Monitoring of zero-inflated Poisson processes with EWMA and DEWMA control charts

The zero-inflated Poisson (ZIP) distribution is an extension of the ordinary Poisson distribution and is used to model count data with an excessive number of zeros. In ZIP models, it is assumed that random shocks occur with probability p, and upon the occurrence of random shock, the number of nonconformities in a product follows the Poisson distribution with parameter λ. In this article, we study in more detail the exponentially weighted moving average control chart based on the ZIP distribution (regarded as ZIP-EWMA) and we also propose a double EWMA chart with an upper time-varying control limit to monitor ZIP processes (regarded as ZIP-DEWMA chart). The two charts are studied to detect upward shifts not only in each parameter individually but also in both parameters simultaneously. The steady-state performance and the performance with estimated parameters are also investigated. The performance of the two charts has been evaluated in terms of the average and standard deviation of the run length, and compared with Shewhart-type and CUSUM schemes for ZIP distribution, it is shown that the proposed chart is very effective especially in detecting shifts in p when λ remains in control (IC) and in both parameters simultaneously. Finally, one real example is given to display the application of the ZIP charts on practitioners.     

Studying software logging using topic models

Software developers insert logging statements in their source code to record important runtime information; such logged information is valuable for understanding system usage in production and debugging system failures. However, providing proper logging statements remains a manual and challenging task. Missing an important logging statement may increase the difficulty of debugging a system failure, while too much logging can increase system overhead and mask the truly important information. Intuitively, the actual functionality of a software component is one of the major drivers behind logging decisions. For instance, a method maintaining network communications is more likely to be logged than getters and setters. In this paper, we used automatically-computed topics of a code snippet to approximate the functionality of a code snippet. We studied the relationship between the topics of a code snippet and the likelihood of a code snippet being logged (i.e., to contain a logging statement). Our driving intuition is that certain topics in the source code are more likely to be logged than others. To validate our intuition, we conducted a case study on six open source systems, and we found that i) there exists a small number of “log-intensive” topics that are more likely to be logged than other topics; ii) each pair of the studied systems share 12% to 62% common topics, and the likelihood of logging such common topics has a statistically significant correlation of 0.35 to 0.62 among all the studied systems; and iii) our topic-based metrics help explain the likelihood of a code snippet being logged, providing an improvement of 3% to 13% on AUC and 6% to 16% on balanced accuracy over a set of baseline metrics that capture the structural information of a code snippet. Our findings highlight that topics contain valuable information that can help guide and drive developers’ logging decisions.     

The impact of big data analytics on firms’ high value business performance

Big Data Analytics (BDA) is an emerging phenomenon with the reported potential to transform how firms manage and enhance high value businesses performance. The purpose of our study is to investigate the impact of BDA on operations management in the manufacturing sector, which is an acknowledged infrequently researched context. Using an interpretive qualitative approach, this empirical study leverages a comparative case study of three manufacturing companies with varying levels of BDA usage (experimental, moderate and heavy). The information technology (IT) business value literature and a resource based view informed the development of our research propositions and the conceptual framework that illuminated the relationships between BDA capability and organizational readiness and design. Our findings indicate that BDA capability (in terms of data sourcing, access, integration, and delivery, analytical capabilities, and people’s expertise) along with organizational readiness and design factors (such as BDA strategy, top management support, financial resources, and employee engagement) facilitated better utilization of BDA in manufacturing decision making, and thus enhanced high value business performance. Our results also highlight important managerial implications related to the impact of BDA on empowerment of employees, and how BDA can be integrated into organizations to augment rather than replace management capabilities. Our research will be of benefit to academics and practitioners in further aiding our understanding of BDA utilization in transforming operations and production management. It adds to the body of limited empirically based knowledge by highlighting the real business value resulting from applying BDA in manufacturing firms and thus encouraging beneficial economic societal changes.     

The SAINT observatory subsystem: an open-source intelligence tool for uncovering cybersecurity threats

International Journal of Information Security - Data from Online Social Networks, search engines, and the World Wide Web are forms of unstructured knowledge that are not regularly used in...     

