Validation of photovoltaics powered UPQC using ANFIS controller in a standard microgrid test environment

The power quality improvement becomes one of the important tasks while using microgrid as main power supply. Because the microgrid is combination of renewable energy resources. The renewable energy resources are intermittent in power supply and at the peak loading condition it has to supply the required power. So, the power quality problems may increase in that time. Out of all power quality issues the voltage drop and harmonic distortion is considered as the most serious one. In recent years unified power quality conditioner (UPQC) is emerged as most promising device which compensates both utility as well as customer side power quality disturbances in effective way. The compensating potentiality used in the UPQC is limited by the use of DC link voltage regulation and the conventional proportional integral (PI) controller. In this paper the compensating potentiality of the UPQC device is controlled by an adaptive neuro fuzzy inference system (ANFIS) control and it is powered from the available photovoltaics (PV) power generation. The effect of adding an intelligent UPQC is tested in the standard IEEE-14bus environment. MATLAB 2017b is used here for testing and plotting the simulation results.

Integrated interpretation of pXRF data on ancient nephrite artifacts excavated from Tomb No.1 in Yuehe Town, Henan Province, China

Previous studies of ancient jade using portable X-ray fluorescence (pXRF) have mostly focused on mineral identification, alteration status and provenance determination. It is usually used as an auxiliary instrument for spectroscopic detection with finer resolution. However, there is no substitute for the efficiency and stability of pXRF in-situ non-destructive analysis, which is less affected by the test environment. The scale of the data from the pXRF analysis did not allow for a more in-depth interpretation of ancient jade in the past. In this study, pXRF has been carried out for a total of 112 pieces of nephrite artifacts unearthed from the Yuehe tomb No.1 in Nanyang City, Henan Province, Central China. Certain patterns become clearer as the size of the data increases. The coefficient of variation, cluster analysis and correlation analysis can be used to separate elements into different assemblages, revealing whether the elements are from the primary and impurity minerals of nephrite itself, from the burial microenvironment in the soil, or even from other specific sources. In addition, most of the secondary whitening occurring in the batch of nephrite are accompanied by an increase in Ca content, confirming the previously refuted theory of calcification. More importantly, the principal component analysis of the twin nephrite artifacts suggests visually indistinguishable elemental changes caused by secondary changes, which may lead to misjudgment of ancient nephrite provenance using elemental data.

On the benefits of representation regularization in invariance based domain generalization

A crucial aspect of reliable machine learning is to design a deployable system for generalizing new related but unobserved environments. Domain generalization aims to alleviate such a prediction gap between the observed and unseen environments. Previous approaches commonly incorporated learning the invariant representation for achieving good empirical performance. In this paper, we reveal that merely learning the invariant representation is vulnerable to the related unseen environment. To this end, we derive a novel theoretical analysis to control the unseen test environment error in the representation learning, which highlights the importance of controlling the smoothness of representation. In practice, our analysis further inspires an efficient regularization method to improve the robustness in domain generalization. The proposed regularization is orthogonal to and can be straightforwardly adopted in existing domain generalization algorithms that ensure invariant representation learning. Empirical results show that our algorithm outperforms the base versions in various datasets and invariance criteria.

Navigation Situation Clustering Model of Human-Operated Ships for Maritime Autonomous Surface Ship Collision Avoidance Tests

The collision avoidance system is one of the core systems of MASS (Maritime Autonomous Surface Ships). The collision avoidance system was validated using scenario-based experiments. However, the scenarios for the validation were designed based on COLREG (International Regulations for Preventing Collisions at Sea) or are arbitrary. Therefore, the purpose of this study is to identify and systematize objective navigation situation scenarios for the validation of autonomous ship collision avoidance algorithms. A data-driven approach was applied to collect 12-month Automatic Identification System data in the west sea of Korea, to extract the ship’s trajectory, and to hierarchically cluster the data according to navigation situations. Consequently, we obtained the hierarchy of navigation situations and the frequency of each navigation situation for ships that sailed the west coast of Korea during one year. The results are expected to be applied to develop a collision avoidance test environment for MASS.

An alternative test method for the dual-port SRAM through the DesignWare SATA AHCI implementation in 3-D IC structures

The conventional methods for testing the Dual Port Random Access Memories (DPRAM) may not be suitable for the Three-Dimensional Integrated Circuit (3-D IC) structures, due to their limited test vectors with heterogeneous integration. This paper takes an Application Specific Integrated Chips (ASIC) approach to gain some insight into the Front-end behavioral testing and backend routability of the dual port memories with complex Serial Advanced Technology Attachment (Serial-ATA) design, in a 3-D IC structure. The presented implementation used commercially available Dual Port memories from the two different vendors. The commercially available DesignWare Advanced Host Controller Interface (SATA/AHCI), which is based on the SATA 2.6 AHCI host and external SATA (eSATA) standard bus architecture, with My_foundry’s 14nm low power process (14lp) technologies for the logical and physical implementations. The methodology evaluates the memory quality and performance/characteristics, in terms of timing, power and area. This paper shows memory testing in both implementation/verification in a readily built-up SATA test environment.

Experimental Research on Narrowband Interference Suppression of GNSS Signals

The navigation satellites are running at a high altitude of 20000 km from the ground, and the satellite signals arriving at the ground are very weak, such as the C/A code on the L1 band, which is only -160 dBW. In complex urban environments, especially when there is an occlusion, the signal power will be even lower. Low power causes the signal to be easily disturbed, where suppressed interference is the most common method of interference. The purpose of this paper is to experiment with the BPSK and BOC signal system to do the narrowband suppression of interference analysis and set up the actual test environment, based on the commonly used LMS algorithm for the two systems of narrowband interference performance contrast analysis, and throughout the simulation, it can be seen that the two improved algorithms can effectively suppress narrowband interference, thus improving the anti-interference performance of satellite navigation receiver.

