An investigation into physicochemical characteristics of ash produced from combustion of oil palm biomass wastein a boiler

Ash derived from combustion of Malaysian oil palm biomass (empty fruit bunches consisting of fibers) was physically and chemically characterized in order to provide a comprehensive understanding of its specific properties in terms of toxicity, compositions and reusability. Principal analyses conducted include particle size distribution, scanning electron microscopy, elemental dispersive X-ray, elemental analysis, toxicity characteristic leaching procedure (TCLP) as well as thermogravimetric, X-ray diffractometry and Fourier-transform infrared analyses. TCLP result indicated that the oil palm ash (OPA) should not be classified as toxic wastes in terms of heavy metal leachability since leachable copper, cadmium, lead and nickel concentrations were detected below the stipulated leachability limits. It was determined that the OPA contained high amount of potassium as well as presence of silica which implied its suitability to be reused as crude fertilizer or cement replacement material.     

直觉线性μ-演算中的合成推理

讨论了以基于前缀封闭集合的Heyting代数的直觉解释的线性μ-演算(IμTL)作为描述“假设-保证”的逻辑基础的问题,提出了一个基于IμTL的“假设-保证”规则.该规则比往常应用线性时序逻辑(LTL)作为规范语言的那些规则具有更好的表达能力,扩展了对形如“always ?”等安全性质的“假设-保证”的范围,具备更一般的“假设-保证”推理能力及对循环推理的支持.     

Local calibration of rigid pavement performance models using resampling methods

The performance prediction models in the Pavement-ME design software are nationally calibrated using in-service pavement material properties, pavement structure, climate and truck loadings, and performance data obtained from the Long-Term Pavement Performance programme. The nationally calibrated models may not perform well if the inputs and performance data used to calibrate those do not represent the local design and construction practices. Therefore, before implementing the new M-E design procedure, each state highway agency (SHA) should evaluate how well the nationally calibrated performance models predict the measured field performance. The local calibrations of the Pavement-ME performance models are recommended to improve the performance prediction capabilities to reflect the unique conditions and design practices. During the local calibration process, the traditional calibration techniques (split sampling) may not necessarily provide adequate results when limited number of pavement sections are available. Consequently, there is a need to employ statistical and resampling methodologies that are more efficient and robust for model calibrations given the data related challenges encountered by SHAs. The main objectives of the paper are to demonstrate the local calibration of rigid pavement performance models and compare the calibration results based on different resampling techniques. The bootstrap is a non-parametric and robust resampling technique for estimating standard errors and confidence intervals of a statistic. The main advantage of bootstrapping is that model parameters estimation is possible without making distribution assumptions. This paper presents the use of bootstrapping and jackknifing to locally calibrate the transverse cracking and IRI performance models for newly constructed and rehabilitated rigid pavements. The results of the calibration show that the standard error of estimate and bias are lower compared to the traditional sampling methods. In addition, the validation statistics are similar to that of the locally calibrated model, especially for the IRI model, which indicates robustness of the local model coefficients.     

DVCC-Based Non-linear Feedback Neural Circuit for?Solving System of Linear Equations

A neural circuit to solve a system of simultaneous linear equations is presented. The circuit employs non-linear feedback to achieve a transcendental energy function that ensures fast convergence to the exact solution while enjoying reduction in hardware complexity over existing schemes. A new building block for analog signal processing, the digitally controlled differential voltage current conveyor (DC-DVCC) is introduced and is utilized for the non-linear synaptic interconnections between neurons. The proof of the energy function has been given and it is shown that the gradient network converges exactly to the solution of the system of equations. PSPICE simulation results are presented for linear systems of equations of various sizes and are found to be in close agreement with the algebraic solution. The use of CMOS DC-DVCCs and operational amplifiers facilitates monolithic integration.     

Layout-Specific Circuit Evaluation in 3-D Integrated Circuits

In this paper, we describe a comprehensive layout methodology for bonded three-dimensional integrated circuits (3D ICs). In bonded 3D integration technology, parts of a circuit are fabricated on different wafers, and then, the wafers are bonded with a glue layer of Cu or polymer based adhesive. Using our layout methodology, designers can layout such 3D circuits with necessary information on inter-wafer via/contact and orientation of each wafer embedded in the layout. We have implemented the layout methodology in 3DMagic. Availability of 3DMagic has led to interesting research with a wide range of layout-specific circuit evaluation, from performance comparison of 2D and 3D circuits to layout-specific reliability analyses in 3D circuits. Using 3DMagic, researchers have designed and simulated an 8-bit encryption processor mapped into 2D and 3D FPGA layouts. Moreover, the layout methodology is an essential element of our ongoing research for the framework of a novel Reliability Computer Aided Design tool, ERNI-3D.     

下一代无线网络架构

无线局域网(WLAN)技术为家庭和企业用户描绘了美好的蓝图,也吸引着众多半导体和系统设备厂商涌入这一市场。WLAN技术的不断演变,将标准制订团体、互操作性论坛(互操作性是市场进一步接受的关键要求)、产品OEM厂商和相应的半导体厂商紧密联系在一起。     

Semi-Supervised Deep Learning for Multi-Tissue Segmentation from Multi-Contrast MRI

Journal of Signal Processing Systems - Segmentation of thigh tissues (muscle, fat, inter-muscular adipose tissue (IMAT), bone, and bone marrow) from magnetic resonance imaging (MRI) scans is useful...     

Long Duration Persistent Photocurrent in 3 nm Thin Doped Indium Oxide for Integrated Light Sensing and In-Sensor Neuromorphic Computation

Miniaturization and energy consumption by computational systems remain major challenges to address. Optoelectronics based synaptic and light sensing provide an exciting platform for neuromorphic processing and vision applications offering several advantages. It is highly desirable to achieve single-element image sensors that allow reception of information and execution of in-memory computing processes while maintaining memory for much longer durations without the need for frequent electrical or optical rehearsals. In this work, ultra-thin (<3 nm) doped indium oxide (In₂O₃) layers are engineered to demonstrate a monolithic two-terminal ultraviolet (UV) sensing and processing system with long optical state retention operating at 50 mV. This endows features of several conductance states within the persistent photocurrent window that are harnessed to show learning capabilities and significantly reduce the number of rehearsals. The atomically thin sheets are implemented as a focal plane array (FPA) for UV spectrum based proof-of-concept vision system capable of pattern recognition and memorization required for imaging and detection applications. This integrated light sensing and memory system is deployed to illustrate capabilities for real-time, in-sensor memorization, and recognition tasks. This study provides an important template to engineer miniaturized and low operating voltage neuromorphic platforms across the light spectrum based on application demand.     

Wireless Brain Computer Interface for Smart Home and Medical System

Wireless Personal Communications - The number of aged and disabled people has been increasing worldwide. To look after these people is a big challenge in this era. However, scientists overcome the...