THE GWAC DATA PROCESSING AND MANAGEMENT SYSTEM

GWAC will have been built an integrated FOV of 5,000 degree2 and have already built 1,800 square degree2. The limit magnitude of a 10-second exposure image in the moonless night is 16R. In each observation night, GWAC produces about 0.7TB of raw data, and the data processing pipeline generates millions of single frame alerts. We describe the GWAC Data Processing and Management System (GPMS), including hardware architecture, database, detection-filtering-validation of transient candidates, data archiving, and user interfaces for the check of transient and the monitor of the system. GPMS combines general technology and software in astronomy and computer field, and use some advanced technologies such as deep learning. Practical results show that GPMS can fully meet the scientific data processing requirement of GWAC. It can online accomplish the detection, filtering and validation of millions of transient candidates, and feedback the final results to the astronomer in real-time. During the observation from October of 2018 to December of 2019, we have already found 102 transients.

A Timeline Optimization Approach of Green Requirement Engineering Framework for Efficient Categorized Natural Language Documents in Non-Functional Requirements

The system's functional requirements (FR) and non-functional requirements (NFR) are derived from the software requirements specification (SRS). The requirement specification is challenging in classification process of FR and NFR requirements. To overcome these issues, the work contains various significant contributions towards SRS, such as green requirements engineering (GRE), to achieve the natural language processing, requirement specification, extraction, classification, requirement specification, feature selection, and testing the quality attributes improvement of NFRs. In addition to this, the test pad-based quality study to determine accuracy, quality, and condition providence to the classification of non-functional requirements (NFR) is also carried out. The resulted classification accuracy was implemented in the MATLAB R2014; the resulted graphical record shows the efficient non-functional requirements (NFR) classification with green requirements engineering (GRE) framework.

Identification, evaluation and minimization of industrial risks relating to gas pipelines

The security of the functioning systems represents, through the four specific components (security, availability, reliability and maintenance), a basic component of the processing requirement. Monitoring of all specific intrinsic and operating parameters of oil and gas pipelines can be technically detected and diagnosed by: –existing defects; –rapid and effective intervention to eliminate the damage, if they occurred. To establish the maintenance programs that can ensure the proper functioning of the gas pipelines, it is necessary to establish their technical status. The research done helps reduce the risk of gas pipeline damage.

Characterization of the Microstructure and Bonding Properties of Zirconium-Carbon Steel Clad Materials by Explosive Welding

An investigation was carried out to characterize the microstructure and bonding properties of the zirconium-carbon steel explosive clad. The microstructure and the composition of the clad were characterized using optical microscopy and scanning electron microscopy. Bonding properties were inspected by using bending and shearing tests. The examination results indicate that the R60702 and Cr70 plates were joined successfully without visible defects. The interface wave is symmetrical. There is no element diffusion across the interface of the clad plate. There are melt blocks at the interface. Bending and shearing test results indicate that the bonding properties of the clad meet the requirements of the ASTM B898 specification. And after shell rolling, no delamination appeared at the interface. Thus, it indicates that the clad plates have good bonding quality and meet the processing requirement.

Classification of Pneumonia images on mobile devices with Quantized Neural Network

This paper presents an approach for the classification of child chest X-ray images into two classes: pneumonia and normal. We employ Convolutional Neural Networks, from pre-trained networks together with a quantization process, using the platform TensorFlow Lite method. This reduces the processing requirement and computational cost. Results have shown accuracy up to 95.4% and 94.2% for MobileNetV1 and MobileNetV2, respectively. The resulting mobile app also presents a simple and intuitive user interface.

Recent Patents on the Electrode Structures and Electrode Materials in EDM Process

Backgroun: Electrical Discharge Machining (EDM) technology is widely applied for micro- manufacturing of difficult-to-process materials and complex shapes, which causes a growing demand for tool electrodes. The machining performance of an electrode eventually affects machining efficiency and accuracy and electrode loss of EDM. Thus, more researches on the electrode structures and electrode materials in the EDM process are gradually conducted. Objective: To meet the growing processing requirement of processing efficiency and accuracy and electrode loss of EDM, the electrode structures and electrode materials in the EDM process are continuously improved. Methods: This paper retraces various current representative patents relative to the electrode structures and electrode materials in the EDM process. Results: Through comparing the characteristics of different electrode structures and electrode materials in the EDM process, the current principal problems such as low machining efficiency and accuracy and serious electrode loss are concluded. Furthermore, the future development tendencies of electrode structures and electrode materials of EDM are discussed. Conclusion: The optimization of electrode structures and electrode materials in the EDM process is conducive to solve the problems of machining efficiency and accuracy and electrode loss during EDM. More correlative patents on electrode structure and electrode material will be filed in the future.

IDENTIFICATION, EVALUATION AND MINIMIZATION OF INDUSTRIAL RISKS RELATING TO OIL PIPELINES

The security of the functioning systems represents, through the four specific components (security, availability, reliability and maintenance), a basic component of the processing requirement. Monitoring of all specific intrinsic and operating parameters of oil and gas pipelines can be technically detected and diagnosed by: • existing defects. • rapid and effective intervention to eliminate the damage, if they occurred. To establish the maintenance programs that can ensure the proper functioning of the oil pipelines, it is necessary to establish their technical status. The research done helps reduce the risk of oil pipeline damage.

Rancang Bangun Piranti Lunak Pengolah Data Pasca Pengujian Terowongan Angin Kecepatan Rendah Indonesia

Data post-processing plays important roles in a wind tunnel test, especially in supporting the validation of the test results and further data analysis related to the design activities of the test objects. One effective solution to carry out the data post-processing in an automated productive manner, and thus eliminate the cumbersome conventional manual way, is building a software which is able to execute calculations and have abilities in presenting and analyzing the data in accordance with the post-processing requirement. Through several prototype development cycles, this work attempts to engineer and realize such software to enhance the overall wind tunnel test activities. Index Terms—software engineering, wind tunnel test, data post-processing, prototype, pseudocode

Application of Grey Model in Intelligent-Control of Micro-Hole Abrasive Flow Machining

In this paper, a control system based on the prediction of processing flow in Abrasive flow machining is designed. In this system,flow is predicted by an improved GM(1,1) model in conformation of background value. Combined with fuzzy control system, it can adapt the pressure to meet the processing requirement automatically. Experiments proved that the improved GM(1,1) model can predict the processing flow accuratly, and the fuzzy control system based on grey prediction can improve the machining accuracy of micro-hole AFM effectively.

OUTSOURCING DECISIONS IN m-MACHINE PERMUTATION FLOW SHOP SCHEDULING PROBLEMS WITH MACHINE-DEPENDENT PROCESSING TIMES

We consider m-machine permutation flow shop problems with an outsourcing option for a special case where each job's processing time equals the job's processing requirement plus a characteristic value of the machine. The objective is to minimize the sum of the performance measure for in-house jobs (the total completion time or the makespan) and the total outsourcing cost. We prove that two problems are polynomially solvable when the number of machines is fixed.