PERFORM: A Metric for Evaluating Autonomous System Performance in Marine Testbed Environments Using Interval Type-2 Fuzzy Logic

Trust and confidence in autonomous behavior is required to send autonomous vehicles into operational missions. The authors introduce the Performance Evaluation and Review Framework Of Robotic Missions (PERFORM), a framework to enable a rigorous and replicable autonomy test environment, thereby filling the void between that of merely simulating autonomy and that of completing true field missions. A generic architecture for defining the missions under test is proposed and a unique Interval Type-2 Fuzzy Logic approach is used as the foundation for the mathematically rigorous autonomy evaluation framework. The test environment is designed to aid in (1) new technology development (i.e., providing direct comparisons and quantitative evaluations between autonomy algorithms), (2) the validation of the performance of specific autonomous platforms, and (3) the selection of the appropriate robotic platform(s) for a given mission type (e.g., for surveying, surveillance, search and rescue). Three case studies are presented to apply the metric to various test scenarios. Results demonstrate the flexibility of the technique with the ability to tailor tests to the user’s design requirements accounting for different priorities related to acceptable risks and goals of a given mission.

Integrated Cloud Computing Environment for Upstream Geoscience Workflows

Extensive computing resources are required to leverage todays advanced geoscience workflows that are used to explore and characterize giant petroleum resources. In these cases, high-performance workstations are often unable to adequately handle the scale of computing required. The workflows typically utilize complex and massive data sets, which require advanced computing resources to store, process, manage, and visualize various forms of the data throughout the various lifecycles. This work describes a large-scale geoscience end-to-end interpretation platform customized to run on a cluster-based remote visualization environment. A team of computing infrastructure and geoscience workflow experts was established to collaborate on the deployment, which was broken down into separate phases. Initially, an evaluation and analysis phase was conducted to analyze computing requirements and assess potential solutions. A testing environment was then designed, implemented and benchmarked. The third phase used the test environment to determine the scale of infrastructure required for the production environment. Finally, the full-scale customized production environment was deployed for end users. During testing phase, aspects such as connectivity, stability, interactivity, functionality, and performance were investigated using the largest available geoscience datasets. Multiple computing configurations were benchmarked until optimal performance was achieved, under applicable corporate information security guidelines. It was observed that the customized production environment was able to execute workflows that were unable to run on local user workstations. For example, while conducting connectivity, stability and interactivity benchmarking, the test environment was operated for extended periods to ensure stability for workflows that require multiple days to run. To estimate the scale of the required production environment, varying categories of users’ portfolio were determined based on data type, scale and workflow. Continuous monitoring of system resources and utilization enabled continuous improvements to the final solution. The utilization of a fit-for-purpose, customized remote visualization solution may reduce or ultimately eliminate the need to deploy high-end workstations to all end users. Rather, a shared, scalable and reliable cluster-based solution can serve a much larger user community in a highly performant manner.

An Alternative Test Method for the Dual Port SRAM Memory through the Designware SATA AHCI Implementation in 3-D IC Structures

Background: It is being considered that conventional methods for testing the dual port memories might not be suitable for the Three-Dimensional Integrated Circuit (3-D IC) structures due to the presence of the limited test vectors with heterogeneous integration. Objective: Find out a novel test methodology DPRAMs in 3-D IC structures. Methods: This paper has taken the approach called as Application Specific Integrated Chips(ASIC) to gain insights on Front-End behavioral testing and Back-End routability of the dual port memories integrated with complex Serial Advanced Technology Attachment (Serial-ATA) design, in a 3-D IC structure. The presented implementation is using commercially available dual port memories from two different vendors. The commercially available DesignWare Advanced Host Controller Interface (SATA/AHCI) is based on the Serial Advanced Technology Attachment (SATA 2.6), AHCI host and external SATA (eSATA) standard bus architecture and being used with My_foundry’s 14nm Low Power (14LP) process technology for logical and physical implementations. Results: This paper shows memory testing in both implementation/verification in a readily built-up SATA test environment. Conclusion: It is being considered that the approach described here might be used as a tool/environment for evaluating any vendor's DPRAMs/2Ports RAMs/2Ports Register Files. As a result, it offers an alternative to the traditional test methodology.

Financial Performance Management System and Wireless Sharing Network Optimization of Listed Enterprises under BPNN

The study aims to respond to the difficulties in establishing an index system in financial performance management and ensuring the security of wireless sharing network and the local extremum and slow convergence speed of the traditional BP neural network (BPNN). First, Levenberg–Marquardt (LM) is used to optimize BPNN, and an improved BPNN is proposed. Second, the financial performance evaluation system of listed companies based on BPNN is constructed. Finally, a wireless network infusion detection system based on the improved BPNN is proposed and tested by constructing datasets and a real test environment. The results show that (1) the financial performance evaluation system of listed enterprises constructed can evaluate the financial performance of listed enterprises with fewer errors. It is easy to operate, and it has high accuracy and the abilities of self-learning and self-adaptation; (2) Wireless Infusion Detection System (WIDS) based on the improved BP algorithm has a high detection rate and a low error rate. The study provides important technical support for listed enterprises to improve the financial performance management level and market competitiveness and strengthen the security protection of networks.