Conception of High-Frequency Power Planar Transformer Prototypes Based on FabLab Platform

Conceiving planar magnetic components for power electronic converters is very constraining, especially in the case of prototype development. Indeed, such making requires skills, specific appliances as well as human time for setting up the machine tools and the fabrication process. With the emergence of Fabrication Laboratory (FabLab), conceiving of planar copper foil prototypes becomes more feasible in a shortened time process for engineers and researchers. This paper presents a methodology and process for conceiving power planar transformers with the help of machines and tools that can be found in the usual FabLab.

A Framework for the Study of Persuasion

Persuasion is a vital part of politics—who wins elections and policy disputes often depends on which side can persuade more people. Given this centrality, the study of persuasion has a long history with an enormous number of theories and empirical inquiries. However, the literature is fragmented, with few generalizable findings. I unify previously disparate dimensions of this topic by presenting a framework focusing on actors (speakers and receivers), treatments (topics, content, media), outcomes (attitudes, behaviors, emotions, identities), and settings (competition, space, time, process, culture). This Generalizing Persuasion (GP) Framework organizes distinct findings and offers researchers a structure in which to situate their work. I conclude with a discussion of the normative implications of persuasion. Expected final online publication date for the Annual Review of Political Science, Volume 25 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Development of Advanced Advisory System for Anomalies (AAA) to Predict and Detect the Abnormal Operation in Fired Heaters for Real Time Process Safety and Optimization

As the technology is emerging, the process industries are actively migrating to Industry 4.0 to optimize energy, production, profit, and the quality of products. It should be noted that real-time process monitoring is the area where most of the energies are being placed for the sake of optimization and safety. Big data and knowledge-based platforms are receiving much attention to provide a comprehensive decision support system. In this study, the Advanced Advisory system for Anomalies (AAA) is developed to predict and detect the abnormal operation in fired heaters for real-time process safety and optimization in a petrochemical plant. This system predicts and raises an alarm for future problems and detects and diagnoses abnormal conditions using root cause analysis (RCA), using the combination of FMEA (failure mode and effects analysis) and FTA (fault tree analysis) techniques. The developed AAA system has been integrated with databases in a petrochemical plant, and the results have been validated well by testing the application over an extensive period. This AAA online system provides a flexible architecture, and it can also be integrated into other systems or databases available at different levels in a plant. This automated AAA platform continuously monitors the operation, checks the dynamic conditions configured in it, and raises an alarm if the statistics exceed their control thresholds. Moreover, the effect of heaters’ abnormal conditions on efficiency and other KPIs (key performance indicators) is studied to explore the scope of improvement in heaters’ operation.

Mixed Spectra for Stable Signals from Discrete Observations

This paper concerns the continuous-time stable alpha symmetric processes which are inivitable in the modeling of certain signals with indefinitely increasing variance. Particularly the case where the spectral measurement is mixed: sum of a continuous measurement and a discrete measurement. Our goal is to estimate the spectral density of the continuous part by observing the signal in a discrete way. For that, we propose a method which consists in sampling the signal at periodic instants. We use Jackson's polynomial kernel to build a periodogram which we then smooth by two spectral windows taking into account the width of the interval where the spectral density is non-zero. Thus, we bypass the phenomenon of aliasing often encountered in the case of estimation from discrete observations of a continuous time process.

PERUBAHAN SIFAT FISIK DAN CITA RASA KOPI ARABIKA ASAL BONDOWOSO PADA BERBAGAI TINGKAT PENYANGRAIAN

Arabica coffee from the plantation on the foothill of Ijen-Raung mountains in Bondowoso is well known for its Java Arabica Coffee specialty. The exploration to strengthen the specialty identity is keep going on. This study aims to determine the changes in physical properties and flavor of that arabica coffee during roasting at various times and temperatures of roasting. The aspects of physical properties that were studied include weight to volume ratio, coffee bean dimension, and a color index of RGB (red green blue). The weight-to-volume ratio and color index of RGB decreased as the time and temperature roasting increased. The change in dimension of the coffee bean was caused by roasting also detected, but not dominant signifies the roasting level. This is due to the dimension change of coffee bean in each roasting profile having tiny differences and the dimension of the green bean had high variation. Based on this study, it is known that the roasting with a maximum temperature of 165°C and total time process of 9.5 minutes gives the highest total score of aroma, flavor, acidity, and aftertaste of that arabica coffee.

Well Performance Monitoring Using Management by Exception Rules and Alerts

Wells in Tengiz and Korolev oil fields are equipped with data transmitting devices, which provide real-time process data used by Production engineers for continuous production monitoring and identification of unusual process conditions. Monitoring and analysis of each well performance becomes a tedious process with growing well inventory. Up until recently, real-time data from wellsite transmitters was not used to its full potential to simplify and automate well performance analysis. To improve the quality of daily well performance monitoring and detection of abnormal process conditions, sets of data rules have been developed to create alerts and screens with real-time process data managed by exception. These alerts and screens help to identify malfunctioning equipment and changes in operating conditions. Timely evaluation of critical conditions helps to proactively prepare a mitigation plan and prevent unscheduled well shutdowns. Data management by exception allows automatic filtering of big data sets and draws attention only to wells with deviations from the stable operating regime. Detailed review of highlighted well conditions helps to differentiate between malfunctioning equipment and actual changes in operating conditions. Fast identification of the issues allows taking preventative actions to maintain process stability of each producing well. Implementation of these tools significantly reduced number of unscheduled well shutdowns due to leaks in Surface Controlled Subsurface Safety Valve (SCSSV) hydraulic system and pneumatic valves control system. The screens also help to identify malfunctioning equipment including pressure and temperature gauges, pressure downhole gauges (PDHGs) and multiphase flow meters (MPFMs), as well as flow assurance issues such as hydrate formation. Developed data rules can be useful for any field equipped with data transmitting devices. This paper aims to share the best practices of using real-time operational data analytics to identify malfunctioning equipment, changing operating conditions and other process related issues to maintain stable production process.

AutoCell Systematic Evolution of Ligands by Exponential Enrichment: The Software Designed and Developed for the Automated Screening System of Nucleic Acid Aptamers

Aptamers are a new kind of nano-probes for bioassays and drug delivery, etc. In this paper, software has been developed as an automatic control center for the automated aptamer selecting system which realized the high integration of aptamer selection, data acquisition and processing. This software, applied in windows system, is developed by C# with the Microsoft Visual Studio 2015 integrated developing environment and the database used in this software is implemented using open source relational database MYSQL. According to the requirement analysis, this software realized various important necessary functions including feasible experiment design, auto-control of the hardware, real time process monitoring and efficient data management which perfectly satisfies the users’ demands. During the actual experiment operation, this software worked smoothly and assumed stable serial port communication between it and the hardware, meanwhile, the interaction between the software and MYSQL remained good stability. As a consequence, it is practical and reasonable to apply this software to the automated aptamer selecting system for research.