Biomechanical model to predict loads on lumbar vertebra of a tractor operator

A biomechanical model is important for prediction of loads likely to arise in specific body parts under various conditions. The biomechanical model was developed to predict compressive and shear loads at L4/L5 (lumbar vertebra) of a tractor operator seating on seats with selected seat pan and backrest cushion materials. A computer program was written to solve the model for various inputs viz. stature and weight of the tractor operators, choice of operating conditions, and reaction forces from seat pan and backrest cushions. It was observed that maximum compressive and shear forces ranged 943–1367 N and 422–991 N, respectively at L4/L5 of tractor operators steering the tractor with leg and hand control actions and occasionally viewing the implement at back. The compressive forces were maximum (1202–1367 N) with coir based composite seat backrest cushion materials (thickness of 80 mm, density of 47.19 kg/m³) and were minimum (943–1108 N) with high density polyurethane foam (thickness of 44 mm, density of 19.09 kg/m³) for the seats.Relevance to industryThe biomechanical model of a tractor operator is important for theoretical understanding the problem of sitting and is also valuable in prediction of compressive and shear loads at L4/L5 of operator under various operating conditions. It will help in design of tractor seat for operator's comfort.     

An Adaptive Clustering Protocol Using Niching Particle Swarm Optimization for Wireless Sensor Networks

Clustering is an hierarchical topology control method, and it is also an energy‐saving and energy efficient technique that extends the sensor network's lifetime. In this paper, we propose and analyze an adaptive clustering protocol using niching particle swarm optimization (ACP‐NPSO), a protocol architecture that uses NPSO to cluster the wireless sensor networks adaptively and efficiently, thus saving energy, balancing energy consumption and enhancing the system's robustness. The simulation results indicate that our proposed protocol ACP‐NPSO can enhance system lifespan, accelerate the convergence speed, and deliver more data by distributing energy dissipation evenly in the networks.     

Remote operation system for novice tractor drivers for situations where automatic driving is difficult

The development of automated tractors is anticipated to address the problem of a declining and aging agricultural labor force. However, there are numerous situations in which automatic driving is difficult in the field. We developed a remote operation system allowing novice tractor drivers to control a tractor remotely in situations where automatic driving is difficult and evaluated its performance on a real tractor in a field. Our challenge was to design a user interface (UI) that allows novices to comprehend the tractor's status and return the tractor situation where automatic operation is possible. The system's UI is inspired by popular video games. In experiments, even novice tractor drivers with little or no experience driving automobiles or playing video games could remotely control the tractor and till according to the goal line. In addition, the participants dealt with an invisible obstacle by viewing illustrations of the tractor sensor data. The designed UI's operation methods and operator attributes were analyzed. Through the experiment, the following facts were revealed. A method of operation that allows the analog stick to adhere to the mechanical guide results in smooth operation. In addition, the participant's preferred control method depends on his/her gaming experience. Thus, this study clarifies some of the specifications and design guidelines necessary for a novice-friendly remote UI for the remote operation of a tractor.     

Adjustable beam lighting with LED matrix and lens array

An adjustable beam lighting solution is coming widely on demand for different applications with improved energy efficiency, reduced light pollution, or enriched decorative effects. A Matrix Lighting configuration, which mainly consists of a light‐emitting diode matrix and a lens array, is proposed as a promising adjustable beam lighting solution. It easily builds up the source‐target mapping based on the integral imaging principle, and it could adjust the light beam and shape freely and timely. The basic configuration, the general design rules with imaging optics, and the optimization approaches based on ray tracing were presented. An example lighting system consists of a 32 × 32 × RGB light‐emitting diode matrix, and the 8 × 8 Fresnel lens array is demonstrated, which accomplishes a localized lighting with addressable regions for power saving. It can also project colorful patterns on the ground or a wall for atmosphere heightening.     

