Modeling of HVDC System to Improve Estimation of Transient DC Current and Voltages for AC Line-to-Ground FaultAn Actual Case Study in Korea

A new modeling method for high voltage direct current (HVDC) systems and associated controllers is presented for the power system simulator for engineering (PSS/E) simulation environment. The aim is to improve the estimation of the transient DC voltage and current in the event of an AC line-to-ground fault. The proposed method consists primary of three interconnected modules for (a) equation conversion; (b) control-mode selection; and (c) DC-line modeling. Simulation case studies were carried out using PSS/E and a power systems computer aided design/electromagnetic transients including DC (PSCAD/EMTDC) model of the Jeju-Haenam HVDC system in Korea. The simulation results are compared with actual operational data and the PSCAD/EMTDC simulation results for an HVDC system during single-phase and three-phase line-to-ground faults, respectively. These comparisons show that the proposed PSS/E modeling method results in the improved estimation of the dynamic variation in the DC voltage and current in the event of an AC network fault, with significant gains in computational efficiency, making it suitable for real-time analysis of HVDC systems.111Ysciescopu

Designing systems for emerging memory technologies

Emerging memory technologies open new challenges in system software: diversity and large capacity. Non-volatile memory (NVM) technologies will have excellent performance, byte- addressability, and large capacity, blurring the line between traditional volatile DRAM and non-volatile storage. NVM diverges from DRAM in significant ways, like limited write bandwidth. It is likely that future storage market will be diversified, having DRAM, NVM, SSD, and hard disk. Unfortunately, current file systems, built on top of old design ideas, cannot provide an efficient way to take advantage of the different storage media. Strata is a cross-media file system, fundamentally redesigning file systems to leverage different strengths of storage technologies while compensating their weaknesses. Modern applications such as large-scale machine learning and graph analytics want to load huge datasets into memory for fast computation. For these workloads, merely adding more RAM to a machine reaches a point of diminishing returns for performance because their poor spatial locality causes them to suffer high virtual to physical memory translation costs. NVM will make this problem worse because it provides cheaper cost-per-capacity than DRAM. Ingens, a efficient memory management system, addresses the shortcomings in modern operating systems and hypervisors that underlies these excessive address translation overheads and redesign huge page memory systems to make huge page widely used in practice.Computer Science

Schwannoma Mimicking Laryngocele

A schwannoma of the larynx is a rare benign tumor that usually presents as a submucosal mass in the pyriform sinus and the aryepiglottic space, and this type of schwannoma constitutes a diagnostic and therapeutic challenge for otolaryngologists. We present here two cases of supraglottic schwannomas that were misdiagnosed as laryngoceles. Both were excised through a lateral thyrotomy approach without a tracheostomy, and the laryngeal function was successfully maintained. We discuss the clinical and imaging findings and the management of this rare neoplasm with focusing on the differential diagnosis of laryngeal schwannoma and laryngocele. We also review the relevant medical literature

Modeling and Analysis of an LCC HVDC System Using DC Voltage Control to Improve Transient Response and Short-Term Power Transfer Capability

A new control method for a line-commutated converter-based (LCC) high-voltage direct-current (HVDC) system is presented and compared to a conventional strategy. In the proposed method, both the DC voltage and current of an LCC HVDC system are regulated to increase the short-term operating margin of DC power transfer and improve transient responses to DC power references. In particular, an increased operating margin of DC power transfer is achieved via the DC voltage regulation method. To verify the effectiveness of the proposed method, a state space model of an LCC HVDC system is developed considering DC voltage and current references as input variables and analyzed for various values of the DC line inductance and converter controller gains. The state space model can be used for time-efficient analyses of the dynamic characteristics of an LCC HVDC system. Simulation case studies are performed using MATLAB, where the state space model of the Jeju-Haenam HVDC system is implemented as a test case and compared to its comprehensive PSCAD model. The case study results suggest that the proposed method increases the short-term operating margin and speeds up the transient response of the HVDC system. Therefore, it will effectively improve real-time grid frequency regulation.11sciescopu

A Robust Controller Design Method for a Flexible Manipulator with a Large Time Varying Payload and Parameter Uncertainties

Abstract. A new robust controller design method is proposed to obtain a less conservative feedback controller and it is applied to a single-link flexible manipulator. The objective is to maximize the control performance guaranteeing the robust stability when regulating the tip position of the flexible manipulator in the presence of a large time-varying payload and parameter uncertainties such as stiffness and joint friction. A descriptor form representation, which allows separate treatment of payload uncertainty from other parametric uncertainties, is used to reduce the conservatism of the conventional robust control approaches. Uncertainty of the payload in the inertia matrix is represented by polytopic approach and the uncertain parameters in the damping and stiffness matrices are treated with descaling techniques. Using aforementioned techniques, the robust LQ controller design problem for a flexible manipulator based on the guaranteed cost approach is formulated. Then, the formulated problem is solved by LMIs

Are Deep Learning-Generated Social Media Profiles Indistinguishable from Real Profiles?

In recent years, deep learning methods have become increasingly capable of generating near photorealistic pictures and humanlike text up to the point that humans can no longer recognize what is real and what is AI-generated. Concerningly, there is evidence that some of these methods have already been adopted to produce fake social media profiles and content. We hypothesize that these advances have made detecting generated fake social media content in the feed extremely difficult, if not impossible, for the average user of social media. This paper presents the results of an experiment where 375 participants attempted to label real and generated profiles and posts in a simulated social media feed. The results support our hypothesis and suggest that even fully-generated fake profiles with posts written by an advanced text generator are difficult for humans to identify

Assise: Performance and Availability via NVM Colocation in a Distributed File System

The adoption of very low latency persistent memory modules (PMMs) upends the long-established model of disaggregated file system access. Instead, by colocating computation and PMM storage, we can provide applications much higher I/O performance, sub-second application failover, and strong consistency. To demonstrate this, we built the Assise distributed file system, based on a persistent, replicated coherence protocol for managing a set of server-colocated PMMs as a fast, crash-recoverable cache between applications and slower disaggregated storage, such as SSDs. Unlike disaggregated file systems, Assise maximizes locality for all file IO by carrying out IO on colocated PMM whenever possible and minimizes coherence overhead by maintaining consistency at IO operation granularity, rather than at fixed block sizes. We compare Assise to Ceph/Bluestore, NFS, and Octopus on a cluster with Intel Optane DC PMMs and SSDs for common cloud applications and benchmarks, such as LevelDB, Postfix, and FileBench. We find that Assise improves write latency up to 22x, throughput up to 56x, fail-over time up to 103x, and scales up to 6x better than its counterparts, while providing stronger consistency semantics. Assise promises to beat the MinuteSort world record by 1.5x

"Jane sent me this article, so it must be true!" - How tie strength and emotional tone influence information behavior

Fake news are a threat of the information age, yet many factors that determine their spread, such as emotional tone and tie strength, remain under-researched. Responding to calls for research, we developed an experimental study that explains the impact of emotional tone and tie strength in the context of instant messaging. We hypothesize effects on the willingness to fact-check and intention to share, mediated by sender credibility and news believability. Our results will contribute to the academic literature on various levels: we consider the emotional and relational dimensions of fake news sharing. Furthermore, we provide a multidimensional understanding of the emotionality of strong-tie contacts sharing fake news in a seemingly private and safe environment. For policymakers, we provide insights that help detect fake news, and we provide individuals with persuasion knowledge to self-protect against fake news