help classify chromosomes into 23 types. ConvNet (Convolutional NN) based deep structured learning was employed to classify 10304 chromosome images, with trained and tested datasets containing 4830 chromosomes. The method we propose is accurate 92.5 percent of the time, the approach outlined by the study's authors fared better than other approaches reported in the literature. We created a statistic called “percentage of well classified karyotypes” to examine how useful our technology is to medical professionals. When tested on this metric, we achieved an accuracy of 91.3 percent, indicating that our modelwill be used by doctors are in genetic diagnosis.
Machine Learning Applied to Speech Emotion Analysis for Depression Recognition

Depression is a psychiatric condition that can have an impact on a person’s emotional and physical health. Untreated depression can make it difficult for a person to go about their everyday lives and trigger a variety of other symptoms. The only available diagnostic techniques today are therapeutic interventions. As a result, this system is suggested to help with clinical management decisions throughout therapy as well as early detection of depression. As machine learning technology advances, more intelligent systems will soon be usable in daily life. Intelligent systems are interactive, operate with little human effort, and rely mostly on voice input.Hence based on the speech input given, a new computational methodology for detecting various emotions and depression is proposed. Audio samples from the DAIC-WOZ dataset and the RAVDESS dataset were used to create the dataset for depression-related data. Speech signal is exposed to a feature extraction process. Speech corpus is classified using long short-term memory (LSTM) algorithm and its performance is compared with conventionally used Support Vector Machine (SVM). Preliminary result indicates whether individual is depressed or not depressed.
Qualitative analysis of a ratio-dependent predator–prey system with diffusion

Ratio-dependent predator–prey models are favoured by many animal ecologists recently as they better describe predator–prey interactions where predation involves a searching process. When densities of prey and predator are spatially homogeneous, the so-called Michaelis–Menten ratio-dependent predator–prey system, which is an ordinary differential system, has been studied by many authors. The present paper deals with the case where densities of prey and predator are spatially inhomogeneous in a bounded domain subject to the homogeneous Neumann boundary condition. Its main purpose is to study qualitative properties of solutions to this reaction-diffusion (partial differential) system. In particular, we will show that even though the unique positive constant steady state is globally asymptotically stable for the ordinary-differential-equation dynamics, non-constant positive steady states exist for the partial-differential-equation model. This demonstrates that stationary patterns arise as a result of diffusion.
Arbiter PUF—A Review of Design, Composition, and Security Aspects

Hardware security modules play a crucial role in protecting and preserving technologically integrated systems that are used in daily life. They employ cryptographic protocols to secure a system against adversaries. Generally, cryptographic algorithms and security keys are quintessential for maintaining the security of a system. Cryptography uses a secret key to encipher and decipher the data. These secret keys are stored in a non-volatile memory that attackers can easily access. The hardware security primitive, Physical Unclonable Function (PUF) is a promising alternative for enhancing the security of interconnected devices. A PUF produces an output in response to an input based on the physical structure and intrinsic manufacturing variations of an integrated circuit (IC). The generated random response being unpredictable, act as a robust secret key in cryptographic protocols. The first silicon PUF is the Arbiter PUF, which can instantly produce significantly more secret keys based on the input with a lightweight design. Due to its advantage, it is best suited for device authentication in resource-constrained applications employing the Internet of Things (IoT). The PUF is also suitable for applications such as the Internet of Vehicles, the Internet of Medical Things, RFID (radio frequency identification) tags, and smart cards. In this paper, the basic Arbiter PUF design is implemented in ZedBoard to analyze the PUF performance characteristics for 16, 32, and 64-bit responses. A review of Arbiter PUF design, different compositions of Arbiter PUF, their individual characteristics, and vulnerabilities against machine-learning attacks have been presented at their broader best in this paper.
Flowfield Produced by a Vortex Ring Near a Plane Wall

Experimental studies were carried out on the flowfield produced by a vortex ring approaching a plane wall perpendicular to its axis of symmetry, using smoke visualization technique. The mechanism of rebound of a vortex ring from the wall is shown to be related to generation of a shear layer separated from the wall and its subsequent development. The effects of Reynolds numbers on the trajectory of the core center of a vortex ring were also examined. Growth of the separated shear layer and generation of the secondary vortex ring due to vorticity concentration in the separated shear layer were visualized in detail.
Attitude Toward Telerehabilitation Among Physical and Occupational Therapists in Korea: A Brief Descriptive Report

