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Journal articles on the topic 'Joint encoding'

Author: Grafiati

Published: 30 November 2024

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1

Chapman, Christian, and Daniel W. Bliss. "Upper Bound on the Joint Entropy of Correlated Sources Encoded by Good Lattices." Entropy 21, no. 10 (September 29, 2019): 957. http://dx.doi.org/10.3390/e21100957.

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Lattices provide useful structure for distributed coding of correlated sources. A common lattice encoder construction is to first round an observed sequence to a `fine’ lattice with dither, then produce the result’s modulo to a `coarse’ lattice as the encoding. However, such encodings may be jointly-dependent. A class of upper bounds is established on the conditional entropy-rates of such encodings when sources are correlated and Gaussian and the lattices involved are a from an asymptotically-well-behaved sequence. These upper bounds guarantee existence of a joint–compression stage which can increase encoder efficiency. The bounds exploit the property that the amount of possible values for one encoding collapses when conditioned on other sufficiently informative encodings. The bounds are applied to the scenario of communicating through a many-help-one network in the presence of strong correlated Gaussian interferers, and such a joint–compression stage is seen to compensate for some of the inefficiency in certain simple encoder designs.

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Elbayad, Maha, Laurent Besacier, and Jakob Verbeek. "Joint source–target encoding with pervasive attention." Machine Translation 35, no. 4 (December 2021): 637–59. http://dx.doi.org/10.1007/s10590-021-09289-7.

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Kondi, L. P., G. Melnikov, and A. K. Katsaggelos. "Joint Optimal Object Shape Estimation and Encoding." IEEE Transactions on Circuits and Systems for Video Technology 14, no. 4 (April 2004): 528–33. http://dx.doi.org/10.1109/tcsvt.2004.825569.

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Rong, Dang, and Feng Gang. "Coordinate-Corrected and Graph-Convolution-Based Hand Pose Estimation Method." Sensors 24, no. 22 (November 14, 2024): 7289. http://dx.doi.org/10.3390/s24227289.

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To address the problem of low accuracy in joint point estimation in hand pose estimation methods due to the self-similarity of fingers and easy self-obscuration of hand joints, a hand pose estimation method based on coordinate correction and graph convolution is proposed. First, the standard coordinate encoding is improved by generating an unbiased heat map, and the distribution-aware method is used for decoding coordinates to reduce the error in decoding the coordinate encoding of joints. Then, the complex dependency relationship between the joints and the relationship between pixels and joints of the hand are modeled by using graph convolution, and the feature information of the hand joints is enhanced by determining the relationship between the hand joints. Finally, the skeletal constraint loss function is used to impose constraints on the joints, and a natural and undistorted hand skeleton structure is generated. Training tests are conducted on the public gesture interaction dataset STB, and the experimental results show that the method in this paper can reduce errors in hand joint point detection and improve the estimation accuracy.

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Rayes, Ramsey K., Rachel N. Mazorow, Leigh A. Mrotek, and Robert A. Scheidt. "Utility and Usability of Two Forms of Supplemental Vibrotactile Kinesthetic Feedback for Enhancing Movement Accuracy and Efficiency in Goal-Directed Reaching." Sensors 23, no. 12 (June 9, 2023): 5455. http://dx.doi.org/10.3390/s23125455.

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Recent advances in wearable sensors and computing have made possible the development of novel sensory augmentation technologies that promise to enhance human motor performance and quality of life in a wide range of applications. We compared the objective utility and subjective user experience for two biologically inspired ways to encode movement-related information into supplemental feedback for the real-time control of goal-directed reaching in healthy, neurologically intact adults. One encoding scheme mimicked visual feedback encoding by converting real-time hand position in a Cartesian frame of reference into supplemental kinesthetic feedback provided by a vibrotactile display attached to the non-moving arm and hand. The other approach mimicked proprioceptive encoding by providing real-time arm joint angle information via the vibrotactile display. We found that both encoding schemes had objective utility in that after a brief training period, both forms of supplemental feedback promoted improved reach accuracy in the absence of concurrent visual feedback over performance levels achieved using proprioception alone. Cartesian encoding promoted greater reductions in target capture errors in the absence of visual feedback (Cartesian: 59% improvement; Joint Angle: 21% improvement). Accuracy gains promoted by both encoding schemes came at a cost in terms of temporal efficiency; target capture times were considerably longer (1.5 s longer) when reaching with supplemental kinesthetic feedback than without. Furthermore, neither encoding scheme yielded movements that were particularly smooth, although movements made with joint angle encoding were smoother than movements with Cartesian encoding. Participant responses on user experience surveys indicate that both encoding schemes were motivating and that both yielded passable user satisfaction scores. However, only Cartesian endpoint encoding was found to have passable usability; participants felt more competent using Cartesian encoding than joint angle encoding. These results are expected to inform future efforts to develop wearable technology to enhance the accuracy and efficiency of goal-directed actions using continuous supplemental kinesthetic feedback.

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Dou Shuaifeng, 窦帅风, 雷鸣 Lei Ming, 沈学举 Shen Xueju, and 林超 Lin Chao. "Joint Fresnel Transform Correlator Based on Phase Encoding." Laser & Optoelectronics Progress 53, no. 12 (2016): 120701. http://dx.doi.org/10.3788/lop53.120701.

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Liu, Chen, Feng Li, Xian Sun, and Hongzhe Han. "Attention-Based Joint Entity Linking with Entity Embedding." Information 10, no. 2 (February 1, 2019): 46. http://dx.doi.org/10.3390/info10020046.