A methodology for performance/energy consumption characterization and modeling of video decoding on heterogeneous SoC and its applications

To meet the increasing complexity of mobile multimedia applications, SoCs equipping modern mobile devices integrate powerful heterogeneous processing elements among which Digital Signal Processors (DSP) and General Purpose Processors (GPP) are the most common ones. Due to the ever-growing gap between battery lifetime and hardware/software complexity in addition to application’s computing power needs, the energy saving issue becomes crucial in the design of such architectures. In this context, we propose in this paper an end-to-end study of video decoding on both GPP and DSP. The study was achieved thanks to a two steps methodology: (1) a comprehensive characterization and evaluation of the performance and the energy consumption of video decoding, (2) an accurate high level energy model is extracted based on the characterization step.The characterization of the video decoding is based on an experimental methodology and was achieved on an embedded platform containing a GPP and a DSP. This step highlighted the importance of considering the end-to-end decoding flow when evaluating the energy efficiency of video decoding application. The measurements obtained in this step were used to build a comprehensive analytical energy model for video decoding on both GPP and DSP. Thanks to a sub-model decomposition, the developed model estimates the energy consumption in terms of processor clock frequency and video bit-rate in addition to a set of constant coefficients which are related to the video complexity, the operating system and the considered hardware architecture. The obtained model gave very accurate results (R² = 97%) for both GPP and DSP energy consumption. Finally, based on the results emerged from the modeling methodology, we show how one can build rapidly a video decoding energy model for a given target architecture without executing the full characterization steps described in this paper.     

复杂机械产品多Agent协同仿真研究

协同仿真是协同设计过程中的重要组成部分,成为检验、指导和优化设计的重要手段。车辆动力系统是一种典型的复杂机械产品。文章为解决协同仿真中复杂的交互通信问题,以动力系统为例,应用多Agent技术,研究复杂机械产品多Agent协同仿真的模型和方法。在分析了动力系统协同仿真的业务需求的基础上,提出了一种适合动力系统协同仿真的多Agent结构模型,Agent之间的通信方式采用KQML/XML,并以曲轴的静力学分析为例说明实现方法。     

Mass Spectrometric Analysis of Cerebrospinal Fluid Ubiquitin in Alzheimer's Disease and Parkinsonian Disorders

1 Purpose

Dysfunctional proteostasis, with decreased protein degradation and an accumulation of ubiquitin into aggregated protein inclusions, is a feature of neurodegenerative diseases. Identifying new potential biomarkers in cerebrospinal fluid (CSF) reflecting this process could contribute important information on pathophysiology.

2 Experimental design

A developed method combining SPE and PRM‐MS is employed to monitor the concentration of ubiquitin in CSF from subjects with Alzheimer's disease (AD), Parkinson's disease (PD), and progressive supranuclear palsy (PSP). Four independent cross‐sectional studies are conducted, studies 1–4, including controls (n = 86) and participants with AD (n = 60), PD (n = 15), and PSP (n = 11).

3 Results

The method shows a repeatability and intermediate precision not exceeding 6.1 and 7.9%, respectively. The determined LOD is 0.1 nm and the LOQ range between 0.625 and 80 nm . The CSF ubiquitin concentration is 1.2–1.5‐fold higher in AD patients compared with controls in the three independent AD‐control studies (Study 1, p < 0.001; Study 2, p < 0.001; and Study 3, p = 0.003). In the fourth study, there is no difference in PD or PSP, compared to controls.

4 Conclusion and clinical relevance

CSF ubiquitin may reflect dysfunctional proteostasis in AD. The described method can be used for further exploration of ubiquitin as a potential biomarker in neurodegenerative diseases.     

Partial product addition in Vedic design-ripple carry adder design fir filter architecture for electro cardiogram (ECG) signal de-noising application

