Novel communication method between power converters for DC micro-grid applications

Communication between power converters is vital for high performance DC micro-grids controls. However, for residential DC micro-grid applications, using external communication link would increase the system cost, and reduce the system flexibility and reliability. This paper presents a novel method to enable the conventional DC/DC converters to transmit data via the common DC Bus. With this technology, cost-effective low bandwidth communication links between power converters can be established within a DC micro-grid, and advanced distributed control algorithms can be developed. A reliable communication with 2 kbps transmission rate has been implemented between the Boost converters through the common input DC bus

Analysis and Prediction of Patterns in Futures Trading Datasets Using LSTM

One of the most promising tools in recent years for the analysis and prediction of time series data, which includes financial market data has been the use of neural networks. To ensure the accuracy of the outcomes of these systems, it is critical to overcome the vanishing gradient and exploding gradient problems that often occur when recurrent neural networks (RNN) process data. Long Short-Term Memory (LSTM) has been shown to provide good performance when dealing with time series datasets. This paper will explore the feasibility of using an RNN with LSTM as a predictive tool for use with futures trading data. Using a dataset comprised of all futures trading occurring on the Bourse de Montréal (TMX) during a 9-month period from January to September 2015, we assessed the predictive effectiveness of an RNN in predicting the price of front-end contracts for the futures symbol BAX. We found that while an RNN provided a degree of short-term predictive capability, this capability did not extend beyond a couple of days. Although it failed as a trading instrument to predict futures prices, the RNN could detect, identify, and reflect underlying trends in the data, indicating the tool may hold promise in the detection of trading patterns.Â

DC power line communication based on power/signal dual modulation in phase shift full bridge converters

For intelligent DC distributed power systems, data communication plays a vital role in system control and device monitoring. To achieve communication in a cost effective way, power/signal dual modulation (PSDM), a method that integrates data transmission with power conversion, can be utilized. In this paper, an improved PSDM method using phase shift full bridge (PSFB) converter is proposed. This method introduces a phase control based freedom in the conventional PSFB control loop to realize communication using the same power conversion circuit. In this way, decoupled data modulation and power conversion are realized without extra wiring and coupling units, and thus the system structure is simplified. More importantly, the signal intensity can be regulated by the proposed perturbation depth, and so this method can adapt to different operating conditions. Application of the proposed method to a DC distributed power system composed of several PSFB converters is discussed. A 2kW prototype system with an embedded 5kbps communication link has been implemented, and the effectiveness of the method is verified by experimental results

Maximizing User Experience with LLMOps-Driven Personalized Recommendation Systems

The integration of LLMOps into personalized recommendation systems marks a significant advancement in managing LLM-driven applications. This innovation presents both opportunities and challenges for enterprises, requiring specialized teams to navigate the complexity of engineering technology while prioritizing data security and model interpretability. By leveraging LLMOps, enterprises can enhance the efficiency and reliability of large-scale machine learning models, driving personalized recommendations aligned with user preferences. Despite ethical considerations, LLMOps is poised for widespread adoption, promising more efficient and secure machine learning services that elevate user experience and shape the future of personalized recommendation systems

Research on the Application of Deep Learning-based BERT Model in Sentiment Analysis

This paper explores the application of deep learning techniques, particularly focusing on BERT models, in sentiment analysis. It begins by introducing the fundamental concept of sentiment analysis and how deep learning methods are utilized in this domain. Subsequently, it delves into the architecture and characteristics of BERT models. Through detailed explanation, it elucidates the application effects and optimization strategies of BERT models in sentiment analysis, supported by experimental validation. The experimental findings indicate that BERT models exhibit robust performance in sentiment analysis tasks, with notable enhancements post fine-tuning. Lastly, the paper concludes by summarizing the potential applications of BERT models in sentiment analysis and suggests directions for future research and practical implementations

Direct sequence spread spectrum based PWM strategy for harmonic reduction and communication

Switched mode power supplies (SMPSs) are essential components in many applications, and electromagnetic interference is an important consideration in the SMPS design. Spread spectrum based PWM strategies have been used in SMPS designs to reduce the switching harmonics. This paper proposes a novel method to integrate a communication function into spread spectrum based PWM strategy without extra hardware costs. Direct sequence spread spectrum (DSSS) and phase shift keying (PSK) data modulation are employed to the PWM of the SMPS, so that it has reduced switching harmonics and the input and output power line voltage ripples contain data. A data demodulation algorithm has been developed for receivers, and code division multiple access (CDMA) concept is employed as communication method for a system with multiple SMPSs. The proposed method has been implemented in both Buck and Boost converters. The experimental results validated the proposed DSSS based PWM strategy for both harmonic reduction and communication

HIV-1 persistence in CD4+ T cells with stem cell-like properties

Cellular HIV-1 reservoirs that persist despite antiretroviral treatment are incompletely defined. We show that during suppressive antiretroviral therapy, CD4+ T memory stem cells (TSCM) harbor high per-cell levels of HIV-1 DNA, and make increasing contributions to the total viral CD4+ T cell reservoir over time. Moreover, phylogenetic studies suggested long-term persistence of viral quasispecies in CD4+ TSCM cells. Thus, HIV-1 may exploit stem cell characteristics of cellular immune memory to promote long-term viral persistence

Techno-economic Assessment of a Hybrid Off-grid DC System for Combined Heat and Power Generation in Remote Islands

Hybrid renewable energy systems that combine heat and electricity generation is an achievable option for remote areas where grid is uneconomical to extend. In this study, a renewable-based system was designed to satisfy the electrical and thermal demands of a remote household in an off-grid Greek island. A hybrid DC system consisted of a combination of photovoltaic modules, wind turbine, electrolyzer-hydrogen tank, fuel cell and batteries were analysed using HOMER Pro software. Based on the optimal obtained system, it is found that such a system can satisfy both electrical and thermal load demand throughout the year in a reliable manner

Power conversion and signal transmission integration method based on dual modulation of DC-DC converters

For the development of communication systems such as Internet of Things, integrating communication with power supplies is an attractive solution to reduce supply cost. This paper presents a novel method of power/signal dual modulation (PSDM), by which signal transmission is integrated with power conversion. This method takes advantage of the intrinsic ripple initiated in switch mode power supplies as signal carriers, by which cost-effective communications can be realized. The principles of PSDM are discussed, and two basic dual modulation methods (specifically PWM/FSK and PWM/PSK) are concluded. The key points of designing a PWM/FSK system, including topology selection, carrier shape, and carrier frequency, are discussed to provide theoretical guidelines. A practical signal modulation-demodulation method is given, and a prototype system provides experimental results to verify the effectiveness of the proposed solution