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Entity linking (also called entity disambiguation) aims to map the mentions in a given document to their corresponding entities in a target knowledge base. In order to build a high-quality entity linking system, efforts are made in three parts: Encoding of the entity, encoding of the mention context, and modeling the coherence among mentions. For the encoding of entity, we use long short term memory (LSTM) and a convolutional neural network (CNN) to encode the entity context and entity description, respectively. Then, we design a function to combine all the different entity information aspects, in order to generate unified, dense entity embeddings. For the encoding of mention context, unlike standard attention mechanisms which can only capture important individual words, we introduce a novel, attention mechanism-based LSTM model, which can effectively capture the important text spans around a given mention with a conditional random field (CRF) layer. In addition, we take the coherence among mentions into consideration with a Forward-Backward Algorithm, which is less time-consuming than previous methods. Our experimental results show that our model obtains a competitive, or even better, performance than state-of-the-art models across different datasets.

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Zhu, Dan, Zhuyuan Wang, Shenfei Zong, Hui Chen, Peng Chen, and Yiping Cui. "Wavenumber–intensity joint SERS encoding using silver nanoparticles for tumor cell targeting." RSC Adv. 4, no. 105 (2014): 60936–42. http://dx.doi.org/10.1039/c4ra11522h.

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A new optical encoding approach, the wavenumber–intensity joint surface enhanced Raman scattering (SERS) spectral encoding method, was demonstrated by using silver nanoparticles with a core–shell structure.

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Shin, Jaehun, Wonkee Lee, Byung-Hyun Go, Baikjin Jung, Youngkil Kim, and Jong-Hyeok Lee. "Exploration of Effective Attention Strategies for Neural Automatic Post-editing with Transformer." ACM Transactions on Asian and Low-Resource Language Information Processing 20, no. 6 (November 30, 2021): 1–17. http://dx.doi.org/10.1145/3465383.

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Automatic post-editing (APE) is the study of correcting translation errors in the output of an unknown machine translation (MT) system and has been considered as a method of improving translation quality without any modification to conventional MT systems. Recently, several variants of Transformer that take both the MT output and its corresponding source sentence as inputs have been proposed for APE; and models introducing an additional attention layer into the encoder to jointly encode the MT output with its source sentence recorded a high-rank in the WMT19 APE shared task. We examine the effectiveness of such joint-encoding strategy in a controlled environment and compare four types of decoder multi-source attention strategies that have been introduced into previous APE models. The experimental results indicate that the joint-encoding strategy is effective and that taking the final encoded representation of the source sentence is the more proper strategy than taking such representation within the same encoder stack. Furthermore, among the multi-source attention strategies combined with the joint-encoding, the strategy that applies attention to the concatenated input representation and the strategy that adds up the individual attention to each input improve the quality of APE results over the strategy using the joint-encoding only.

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Song, Wenjun, Congxian Li, and Qiuwen Zhang. "Rapid CU Partitioning and Joint Intra-Frame Mode Decision Algorithm." Electronics 13, no. 17 (August 31, 2024): 3465. http://dx.doi.org/10.3390/electronics13173465.

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H.266/Versatile Video Coding (VVC) introduces new techniques that build upon previous standards, proposing a nested multi-type tree quadtree (QTMT). The introduction of this structure significantly enhances video coding efficiency; additionally, the number of directional modes in H.266 has increased by 32 compared to H.265, accommodating a greater variety of texture patterns. However, the changes in the related structures have also led to a significant increase in encoding complexity. To address the issue of excessive computational complexity, this paper proposes a targeted rapid Coding Units segmenting approach combined with decision-making for an intra-frame modes algorithm. In the first phase of the algorithm, we extract different features for CU blocks of various sizes and input them into the decision tree model’s classifier for classification processing, determining the CU partitioning mode to prematurely terminate the partitioning, thereby reducing the encoding complexity to some extent. In the second phase of the algorithm, we put forward an intra-frame mode decision strategy grounded in gradient descent techniques with a bidirectional search mode. This maximizes the approach to the global optimum, thereby obtaining the optimal intra-frame mode and further reducing the encoding complexity. Experimentation has demonstrated that the algorithm achieves a 54.53% reduction in encoding time. In comparison, the BD-BR (Bitrate-Distortion Rate) only increases by 1.38%, striking an optimal balance between the fidelity of video and the efficacy of the encoding process.

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Zheng, Yayu, Fan Zhou, Xiang Tian, and Yaowu Chen. "Lightweight content-adaptive coding in joint analyzing-encoding framework." IEEE Transactions on Consumer Electronics 54, no. 2 (May 2008): 614–22. http://dx.doi.org/10.1109/tce.2008.4560138.

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12

Javidi, Bahram, and Qing Tang. "Binary encoding of gray scale nonlinear joint transform correlators." Applied Optics 30, no. 11 (April 10, 1991): 1321. http://dx.doi.org/10.1364/ao.30.001321.

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Lee, Chungcheng, and Chulung Chen. "Color pattern recognition using image encoding joint transform correlator." Microwave and Optical Technology Letters 49, no. 7 (2007): 1665–69. http://dx.doi.org/10.1002/mop.22554.

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Gouze, Jean-Noel, Steven C. Ghivizzani, Elvire Gouze, Glyn D. Palmer, Oliver B. Betz, Paul D. Robbins, Christopher H. Evans, and James H. Herndon. "GENE THERAPY FOR RHEUMATOID ARTHRITIS." Hand Surgery 06, no. 02 (December 2001): 211–19. http://dx.doi.org/10.1142/s0218810401000709.

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Advances in understanding the biology of rheumatoid arthritis (RA) have opened new therapeutic avenues. One of these, gene therapy, involves the delivery to patients of genes encoding anti-arthritic proteins. This approach has shown efficacy in animal models of RA, and the first human, phase I trial has just been successfully completed. Hand surgery featured prominently in this pioneering study, as a potentially anti-arthritic gene encoding the interleukin-1 receptor antagonist was transferred to the metacarpophalangeal joints of subjects with RA one week before total joint arthroplasty. This study has confirmed that it is possible to transfer genes safely to human joints. It should pave the way for additional application of gene therapy to arthritis and other orthopaedic conditions.

