Automatic Longitudinal Regenerative Control of EVs Based on a Driver Characteristics-Oriented Deceleration Model

To preserve the fun of driving and enhance driving convenience, a smart regenerative braking system (SRS) is developed. The SRS provides automatic regeneration that is appropriate for the driving conditions, but the existing technology has a low level of acceptability and comfort. To solve this problem, this paper presents an automatic regenerative control system based on a deceleration model that reflects the driver&rsquo s characteristics. The deceleration model is designed as a parametric model that mimics the driver&rsquo s behavior. In addition, it consists of parameters that represent the driver&rsquo s characteristics. These parameters are updated online by a learning algorithm. The validation results of the vehicle testing show that the vehicle maintained a safe distance from the leading car while simulating a driver&rsquo s behavior. Of all the deceleration that occurred during the testing, 92% was conducted by the automatic regeneration system. In addition, the results of the online learning algorithm are different based on the driver&rsquo s deceleration pattern. The presented automatic regenerative control system can be safely used in diverse car-following situations. Moreover, the system&rsquo s acceptability is improved by updating the driver characteristics. In the future, the algorithm will be extended for use in more diverse deceleration situations by using intelligent transportation system information. Document type: Articl

Magnetic Actuator Design Using Level Set Based Topology Optimization

This paper presents a novel design methodology for optimum structural design of magnetic actuators using a level set based topology optimization method where the level set method can represent the precise boundary shape of a structure and also deal with complex topological changes during the optimization process. The distribution of ferromagnetic material is represented by introducing a level set function into the definition of the magnetic reluctivity. The optimization problem is defined to obtain optimal configurations that maximize the magnetic energy of actuators under a minimum bound of total volume. The movement of the implicit moving boundaries of the structure is driven by a transformation of design sensitivities of the objective and the constraints into speed functions that govern the level set propagation. The proposed method is applied to the structural design of magnetic actuators, and is confirmed to be useful for achieving optimal configurations that deliver higher performance and lighter weight designs

An Experimental Study on the Shear Hysteresis and Energy Dissipation of the Steel Frame with a Trapezoidal-Corrugated Steel Plate

The steel frame reinforced with steel shear wall is a lateral load resisting system and has higher strength and shear performance than the concrete shear wall system. Especially, using corrugated steel plates in these shear wall systems improves out-of-plane stiffness and flexibility in the deformation along the corrugation. In this paper, a cyclic loading test of this steel frame reinforced with trapezoidal-corrugated steel plate was performed to evaluate the structural performance. The hysteresis behavior and the energy dissipation capacity of the steel frame were also compared according to the corrugated direction of the plate. For the test, one simple frame model without the wall and two frame models reinforced with the plate are considered and designed. The test results showed that the model reinforced with the corrugated steel plate had a greater accumulated energy dissipation capacity than the experimental result of the non-reinforced model. Furthermore, the energy dissipation curves of two reinforced frame models, which have different corrugated directions, produced similar results

Continuous-Depth Head-Mounted Display for Virtual Reality

Conventional head-mounted display for virtual reality, which simply adopts the structure of binocular sets of display and floating lens, may result in visual discomfort for the user such as nausea and double vision as it limits the user's accommodative states which leads to the vergence-accommodation conflict. In this paper, we overview the tomographic near-eye display which achieves a high-resolution, large depth of field and quasi-continuous depth at 60 frames per second for resolving vergence-accommodation conflict. In addition, we investigate several design issues and solutions to implement the specific system in the form of a compact head-mounted display and demonstrate the prototypes and experimental results.N

Secure Key Issuing in ID-based Cryptography

ID-based cryptosystems have many advantages over PKI based cryptosystems in key distribution, but they also have an inherent drawback of key escrow problem, i.e. users ’ private keys are known to the key generation center (KGC). Therefore secure key issuing (SKI) is an important issue in ID-based cryptography. In multiple authority approach (Boneh & Franklin 2001, Chen et al. 2002), key generation function is distributed to multiple authorities. Keeping key privacy using user-chosen secret information (Gentry 2003, Al-Riyami & Paterson 2003) is a simple and efficient solution, but it loses the advantages of ID-based cryptosystems. In this paper we propose a new secure key issuing protocol in which a private key is issued by a key generation center (KGC) and then its privacy is protected by multiple key privacy authorities (KPAs). In this protocol we provide a secure channel by using simple blinding technique in pairing-based cryptography. Only a legitimate user who has the secret blinding parameter can retrieve his private key from the protocol. Keywords: Bilinear pairing, ID-based cryptography, Secure key issuing (SKI), Key generation cente

Integration of relay optics in LED-based reflective off-axis digital holographic microscopy

Digital holography is widely known as one of the techniques reconstructing a depth profile of the object. For digital holography (DH), the light source that has a long coherence length such as laser or laser diode is generally recommended. Recently, digital holographic microscopy (DHM) utilizing light emitting diode (LED) as a light source has attracted attention. However, it has to satisfy certain conditions for LED be utilized in off-axis DHM as it has small coherence length. Due to this fact, the hologram cannot be captured from the other side of a beam splitter. Therefore, we propose an LED-based off-axis reflective DHM that combines a 4-f system that optically relays the field to the sensor plane of charge-coupled device (CCD). We analyze the reason why the sample plane has to be relayed by 4-f system. We provide experimental results to verify the necessity of relay optics in LED-based reflective off-axis DHM.N

Dynamically Manipulated Accommodation-invariant Displays

Computational accommodation-invariant (AI) display attempts to mitigate vergence-accommodation conflict (VAC) by showing a constant imagery no matter where the observer focuses on. However, due to the usage of an electrically focus-tunable lens, the contrast of imagery is degraded as point-spread functions of multiple foci are integrated. In this paper, we introduce the content-adaptive approach to improve the contrast at the depth of highly salient region in the image. The position of focal plane is dynamically determined considering the zone of comfort and the mean focal distance of salient region. The contrast enhancement compared to conventional accommodation-invariant display is shown through simulation results using USAF resolution target image. We demonstrate our proof-of-concept prototype and its optical feasibility is verified with experimental results.N

Exploration of Systolic-Vector Architecture with Resource Scheduling for Dynamic ML Workloads

As artificial intelligence (AI) and machine learning (ML) technologies disrupt a wide range of industries, cloud datacenters face ever-increasing demand in inference workloads. However, conventional CPU-based servers cannot handle excessive computational requirements of deep neural network (DNN) models, while GPU-based servers suffer from huge power consumption and high operating cost. In this paper, we present a scalable systolic-vector architecture that can cope with dynamically changing DNN workloads in cloud datacenters. We first devise a lightweight DNN model description format called unified model format (UMF) that enables general model representation and fast decoding in hardware accelerator. Based on this model format, we propose a heterogeneous architecture that features a load balancer that performs a high-level workload distribution and multiple systolic-vector clusters, in which each cluster consists of a programmable scheduler, throughput-oriented systolic arrays, and function-oriented vector processors. We also propose a heterogeneity-aware scheduling algorithm that enables concurrent execution of multiple DNN workloads while maximizing heterogeneous hardware utilization based on computation and memory access time estimation. Finally, we build an architecture simulation framework based on actual synthesis and place-and-route implementation results and conduct design space exploration for the proposed architecture. As a result, the proposed systolic-vector architecture achieves 10.9x higher throughput performance and 30.17x higher energy efficiency than a compatible GPU on realistic ML workloads. The proposed heterogeneity-aware scheduling algorithm improves the throughput and energy efficiency by 81% and 20%, respectively, compared to a standard round-robin scheduling