Two-Port Feedback Analysis On Miller-Compensated Amplifiers

In this paper, various Miller-compensated amplifiers are analyzed by using the two-port feedback analysis together with the root-locus diagram. The proposed analysis solves problems of Miller theorem/approximation that fail to predict a pole-splitting and that require an impractical assumption that an initial lower frequency pole before connecting a Miller capacitor in a two-stage amplifier should be associated with the input of the amplifier. Since the proposed analysis sheds light on how the closed-loop poles originate from the open-loop poles in the s-plane, it allows the association of the closed-loop poles with the circuit components and thus provides a design insight for frequency compensation. The circuits analyzed are two-stage Miller-compensated amplifiers with and without a current buffer and a three-stage nested Miller-compensated amplifier

A Thermo-Mechanical Properties Evaluation of Multi-Directional Carbon/Carbon Composite Materials in Aerospace Applications

Carbon/carbon (C/C) composite materials are widely used in aerospace structures operating in high temperature environments based on their high performance thermal and mechanical properties. The C/C composite material has a yarn architecture in which fiber bundles in different directions cross each other, and it is also divided into architecture types, such as 3-D orthogonal, 4-D in-plane, and 4-D diagonal, according to the arrangement of the fiber bundles. The thermo-mechanical performance of the carbon/carbon composite material may vary depending on the yarn architecture, and the material properties are also tailored according to constituent materials, such as fiber and matrix, and manufacturing parameters, such as yarn size, yarn spacing, and fiber volume fraction. In this paper, three types of geometric models are defined for repeating unit cells (RUCs), according to the yarn architecture of the C/C composite material, and the effective stiffness was predicted by applying the iso-strain assumption and stress averaging technique. In addition, the thermo-mechanical characteristics according to the yarn architecture and fiber volume fraction of RUC were compared and evaluated

Discrete Sine Transform-Based Interpolation Filter for Video Compression

Fractional pixel motion compensation in high-efficiency video coding (HEVC) uses an 8-point filter and a 7-point filter, which are based on the discrete cosine transform (DCT), for the 1/2-pixel and 1/4-pixel interpolations, respectively. In this paper, discrete sine transform (DST)-based interpolation filters (DST-IFs) are proposed for fractional pixel motion compensation in terms of coding efficiency improvement. Firstly, a performance of the DST-based interpolation filters (DST-IFs) using 8-point and 7-point filters for the 1/2-pixel and 1/4-pixel interpolations is compared with that of the DCT-based IFs (DCT-IFs) using 8-point and 7-point filters for the 1/2-pixel and 1/4-pixel interpolations, respectively, for fractional pixel motion compensation. Finally, the DST-IFs using 12-point and 11-point filters for the 1/2-pixel and 1/4-pixel interpolations, respectively, are proposed only for bi-directional motion compensation in terms of the coding efficiency. The 8-point and 7-point DST-IF methods showed average Bjøntegaard Delta (BD)-rate reductions of 0.7% and 0.3% in the random access (RA) and low delay B (LDB) configurations, respectively, in HEVC. The 12-point and 11-point DST-IF methods showed average BD-rate reductions of 1.4% and 1.2% in the RA and LDB configurations for the Luma component, respectively, in HEVC

An inference method from multi-layered structure of biomedical data

Abstract Background Biological system is a multi-layered structure of omics with genome, epigenome, transcriptome, metabolome, proteome, etc., and can be further stretched to clinical/medical layers such as diseasome, drugs, and symptoms. One advantage of omics is that we can figure out an unknown component or its trait by inferring from known omics components. The component can be inferred by the ones in the same level of omics or the ones in different levels. Methods To implement the inference process, an algorithm that can be applied to the multi-layered complex system is required. In this study, we develop a semi-supervised learning algorithm that can be applied to the multi-layered complex system. In order to verify the validity of the inference, it was applied to the prediction problem of disease co-occurrence with a two-layered network composed of symptom-layer and disease-layer. Results The symptom-disease layered network obtained a fairly high value of AUC, 0.74, which is regarded as noticeable improvement when comparing 0.59 AUC of single-layered disease network. If further stretched to whole layered structure of omics, the proposed method is expected to produce more promising results. Conclusion This research has novelty in that it is a new integrative algorithm that incorporates the vertical structure of omics data, on contrary to other existing methods that integrate the data in parallel fashion. The results can provide enhanced guideline for disease co-occurrence prediction, thereby serve as a valuable tool for inference process of multi-layered biological system