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Pinardi, Mattia, Alessia Noccaro, Luigi Raiano, Domenico Formica, and Giovanni Di Pino. "Comparing end-effector position and joint angle feedback for online robotic limb tracking." PLOS ONE 18, no. 6 (June 8, 2023): e0286566. http://dx.doi.org/10.1371/journal.pone.0286566.

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Somatosensation greatly increases the ability to control our natural body. This suggests that supplementing vision with haptic sensory feedback would also be helpful when a user aims at controlling a robotic arm proficiently. However, whether the position of the robot and its continuous update should be coded in a extrinsic or intrinsic reference frame is not known. Here we compared two different supplementary feedback contents concerning the status of a robotic limb in 2-DoFs configuration: one encoding the Cartesian coordinates of the end-effector of the robotic arm (i.e., Task-space feedback) and another and encoding the robot joints angles (i.e., Joint-space feedback). Feedback was delivered to blindfolded participants through vibrotactile stimulation applied on participants’ leg. After a 1.5-hour training with both feedbacks, participants were significantly more accurate with Task compared to Joint-space feedback, as shown by lower position and aiming errors, albeit not faster (i.e., similar onset delay). However, learning index during training was significantly higher in Joint space feedback compared to Task-space feedback. These results suggest that Task-space feedback is probably more intuitive and more suited for activities which require short training sessions, while Joint space feedback showed potential for long-term improvement. We speculate that the latter, despite performing worse in the present work, might be ultimately more suited for applications requiring long training, such as the control of supernumerary robotic limbs for surgical robotics, heavy industrial manufacturing, or more generally, in the context of human movement augmentation.

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Kim, Man-Seok, Jo-Hwan Kim, Min-Goo Choi, and Jong-Wook Kim. "A New Trajectory Generation Scheme for Direction Turning in Biped Walking." Journal of Advanced Computational Intelligence and Intelligent Informatics 14, no. 5 (July 20, 2010): 550–54. http://dx.doi.org/10.20965/jaciii.2010.p0550.

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This paper proposes a new trajectory generation scheme for direction turning during biped walking based on our previous study and experiences. For turning in walking, two joints in the sagittal plane should be added in the robot model, and each joint should rotate appropriately considering stability and landing precision. All the angular trajectories for 12 joints in the lower body are approximated by blending polynomials optimized by univariate Dynamic Encoding Algorithm for Searches (uDEAS). The proposed walking scheme is validated via simulation.

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Foldes, Tamas, Lorena Santamaria, and Penny Lewis. "Sleep-related benefits to transitive inference are modulated by encoding strength and joint rank." Learning & Memory 30, no. 9 (September 2023): 201–11. http://dx.doi.org/10.1101/lm.053787.123.

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Transitive inference is a measure of relational learning that has been shown to improve across sleep. Here, we examine this phenomenon further by studying the impact of encoding strength and joint rank. In experiment 1, participants learned adjacent premise pairs and were then tested on inferential problems derived from those pairs. In line with prior work, we found improved transitive inference performance after retention across a night of sleep compared with wake alone. Experiment 2 extended these findings using a within-subject design and found superior transitive inference performance on a hierarchy, consolidated across 27 h including sleep compared with just 3 h of wake. In both experiments, consolidation-related improvement was enhanced when presleep learning (i.e., encoding strength) was stronger. We also explored the interaction of these effects with the joint rank effect, in which items were scored according to their rank in the hierarchy, with more dominant item pairs having the lowest scores. Interestingly, the consolidation-related benefit was greatest for more dominant inference pairs (i.e., those with low joint rank scores). Overall, our findings provide further support for the improvement of transitive inference across a consolidation period that includes sleep. We additionally show that encoding strength and joint rank strongly modulate this effect.

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Kaneguchi, A., and J. Ozawa. "Inflammation and Fibrosis Induced by Joint Remobilization, and Relevance to Progression of Arthrogenic Joint Contracture: A Narrative Review." Physiological Research 71, no. 4 (June 30, 2022): 447–55. http://dx.doi.org/10.33549/physiolres.934876.

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Joint immobilization is frequently administered after fractures and ligament injuries and can cause joint contracture as a side effect. The structures responsible for immobilization-induced joint contracture can be roughly divided into muscular and articular. During remobilization, although myogenic contracture recovers spontaneously, arthrogenic contracture is irreversible or deteriorates further. Immediately after remobilization, an inflammatory response is observed, characterized by joint swelling, deposit formation in the joint space, edema, inflammatory cell infiltration, and the upregulation of genes encoding proinflammatory cytokines in the joint capsule. Subsequently, fibrosis in the joint capsule develops, in parallel with progressing arthrogenic contracture. The triggers of remobilization-induced joint inflammation are not fully understood, but two potential mechanisms are proposed: 1) micro-damage induced by mechanical stress in the joint capsule, and 2) nitric oxide (NO) production via NO synthase 2. Some interventions can modulate remobilization-induced inflammatory and subsequent fibrotic reactions. Anti-inflammatory treatments, such as steroidal anti-inflammatory drugs and low-level laser therapy, can attenuate joint capsule fibrosis and the progression of arthrogenic contracture in remobilized joints. Antiproliferative treatment using the cell-proliferation inhibitor mitomycin C can also attenuate joint capsule fibrosis by inhibiting fibroblast proliferation without suppressing inflammation. Conversely, aggressive exercise during the early remobilization phases is counterproductive, because it facilitates inflammatory and then fibrotic reactions in the joint. However, the adverse effects of aggressive exercise on remobilization-induced inflammation and fibrosis are offset by anti-inflammatory treatment. To prevent the progression of arthrogenic contracture during remobilization, therefore, care should be taken to control inflammatory and fibrotic reactions in the joints.

