Optimization of silicon solar cell fabrication based on neural network and genetic programming modeling

This study describes techniques for the cascade modeling and the optimization that are required to conduct the simulator-based process optimization of solar cell fabrication. Two modeling approaches, neural networks and genetic programming, are employed to model the crucial relation for the consecutively connected two processes in solar cell fabrication. One model (Model 1) is used to map the five inputs (time, amount of nitrogen and DI water in surface texturing and temperature and time in emitter diffusion) to the two outputs (reflectance and sheet resistance) of the first process. The other model (Model 2) is used to connect the two inputs (reflectance and sheet resistance) to the one output (efficiency) of the second process. After modeling of the two processes, genetic algorithms and particle swarm optimization were applied to search for the optimal recipe. In the first optimization stage, we searched for the optimal reflectance and sheet resistance that can provide the best efficiency in the fabrication process. The optimized reflectance and sheet resistance found by the particle swarm optimization were better than those found by the genetic algorithm. In the second optimization stage, the five input parameters were searched by using the reflectance and sheet resistance values obtained in the first stage. The found five variables such as the texturing time, amount of nitrogen, DI water, diffusion time, and temperature are used as a recipe for the solar cell fabrication. The amount of nitrogen, DI water, and diffusion time in the optimized recipes showed considerable differences according to the modeling approaches. More importantly, repeated applications of particle swarm optimization yielded process conditions with smaller variations, implying greater consistency in recipe generation.     

Driving characteristics of the electrowetting-on-dielectric device using atomic-layer-deposited aluminum oxide as the dielectric

Electrowetting on dielectric (EWOD) is useful in manipulating droplets for digital (droplet-based) microfluidics, but its high driving voltage over several tens of volts has been a barrier to overcome. This article presents the characteristics of EWOD device with aluminum oxide (Al₂O₃, ε _r  ≈ 10) deposited by atomic layer deposition (ALD), for the first time as the high-k dielectric for lowering the EWOD driving voltage substantially. The EWOD device of the single-plate configuration was fabricated by several steps for the control electrode array of 1 mm × 1 mm squares with 50 μm space, the dielectric layer of 1,270 Å thick ALD Al₂O₃, the reference electrode of 20 μm wide line electrode, and the hydrophobic surface treatment by Teflon-AF coating, respectively. We observed the movement of a 2 μl water droplet in an air environment, applying a voltage between one of the control electrodes and the reference electrode in contact with the droplet. The droplet velocity exponentially depending on the applied voltage below 15 V was obtained. The measured threshold voltage to move the droplet was as low as 3 V which is the lowest voltage reported so far in the EWOD researches. This result opens a possibility of manipulating droplets, without any surfactant or oil treatment, at only a few volts by EWOD using ALD Al₂O₃ as the dielectric.     

Content-based image authentication: current status, issues, and challenges

With today’s global digital environment, the Internet is readily accessible anytime from everywhere, so does the digital image manipulation software; thus, digital data is easy to be tampered without notice. Under this circumstance, integrity verification has become an important issue in the digital world. The aim of this paper is to present an in-depth review and analysis on the methods of detecting image tampering. We introduce the notion of content-based image authentication and the features required to design an effective authentication scheme. We review major algorithms and frequently used security mechanisms found in the open literature. We also analyze and discuss the performance trade-offs and related security issues among existing technologies.     

基于OCTEON的千兆入侵防御系统

随着计算机技术和通信技术的进步,网络已经成为我们学习、生活与工作不可或缺的一部分。但是随着安全漏洞的不断被发现与黑客的技,亍及破坏力不断提高,网络安全频繁受到挑战。在基于OCTEON的硬件平台下,设计并实现了一种基于专用多核的千兆入侵防御系统,该系统包含了入侵防御中的数据包预处理、检测以及响应全部组件,实验表明,该系统在千兆环境下具有较好的实用性。     

基于主从多机通信的机器人控制系统开发

为了实现对机器人的实时控制,要求主控制器与各个感应机构和执行机构之间高效稳定的通信;对机器人控制系统的开发,需要设计一种满足实时性和高效性要求的多机通信系统;控制系统采用二级分布式结构,主控制器作为上位机,各传感器和电机内置的微处理器作为下位机;基于AVR单片机的主从多机通信方式,利用半双工的异步串行方式通信;这种数字化的通信方式具有高效,稳定的优点,可以大大简化控制程序的开发;实验证明,应用这种控制系统的小型机器人具有灵活性高、开发周期短且稳定性高的特点.     

一种航空直流固态功率控制器的设计

提出了一种基于嵌入式实时操作系统μC/OS-Ⅱ和CPLD的SSPC设计方案.对整个系统的结构进行了分析,结合分析给出了系统硬件和软件设计方案.硬件设计部分给出了系统的硬件结构原理图,分析了系统性能和各部分功能,并绘出了子系统的设计;软件部分根据μC/OS-Ⅱ系统建立了任务结构框图和系统流程,给出了I2T反时限保护的一种算法,并通过对CPLD的编程实现SSPC的短路保护功能;实验证明这种设计方案具有硬件电路设计简单、实时性好、可靠性高和智能化水平高的优点,符合航空直流固态功率控制器的设计要求.     

电子类专业计算机网络课程实践教学体系

针对电子类专业人才对网络技术的新需求,以该专业的网络应用为背景,从培养具有创新精神的电子类应用型人才角度出发,提出一个电子类专业计算机网络课程的实践教学体系,以提高教学效果和学生的综合应用能力。     

针对SoC系统的Cache攻击方法及建模分析

针对SoC平台,提出并实现了一种高效的基于Cache的AES旁道攻击方法.该方法利用AES软件运行过程中查找表操作泄漏的时间信息,结合AES算法前两轮的特征,快速确定攻击表与AES查找表间的映射关系,并最终恢复出全部128b密钥.基于此攻击方法,在充分考虑各种系统噪声影响的情况下,进一步提出了一种统计分析模型.该模型揭示了上述攻击方法的内在机理,并能够较为准确地估算攻击所需的最小样本数.该模型的重要意义在于不仅可以用来衡量特定SoC系统的抗攻击能力,同时为抗攻击研究指明了方向.     

面向数值型敏感属性的分级l-多样性模型

近年来,数据发布隐私保护问题受到了广泛关注,相继提出了多种隐私保护匿名模型.l-多样性模型是其中保护个体隐私的有效方法,但现有的l-多样性模型只适合处理分类型敏感属性,不适合处理数值型敏感属性.为此,提出面向数值型敏感属性的分级l-多样性模型,包括分级相异l-多样性、分级信息熵l-多样性和分级递归(c,l)-多样性.所提出的模型首先将数值型敏感属性域分级,再基于分级信息实现数值型敏感属性的l-多样性.设计了实现这些模型的l-Incognito算法.并且从匿名表的多样性角度进行了比较,实验表明分级l-多样性表比未分级的l-多样性表具有更高的多样度,因此具有更强的抵制同质性攻击和背景知识攻击的能力.