A novel adaptive sampling based methodology for feasible region identification of compute intensive models using artificial neural network

Identification of feasible region of operations in multivariate processes is a problem of interest in several fields. This is particularly challenging when the process model is black-box in nature and/or is computationally expensive, as analytical solutions are not available and the number of possible model evaluations is limited. An efficient methodology is required to identify samples where the model is evaluated for developing a computationally efficient surrogate model. In this work, an artificial neural network based surrogate model is proposed which is integrated with a statistical-based approach (Jack-knifing) to estimate the variance of the surrogate model prediction. This allows implementation of an adaptive sampling approach where new samples are identified close to the feasible region boundary or in regions of high prediction uncertainty. The proposed approach performs better than a previously published kriging based method for different dimensionality case studies.     

An E-Business Event Stream Mechanism for Improving User Tracing Processes

With the rapid development in business transactions, especially in recent years, it has become necessary to develop different mechanisms to trace business user records in web server log in an efficient way. Online business transactions have increased, especially when the user or customer cannot obtain the required service. For example, with the spread of the epidemic Coronavirus (COVID-19) throughout the world, there is a dire need to rely more on online business processes. In order to improve the efficiency and performance of E-business structure, a web server log must be well utilized to have the ability to trace and record infinite user transactions. This paper proposes an event stream mechanism based on formula patterns to enhance business processes and record all user activities in a structured log file. Each user activity is recorded with a set of tracing parameters that can predict the behavior of the user in business operations. The experimental results are conducted by applying clustering-based classification algorithms on two different datasets; namely, Online Shoppers Purchasing Intention and Instacart Market Basket Analysis. The clustering process is used to group related objects into the same cluster, then the classification process measures the predicted classes of clustered objects. The experimental results record provable accuracy in predicting user preferences on both datasets.     

对抗样本生成技术综述

如今,深度学习已被广泛应用于图像分类和图像识别的问题中,取得了令人满意的实际效果,成为许多人工智能应用的关键所在.在对于模型准确率的不断探究中,研究人员在近期提出了“对抗样本”这一概念.通过在原有样本中添加微小扰动的方法,成功地大幅度降低原有分类深度模型的准确率,实现了对于深度学习的对抗目的,同时也给深度学习的攻方提供了新的思路,对如何开展防御提出了新的要求.在介绍对抗样本生成技术的起源和原理的基础上,对近年来有关对抗样本的研究和文献进行了总结,按照各自的算法原理将经典的生成算法分成两大类——全像素添加扰动和部分像素添加扰动.之后,以目标定向和目标非定向、黑盒测试和白盒测试、肉眼可见和肉眼不可见的二级分类标准进行二次分类.同时,使用MNIST数据集对各类代表性的方法进行了实验验证,以探究各种方法的优缺点.最后总结了生成对抗样本所面临的挑战及其可以发展的方向,并就该技术的发展前景进行了探讨.     

Mixture ratio modeling of dynamic systems

Any knowledge extraction relies (possibly implicitly) on a hypothesis about the modelled-data dependence. The extracted knowledge ultimately serves to a decision-making (DM). DM always faces uncertainty and this makes probabilistic modelling adequate. The inspected black-box modeling deals with “universal” approximators of the relevant probabilistic model. Finite mixtures with components in the exponential family are often exploited. Their attractiveness stems from their flexibility, the cluster interpretability of components and the existence of algorithms for processing high-dimensional data streams. They are even used in dynamic cases with mutually dependent data records while regression and auto-regression mixture components serve to the dependence modeling. These dynamic models, however, mostly assume data-independent component weights, that is, memoryless transitions between dynamic mixture components. Such mixtures are not universal approximators of dynamic probabilistic models. Formally, this follows from the fact that the set of finite probabilistic mixtures is not closed with respect to the conditioning, which is the key estimation and predictive operation. The paper overcomes this drawback by using ratios of finite mixtures as universally approximating dynamic parametric models. The paper motivates them, elaborates their approximate Bayesian recursive estimation and reveals their application potential.     

Epidemic contact tracing with smartphone sensors

ABSTRACT

Contact tracing is widely considered as an effective procedure in the fight against epidemic diseases. However, one of the challenges for technology based contact tracing is the high number of false positives, questioning its trust-worthiness and efficiency amongst the wider population for mass adoption. To this end, this paper proposes a novel, yet practical smartphone-based contact tracing approach, employing WiFi and acoustic sound for relative distance estimate, in addition to the air pressure and the magnetic field for ambient environment matching. We present a model combining six smartphone sensors, prioritising some of them when certain conditions are met. We empirically verified our approach in various realistic environments to demonstrate an achievement of up to 95% fewer false positives, and 62% more accurate than Bluetooth-only system. To the best of our knowledge, this paper was one of the first work to propose a combination of smartphone sensors for contact tracing.     