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Dai Chaoyue, 戴朝约, 葛鹏 Ge Peng, 李奇 Li Qi, 冯华君 Feng Huajun, and 徐之海 Xu Zhihai. "Image Displacement Measurement Using Double Phase-Encoding Joint Transform Correlator." Acta Optica Sinica 31, no. 7 (2011): 0712004. http://dx.doi.org/10.3788/aos201131.0712004.

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Yu, F. T. S., Guowen Lu, Mingzhe Lu, and Dazun Zhao. "Application of position encoding to a complex joint transform correlator." Applied Optics 34, no. 8 (March 10, 1995): 1386. http://dx.doi.org/10.1364/ao.34.001386.

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Jung, Bongsoo. "Joint motion vector encoding scheme with a pooled macroblock type." Optical Engineering 47, no. 12 (December 1, 2008): 120501. http://dx.doi.org/10.1117/1.3046713.

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Plass, John, EunSeon Ahn, Vernon L. Towle, William C. Stacey, Vibhangini S. Wasade, James Tao, Shasha Wu, Naoum P. Issa, and David Brang. "Joint Encoding of Auditory Timing and Location in Visual Cortex." Journal of Cognitive Neuroscience 31, no. 7 (July 2019): 1002–17. http://dx.doi.org/10.1162/jocn_a_01399.

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Co-occurring sounds can facilitate perception of spatially and temporally correspondent visual events. Separate lines of research have identified two putatively distinct neural mechanisms underlying two types of crossmodal facilitations: Whereas crossmodal phase resetting is thought to underlie enhancements based on temporal correspondences, lateralized occipital evoked potentials (ERPs) are thought to reflect enhancements based on spatial correspondences. Here, we sought to clarify the relationship between these two effects to assess whether they reflect two distinct mechanisms or, rather, two facets of the same underlying process. To identify the neural generators of each effect, we examined crossmodal responses to lateralized sounds in visually responsive cortex of 22 patients using electrocorticographic recordings. Auditory-driven phase reset and ERP responses in visual cortex displayed similar topography, revealing significant activity in pericalcarine, inferior occipital–temporal, and posterior parietal cortex, with maximal activity in lateral occipitotemporal cortex (potentially V5/hMT+). Laterality effects showed similar but less widespread topography. To test whether lateralized and nonlateralized components of crossmodal ERPs emerged from common or distinct neural generators, we compared responses throughout visual cortex. Visual electrodes responded to both contralateral and ipsilateral sounds with a contralateral bias, suggesting that previously observed laterality effects do not emerge from a distinct neural generator but rather reflect laterality-biased responses in the same neural populations that produce phase-resetting responses. These results suggest that crossmodal phase reset and ERP responses previously found to reflect spatial and temporal facilitation in visual cortex may reflect the same underlying mechanism. We propose a new unified model to account for these and previous results.

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Gao, Guangchun, Lina Shang, and Kai Xion. "Study on joint speech encoding technology based on compressed sensing." International Journal of Multimedia and Ubiquitous Engineering 9, no. 7 (July 31, 2014): 47–60. http://dx.doi.org/10.14257/ijmue.2014.9.7.05.

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Alaoui-Fdili, Othmane, François-Xavier Coudoux, Youssef Fakhri, Patrick Corlay, and Driss Aboutajdine. "Energy-efficient joint video encoding and transmission framework for WVSN." Multimedia Tools and Applications 77, no. 4 (July 7, 2017): 4509–41. http://dx.doi.org/10.1007/s11042-017-4904-6.

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Zhu, Qiang, Cheng Hong, Yajie Meng, Huali Yang, and Weizhong Zhao. "Joint extraction of biomedical overlapping triples through feature partition encoding." Expert Systems with Applications 241 (May 2024): 122723. http://dx.doi.org/10.1016/j.eswa.2023.122723.

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Wang, Tianyu, Meng Xiang, Fei Liu, Jinpeng Liu, Xue Dong, Sen Wang, Gang Li, and Xiaopeng Shao. "Multi-Aperture Joint-Encoding Fourier Ptychography for a Distributed System." Remote Sensing 16, no. 6 (March 13, 2024): 1017. http://dx.doi.org/10.3390/rs16061017.

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High-resolution infrared remote sensing imaging is critical in planetary exploration, especially under demanding engineering conditions. However, due to diffraction, the spatial resolution of conventional methods is relatively low, and the spatial bandwidth product limits imaging systems’ design. Extensive research has been conducted with the aim of enhancing spatial resolution in remote sensing using a multi-aperture structure, but obtaining high-precision co-phase results using a sub-aperture remains challenging. A new high-resolution imaging method utilizing multi-aperture joint-encoding Fourier ptychography (JEFP) is proposed as a practical means to achieve super-resolution infrared imaging using distributed platforms. We demonstrated that the JEFP approach achieves pixel super-resolution with high efficiency, without requiring subsystems to perform mechanical scanning in space or to have high position accuracy. Our JEFP approach extends the application scope of Fourier ptychographic imaging, especially in distributed platforms for planetary exploration applications.

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LUQUE, NICETO R., JESÚS A. GARRIDO, JARNO RALLI, JUANLU J. LAREDO, and EDUARDO ROS. "FROM SENSORS TO SPIKES: EVOLVING RECEPTIVE FIELDS TO ENHANCE SENSORIMOTOR INFORMATION IN A ROBOT-ARM." International Journal of Neural Systems 22, no. 04 (July 25, 2012): 1250013. http://dx.doi.org/10.1142/s012906571250013x.

