A Flexible-Frame-Rate Vision-Aided Inertial Object Tracking System for Mobile Devices

Real-time object pose estimation and tracking is challenging but essential for emerging augmented reality (AR) applications. In general, state-of-the-art methods address this problem using deep neural networks which indeed yield satisfactory results. Nevertheless, the high computational cost of these methods makes them unsuitable for mobile devices where real-world applications usually take place. In addition, head-mounted displays such as AR glasses require at least 90~FPS to avoid motion sickness, which further complicates the problem. We propose a flexible-frame-rate object pose estimation and tracking system for mobile devices. It is a monocular visual-inertial-based system with a client-server architecture. Inertial measurement unit (IMU) pose propagation is performed on the client side for high speed tracking, and RGB image-based 3D pose estimation is performed on the server side to obtain accurate poses, after which the pose is sent to the client side for visual-inertial fusion, where we propose a bias self-correction mechanism to reduce drift. We also propose a pose inspection algorithm to detect tracking failures and incorrect pose estimation. Connected by high-speed networking, our system supports flexible frame rates up to 120 FPS and guarantees high precision and real-time tracking on low-end devices. Both simulations and real world experiments show that our method achieves accurate and robust object tracking

A Hint-Based Random Access Protocol for mMTC in 5G Mobile Network

With the increasing popularity of machine-type communication (MTC) devices, several new challenges are encountered by the legacy long term evolution (LTE) system. One critical issue is that a massive number of MTC devices trying to conduct random access procedures may cause significant collisions and long delays. In this work, we present a new random access mechanism by splitting the contention-based preambles in LTE into two logically disjoint parts, one for the user equipment (UE) being paged and the other for the UEs not being paged. Since the IDs of paged UEs are known by the base station, a novel hash-based random access, which we call hint, is possible. The main idea is to pre-allocate preambles to paged UEs in a contention-free manner and confines non-paged UEs to contend in a separate region. We further build a mathematical model to find the optimal ratio of pre-allocated preambles. Extensive simulations are conducted to validate our results

r-Hint: A message-efficient random access response for mMTC in 5G networks

Massive Machine Type Communication (mMTC) has attracted increasing attention due to the explosive growth of IoT devices. Random Access (RA) for a large number of mMTC devices is especially difficult since the high signaling overhead between User Equipments (UEs) and an eNB may overwhelm the available spectrum resources. To address this issue, we propose “respond by hint” (r-Hint), an ID-free handshaking protocol for contention-based RA in mMTC. The core idea of r-Hint is to avoid sequentially notifying contending UEs of their IDs by broadcasting a hint in the RA Response (RAR). To do so, we exploit the concept of prime factorization and hashing to encode the hint such that UEs can extract their required information accordingly. Our simulation results show that r-Hint reduces the RAR message size by 20%–40%. Such reduction can be translated to around 50% improvement of spectrum efficiency in LTE-M

On Scalable Service Function Chaining with O(1) Flowtable Entries

The emergence of Network Function Virtualization (NFV) enables flexible and agile service function chaining in a Software Defined Network (SDN). While this virtualization technology efficiently offers customization capability, it however comes with a cost of consuming precious TCAM resources. Due to this, the number of service chains that an SDN can support is limited by the flowtable size of a switch. To break this limitation, this paper presents CRT-Chain, a service chain forwarding protocol that requires only constant flowtable entries, regardless of the number of service chain requests. The core of CRT-Chain is an encoding mechanism that leverages Chinese Remainder Theorem (CRT) to compress the forwarding information into small labels. A switch does not need to insert forwarding rules for every service chain request, but only needs to conduct very simple modular arithmetic to extract the forwarding rules directly from CRT-Chain's labels attached in the header. We further incorporate prime reuse and path segmentation in CRT-Chain to reduce the header size and, hence, save bandwidth consumption. Our evaluation results show that, when a chain consists of no more than 5 functions, CRT-Chain actually generates a header smaller than the legacy 32-bit header defined in IETF. By enabling prime reuse and segmentation, CRT-Chain further reduces the total signaling overhead to a level lower than the conventional scheme, showing that CRT-Chain not only enables scalable flowtable-free chaining but also improves network efficiency

On Optimizing Signaling Efficiency of Retransmissions for Voice LTE

The emergence of voice over LTE enables voice traffic transmissions over 4G packet-switched networks. Since voice traffic is characterized by its small payload and frequent transmissions, the corresponding control channel overhead would be high. Semi-persistent scheduling (SPS) is hence proposed in LTE-A to reduce such overhead. However, as wireless channels typically fluctuate, tremendous retransmissions due to poor channel conditions, which are still scheduled dynamically, would lead to a large overhead. To reduce the control message overhead caused by SPS retransmissions, we propose a new SPS retransmission protocol. Different from traditional SPS, which removes the downlink control indicators (DCI) directly, we compress some key fields of all retransmissions' DCIs in the same subframe as a fixed-length hint. Thus, the base station does not need to send this information to different users individually but just announces the hint as a broadcast message. In this way, we reduce the signaling overhead and at the same time, preserve the flexibility of dynamic scheduling. Our simulation results show that, by enabling DCI compression, our design improves signaling efficiency by 2.16\times, and the spectral utilization can be increased by up to 60%

