Refining Wi-Fi Based Indoor Localization with Li-Fi Assisted Model Calibration in Smart Buildings

In recent years, there has been an increasing number of information technologies utilized in buildings to advance the idea of "smart buildings". Among various potential techniques, the use of Wi-Fi based indoor positioning allows to locate and track smartphone users inside a building, therefore, location-aware intelligent solutions can be applied to control and of building operations. These location-aware indoor services (e.g., path finding, internet of things, location based advertising) demand real-time accurate indoor localization, which is a key issue to guarantee high quality of service in smart buildings. This paper presents a new Wi-Fi based indoor localization technique that achieves significantly improvement of indoor positioning accuracy with the help of Li-Fi assisted coefficient calibration. The proposed technique leverages indoor existing Li-Fi lighting and Wi-Fi infrastructure, and results in a cost-effective and user-convenient indoor accurate localization framework. In this work, experimental study and measurements are conducted to verify the performance of the proposed idea. The results substantiate the concept of refining Wi-Fi based indoor localization with Li-Fi assisted computation calibration.Comment: International Conference on Computing in Civil and Building Engineering (ICCCBE) 201

FreeLong: Training-Free Long Video Generation with SpectralBlend Temporal Attention

Video diffusion models have made substantial progress in various video generation applications. However, training models for long video generation tasks require significant computational and data resources, posing a challenge to developing long video diffusion models. This paper investigates a straightforward and training-free approach to extend an existing short video diffusion model (e.g. pre-trained on 16-frame videos) for consistent long video generation (e.g. 128 frames). Our preliminary observation has found that directly applying the short video diffusion model to generate long videos can lead to severe video quality degradation. Further investigation reveals that this degradation is primarily due to the distortion of high-frequency components in long videos, characterized by a decrease in spatial high-frequency components and an increase in temporal high-frequency components. Motivated by this, we propose a novel solution named FreeLong to balance the frequency distribution of long video features during the denoising process. FreeLong blends the low-frequency components of global video features, which encapsulate the entire video sequence, with the high-frequency components of local video features that focus on shorter subsequences of frames. This approach maintains global consistency while incorporating diverse and high-quality spatiotemporal details from local videos, enhancing both the consistency and fidelity of long video generation. We evaluated FreeLong on multiple base video diffusion models and observed significant improvements. Additionally, our method supports coherent multi-prompt generation, ensuring both visual coherence and seamless transitions between scenes.Comment: Project page: https://yulu.net.cn/freelon

Power Efficient SRAM Design with Integrated Bit Line Charge Pump

Bit line toggling of SRAM systems in write operations leads to the largest portion of power dissipation. To reduce this amount of power loss and achieve power efficient memory, we propose a new SRAM design that integrates charge pump circuits to harvest and reuse bit line charge. In this work, a power-efficient charge recycling SRAM is designed and implemented in 180nm CMOS technology. Post-layout simulation demonstrates an 11% of power saving and 3.8% of area overhead, if the bit width of SRAM is chosen as 8. Alternatively, 22% of power reduction is obtained if the bit width of SRAM is extended to 64. Compared with existing charge recycling SRAM schemes, this proposed SRAM is robust to process variation, demonstrates good read/write stability, and illustrates better trade-off between design complexity and power reduction

Efficient RLHF: Reducing the Memory Usage of PPO

Reinforcement Learning with Human Feedback (RLHF) has revolutionized language modeling by aligning models with human preferences. However, the RL stage, Proximal Policy Optimization (PPO), requires over 3x the memory of Supervised Fine-Tuning (SFT), making it infeasible to use for most practitioners. To address this issue, we present a comprehensive analysis the memory usage, performance, and training time of memory-savings techniques for PPO. We introduce Hydra-RLHF by first integrating the SFT and Reward models and then dynamically turning LoRA "off" during training. Our experiments show: 1. Using LoRA during PPO reduces its memory usage to be smaller than SFT while improving alignment across four public benchmarks, and 2. Hydra-PPO reduces the latency per sample of LoRA-PPO by up to 65% while maintaining its performance. Our results demonstrate that Hydra-PPO is a simple and promising solution for enabling more widespread usage of RLHF

A fully integrated RSSI and an ultra-low power SAR ADC for 5.8 GHz DSRC ETC transceiver

This study presents a monolithic received signal strength indicator (RSSI) and an ultra-low power SAR ADC for 5.8 GHz DSRC transceiver in China electronic toll collection systems. In order to meet the stringent requirement of wide input range for the transceiver, two RSSIs collaborate with auxiliary ADC circuits to provide the digitalized received signal strength to the digital baseband of a transceiver. The RSSI design achieves fast transient response and low power consumption with a small die area by using internal active low-pass filters instead of external passive ones. The proposed design has been fabricated using a 0.13 μm 2P6M CMOS technology. Measurement results show that the overall input dynamic range is 86 dB with an accuracy of ±1.72 dB and a transient response of less than 2 μs. Compared with the state-of-the-art designs in the literature, the overall input range and transient settling time are improved by at least 14.6%, and 300%, respectively

Analysis for the Effect of Sea Surface Temperature (SST) on the Coastal Environments of Jiangsu Province, China

In this chapter, we present the analysis for the effect of summertime SST on the coastal environments of Jiangsu province, China. We analyze the relationship between the SST and the Jiangsu precipitation in summer based on GPCP’s precipitation data and NOAA’s SST data from 1979 to 2011, using approaches that include correlation analysis, regression analysis, and lead-lag analysis. The results show that certain strong oceanic signals affect summer Jiangsu precipitation, showing that SST of some oceanic areas significantly affect the precipitation of Jiangsu in summer. By the lead-lag analysis, it is found that the spring SST plays an important role in the summer precipitation in the coastal areas of Jiangsu, China

Evaluating Urban Heat Island Effects in Rapidly Developing Coastal Cities

In this chapter, we present the analysis of urban heat island (UHI) effects on coastal urban areas using satellite images as a case study in Hangzhou, China. With the sustainable development of coastal areas, land use and land cover have been dramatically changed. Such changes make the phenomenon of urban heat island (UHI) becoming serious, which has brought some negative influences on human activities or public health issues in coastal regions. This study takes Hangzhou as an example of coastal cities and uses the Landsat TM, ETM+ and OLI images to retrieve the urban land surface temperature (LST). We also mapped and compared the intensity of UHI effects in different years of 2003, 2008 and 2013. The result shows that the intensity of UHI effect in 2013 was more serious than previous years, which is increasing year by year. The study also analyzed the relationship between UHI, NDVI, and NDBI and provided some useful suggestions to mitigate the UHI effects on coastal cities such as Hangzhou in China

Analysis for Soil Moisture in Jiangsu Province, China, Using GLDAS Data

In this chapter, we present the analysis for the evolution characteristics of temperature, precipitation, and soil moisture. We choose a newly developed method that is based on the information flow (IF) concept to research the causality between annual mean temperature, precipitation, and soil moisture in Jiangsu province, China, from 1961 to 2011 by using the Global Land Data Assimilation System (GLDAS). The correlation and the causality of air temperature and precipitation on soil moisture were compared and discussed. The causality value of 0–10 cm layer is significantly different from zero, while the deeper, in comparison to the surface layer, is negligible. This result unambiguously shows the causality in the sense that the precipitation increase and the temperature decrease are causing the shallow soil moisture to increase. Temperature and all layers of soil moisture have a negative correlation, but precipitation inverses. Precipitation strongly has the greatest effects on soil moisture in the surface layer, though the rest layers are not obvious