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In biological systems, instead of actual encoders at different joints, proprioception signals are acquired through distributed receptive fields. In robotics, a single and accurate sensor output per link (encoder) is commonly used to track the position and the velocity. Interfacing bio-inspired control systems with spiking neural networks emulating the cerebellum with conventional robots is not a straight forward task. Therefore, it is necessary to adapt this one-dimensional measure (encoder output) into a multidimensional space (inputs for a spiking neural network) to connect, for instance, the spiking cerebellar architecture; i.e. a translation from an analog space into a distributed population coding in terms of spikes. This paper analyzes how evolved receptive fields (optimized towards information transmission) can efficiently generate a sensorimotor representation that facilitates its discrimination from other "sensorimotor states". This can be seen as an abstraction of the Cuneate Nucleus (CN) functionality in a robot-arm scenario. We model the CN as a spiking neuron population coding in time according to the response of mechanoreceptors during a multi-joint movement in a robot joint space. An encoding scheme that takes into account the relative spiking time of the signals propagating from peripheral nerve fibers to second-order somatosensory neurons is proposed. Due to the enormous number of possible encodings, we have applied an evolutionary algorithm to evolve the sensory receptive field representation from random to optimized encoding. Following the nature-inspired analogy, evolved configurations have shown to outperform simple hand-tuned configurations and other homogenized configurations based on the solution provided by the optimization engine (evolutionary algorithm). We have used artificial evolutionary engines as the optimization tool to circumvent nonlinearity responses in receptive fields.

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McGibbon, Chris A. "A biomechanical model for encoding joint dynamics: applications to transfemoral prosthesis control." Journal of Applied Physiology 112, no. 9 (May 1, 2012): 1600–1611. http://dx.doi.org/10.1152/japplphysiol.01251.2011.

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This paper presents and tests a framework for encoding joint dynamics into energy states using kinematic and kinetic knee joint sensor data and demonstrates how to use this information to predict the future energy state (torque and velocity requirements) of the joint without a priori knowledge of the activity sequence. The intended application is for enhancing micro-controlled prosthetics by making use of the embedded sensory potential of artificial limbs and classical mechanical principles of a prosthetic joint to report instantaneous energy state and most probable next energy state. When applied to the knee during preferred and fast speed walking in 8 human subjects (66 preferred-speed trials and 50 fast-speed trials), it was found that joint energy states could be consistently sequenced (75% consensus) according to mechanical energy transference conditions and subsequences appeared to reflect the stability and energy dissipation requirements of the knee during gait. When simple constraints were applied to the energy transfer input conditions (their signs), simulations indicated that it was possible to predict the future energy state with an accuracy of >80% when 2% cycle in advance (∼20 ms) of the switch and >60% for 4% (∼40 ms) in advance. This study justifies future research to explore whether this encoding algorithm can be used to identify submodes of other human activity that are relevant to TFP control, such as chair and stair activities and their transitions from walking, as well as unexpected perturbations.

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Shi, Yaxin, Yuangang Pan, Donna Xu, and Ivor W. Tsang. "Multiview Alignment and Generation in CCA via Consistent Latent Encoding." Neural Computation 32, no. 10 (October 2020): 1936–79. http://dx.doi.org/10.1162/neco_a_01309.

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Multiview alignment, achieving one-to-one correspondence of multiview inputs, is critical in many real-world multiview applications, especially for cross-view data analysis problems. An increasing amount of work has studied this alignment problem with canonical correlation analysis (CCA). However, existing CCA models are prone to misalign the multiple views due to either the neglect of uncertainty or the inconsistent encoding of the multiple views. To tackle these two issues, this letter studies multiview alignment from a Bayesian perspective. Delving into the impairments of inconsistent encodings, we propose to recover correspondence of the multiview inputs by matching the marginalization of the joint distribution of multiview random variables under different forms of factorization. To realize our design, we present adversarial CCA (ACCA), which achieves consistent latent encodings by matching the marginalized latent encodings through the adversarial training paradigm. Our analysis, based on conditional mutual information, reveals that ACCA is flexible for handling implicit distributions. Extensive experiments on correlation analysis and cross-view generation under noisy input settings demonstrate the superiority of our model.

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Arnoux, Léo, Sebastien Fromentin, Dario Farotto, Mathieu Beraneck, Joseph McIntyre, and Michele Tagliabue. "The visual encoding of purely proprioceptive intermanual tasks is due to the need of transforming joint signals, not to their interhemispheric transfer." Journal of Neurophysiology 118, no. 3 (September 1, 2017): 1598–608. http://dx.doi.org/10.1152/jn.00140.2017.

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To perform goal-oriented hand movement, humans combine multiple sensory signals (e.g., vision and proprioception) that can be encoded in various reference frames (body centered and/or exo-centered). In a previous study (Tagliabue M, McIntyre J. PLoS One 8: e68438, 2013), we showed that, when aligning a hand to a remembered target orientation, the brain encodes both target and response in visual space when the target is sensed by one hand and the response is performed by the other, even though both are sensed only through proprioception. Here we ask whether such visual encoding is due 1) to the necessity of transferring sensory information across the brain hemispheres, or 2) to the necessity, due to the arms’ anatomical mirror symmetry, of transforming the joint signals of one limb into the reference frame of the other. To answer this question, we asked subjects to perform purely proprioceptive tasks in different conditions: Intra, the same arm sensing the target and performing the movement; Inter/Parallel, one arm sensing the target and the other reproducing its orientation; and Inter/Mirror, one arm sensing the target and the other mirroring its orientation. Performance was very similar between Intra and Inter/Mirror (conditions not requiring joint-signal transformations), while both differed from Inter/Parallel. Manipulation of the visual scene in a virtual reality paradigm showed visual encoding of proprioceptive information only in the latter condition. These results suggest that the visual encoding of purely proprioceptive tasks is not due to interhemispheric transfer of the proprioceptive information per se, but to the necessity of transforming joint signals between mirror-symmetric limbs. NEW & NOTEWORTHY Why does the brain encode goal-oriented, intermanual tasks in a visual space, even in the absence of visual feedback about the target and the hand? We show that the visual encoding is not due to the transfer of proprioceptive signals between brain hemispheres per se, but to the need, due to the mirror symmetry of the two limbs, of transforming joint angle signals of one arm in different joint signals of the other.