Prism coupling method to evaluate the light extraction efficiency of outcoupling substrates

One of the key challenges in organic light-emitting diodes (OLEDs) for lighting applications is efficient light extraction from the planar, multi-layered OLED stack. Several different light extraction approaches are being explored currently by researchers, however characterizing light extraction films after fabricating OLEDs is not a viable approach when the outcoupling films have large surface roughness and is time consuming as well. Here we apply prism coupling method (PCM), a simple and elegant tool, to characterize outcoupling films. We show the effectiveness of PCM in estimating light extraction efficiency of outcoupling films. PCM can expedite selection and optimization of various light extraction approaches without the need to build OLEDs. The experimental results are corroborated by the optical simulations done using ray tracing method taking into account Mie scattering from wavelength sized spherical inclusions in an outcoupling film.     

四川盆地高石梯-磨溪地区下二叠统气源示踪

以天然气、烃源岩及储层沥青的地球化学特征为主要依据,通过天然气-天然气、储层沥青-烃源岩、天然气-烃源岩3个方面对比,深入探讨四川盆地高石梯-磨溪地区下二叠统天然气来源。研究表明,四川盆地高石梯-磨溪地区下二叠统天然气主要来源于筇竹寺组泥岩。其5项证据分别为:下二叠统天然气乙烷碳同位素小于-30.5‰,甲、乙烷碳同位素倒转是由高演化程度烃源岩所致;多数下二叠统天然气与龙王庙组天然气特征最为相似;GS18,NC1井下二叠统天然气特征与寒武系相似,说明上下层气源一致;高石梯-磨溪地区下二叠统储层沥青地球化学特征与筇竹寺组泥岩最为相似;筇竹寺组泥岩主要为下二叠统供气,这一认识符合干酪根油气生成理论和同位素分馏规律。     

Assessing the impact of non-ideal optical factors on optimized solar dish collector system with mirror rearrangement

An optimized solar dish collector (OPSDC) system was proposed in our previous work, which can achieve excellent the optical efficiency and flux uniformity under ideal optics. On this basis, the impacts of the non-ideal optical factors on the optical performance of OPSDC system with a cylindrical and conical receiver are studied in detail and compared with the conventional solar dish collector (COSDC) system in this paper. Where the non-ideal optical factors considered are relatively comprehensive, including the mirror slope error, tracking error, installation error of the mirror and receiver, and receiver's absorptivity degeneration. An optical model with the non-ideal optical factors is built in detail by the ray tracing method, and the corresponding ray tracing codes are developed and verified by literatures and optical software OptisWorks 2012. The results show that the OPSDC system not only has a significantly smaller peak local concentration ratio (LCR) and non-uniformity factor than the COSDC system under the same non-ideal optical factor, but also has excellent optical performance. This means that OPSDC system can effectively avoid the heat absorber generating high-temperature hot spots, thus significantly improving its working reliability and service lifetime. In addition, the tracking error, installation error of the receiver and mirror all lead to the increase of the peak LCR and non-uniform factor, while the mirror slope error and absorber's absorptivity degeneration are conducive to reducing the peak LCR and non-uniform factor. This work can provide a reference for error control of COSDC system and OPSDC system in manufacturing, installation and operation.     

Automated contact tracing: a game of big numbers in the time of COVID-19

One of the more widely advocated solutions for slowing down the spread of COVID-19 has been automated contact tracing. Since proximity data can be collected by personal mobile devices, the natural proposal has been to use this for automated contact tracing providing a major gain over a manual implementation. In this work, we study the characteristics of voluntary and automated contact tracing and its effectiveness for mapping the spread of a pandemic due to the spread of SARS-CoV-2. We highlight the infrastructure and social structures required for automated contact tracing to work. We display the vulnerabilities of the strategy to inadequate sampling of the population, which results in the inability to sufficiently determine significant contact with infected individuals. Of crucial importance will be the participation of a significant fraction of the population for which we derive a minimum threshold. We conclude that relying largely on automated contact tracing without population-wide participation to contain the spread of the SARS-CoV-2 pandemic can be counterproductive and allow the pandemic to spread unchecked. The simultaneous implementation of various mitigation methods along with automated contact tracing is necessary for reaching an optimal solution to contain the pandemic.     

基于RFID的煤矿井下人车智能安全管理系统的设计与应用

随着RFID技术的不断发展,应用也愈来愈广泛。结合矿井生产的特点提出了基于RFID的煤矿井下人车智能安全管理系统的框架并分析了系统功能、整体方案。实现了煤矿井下的目标监测、跟踪等自动化和信息化管理,为煤矿的安全生产管理提供科学的透明化管理手段。