Design of adder plays a major role in deciding overall performance of system as it is a major building block through generations of design in an innovative design of circuits. In VLSI system and signal processing field applications, various versions of adders are utilized. In applications of signal processing, in recent days, major role is contributed by Finite Impulse Response (FIR) filter. Various authors and papers described its design in a several ways. With the design of effective multiplier, signal denoising application was not explained by any of the existing works. For the generation of partial products, 8-bit multiplier based on a Vedic Mathematics –UrdhvaTiryagbhyam sutra- is proposed in this work. In Vedic multiplier, carry skip method is used for realizing addition of partial product. Four Vedic multipliers of 4 × 4 size are used for designing 8-bit multiplier. Carry skip and UrdhvaTiryagbhyam methods are used for this design. For addition of partial product, this multiplier is designed. Ripple carry adder's logic levels are modified for adding these Vedic multiplier's output. Powerful elimination of ECG noise can be done using this proposed fast FIR filter. In applications of healthcare and biomedical field, they are used. In Vedic design, Ripple Carry Adder (RCA) is used for carrying out partial product addition. Operation of FIR filter with Electro Cardiogram (ECG) signal is done by proposing architecture of FIR filter. It is termed as PPAVD-RCA-FIR and used in de-noising applications. From de-noised signal, Signal to Noise Ratio (SNR), Bit Error Rate (BER) and Mean Square Error (MSE) are computed, which are used for evaluating the performances. When compared with general Vedic multiplier, speed of the proposed design is increased about 13.65% as shown by results.     

Wandering: A Web-based platform for the creation of location-based interactive learning objects

Wandering is an innovative web-based platform that was designed to facilitate outdoor, authentic, and interactive learning via the creation of location-based interactive learning objects (LILOs). Wandering was integrated as part of a novel environmental education program among middle school students. This paper describes the Wandering platform's structural architecture and an evaluation study that was conducted among grade nine students (N = 102) who participated in the innovative educational program. Our goal was to examine students' learning outcomes and experiences while creating LILOs' and providing comments. Findings indicated high motivation among students to use Wandering, not only for completing their school assignment, but also for contributing to the community. Despite the fact that the tagging and commenting tools could have been used more efficiently by students, more than one third of the LILOs received an excellent grad. In addition, our findings indicated that Wandering is a good platform for enhancing 21st century skills, including: engagement with others, personalization, control release, and change adaption.     

A novel high-density dual threshold GNRFET SRAM design with improved stability

We propose a novel single-ended static random access memory (SRAM) design with nine graphene nanoribbon FETs (9-GNRFET) in this paper. Single-ended has an impact on density, delays, static noise margin (SNM) and power consumption. The proposed model is implemented in HSPICE as a library for 16 nm GNRFET technology. This HSPICE-compatible compact model provides accuracy while maintain compactness, and make possible efficient circuit level simulations of futuristic GNRFET-based SRAM cells design. Simulations at low supply voltage of 0.325 V have shown that proposed cell provides power saving 4.8 × as compared to a supply voltage of 0.7 V. The half-select free technique provides bit interleaving architecture, consisting of error-free operations with V_DD down to 325 mV. The proposed architecture implemented in 16 nm low leakage GNRFET technology presents the scalability of these cells near threshed voltage region, which can significantly reduce power consumptions with 0.21µW. The proposed SRAM cell design is based on simulations and results are verified on GNRFET HSPICE-compact model. The proposed cell verified under process variation, and is demonstrated with write-assist, the impact of geometrical liability and adaptive supply voltage scaling.     

Virtualized Web server cluster self-configuration to optimize resource and power use

This work proposes a reusable architecture that enables the self-configuration of a supporting infrastructure for Web server clusters using virtual machines. The goal of the architecture is to ensure service quality, evaluating how broadly it complies with the application's operating restrictions and proportionally acting on the configuration of physical servers (hosts) or virtual machines. In addition, through the rational use of resources, the proposal aims at saving energy. A prototype of the architecture was developed and a performance evaluation carried out with two different resource management approaches. This evaluation shows how fully functional and advantageous the proposal is in terms of using resources, avoiding waste, yet maintaining the application's quality of service within acceptable levels. The architecture also shows to be flexible enough to accept, with a reasonable amount of effort, different resource self-configuration policies.     