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Han, Xiao-Wei, Xing-Yu Chen, Ying Cui, Qiu-Yang Guo, and Wen Hu. "Adaptive Channel-Enhanced Graph Convolution for Skeleton-Based Human Action Recognition." Applied Sciences 14, no. 18 (September 11, 2024): 8185. http://dx.doi.org/10.3390/app14188185.

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Obtaining discriminative joint features is crucial for skeleton-based human action recognition. Current models mainly focus on the research of skeleton topology encoding. However, their predefined topology is the same and fixed for all action samples, making it challenging to obtain discriminative joint features. Although some studies have considered the complex non-natural connection relationships between joints, the existing methods cannot fully capture this complexity by using high-order adjacency matrices or adding trainable parameters and instead increase the computation parameters. Therefore, this study constructs a novel adaptive channel-enhanced graph convolution (ACE-GCN) model for human action recognition. The model generates similar and affinity attention maps by encoding channel attention in the input features. These maps are complementarily applied to the input feature map and graph topology, which can realize the refinement of joint features and construct an adaptive and non-shared channel-based adjacency matrix. This method of constructing the adjacency matrix improves the model’s capacity to capture intricate non-natural connections between joints, prevents the accumulation of unnecessary information, and minimizes the number of computational parameters. In addition, integrating the Edgeconv module into a multi-branch aggregation improves the model’s ability to aggregate different scale and temporal features. Ultimately, comprehensive experiments were carried out on NTU-RGB+D 60 and NTU-RGB+D 120, which are two substantial datasets. On the NTU RGB+D 60 dataset, the accuracy of human action recognition was 92% (X-Sub) and 96.3% (X-View). The model achieved an accuracy of 96.6% on the NW-UCLA dataset. The experimental results confirm that the ACE-GCN exhibits superior recognition accuracy and lower computing complexity compared to current methodologies.

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Shang, Bin, Zhe Chen, Yuxi Lin, Hong Chang, and Jianing Wei. "A systematic classification and typological assessment method for mortise and tenon joints." BioResources 19, no. 3 (June 5, 2024): 4918–40. http://dx.doi.org/10.15376/biores.19.3.4918-4940.

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The classification of Mortise and Tenon (MT) joints is vital, as it enables standardized terminology, facilitates comparative analysis, and enhances understanding of construction techniques across a variety of applications including the design, manufacturing, and management of wood products. Although the classification of MT joints is crucial, current research in this area lacks a systematic approach. The study adopts a morphological composition paradigm to investigate MT joints. This study introduces a 6-level classification index hierarchy for MT morphology, employing methods from biological classification and arithmetic cross-method coding. By encoding joint features and morphological composition, the study delineates 352 possible joint types and 1056 theoretical compositions across dimensions, elucidating diverse structural logics and aiding comprehension. Next, a feasibility typicality assessment identifies 198 typical and 310 atypical morphological types, presented clearly in graphical form. Validations are conducted through analysis of 2654 research cases, which are encoded according to the index hierarchy, thereby affirming the scientific validity and practical utility of the classification system.

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Thiele, Maleen, Robert Hepach, Christine Michel, and Daniety B. M. Haun. "Observing others’ joint attention increases 9-month-old infants’ object encoding." Developmental Psychology 57, no. 6 (June 2021): 837–50. http://dx.doi.org/10.1037/dev0001189.

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Alsaade, Fawaz Waselallah, and Mahaboob Basha Shaik. "Joint Photographic Experts Group Image Compression using Revised Run Length Encoding." Research Journal of Information Technology 9, no. 1 (December 15, 2016): 38–45. http://dx.doi.org/10.3923/rjit.2017.38.45.

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Wang, Anran, Jiwen Lu, Jianfei Cai, Gang Wang, and Tat-Jen Cham. "Unsupervised Joint Feature Learning and Encoding for RGB-D Scene Labeling." IEEE Transactions on Image Processing 24, no. 11 (November 2015): 4459–73. http://dx.doi.org/10.1109/tip.2015.2465133.

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Hirokawa, Katsuhisa, Kazuyoshi Itoh, and Yoshiki Ichioka. "Optical wavelet processor by holographic bipolar encoding and joint-transform correlation." Applied Optics 36, no. 5 (February 10, 1997): 1023. http://dx.doi.org/10.1364/ao.36.001023.

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Yuan, Xiang Yan. "Distortion-invariant joint transform correlator based on a phase-encoding technique." Optical Engineering 41, no. 11 (November 1, 2002): 2923. http://dx.doi.org/10.1117/1.1512664.

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Kafaie, Somayeh, Yuanzhu Chen, Mohamed Hossam Ahmed, and Octavia A. Dobre. "FlexONC: Joint Cooperative Forwarding and Network Coding With Precise Encoding Conditions." IEEE Transactions on Vehicular Technology 66, no. 8 (August 2017): 7262–77. http://dx.doi.org/10.1109/tvt.2017.2659539.

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Gong, Yaoqin, Deborah Krakow, Jose Marcelino, Douglas Wilkin, David Chitayat, Riyana Babul-Hirji, Louanne Hudgins, et al. "Heterozygous mutations in the gene encoding noggin affect human joint morphogenesis." Nature Genetics 21, no. 3 (March 1999): 302–4. http://dx.doi.org/10.1038/6821.

