Real time forecasting of the Bay of Bengal cyclonic storm “RASHMI” of October 2008 – A statistical-dynamical approach

A four-step statistical-dynamical approach is applied for real time forecasting of the Bay of Bengal cyclonic storm “RASHMI” of October 2008 which made landfall near Khepupara (Bangladesh) around 2200 UTC of 26 October 2008. The four-step approach consists of (a) Analysis of Genesis Potential Parameter (GPP), (b) Track prediction, (c) Intensity Prediction by Statistical Cyclone Intensity Prediction (SCIP) model and (d) Prediction of decaying intensity after the landfall. The results show that the analysis of Genesis Potential Parameter (GPP) at early stages of development strongly indicated that the cyclone “RASHMI” had enough potential to reach its cyclone stage. The 48 hours landfall forecast position error based on 0000 UTC on 25 October shows that the error varies from around 10 km to 95 km and landfall time error varies from 12 hours early to 23 hours delay by different numerical models (NWP). The consensus forecast (ensemble) based on these NWP models shows that landfall forecast position error is around 10 km and landfall time error is around 2 hours delay. The updated 24 hours forecast based on 0000 UTC of 26 October shows improvement in the forecast. The model predicted landfall position error varies from around 10 km to 55 km with landfall time 6 hours early to 3 hours delay. The Multiple Model Ensemble (MME) forecast shows that the landfall forecast position is close to observed landfall point and the landfall time is early by 2 hours. The JMA (Japan Meteorological Agency) and ensemble forecasts are found to be consistent both in terms of 24-hourly forecasts position, landfall point and landfall time. The 12–hourly intensity prediction up to 24 hours forecasts based on 0000 UTC on 26 October show that the model (SCIP) could pick up the intensification of the cyclone. The model forecasts till the landfall point show that there is an underestimation of intensity by 2 knots and 8 knots at 12 hour and 24 hour forecasts respectively. The 6-hourly decaying intensity forecast after the landfall shows an overestimation of 6 knots and 10 knots at 6-hour and 12-hour forecasts respectively. The approach provided useful guidance to the forecasters for real time forecasting of the cyclone.

Investigating the Immediate Influence of Moderate Pedal Exercises during an Assembly Work on Performance and Workload in Healthy Men

Physical inactivity has increased in prevalence among adults in industrialized and developing countries owing to the fact that the majority of job situations require individuals to remain seated for extended periods of time. This research aims to evaluate the influence of cycling on a stationary bike while executing a keyboard assembly task on the task completion time, error percentage, and physiological and subjective measurements. The physiological measures were electroencephalography (EEG) and electrocardiographic (ECG) signal responses, whereas the subjective measures were subjective workload ratings and subjective body discomforts. Two variables were evaluated, namely assembly methods (with versus without pedal exercises at a moderate intensity) and session testing (pre- versus post-test). Thus, the repeated measures design (i.e., assembly method by session testing of participants) was used. According to the completion time, error %, participant self-reports, and ECG and EEG statistical analysis data, the participants’ performances in the keyboard assembly task did not decrease while they performed pedaling exercises (p > 0.05). Additionally, when participants completed the assembly task while executing the pedaling exercises, the mean inter-beat (RR) intervals significantly reduced (p < 0.05) while the mean heart rate increased (p < 0.05), which mean that pedaling exercises caused physical workloads on the participants. Participant performance was unaffected by performing a workout while performing the assembly activity. Thus, administrations should encourage their employees to engage in short sessions of moderate-intensity exercise similar to the suggested exercise in the study to improve a person’s physical health during work without interfering with the effectiveness of work.

Load Test pada Microservice yang menerapkan CQRS dan Event Sourcing

Load Test on Microservice implementing CQRS and Event Sourcing. In developing an application, determining the architecture is a very important job. This research implements microservice architecture with CQRS pattern and event sourcing on OpenAPI, API-driven and event-driven integration between services. Applying the right architecture can make the performance of the application faster. There are two test activities that are useful to find out the difference in the frequency of requests for APIdriven and event-driven that can affect response time, error rate and throughput, as well as analyze which architecture has better performance. The test is carried out using a load test technique using the JMeter tool. This study proves that microservices with CQRS and Event Sourcing patterns have 3.7% faster performance compared to API-driven, and communication between services has no effect on error rate and throughput. Keywords: microservice, load test, CQRS, event sourcing, software architecture Abstrak. Dalam pengembangan sebuah aplikasi, penentuan arsitektur merupakan pekerjaan yang sangat penting. Penelitian ini mengimplementasikan arsitektur microservice dengan pola CQRS dan event sourcing pada OpenAPI, integrasi antar service berbasis API-driven dan event-driven. Penerapan arsitektur yang tepat dapat membuat performansi dari aplikasi menjadi lebih cepat. Terdapat dua aktivitas pengujian yang berguna untuk mengetahui perbedaan frekuensi request pada API-driven dan eventdriven yang dapat mempengaruhi response time, error rate dan juga throughput, serta menganalisis arsitektur mana yang memiliki performa yang lebih baik. Pengujian dilakukan dengan teknik load test yang menggunuakan tool JMeter. Penelitian ini membuktikan bahwa microservice dengan pola CQRS dan Event Sourcing memiliki performansi lebih cepat 3,7% dibandingkan dengan API-driven, serta komunikasi antar service tidak berpengaruh pada error rate dan throughput.Kata Kunci: microservice, load Test, CQRS, event sourcing, software arsitektur

VIRTUAL COMMISSIONING IN MACHINE TOOL MANUFACTURING: A SURVEY FROM INDUSTRY

Virtual commissioning has acquired a major interest with the introduction of Industry 4.0. It is demonstrated that virtual commissioning can significantly reduce the commissioning time, error rate and costs. However, industry is still experiencing difficulties with the integration of these new technologies. This paper is one of the first empirical surveys conducted in the industry that aims at understanding the challenges and current practices with respect to virtual commissioning, with special focus on the machine tool manufacturing sector. The survey contextualizes the practice of virtual commissioning and the digital twin in industry, and benchmarks the results with academia, in which main gaps are identified. Keywords: empirical survey, virtual commissioning, digital twin, machine tool manufacturing, testing

Low-Cost Multisensor Integrated System for Online Walking Gait Detection

A three-dimensional motion capture system is a useful tool for analysing gait patterns during walking or exercising, and it is frequently applied in biomechanical studies. However, most of them are expensive. This study designs a low-cost gait detection system with high accuracy and reliability that is an alternative method/equipment in the gait detection field to the most widely used commercial system, the virtual user concept (Vicon) system. The proposed system integrates mass-produced low-cost sensors/chips in a compact size to collect kinematic data. Furthermore, an x86 mini personal computer (PC) running at 100 Hz classifies motion data in real-time. To guarantee gait detection accuracy, the embedded gait detection algorithm adopts a multilayer perceptron (MLP) model and a rule-based calibration filter to classify kinematic data into five distinct gait events: heel-strike, foot-flat, heel-off, toe-off, and initial-swing. To evaluate performance, volunteers are requested to walk on the treadmill at a regular walking speed of 4.2 km/h while kinematic data are recorded by a low-cost system and a Vicon system simultaneously. The gait detection accuracy and relative time error are estimated by comparing the classified gait events in the study with the Vicon system as a reference. The results show that the proposed system obtains a high accuracy of 99.66% with a smaller time error (32 ms), demonstrating that it performs similarly to the Vicon system in the gait detection field.