物联网云平台ZigBee无线通信网络节点设计

随着科学技术的发展,无线通信技术不断成为当今社会的通信方面的主流发展方向;对于一种可以集所有通讯方式的优点为一体,并且可以实现远距离网络通信传输的方式成为现在通讯技术行业的主要研究方向;而文章根据一种基于ZigBee协议的无线网络通信架构进行研究,设计出一种可以满足当今通信需求的硬件平台;其中应用到ZigBee协议中的短距离传输技术和将其与SPI接口连接完成的一种通信技术手段;最后将ZigBee单片机通过USB接口与计算机相连接完成通信无线传输工作;文章中提出了这种平台设计的软件设计方案和硬件设计方案,并且通过软硬件设计,分析出其所具备的优点和未来发展能力;通过对比试验,得出这种无线传播方式有更好的传播效率和节省能源的优势。     

A novel method for the classification of Alzheimer's disease from normal controls using magnetic resonance imaging

Alzheimer's disease (AD) is the most prevalent form of dementia. Although fewer people, who suffer from AD are correctly and promptly diagnosed, due to a lack of knowledge of its cause and unavailability of treatment, AD is more manageable if the symptoms of mild cognitive impairment (MCI) are in an early stage. In recent years, computer‐aided diagnosis has been widely used for the diagnosis of AD. The main motive of this paper is to improve the classification and prediction accuracy of AD. In this paper, a novel approach is developed to classify MCI, normal control (NC), and AD using structural magnetic resonance imaging (sMRI) from the Alzheimer's disease Neuroimaging Initiative (ADNI) dataset (50 AD, 50 NC, 50 MCI subjects). FreeSurfer is used to process these MRI data and obtain cortical features such as volume, surface area, thickness, white matter (WM), and intrinsic curvature of the brain regions. These features are modified by normalizing each cortical region's features using the absolute maximum value of that region's features from all subjects in each group of MCI, NC, and AD independently. A total of 420 features are obtained. To address the curse of dimensionality, the obtained features are reduced to 30 features using a sequential feature selection technique. Three classifiers, namely the twin support vector machine (TSVM), least squares TSVM (LSTSVM), and robust energy‐based least squares TSVM (RELS‐TSVM), are used to evaluate the classification accuracy from the obtained features. Five‐fold and 10‐fold cross‐validation are used to validate the proposed method. Experimental results show an accuracy of 100% for the studied database. The proposed approach is innovative due to its higher classification accuracy compared to methods in the existing literature.     

云存储系统节能研究综述

云存储系统作为云计算的重要组成部分,是各种云计算服务的基础。但随云存储系统规模的不断扩大和在设计时对能耗因素的忽略,使其日益暴露出高能耗、低效率的问题。因为云存储系统占整个云计算中心能耗的27%～40%,所以无论从降低服务提供商的运营成本,还是从降低能耗以保护环境的角度出发,研究云存储系统中的节能技术都具有很大的现实意义与应用前景。将存储系统中的能耗优化问题分为基于硬件的节能方法与基于调度的节能方法两大类进行讨论;并将基于调度的节能方法分为基于节点调度、基于数据调度和基于缓存预取技术3类进行综合比较;最后,对适应节能的云存储体系结构、节能模式下的QoS保证、节能模式与计算模式的匹配以及纠删码容错技术下的节能研究4个方向进行了展望。     

Application-driven dynamic bandwidth allocation for two-layer network-on-chip design

Network-on-Chip (NoC) architecture has been widely used in many multi-core system designs. To improve the communication efficiency and the bandwidth utilization of NoC for various applications, we firstly propose a table-based algorithm for identifying the dominant flows at runtime. Then a two-layer NoC architecture with an application-driven bandwidth allocation scheme is presented, which is capable of identifying heavy-load dataflows and dynamically reconfiguring point-to-point (P2P) connections to optimize the heavy-load traffic. Experimental results reveal that our design (8 × 8 mesh NoC) achieves 28.5% performance improvement and 25.9% power consumption saving compared to the baseline NoC.     