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Chen, Liwei, Yansong Feng, Songfang Huang, Bingfeng Luo, and Dongyan Zhao. "Encoding implicit relation requirements for relation extraction: A joint inference approach." Artificial Intelligence 265 (December 2018): 45–66. http://dx.doi.org/10.1016/j.artint.2018.08.004.

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Larkman, David J., Philip G. Batchelor, David Atkinson, Daniel Rueckert, and Jo V. Hajnal. "Beyond theg-factor limit in sensitivity encoding using joint histogram entropy." Magnetic Resonance in Medicine 55, no. 1 (2005): 153–60. http://dx.doi.org/10.1002/mrm.20752.

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Zhang, Fenghao, Lin Zhao, Shengling Li, Wanjuan Su, Liman Liu, and Wenbing Tao. "3D hand pose and shape estimation from monocular RGB via efficient 2D cues." Computational Visual Media 10, no. 1 (February 2023): 79–96. http://dx.doi.org/10.1007/s41095-023-0346-4.

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AbstractEstimating 3D hand shape from a single-view RGB image is important for many applications. However, the diversity of hand shapes and postures, depth ambiguity, and occlusion may result in pose errors and noisy hand meshes. Making full use of 2D cues such as 2D pose can effectively improve the quality of 3D human hand shape estimation. In this paper, we use 2D joint heatmaps to obtain spatial details for robust pose estimation. We also introduce a depth-independent 2D mesh to avoid depth ambiguity in mesh regression for efficient hand-image alignment. Our method has four cascaded stages: 2D cue extraction, pose feature encoding, initial reconstruction, and reconstruction refinement. Specifically, we first encode the image to determine semantic features during 2D cue extraction; this is also used to predict hand joints and for segmentation. Then, during the pose feature encoding stage, we use a hand joints encoder to learn spatial information from the joint heatmaps. Next, a coarse 3D hand mesh and 2D mesh are obtained in the initial reconstruction step; a mesh squeeze-and-excitation block is used to fuse different hand features to enhance perception of 3D hand structures. Finally, a global mesh refinement stage learns non-local relations between vertices of the hand mesh from the predicted 2D mesh, to predict an offset hand mesh to fine-tune the reconstruction results. Quantitative and qualitative results on the FreiHAND benchmark dataset demonstrate that our approach achieves state-of-the-art performance.

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Caraffi, Maini, Ivanovski, Pollazzon, Giangiobbe, Valli, Rossi, et al. "Severe Peripheral Joint Laxity is a Distinctive Clinical Feature of Spondylodysplastic-Ehlers-Danlos Syndrome (EDS)-B4GALT7 and Spondylodysplastic-EDS-B3GALT6." Genes 10, no. 10 (October 12, 2019): 799. http://dx.doi.org/10.3390/genes10100799.

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Variations in genes encoding for the enzymes responsible for synthesizing the linker region of proteoglycans may result in recessive conditions known as “linkeropathies”. The two phenotypes related to mutations in genes B4GALT7 and B3GALT6 (encoding for galactosyltransferase I and II respectively) are similar, characterized by short stature, hypotonia, joint hypermobility, skeletal features and a suggestive face with prominent forehead, thin soft tissue and prominent eyes. The most outstanding feature of these disorders is the combination of severe connective tissue involvement, often manifesting in newborns and infants, and skeletal dysplasia that becomes apparent during childhood. Here, we intend to more accurately define some of the clinical features of B4GALT7 and B3GALT6-related conditions and underline the extreme hypermobility of distal joints and the soft, doughy skin on the hands and feet as features that may be useful as the first clues for a correct diagnosis.

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Zhao, Suping, Yushuang Du, Chaobo Chen, Xiaohua Song, and Xiaoyan Zhang. "Multitask-Based Anti-Collision Trajectory Planning of Redundant Manipulators." Biomimetics 9, no. 11 (November 6, 2024): 679. http://dx.doi.org/10.3390/biomimetics9110679.

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During performing multiple tasks of a redundant manipulator, the obstacles affect the sequential order of task areas and the joint trajectories. The end-effector is constrained to visit multiple task areas with an optimal anti-collision path, while the joints are required to move smoothly and avoid predefined obstacles. A special encoding genetic algorithm (SEGA) is proposed for multitask-based anti-collision trajectory planning. Firstly, the spatial occupancy relationship between obstacles and manipulator is developed utilizing the theory of spherical enclosing box and spatial superposition. The obstacles are detected according to the relative position relationship between linear segments and spheres. Secondly, each joint trajectory between adjacent task areas is depicted with a sixth-degree polynomial. Additionally, each joint trajectory is improved via optimizing the unknown six-order coefficient. By searching for optimal sequential order of task areas, optimal collision detection results, and optimal joint trajectories, the multitask-based anti-collision trajectory planning problem is transformed into a parameter optimization problem. In SEGA, the cost function consists of two parts, including the end-effector path length and the variation of joint angles. Moreover, each chromosome consists of three categories of genes, including the sequential order of task areas, the sequential order of joint configurations corresponding to task areas, and the unknown coefficients for anti-collision joint trajectories. Finally, numerical simulations are carried out to verify the proposed method.

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Sun, Hua, and Chao Tian. "Breaking the MDS-PIR Capacity Barrier via Joint Storage Coding." Information 10, no. 9 (August 22, 2019): 265. http://dx.doi.org/10.3390/info10090265.