On using reservoir computing for sensing applications: exploring environment-sensitive memristor networks

Abstract

Recently, the SWEET sensing setup has been proposed as a way of exploiting reservoir computing for sensing. The setup features three components: an input signal (the drive), the environment and a reservoir, where the reservoir and the environment are treated as one dynamical system, a super-reservoir. Due to the reservoir-environment interaction, the information about the environment is encoded in the state of the reservoir. This information can be inferred (decoded) by analysing the reservoir state. The decoding is done by using an external drive signal. This signal is optimised to achieve a separation in the space of the reservoir states: Under different environmental conditions, the reservoir should visit distinct regions of the configuration space. We examined this approach theoretically by using an environment-sensitive memristor as a reservoir, where the memristance is the state variable. The goal has been to identify a suitable drive that can achieve the phase space separation, which was formulated as an optimization problem, and solved by a genetic optimization algorithm developed in this study. For simplicity reasons, only two environmental conditions were considered (describing a static and a varying environment). A suitable drive signal has been identified based on intuitive analysis of the memristor dynamics, and by solving the optimization problem. Under both drives the memristance is driven to two different regions of the one-dimensional state space under the influence of the two environmental conditions, which can be used to infer about the environment. The separation occurs if there is a synchronisation between the drive and the environmental signals. To quantify the magnitude of the separation, we introduced a quality of sensing index: The ability to sense depends critically on the synchronisation between the drive and environmental conditions. If this synchronisation is not maintained the quality of sensing deteriorates.     

Discharge Redistribution as a Key Process for Heuristic Optimization of Energy Production with Pumps as Turbines in a Water Distribution Network

Water Resources Management - Water distribution networks often exhibit excess pressure that could lead to extensive leakage and infrastructure damages. While this problem can be mitigated with...     

Ionic liquid mediated surface micropatterning of polymer blends

A polymer of intrinsic porosity (i.e., PIM‐1) has been blended with different ionic liquids (ILs) in order to evaluate the effect of the ILs on the microstructure of the polymer blend. [C₈MIM][Cl], [BMIM][DCa], [BMPyr][DCa], and [BMIM][Tf₂N] have been selected and were mixed with PIM‐1. Polymer blends containing up to 80 wt % of ILs were prepared by a casting method with chloroform as solvent. SEM images show that during the film formation a structuring of the surface appears depending on the nature and the concentration of ILs, with appearance of well‐defined microstructure in the case of [BMIM][Tf₂N] and [BMIM][DCa]. In the case of [BMIM][Tf₂N]/PIM‐1 film, the lower IL concentration induces the denser film with small micropatterns onto the surface. AFM analysis indicates that the ILs are well dispersed on the surface. X‐ray photoelectron spectroscopy, Fourier transform infrared spectroscopy, and water contact angle measurements show that a gradient of IL concentration is observed across the film thickness. It is demonstrated that ILs are versatile co‐solvents for inducing controlled micropatterns in polymer membrane surfaces. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2018 , 135, 46109.     

Road to Next Generation Mobile Networks: An Evolutionary Dynamics Approach

One of the major challenges that mobile operators (MOs) are faced with nowadays is the transition to 4th Generation (4G) mobile communication technologies. The main reason for this lies on the reluctance of MOs to invest in a new technology without being sure about its success. The current paper investigates the decision-making procedures of a MO that wishes to migrate from its current technology type to 4G. Traditionally, the decision of deploying a new technology has been based on the analysis of similar implementations in other countries. However, such approaches can be inefficient and time consuming, as there are discrepancies concerning the technological progress among different countries. To this end, the authors employ evolutionary game theory to model the interactions of the MO’s decisions and the subscribers’ needs, and propose a practical and efficient qualitative model that identifies the circumstances under which the transition towards 4G networking can be facilitated. Specifically, the mathematical foundation of the decision making process is provided and the key role of the charging price and the quality of experience by the subscribers for using 4G connectivity is proven. With the process of 4G deployment still ongoing, this paper aims to present an analysis that can be used supplementary to the decision process of a MO that aims to evolve his network.     

漫湾水电站水库水温分布观测与数学模型计算研究

近年来建设的高坝大库越来越多,下泄低温水的影响日趋严重,对水库下泄低温水的影响和减缓措施的研究应给予关注和不断加强。本文是对已投入运行的漫湾水电站库区的水温结构进行研究。通过2004年2月对漫湾水库进行水温分布现场观测,并辅以三维数值模型计算,获得了较详细的水温分布成果。研究结果表明,漫湾水库的水温结构既不属于典型分层型又不属于完全混合型,应属于局部分层型或过渡型。该成果对于流域梯级水电开发对水环境的影响研究,具有一定的代表性,可用于类比分析研究与漫湾水库条件类似的其它水电站。