Computation-Performance Optimization of Convolutional Neural Networks with Redundant Kernel Removal

Deep Convolutional Neural Networks (CNNs) are widely employed in modern computer vision algorithms, where the input image is convolved iteratively by many kernels to extract the knowledge behind it. However, with the depth of convolutional layers getting deeper and deeper in recent years, the enormous computational complexity makes it difficult to be deployed on embedded systems with limited hardware resources. In this paper, we propose two computation-performance optimization methods to reduce the redundant convolution kernels of a CNN with performance and architecture constraints, and apply it to a network for super resolution (SR). Using PSNR drop compared to the original network as the performance criterion, our method can get the optimal PSNR under a certain computation budget constraint. On the other hand, our method is also capable of minimizing the computation required under a given PSNR drop.Comment: This paper was accepted by 2018 The International Symposium on Circuits and Systems (ISCAS

Transcriptomic comparison of the self-pollinated and cross-pollinated flowers of Erigeron breviscapus to analyze candidate self-incompatibility-associated genes

Table S1. Functional annotation of E.breviscapus transcriptome. (XLSX 4281 kb

Evaluations of the BGA Solder Ball Shape by Using Energy Method

Presented herein are the evaluation results of the BGA solder ball shape using energy method, two types of solder, viz. Sn37Pb and Sn80Pb, are selected .The geometry of the solder bump is firstly estimated using free computer software, the Surface Evolver, an interactive program which is an energy-based approach for the study of liquid droplet surfaces shaped by surface tension and other energies. The solder bump is then numerically constructed in a finite element model that simulates a BGA package. The influences of both upper and bottom solder pad radii, the surface tension on the balls, and the external load axially applied to the reflow solders on the stand-off height and the contact angle for both solder materials are investigated. The results show that for both solder materials, the stand-off height remains at a height under some pad radius. The height decreases as both upper and bottom pad radii increase. On the other hand, the contact angle presents a nearly inverse trend with respect to the pad radii. The study of the effect of surface tension reveals that at a constant pad radius, the solder ball stand-off height increases with surface tension; however, the trend becomes saturated eventually. The contact angle decreases as the surface tension becomes large. The trend also tends to be saturated. The results of the effects of axially applied load on the stand-off height and the contact angle show that as the applied load is increased so is the contact angle; nevertheless, the stand-off height becomes shorter

An Optimization Analysis of UBM Thicknesses and Solder Geometry on A Wafer Level Chip Scale Package Using Robust Methods

Wafer level chip scale package (WLCSP) has been recognized providing clear advantages over traditional wire-bond package in relaxing the need of underfill while offering high density of I/O interconnects. Without the underfill, the solder joint reliability becomes more critical. Adding to the reliability concerns is the safety demand trend toward "green'' products on which unleaded material, e.g. lead-free solders, is required. The requirement of lead-free solders on the packages results in a higher reflow temperature profile in the package manufacturing process, in turn, complicating the reliability issue. This paper presents an optimization study, considering the fatigue reliability, for a wafer level chip scale IC package in which a Ti/Cu/Ni UBM is involved. A finite element model is developed for the package. The model employs Sn3.8Ag0.7Cu lead-free solders built on build-up layers with micro-vias. Finite element analyses are performed to study the mechanical behaviors of the package elements in which the solder as well as the UBM is of interest. Firstly, a Surface Evolver program is used to construct the solder based non-solder mask defined (NSMD) pad. Then, multi-purpose finite element software, ANSYStm, is used to create a double symmetric 3-D numerical model to investigate the mechanical behaviors including deformation, stress-strain relation as well as hysteresis loops for temperature cycles. The Garofalo-Arrhenius Creep Model is employed. A modified Coffin-Manson formula is also employed to estimate the fatigue life for the package. Finally, the Taguchi robust analysis is adopted for optimization analysis of UBM thicknesses and solder geometry. Our results show that thicker UBM layers tend to increase the fatigue life while a small solder pad will prolong the fatigue life and as volume increases so does the fatigue life. From the results of Taguchi robust analysis, it is shown that among the factors of UBM layer thickness, solder pad radius and solder volume, the solder volume is the most dominating factor on the fatigue life of the package. The optimal combination of UBM thickness set at 0.0066 mm (level 3), solder pad radius set at 0.10 mm (Level 1), and solder volume set at 0.020 mm3 (Level 3) contributes the greatest fatigue life of 1229 cycles which is 448% gained over our reference package model