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The capacity of private information retrieval (PIR) from databases coded using maximum distance separable (MDS) codes was previously characterized by Banawan and Ulukus, where it was assumed that the messages are encoded and stored separably in the databases. This assumption was also usually made in other related works in the literature, and this capacity is usually referred to as the MDS-PIR capacity colloquially. In this work, we considered the question of if and when this capacity barrier can be broken through joint encoding and storing of the messages. Our main results are two classes of novel code constructions, which allow joint encoding, as well as the corresponding PIR protocols, which indeed outperformed the separate MDS-coded systems. Moreover, we show that a simple, but novel expansion technique allows us to generalize these two classes of codes, resulting in a wider range of the cases where this capacity barrier can be broken.

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Samanta, Soumitra, Steve O’Hagan, Neil Swainston, Timothy J. Roberts, and Douglas B. Kell. "VAE-Sim: A Novel Molecular Similarity Measure Based on a Variational Autoencoder." Molecules 25, no. 15 (July 29, 2020): 3446. http://dx.doi.org/10.3390/molecules25153446.

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Molecular similarity is an elusive but core “unsupervised” cheminformatics concept, yet different “fingerprint” encodings of molecular structures return very different similarity values, even when using the same similarity metric. Each encoding may be of value when applied to other problems with objective or target functions, implying that a priori none are “better” than the others, nor than encoding-free metrics such as maximum common substructure (MCSS). We here introduce a novel approach to molecular similarity, in the form of a variational autoencoder (VAE). This learns the joint distribution p(z|x) where z is a latent vector and x are the (same) input/output data. It takes the form of a “bowtie”-shaped artificial neural network. In the middle is a “bottleneck layer” or latent vector in which inputs are transformed into, and represented as, a vector of numbers (encoding), with a reverse process (decoding) seeking to return the SMILES string that was the input. We train a VAE on over six million druglike molecules and natural products (including over one million in the final holdout set). The VAE vector distances provide a rapid and novel metric for molecular similarity that is both easily and rapidly calculated. We describe the method and its application to a typical similarity problem in cheminformatics.

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Cheng, Dongyang, Zhenchang Liu, Zhengwei Guo, Gaofeng Shu, and Ning Li. "A Repeater-Type SAR Deceptive Jamming Method Based on Joint Encoding of Amplitude and Phase in the Intra-Pulse and Inter-Pulse." Remote Sensing 14, no. 18 (September 14, 2022): 4597. http://dx.doi.org/10.3390/rs14184597.

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Due to advantages such as low power consumption and high concealment, deceptive jamming against synthetic aperture radar (SAR) has received extensive attention in electronic countermeasures. However, the false targets generated by most of the deceptive jamming methods still have limitations, such as poor controllability and strong regularity. Inspired by the idea of waveform coding, this paper proposed a repeater-type SAR deceptive jamming method through the joint encoding of amplitude and phase in intra-pulse and inter-pulse, which can generate a two-dimensional controllable deceptive jamming effect. Specifically, the proposed method mainly includes two parts, i.e., grouping and encoding. The number of groups determines the number of false targets, and the presence of the phase encoding produces false targets. The amplitude encoding affects the amplitude of the false targets. For the intra-pulse cases, the proposed method first samples the intercepted SAR signal. Meanwhile, the sampling points are grouped in turn. For the inter-pulse cases, the grouped objects are the pulses. Subsequently, the joint encoding of amplitude and phase is performed on each group, which generates jamming signals with deceptive effects. In this paper, the imaging effect of the generated jamming signals is analyzed in detail, and the characteristics of false targets, including numbers, position, and amplitude, are derived. The simulation and experimental results verify the correctness of the theoretical analysis. In addition, the superiority of the proposed method is verified by comparing it with other methods.

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Bursalioglu, O. Y., M. Fresia, G. Caire, and H. V. Poor. "Lossy Joint Source-Channel Coding Using Raptor Codes." International Journal of Digital Multimedia Broadcasting 2008 (2008): 1–18. http://dx.doi.org/10.1155/2008/124685.

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The straightforward application of Shannon's separation principle may entail a significant suboptimality in practical systems with limited coding delay and complexity. This is particularly evident when the lossy source code is based on entropy-coded quantization. In fact, it is well known that entropy coding is not robust to residual channel errors. In this paper, a joint source-channel coding scheme is advocated that combines the advantages and simplicity of entropy-coded quantization with the robustness of linear codes. The idea is to combine entropy coding and channel coding into a single linear encoding stage. If the channel is symmetric, the scheme can asymptotically achieve the optimal rate-distortion limit. However, its advantages are more clearly evident under finite coding delay and complexity. The sequence of quantization indices is decomposed into bitplanes, and each bitplane is independently mapped onto a sequence of channel coded symbols. The coding rate of each bitplane is chosen according to the bitplane conditional entropy rate. The use of systematic raptor encoders is proposed, in order to obtain a continuum of coding rates with a single basic encoding algorithm. Simulations show that the proposed scheme can outperform the separated baseline scheme for finite coding length and comparable complexity and, as expected, it is much more robust to channel errors in the case of channel capacity mismatch.

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Zill, Sasha N., Chris J. Dallmann, Nicholas S. Szczecinski, Ansgar Büschges, and Josef Schmitz. "Evaluation of force feedback in walking using joint torques as “naturalistic” stimuli." Journal of Neurophysiology 126, no. 1 (July 1, 2021): 227–48. http://dx.doi.org/10.1152/jn.00120.2021.

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Sensory encoding of forces during walking by campaniform sensilla was characterized in stick insects using waveforms of joint torques calculated by inverse dynamics as mechanical stimuli. Tests using the mean joint torque and torques of individual steps showed the system is highly sensitive to force dynamics (dF/dt). Use of “naturalistic” stimuli can reproduce characteristics of sensory discharges seen in freely walking insects, such as load transfer among legs.

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Odinokov, S. B. "Access control holographic system based on joint transform correlator and image encoding." Optical Memory and Neural Networks 17, no. 3 (September 2008): 220–31. http://dx.doi.org/10.3103/s1060992x08030053.

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