Hey! I Have Something for You: Paging Cycle Based Random Access for LTE-A

The surge of M2M devices imposes new challenges for the current cellular network architecture, especially in radio access networks. One of the key issues is that the M2M traffic, characterized by small data and massive connection requests, makes significant collisions and congestion during network access via the random access (RA) procedure. To resolve this problem, in this paper, we propose a paging cycle-based protocol to facilitate the random access procedure in LTE-A. The high-level idea of our design is to leverage a UE's paging cycle as a hint to preassign RA preambles so that UEs can avoid preamble collisions at the first place. Our rpHint has two modes: (1) collision-free paging, which completely prevents cross-collision between paged user equipment (UEs) and random access UEs, and (2) collision-avoidance paging, which alleviates cross-collision. Moreover, we formulate a mathematical model to derive the optimal paging ratio that maximizes the expected number of successful UEs. This analysis also allows us to adapt dynamically to the better one between the two modes. We show via extensive simulations that our design increases the number of successful UEs in an RA procedure by more than 3× as compared to the legacy RA scheme of the LTE

CPEB4-Dependent Neonate-Born Granule Cells Are Required for Olfactory Discrimination

The rodent olfactory bulb (OB) contains two distinct populations of postnatally born interneurons, mainly granule cells (GCs), to support local circuits throughout life. During the early postnatal period (i.e., 2 weeks after birth), GCs are mostly produced locally from progenitor cells in the OB with a proportion of them deriving from proliferating cells in the rostral migratory stream (RMS). Afterward, the replenishment of GCs involves differentiated neuroblasts from the subventricular zone (SVZ) in a process known as adult neurogenesis. Although numerous studies have addressed the role of SVZ-born GCs in olfactory behaviors, the function of GCs produced early postnatally in the OB remains elusive. Our previous study demonstrated that the translational regulator, cytoplasmic polyadenylation element-binding protein 4 (CPEB4), is a survival factor exclusively for neonate-born but not SVZ/adult-derived GCs, so CPEB4-knockout (KO) mice provide unique leverage to study early postnatal-born GC-regulated olfactory functions. CPEB4-KO mice with hypoplastic OBs showed normal olfactory sensitivity and short-term memory, but impaired ability to spontaneously discriminate two odors. Such olfactory dysfunction was recapitulated in specific ablation of Cpeb4 gene in inhibitory interneurons but not in excitatory projection neurons or SVZ-derived interneurons. The continuous supply of GCs from adult neurogenesis eventually restored the OB size but not the discrimination function in 6-month-old KO mice. Hence, in the early postnatal OB, whose function cannot be replaced by adult-born GCs, construct critical circuits for odor discrimination

Self-supervised learning-based general laboratory progress pretrained model for cardiovascular event detection

The inherent nature of patient data poses several challenges. Prevalent cases amass substantial longitudinal data owing to their patient volume and consistent follow-ups, however, longitudinal laboratory data are renowned for their irregularity, temporality, absenteeism, and sparsity; In contrast, recruitment for rare or specific cases is often constrained due to their limited patient size and episodic observations. This study employed self-supervised learning (SSL) to pretrain a generalized laboratory progress (GLP) model that captures the overall progression of six common laboratory markers in prevalent cardiovascular cases, with the intention of transferring this knowledge to aid in the detection of specific cardiovascular event. GLP implemented a two-stage training approach, leveraging the information embedded within interpolated data and amplify the performance of SSL. After GLP pretraining, it is transferred for TVR detection. The proposed two-stage training improved the performance of pure SSL, and the transferability of GLP exhibited distinctiveness. After GLP processing, the classification exhibited a notable enhancement, with averaged accuracy rising from 0.63 to 0.90. All evaluated metrics demonstrated substantial superiority (p < 0.01) compared to prior GLP processing. Our study effectively engages in translational engineering by transferring patient progression of cardiovascular laboratory parameters from one patient group to another, transcending the limitations of data availability. The transferability of disease progression optimized the strategies of examinations and treatments, and improves patient prognosis while using commonly available laboratory parameters. The potential for expanding this approach to encompass other diseases holds great promise.Comment: published in IEEE Journal of Translational Engineering in Health & Medicin

Gradient static-strain stimulation in a microfluidic chip for 3D cellular alignment

This is the published version. Copyright 2014 Royal Society of ChemistryCell alignment is a critical factor to govern cellular behavior and function for various tissue engineering applications ranging from cardiac to neural regeneration. In addition to physical geometry, strain is a crucial parameter to manipulate cellular alignment for functional tissue formation. In this paper, we introduce a simple approach to generate a range of gradient static strains without external mechanical control for the stimulation of cellular behavior within 3D biomimetic hydrogel microenvironments. A glass-supported microfluidic chip with a convex flexible polydimethylsiloxane (PDMS) membrane on the top was employed for loading the cells suspended in a prepolymer solution. Following UV crosslinking through a photomask with a concentric circular pattern, the cell-laden hydrogels were formed in a height gradient from the center (maximum) to the boundary (minimum). When the convex PDMS membrane retracted back to a flat surface, it applied compressive gradient forces on the cell-laden hydrogels. The concentric circular hydrogel patterns confined the direction of hydrogel elongation, and the compressive strain on the hydrogel therefore resulted in elongation stretch in the radial direction to guide cell alignment. NIH3T3 cells were cultured in the chip for 3 days with compressive strains that varied from ~65% (center) to ~15% (boundary) on hydrogels. We found that the hydrogel geometry dominated the cell alignment near the outside boundary, where cells aligned along the circular direction, and the compressive strain dominated the cell alignment near the center, where cells aligned radially. This study developed a new and simple approach to facilitate cellular alignment based on hydrogel geometry and strain stimulation for tissue engineering applications. This platform offers unique advantages and is significantly different from the existing approaches owing to the fact that gradient generation was accomplished in a miniature device without using an external mechanical source