Prediction of Yelp Score from Reviewswith Machine Learning Model

Yelp has been a dominating company in the business rating industry. In the current days, reviews and ratings critically affect people’s decisions. A model that effectively predicts the ratings could be supportive to businesses. In this research, we develop several models based on various NLP and regression methods based on the text review and other traits of the reviews to predict the final star rating of each. Models including LSTM, GRU, BERT, and multinomial logistic regression are utilized. The fine-tuning BERT model has the best result of 68.8% on the testing dataset. Although the model predicts well in general, we could further investigate and evaluate text reviews on multiple aspects

Recent Progress in Synthesis and Application of Low-Dimensional Silicon Based Anode Material for Lithium Ion Battery

Silicon is regarded as the next generation anode material for LIBs with its ultra-high theoretical capacity and abundance. Nevertheless, the severe capacity degradation resulting from the huge volume change and accumulative solid-electrolyte interphase (SEI) formation hinders the silicon based anode material for further practical applications. Hence, a variety of methods have been applied to enhance electrochemical performances in terms of the electrochemical stability and rate performance of the silicon anodes such as designing nanostructured Si, combining with carbonaceous material, exploring multifunctional polymer binders, and developing artificial SEI layers. Silicon anodes with low-dimensional structures (0D, 1D, and 2D), compared with bulky silicon anodes, are strongly believed to have several advanced characteristics including larger surface area, fast electron transfer, and shortened lithium diffusion pathway as well as better accommodation with volume changes, which leads to improved electrochemical behaviors. In this review, recent progress of silicon anode synthesis methodologies generating low-dimensional structures for lithium ion batteries (LIBs) applications is listed and discussed

Development of Metal Oxide Based Materials for Li-ion Batteries : From Titania to Titanates

Metal oxides are a class of materials that have been widely studied for energy storage applications because of their unique physical and chemical properties. Many metal oxides play an important role in electrochemical devices. For instance, lithium cobalt oxide (LCO) and lithium iron phosphate oxide (LFP) now have been commercialized as cathode materials in lithium ion batteries (LIBs). However, there are still significant challenges in balancing the activity and stability of metal oxide based electrodes for high-performance, long life LIBs. In this thesis, four different metal oxides were investigated for the application of LIBs. Tetragonal anatase TiO2 and cubic perovskite strontium titanate (STO) nanoparticles with small diameters (≤ 20 nm) were used as coating materials to develop composites with NMC and LNMO cathodes respectively. Structurally and chemically stable STO and TiO2 nanoparticles have significantly improved battery performance regarding capacity and stability. At 1C, 5 wt.% TiO2-coated NMC 811 exhibited 16.7% higher initial discharge capacity than the pristine NMC 811; 10 wt.% STO-coated LNMO showed 24.4% higher initial discharge capacity and 19.0% higher Coulombic efficiency than the pristine LNMO.Lithium titanate (LTO) nanoparticles with different levels of oxygen vacancy were synthesized. Battery testing and computational simulation were employed to investigate the relationship between oxygen vacancy and electrochemical behaviors of LTO nano-anodes. A threshold concentration of oxygen vacancy (~7%) was found regarding performance improvement of LTO anodes. Lithium lanthanum titanate (LLTO) nanoparticles were synthesized to produce free-standing LLTO solid-state electrolytes. LLTO particles were then mixed with LTO particles to form composite anodes. Battery performance showed that the composite anodes exhibited 4.9% higher initial capacity and 6% higher Coulombic efficiency than pristine LTO anodes.In summary, TiO2 and related three types of titanates were investigated as different components for LIBs. Their performance was systematically studied, and the mechanism was analyzed and studied. This thesis indicated that those four different metal oxides have potential for further industrial applications

Facing the Wildfire Spread Risk Challenge: Where Are We Now and Where Are We Going?

Wildfire is a sudden and highly destructive natural disaster that poses significant challenges in terms of response and rescue efforts. Influenced by factors such as climate, combustible materials, and ignition sources, wildfires have been increasingly occurring worldwide on an annual basis. In recent years, researchers have shown growing interest in studying wildfires, leading to a substantial body of related research. These studies encompass various topics, including wildfire prediction and forecasting, the analysis of spatial and temporal patterns, the assessment of ecological impacts, the simulation of wildfire behavior, the identification of influencing factors, the development of risk assessment models, techniques for managing combustible materials, decision-making technologies for firefighting, and fire-retardant methods. Understanding the factors that affect wildfire spread behavior, employing simulation methods, and conducting risk assessments are vital for effective wildfire prevention, disaster mitigation, and emergency response. Consequently, it is imperative to comprehensively review and explore further research in this field. This article primarily focuses on elucidating and discussing wildfire spread behavior as a key aspect. It summarizes the driving factors of wildfire spread behavior and introduces a wildfire spread behavior simulation software and its main applications based on these factors. Furthermore, it presents the research progress in wildfire risk assessment based on wildfire spread behavior factors and simulation, and provides an overview of various methods used for wildfire risk assessment. Finally, the article proposes several prospects for future research on wildfire spread: strengthening the dynamic monitoring of wildfires and utilizing comprehensive data from multiple sources, further exploring the differential effects of key factors on wildfire spread, investigating differences in driving factors, improving wildfire models in China, developing applicable software, and conducting accurate and scientific assessments of wildfire risks to protect ecological resources

Multisatellite Task Allocation and Orbit Planning for Asteroid Terminal Defence

Near-Earth asteroids are a great threat to the Earth, especially potential rendezvous and collision asteroids. To protect the Earth from an asteroid collision, it is necessary to investigate the asteroid defence problem. An asteroid terminal defence method based on multisatellite interception was designed in this study. For an asteroid intruding in the sphere of the gravitational influence of the Earth, multiple interceptor satellites are used to apply a kinetic energy impulse to deflect the orbit of the asteroid. First, the effects of planned interception time and planned interception position on the required impulse velocity increment applied to the asteroid are assessed for interception opportunity selection. Second, multiple interceptor satellites are selected to perform the defence task from the on-orbit available interceptor satellite formation. An improved contract net protocol algorithm considering the Lambert orbital manoeuvre is designed to fulfil the task allocation and satellite orbit planning. Finally, simulation experiments demonstrate the rationale and effectiveness of the proposed method, which provides support for asteroid terminal defence technology