Pif: In-flash acceleration for data-intensive applications

© 2022 ACM.To minimize unnecessary data movements from storage to a host, processing-in-storage (PiS) techniques, which move a compute unit to storage, have been proposed. In this position paper, we propose an extreme version of PiS solutions, called a processing-in-flash (PiF) scheme, that moves computation inside flash chips where data are physically present. As a key building block of a PiF solution, we present a novel flash chip architecture, CoX. Using a prototype PiF SSD based on CoX chips, we demonstrate that PiF-based SSDs are promising in accelerating data-intensive applications.N

Inference on chains of disease progression based on disease networks.

MOTIVATION:Disease progression originates from the concept that an individual disease may go through different changes as it evolves, and such changes can cause new diseases. It is important to find a progression between diseases since knowing the prior-posterior relationship beforehand can prevent further complications or evolutions to other diseases. Furthermore, the series of progressions can be represented in the form of a chain, which enables us to readily infer successive influences from one disease to another after many passages through other diseases. METHODS:In this paper, we propose a systematic approach for finding a disease progression chain from a source disease to a target one via exploring a disease network. The network is constructed based on various sets of biomedical data. To find the most influential progression chains, the k-shortest path search algorithm is employed. The most representative algorithms such as A*, Dijkstra, and Yen's are incorporated into the proposed method. RESULTS:A disease network consisting of 3,302 diseases was constructed based on four sources of biomedical data: disease-protein relations, biological pathways, clinical history, and biomedical literature information. The last three sets of data contain prior-posterior information, and they endow directionality on the edges of the network. The results were interesting and informative: for example, when colitis and respiratory insufficiency were set as a source disease and a target one, respectively, five progression chains were found within several seconds (when k = 5). Each chain was provided with a progression score, which indicates the strength of plausibility relative to others. Similarly, the proposed method can be expanded to any pair of source-target diseases in the network. This can be utilized as a preliminary tool for inferring complications or progressions between diseases

Topology control method using adaptive redundant transmission range in mobile wireless sensor network

In this paper, we simulate the effect of RTR (Redundant Transmission Range) which is used to maintain network connectivity in mobile wireless networks such as ad-hoc or sensor networks. The simulation result shows that the RTR scheme greatly increases network connectivity time. Based on the simulation result, we propose an A-RTR (Adaptive-RTR) algorithm. A-RTR use variable RTR as node's moving speed and neighbors' speed. This algorithm can be used any topology control algorithms and prolong the network connectivity time in mobility environment. Simulation results show good performance not only the network connectivity but also node's energy consumption

Novel method of imaging and parameter estimation for moving targets with single-channel SAR

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Lens-free reflective topography for high-resolution wafer inspection

Abstract The demand for high-resolution and large-area imaging systems for non-destructive wafer inspection has grown owing to the increasing complexity and extremely fine nature of semiconductor processes. Several studies have focused on developing high-resolution imaging systems; however, they were limited by the tradeoff between image resolution and field of view. Hence, computational imaging has arisen as an alternative method to conventional optical imaging, aimed at enhancing the aforementioned parameters. This study proposes a method for improving the resolution and field of view of an image in a lens-less reflection-type system. Our method was verified by computationally restoring the final image from diffraction images measured at various illumination positions using a visible light source. We introduced speckle illumination to expand the numerical aperture of the entire system, simultaneously improving image resolution and field of view. The image reconstruction process was accelerated by employing a convolutional neural network. Using the reconstructed phase images, we implemented high-resolution topography and demonstrated its applicability in wafer surface inspection. Furthermore, we demonstrated an ideal diffraction-limited spatial resolution of 1.7 μm over a field of view of 1.8 × 1.8 mm2 for the topographic imaging of targets with various surface roughness. The proposed approach is suitable for applications that simultaneously require high throughput and resolution, such as wafer-wide integrated metrology, owing to its compact design, cost-effectiveness, and mechanical robustness