A simulation study on the measurement of D0-D0bar mixing parameter y at BES-III

We established a method on measuring the \dzdzb mixing parameter $y$ for BESIII experiment at the BEPCII $e^+e^-$ collider. In this method, the doubly tagged $\psi(3770) \to D^0 \overline{D^0}$ events, with one $D$ decays to CP-eigenstates and the other $D$ decays semileptonically, are used to reconstruct the signals. Since this analysis requires good $e/\pi$ separation, a likelihood approach, which combines the $dE/dx$, time of flight and the electromagnetic shower detectors information, is used for particle identification. We estimate the sensitivity of the measurement of $y$ to be 0.007 based on a $20fb^{-1}$ fully simulated MC sample.Comment: 6 pages, 7 figure

Differentiated QoS Provisioning in Wireless Networks Based on Deep Reinforcement Learning

Wireless networks manage performance by adjusting the contention window, as they cannot directly detect collisions. Traditional contention window adjustment algorithms, such as the Binary Exponential Backoff (BEB) algorithm, may lead to lower throughput when multiple services with varying bandwidth demands coexist. To address this issue, this study aims to enhance network throughput by enabling differentiated bandwidth allocation for various services. Using deep reinforcement learning, the state space, action space, and reward functions are defined to optimize this differentiation. These definitions are integrated into the Deep Deterministic Policy Gradient (DDPG) technique, implemented in the Access Point (AP) to intelligently adjust the contention window. Leveraging DDPG’s capability for continuous actions, the proposed method provides Quality of Service (QoS) differentiation, ensuring that each service at its respective priority level meets its transmission requirements. Compared to the BEB algorithm, the proposed approach offers improved traffic allocation and higher network bandwidth utilization

Eliminating Noise of Mud Pressure Phase Shift Keying Signals with A Self-Adaptive Filter

The feasibility of applying a self-adaptive filter to eliminate noise in the downhole mud pressure phase shift keying (PSK) signals is studied. The self-adaptive filter with carrier wave as the filter input signal and mud pressure PSK signal including noise as the filter expected input signal in structure was adopted to process the mud pressure PSK signals with the broadband signal characteristic in communication. Mathematical model of the filter was built to reconstruct the mud pressure PSK signals based on the evaluation criterion of least mean square error (LMS) and the mathematical model of mud pressure PSK signals. According to the filter mathematical model, a special self-adaptive control algorithm was adopted to realize the filter by adjusting the filter weight coefficients self-adaptively and the impacts of the filter step-size factor on signal to noise ratio (SNR) and distortion factors of the reconstructed mud pressure PSK signals were analyzed. Numerical calculation and simulation show that the self-adaptive filter can efficiently eliminate random noise in the signal frequency band and reconstruct the mud pressure PSK signals. In addition, low distortion factors of the reconstructed mud pressure PSK signals can be obtained by reasonable selecting the filter step-size factor. DOI: http://dx.doi.org/10.11591/telkomnika.v11i6.261

Genomewide association study of leprosy.

BACKGROUND: The narrow host range of Mycobacterium leprae and the fact that it is refractory to growth in culture has limited research on and the biologic understanding of leprosy. Host genetic factors are thought to influence susceptibility to infection as well as disease progression. METHODS: We performed a two-stage genomewide association study by genotyping 706 patients and 1225 controls using the Human610-Quad BeadChip (Illumina). We then tested three independent replication sets for an association between the presence of leprosy and 93 single-nucleotide polymorphisms (SNPs) that were most strongly associated with the disease in the genomewide association study. Together, these replication sets comprised 3254 patients and 5955 controls. We also carried out tests of heterogeneity of the associations (or lack thereof) between these 93 SNPs and disease, stratified according to clinical subtype (multibacillary vs. paucibacillary). RESULTS: We observed a significant association (P<1.00x10(-10)) between SNPs in the genes CCDC122, C13orf31, NOD2, TNFSF15, HLA-DR, and RIPK2 and a trend toward an association (P=5.10x10(-5)) with a SNP in LRRK2. The associations between the SNPs in C13orf31, LRRK2, NOD2, and RIPK2 and multibacillary leprosy were stronger than the associations between these SNPs and paucibacillary leprosy. CONCLUSIONS: Variants of genes in the NOD2-mediated signaling pathway (which regulates the innate immune response) are associated with susceptibility to infection with M. leprae