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In this paper, we will first explain the FS (familiarity and strangeness) model as a requirement for attracting people's attention and bringing about analogical thinking. After introducing the idea of shikake (triggers for behavior change) and its requirements, we propose the inclusion of the FS model as an attribute of MoDAT in order to encourage MoDAT participants to come up with new shikake ideas.
The paper introduces the research of tube-type bottle defects detection algorithm based on machine vision system, and the implementation method of detection system using machine vision and digital image processing technology. Industrial camera is used to collect the image of tube-type bottle, then the image is processed and analyzed by image processing technology. On this basis, by comparing with...
Neodymium, cerium and lanthanum are commonly used critical rare earth elements in the last years. This study analyzes environmental impacts that may occur mainly from neodymium (Ne), cerium (Ce) and lanthanum (La) obtained from secondary sources, derived from the New Kankberg (Sweden) flotation tailings case study. The possibilities of extraction of Ne, Ce and La using magnetic separation can be reached...
Blast furnace (BF) ironmaking process is a typical complex nonlinear industrial process. Aiming at the problem that the relationship between the operating parameters and the main production indicators in BF ironmaking process mainly depends on the subjective experience of the specialized operators and experts, and is difficult to be inherited and studied later, this paper introduces data mining technology...
This work studies a data-driven methodology for detecting systematic defects using layout-aware scan diagnosis data. As part of volume diagnosis, this methodology focuses on ranking the most systematic defective signatures, while possible random defects are also present in the wafer. The main analysis components utilize χ2 Independence Tests to establish systematic relationships between reported defective...
The aim of this paper is to show the strengths and the weakness of process mining tools in post-delivery validation. This is illustrated on two use-cases from a real-world system. We also indicate what type of research has to be done to make process mining tools more usable for validation purposes.
In this paper, we present an impression estimation method for television commercials with a visualization method. Our method estimates the impressions viewers might have of a new proposal for a TV commercial written in text as weighted favorable factors and visualizes the estimated favorable factors. During the production of TV commercials, it is important to create commercials that clearly communicate...
Log analysis plays an important role for computer failure diagnosis. With the ever increasing size and complexity of logs, the task of analyzing logs has become cumbersome to carry out manually. For this reason, recent research has focused on automatic analysis techniques for large log files. However, log messages are texts with certain formats and it is very challenging for automatic analysis to...
Increased competition and customer' expectations forces industries (1st) to react more quickly and agile to marked trends, (2nd) to shorten their product release cycles, and (3rd) to create innovative and intelligent products able to self-adapt to their owners' or licensee' requirements depending on the current context. This paper presents (1st) an overview of a novel ICT engineering platform for...
Tapioca starch is the important for Thai agricultural industry economy. According to the 4th industrial revolution, cyber-physical system becomes the key technology to enable vertical and horizontal automation system integration. This study aims to develop cyber-physical system based production monitoring for tapioca starch production. To achieve the service oriented architecture (SOA) based solution...
Surgical workflow modeling is becoming increasingly useful to train surgical residents for complex surgical procedures. Rule-based surgical workflows have shown to be useful to create context-aware systems. However, manually constructing production rules is a time-intensive and laborious task. With the expansion of new technologies, large video archive can be created and annotated exploiting and storing...
This paper presents a clustering based data mining method for determining the typical wind power profiles and also to estimate the share of wind power from the total power required by the electrical power system in one year. The proposed method was tested using a real data set with information's about power produced in one year (2016), in Romania. The results demonstrate the efficiency of the methodology...
Detecting execution anomalies is very important to monitoring and maintenance of cloud systems. People often use execution logs for troubleshooting and problem diagnosis, which is time consuming and error-prone. There is great demand for automatic anomaly detection based on logs. In this paper, we mine a time-weighted control flow graph (TCFG) that captures healthy execution flows of each component...
The aim of this paper is to examine possibilities for the initial data analyses of the failure data from industrial production process. To perform the initial data analysis of the data from production process we have used graphical statistical method and also data mining methods like drill-down analysis and cluster analysis. Before applying mentioned techniques and methods it was necessary to know...
This article details a practical technique that safely reconciles the production stability and integrity of the HathiTrust Digital Library (HTDL) with the riskier and potentially disruptive experimental functionalities created by the HathiTrust Research Center. Web systems produced by HTRC are necessarily more speculative and, understandably, operate on equipment outside of the HTDL production environment...
Deep cone thickener control problem is a key point of Tailings paste fill (TSF). This paper presents a new method to extract inherent and practical parameters of the thickener, and determine control strategy based on thickening process data mining. Bypassing difficulty in deep cone thickener modeling, the proposed method could obtain practical control rules, also has good adaptability to different...
In the production process of hydrometallurgy, the concentration and flow rate of the slurry in the dehydration and mixing process have an important influence on the leaching process. However, due to the lack of online hardware analyzers in the dehydration and mixing process, it is difficult to realize the automatic control of the concentration and flow rate of the slurry and the artificial control...
Over the last two decades, manufacturing across the globe has evolved to be more intel-ligent and data driven. In the age of industrial Internet of Things, a smart production unit can be perceived as a large connected industrial system of materials, parts, machines, tools, inventory, and logistics that can relay data and communicate with each other. While, traditionally, the focus has been on machine...
A good understanding of the practices followed by software development projects can positively impact their success — particularly for attracting talent and on-boarding new members. In this paper, we perform a cluster analysis to classify software projects that follow continuous integration in terms of their activity, popularity, size, testing, and stability. Based on this analysis, we identify and...
This study explores the application of artificial intelligence on the causal relationship between mining production index and electricity load. The data used is the total mining production index and total electricity consumption in the mining sector sampled on a monthly basis from January 1985 to December 2011 in South Africa. Optimally-pruned and basic extreme learning machines were used to develop...
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