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.     

CFD modeling of thermal contact resistance between solid contacting surfaces

Heat transfer has considerable applications in different industries such as designing of heat exchanger, nuclear reactor cooling, control system for spacecraft, and designing of microelectronics cooling. As the surfaces of two metals contact each other, this issue becomes so crucial. Thermal contact resistance (TCR) is one of the key physical parameters in heat transfer of mentioned surfaces. Measuring the experimental value of TCR in laboratory is highly expensive and difficult. As an alternative, numerical modeling methods could be engaged. In this study, inverse problem method solution is utilized as a proper method for estimation of TCR value. In this order, three different configurations (flat-flat, flat-cylinder, and cylinder-cylinder) were utilized in two steady and unsteady state conditions to predict the value of TCR. A comparison between the measured values and obtained values from the simulation show the errors for flat-flat, flat-cylinder, and cylinder-cylinder configuration after 10 min from starting the experiment are 4.6074%, 0.1662%, and 0.5622%, respectively. And in steady-state condition, the corresponding errors are 6.06e-3%, 1.506%, and 0.846%, respectively. In conclusion, the final results establish the fact that the inverse problem method solution can predict TCR values between contacting surfaces.     

35CrMo钢组织遗传消除工艺研究

通过对船用长轴类大锻件的热处理工艺研究得知,采用临界区高温侧正火热处理工艺可以有效消除35CrMo钢组织遗传现象,细化晶粒。     

红土镍矿冶金技术研究进展

如今世界经济迅猛发展,金属镍的需求量也在加速增长。人们主要从硫化镍矿和红土镍矿中提炼金属镍。然而硫化镍矿资源因大规模开发而不断减少,红土镍矿未来将成为镍的主要来源。因此研究红土镍矿的高效开发利用,是当今围绕镍资源研究的热点,对实际生产具有重要的现实意义。本文简要介绍了镍的应用、开发红土镍矿的意义、红土镍矿的矿物学特性、红土镍矿世界范围内的储量和分布,并且列举并分析了红土镍矿的各种冶炼工艺及其优点与不足,同时综述了有关红土镍矿研究的新方法,为红土镍矿高附加值综合利用研究提出思路。     

桁架式火星探测器的着陆缓冲特性分析

着陆缓冲机构是着陆器实现行星探测软着陆的关键部位之一,它的缓冲性能直接关系到着陆器是否能安全地在行星表面实现软着陆。根据某院提供的火星着陆器模型,在三维建模软件中建立着陆器的合理简化模型,为了提高分析着陆器软着陆过程冲击响应的准确性,采用MSC公司的Patran/Dytran有限元软件,用瞬态动力学的方法对着陆器的缓冲性能进行分析。仿真结果与试验数据十分吻合,着陆器的缓冲和传力性能良好。因此,采用拉杆缓冲的桁架式火星着陆器是可行的,仿真结果与试验数据也为今后的火星探测提供了参考。     

一种液压摩擦焊机电液系统研究与试验

针对海上石油平台、海底输送管线维修的需要,提供了一种液压摩擦焊机液压和电器系统设计思路,通过参数计算、电液控制系统设计,研发了一种液压摩擦焊机,通过对DH38钢摩擦叠焊单元成型工艺试验,发现焊接接头拉伸强度达到了母材强度的76%以上,验证了液压摩擦焊机的可靠性能,通过该研究的应用,可对海上石油平台、海底输送管线的维修起到积极作用。     

Value stream mapping approach and analytical network process to identify and prioritize production system’s Mudas (case study: natural fibre clothing manufacturing company)

The current research has been done to identify and prioritize the Mudas of the production line of a natural fibre clothing manufacturing company; in this way, value stream mapping has been used to identify the Mudas, then analytical hierarchy method has been used to screen the Mudas. In the first step, necessary information to design value stream of production process has been obtained by observation, measurement and interview; afterward, according to the obtained information and by forming a focus group, Mudas in the production line have been identified and prioritized according to seven categories of Mudas. In order to prioritizing the Mudas by the usage of analytical hierarchy method, the Super Decision software has been applied. Then, according to the obtained priorities, suggested map of the future value system has been drawn and some suggestions have been presented to eliminate Mudas and move towards the lean manufacturing.     

Patient involvement in Danish hospital design

This paper examines patient-involvement in the process used to design new hospitals. Denmark is in the midst of a phase of hospital building. This recent experience is studied by means of expert interviews with senior practitioners involved in three projects. Examined thematically, the data covers the structure of the design process, identification and ranking of stakeholders, the methods of user-involvement and approaches to accessibility. The paper adds new insight on an under-studied area, design for hospitals and makes recommendations for a change of approach to user-participation in their design. It highlights the difficulties in applying the methods of user-centred design and Design for All in large projects.     

Optimal inspection for randomly triggered hidden deterioration processes

This paper deals with degradation processes whose onset is triggered at a random time and which stay hidden until they are discovered through inspection or when they begin to show symptoms. This is applicable in many healthcare and industrial scenarios, for example, in the modeling of breast cancer or termite infestation. In our model, we assume that symptoms appear after hitting a random critical threshold and that inspections may have a sensitivity less than one as well as a nonzero false positive rate. The expected cost of repair is derived, and the inspection rate is optimized for a cycle (which lasts from degradation-free to repaired state). This gives results for three cases: the first is for a finite observation period with no degradation recurrence, the second for infinite time horizon allowing recurrence. In the third case, we derive an upper bound for the expected cost in a given constant time period. Finally, the model is applied to determine the optimal strategy for breast cancer screening with regard to the effects of different parametrizations.