Applied data science in patient-centric healthcare: Adaptive analytic systems for empowering physicians and patients

We define the emerging research field of applied data science as the knowledge discovery process in which analytic systems are designed and evaluated to improve the daily practices of domain experts. We investigate adaptive analytic systems as a novel research perspective of the three intertwining aspects within the knowledge discovery process in healthcare: domain and data understanding for physician- and patient-centric healthcare, data preprocessing and modelling using natural language processing and (big) data analytic techniques, and model evaluation and knowledge deployment through information infrastructures. We align these knowledge discovery aspects with the design science research steps of problem investigation, treatment design, and treatment validation, respectively. We note that the adaptive component in healthcare system prototypes may translate to data-driven personalisation aspects including personalised medicine. We explore how applied data science for patient-centric healthcare can thus empower physicians and patients to more effectively and efficiently improve healthcare. We propose meta-algorithmic modelling as a solution-oriented design science research framework in alignment with the knowledge discovery process to address the three key dilemmas in the emerging “post-algorithmic era” of data science: depth versus breadth, selection versus configuration, and accuracy versus transparency.     

Exergy analysis of the diesel pre-reforming solid oxide fuel cell system with anode off-gas recycling in the SchIBZ project. Part I: Modeling and validation

Solid oxide fuel cell (SOFC) systems with anode off-gas recirculation (AGR) and diesel pre-reforming are advantageous because they can operate with the current fuel infrastructure. In the SchIBZ-project, the prototype of such a SOFC system for maritime applications has already been commissioned. In this first paper, we model the system devices to conduct an exergy analysis of this real SOFC plant and validate them with experimental values from experiments in laboratory scale. The results of our simulation agree well with the experimental values. The calculations with the validated results may be closer to the real thermodynamic behavior of such system components than previous literature.     

Plant inspection by using a ground vehicle and an aerial robot: lessons learned from plant disaster prevention challenge in world robot summit 2018

Abstract

In recent years, to prevent accidents and disaster are desired by implementing maintenance and management of facilities, such as conducting periodic inspections with appropriate frequency at plants. However, because the dangerous materials such as flammable gas and explosives is used in a plant, and there are many dangerous places in a plant such as high-temperature environment and high places and narrow spaces, it is desirable to use a remote-controlled robot for safety work and short inspections. Against this background, the Disaster Robotics Category-Plant Disaster Prevention Challenge was held in Japan at the World Robot Summit 2018. Our team was ranked 3rd in this competition, because our strategy of ‘inspection and investigation in cooperation with UGV and UAV’ was effective. In this paper, the competition contents of World Robot Summit 2018 and the robot inspection system that we are studying are explained. And what kind of strategy was challenged and result for these given competition tasks by using our robot system are introduced. And the lessons learned such as advantages and issues in UGV and UAV collaboration work at this competition are described for evaluate a robot investigation system for disaster response and inspection work at plants.     

多层圆片级堆叠THz硅微波导结构的制作

基于微电子机械系统(MEMS)工艺,提出一种多层圆片堆叠的THz硅微波导结构及其制作方法。为了验证该结构在制作THz无源器件中的优势,基于6层圆片堆叠的硅微波导结构,设计了一种中心频率365 GHz、带宽80 GHz的功率分配/合成结构,并对其进行了仿真。研究了制作该结构的工艺流程,攻克了工艺过程中的关键技术,包括硅深槽刻蚀技术和多层热压键合技术,并给出了工艺结果。最终实现了多层圆片堆叠功率分配/合成结构的工艺制作和测试。测试结果表明,尽管样品的插入损耗较仿真值增加3 dB左右,考虑到加工误差和夹具损耗等情况,样品主要技术指标与设计值较为一致。     

基于自适应阈值活动语音检测和最小均方误差对数谱幅度估计的低信噪比降噪算法

针对低信噪比(SNR)环境下传统方法对声信号降噪的局限性，提出了一种联合自适应阈值活动语音检测（VAD）算法和最小均方误差对数谱幅度估计（MMSE-LSA）的实时降噪算法。首先，在VAD算法中通过基于能量概率最大值的概率统计来对背景噪声进行估计，对得到的背景噪声进行实时更新并保存；然后，将实时更新的背景噪声作为MMSE-LSA的参考噪声，并对噪声幅度谱进行自适应更新，最后进行降噪处理。通过在真实场景中对四类声信号进行实验，结果表明，该算法在保证对低SNR声信号的实时处理的情况下，相较于传统MMSE-LSA算法，降噪信号的SNR能够提高10~15 dB，且不存在信号过减的情况，可应用于实际工程。     

数据驱动的机床等待过程节能方法研究

为了降低机床等待过程中的能耗，提出了一种实时数据驱动的机床等待时间预测与节能控制方法。首先，建立了射频识别驱动的生产进度评估方法，并以生产进度数据作为输入，构建了基于堆栈降噪自编码的机床等待时间预测模型；其次，依据预测的机床等待时间，提出了机床状态切换方法，以降低机床能耗；最后，通过一个电梯零部件制造车间的案例分析，表明该方法的预测误差仅为4.1%，同时将机床等待过程能耗降低了57%，实现了制造车间的节能减排。     

Design of an adaptive super-twisting decoupled terminal sliding mode control scheme for a class of fourth-order systems

This paper proposes an adaptive super-twisting decoupled terminal sliding mode control technique for a class of fourth-order systems. The adaptive-tuning law eliminates the requirement of the knowledge about the upper bounds of external perturbations. Using the proposed control procedure, the state variables of cart-pole system are converged to decoupled terminal sliding surfaces and their equilibrium points in the finite time. Moreover, via the super-twisting algorithm, the chattering phenomenon is avoided without affecting the control performance. The numerical results demonstrate the high stabilization accuracy and lower performance indices values of the suggested method over the other ones. The simulation results on the cart-pole system as well as experimental validations demonstrate that the proposed control technique exhibits a reasonable performance in comparison with the other methods.     

New batch and continuous systems for converting hydrogen from water hyacinth

Water hyacinth was the chosen alternative biomass for H₂ production in this study. A batch and a continuous pilot plant systems are proposed. A batch system of 500?ml capacity was developed first for finding an appropriate biomass ratio which was found to be 2.5%wt. Results from the batch system was used to construct a kinetic model of water hyacinth hydrolysis. The same biomass and water ratio was used in the continuous system. Besides water hyacinth, glucose and cellulose?+?lignin biomasses were tested. During processing, temperature, pressure, and electric consumption of the system were recorded. The quality and quantity of gas products were analyzed by gas chromatography (GC). The water hyacinth biomass attained the highest rate of H₂ production (providing energy of 11.43?kWh/mole of glucose). Comparing the batch and continuous pilot systems, the continuous system achieved 2.7 times more H₂ mole% than the batch system did.