Facebook and people's state self-esteem: The impact of the number of other users' Facebook friends

The present two experimental studies examined the extent to which upward and downward comparison processes on Facebook influence people's state self-esteem. Participants were exposed to mock-up Facebook profiles of female and male targets with many or few Facebook friends. Participant sex was also included in the experimental design. In Study 1, a 2 (number of Facebook friends) × 2 (profile owner sex) × 2 (participant sex) experimental design was employed. Unexpectedly, the manipulation had no significant impact on people's state self-esteem. In Study 2, it was examined whether there would be a curvilinear relationship between the number of other's Facebook friends and participant's self-esteem, in that exposure to others with many or few Facebook friends increases self-esteem compared to others with a moderate number of Facebook friends. Hence, Study 2 employed a 3 (number of Facebook friends) × 2 (profile owner sex) × 2 (participant sex) between-participants experimental design. However, there was neither a linear nor a curvilinear impact of the number of other's Facebook friends on participant's level of state self-esteem. Both studies also revealed that the effects were not more pronounced when participants were exposed to same-sex rather than other-sex Facebook profiles.     

Parallel protein secondary structure prediction schemes using Pthread and OpenMP over hyper-threading technology

Protein secondary structure prediction has a fundamental influence on today’s bioinformatics research. In this work, tertiary classifiers for the protein secondary structure prediction are implemented on Denoeux Belief Neural Network (DBNN) architecture. Hydrophobicity matrix, orthogonal matrix, BLOSUM62 matrix and PSSM matrix are experimented separately as the encoding schemes for DBNN. Hydrophobicity matrix, BLOSUM62 matrix and PSSM matrix are applied to DBNN architecture for the first time. The experimental results contribute to the design of new encoding schemes. Our accuracy of the tertiary classifier with PSSM encoding scheme reaches 72.01%, which is almost 10% better than the previous results obtained in 2003. Due to the time consuming task of training the neural networks, Pthread and OpenMP are employed to parallelize DBNN in the Hyper-Threading enabled Intel architecture. Speedup for 16 Pthreads is 4.9 and speedup for 16 OpenMP threads is 4 in the 4 processors shared memory architecture. Both speedup performance of OpenMP and Pthread is superior to that of other research. With the new parallel training algorithm, thousands of amino acids can be processed in reasonable amount of time. Our research also shows that Hyper-Threading technology for Intel architecture is efficient for parallel biological algorithms.

水泥企业能源管理系统

分析了水泥企业能源管理系统建设的需求特点和建设原则,提出一种利用OPC技术、基于.NET的多层体系架构技术构建水泥企业能源管理系统的设计方案,并对系统设计原理、系统中的软硬件架构以及系统的功能特点进行了介绍.该系统具有与水泥企业DCS系统（集散式控制系统）、余热发电系统实现数据共享,进行全局性能源平衡分析的特色功能,可为水泥企业合理利用能源、实现节能增效提供数据支撑.     

膜材在LOFT建筑节能设计中的应用设想

近年来,国内LOFT建筑改造发展得如火如荼,然而,绝大多数的案例强调的是LOFT建筑的空间艺术设计,很多人都忽视了LOFT建筑中节能设计的重要性。在全球可持续发展和环境保护的大背景下,发展建筑节能是必需的,文章通过简要分析LOFT建筑的能耗特点,探索膜结构在LOFT建筑节能设计中的各种应用方式,试图最大限度地节省改造资源,节省能源。     

不同政府目标决策下具有奖惩机制的绿色供应链模型

考虑由一个制造商主导和一个零售商跟随的绿色供应链,产品销售量受价格及节能水平影响.运用Stackelberg博弈理论分别构建无奖惩机制和3种有奖惩机制的博弈模型,得到4种情形下的零售价、批发价、产品需求量、节能水平、政府节能奖惩力度及制造商和零售商利润的均衡解.通过比较分析发现:政府的节能奖惩机制不仅能提高产品节能水平,还可以提升全社会福利水平;政府综合考虑企业收益、消费者福利和环保效益的奖惩机制效果最优;奖惩力度与产品市场规模、环境效益系数和节能水平敏感系数正相关,与制造商节能成本投入系数、政府奖惩机制的成本投入系数、制造商单位生产成本和零售商单位销售成本负相关.最后运用数值分析验证模型的有效性.