The attitude toward telerehabilitation (TR) among therapists (191 physical therapists and 159 occupational therapists) in Korea was surveyed. The survey consisted of 15 questions in the following 8 domains: awareness(AW), attitude (AT), perceived usefulness (PU), perceived behavioral control (PBC), self-efficacy (SE), facilitating conditions (FC), barriers (B), and behavioral intention (BI). Therapists with experience in TR responded with higher scores in all domains except B, regardless of their specialty. The most perceived barriers to TR were unmatched insurance fees and a lack of technical support. Experience with TR was a major factor in attitude and behavior intention toward TR.
AUTOMATIC IMAGE SEGMENTATION BASED ON DEFOR MABLE MODELS AND PIXEL AFFINITY STATISTIC

A general purpose automatic image segmentation scheme that integrates deformable models and region statistics was proposed. By using a combination of image cues including intensity, gradient, color, and texture rather a single source of information such as gradient magnitude, and gradient vector flow(GVF) Snakes technology, this scheme is able to automatically segment objects of an unknown number and unknown locations in images. For reasonable segmentation results, affine cell decomposition (ACD) technology was employed to automatically merge models corresponding to the same object, while split models corresponding to different objects. Experiments on synthetic images with low signal to noise ratio images and nature images show good performmance and robust of the approach, especially it’s capable to capture the discontinuous boundary and move snakes into boundary concavities.
Neglected bilateral geno valgum deformity managed with a dynamic compression plate and the ilizarov construct: a case report

Introduction: Deformities of the lower limb are common in childhood; however, they are mainly variations of the natural growth pattern. The rare case showed up late with a genu valgum deformity centered on both tibias and a closed physis. Case presentation: A 20-year-old male has suffered from bilateral knee pain and genu valgum deformity centered at both tibias with a closed physis. Management was challenging, requiring multiple surgeries and high patient cooperation. The patient underwent two surgeries: a right-sided osteotomy and Ilizarov fixation with gradual deformity correction. In the second operation, a proximal tibia osteotomy of the left side was executed with acute correction of the deformity and open reduction and internal fixation of the tibia with a medial tibial dynamic compression plate. Ultimately, the authors successfully corrected both leg deformities. Conclusion: This results reflect the efficacy of dynamic compression plates and Ilizarov for correcting genu valgum deformity in patients with closed epiphyseal plates.
A Wide-Dynamic Range (-40 °C to 180 °C) Active Wireless MEMS Temperature Sensor With 7m °C Sensitivity

We demonstrate a highly accurate active wireless microelectromechanical systems (MEMS) temperature sensor with the largest reported dynamic range (–40 °C to 180 °C) among active MEMS temperature sensors. The sensor uses a 27.2-MHz high quality factor ( ${Q} >$ 3200) aluminum nitride-on-silicon (AlN-on-Si) thin-film piezoelectric-on-silicon (TPoS) MEMS resonator to enable highly accurate temperature sensing, with minimum sensitivity ( ${S}$ ), better than 0.011 °C across this wide temperature range. The wireless sensor uses an innovative frequency shift keying (FSK) 900-MHz direct upconversion transmitter. The transmitter uses frequency multipliers for upconversion, obviating the need for a temperature-stable frequency reference clock, thereby preserving the temperature coefficient of frequency (TCF) of the resonator and, consequently, the sensitivity of the sensor. The experimental results show a very high correlation (< 0.03% error) between the TCF of the MEMS oscillator and that of the transmitter output signal, demonstrating the viability of the proposed direct upconversion technique. A detailed analysis of the Allan variance for MEMS temperature sensors, which can be used to design for a given minimum sensitivity, is also presented in this article.
Study on Target Model Update Method in Mean Shift Algorithm

Mean shift is a robust and real-time pattern matching algorithm.At present,the total model update strategy of the mean shift algorithm still has shortage under changed scenes,e.g.,target appearance changes,non-target occlusion.Therefore,the paper presents a selective sub-model update strategy for the mean shift algorithm.The proposed method treats each sub-model of target model as singleton,selects and updates sub-model and its weight based on match contributing degree of each sub-model in the current frame.The experiment result shows the proposed method is more robust and effective than the total model update strategy.