Design of a portable radio-frequency-identification reader capable to reading a user memory bank for smart-building energy management

Communication is an important factor in smart-building energy management (SBEM). Many communications technologies have been applied to SBEM, including radio-frequency identification (RFID). RFID has been used not only for identification but also for carrying information, which is stored in a user memory bank attached to the tag. To access the user memory bank, an RFID reader should comply with ISO 18000-6C standards. The greatest challenge of RFID-reader technology is its short communication range, which limits the sensing area. To overcome this problem, this paper proposes a portable RFID reader built to an ISO 18000-6C standard to extend the sensing area due to its moveability. The reader is designed using low-cost devices widely available on the market for ease of duplication and assembly by researchers, educators, and startups. The proposed RFID reader can read passive tags with distances up to 12 and 5.5 m for line-of-sight (LOS) and non-line-of-sight (NLOS) communication, respectively. The minimum received-signal-strength indicators (RSSIs) for LOS and NLOS are found to be −63.75 and −59.66 dBm, respectively. These results are comparable with those of non-portable RFID readers on the market.

Domain-Smoothing Network for Zero-Shot Sketch-Based Image Retrieval

Zero-Shot Sketch-Based Image Retrieval (ZS-SBIR) is a novel cross-modal retrieval task, where abstract sketches are used as queries to retrieve natural images under zero-shot scenario. Most existing methods regard ZS-SBIR as a traditional classification problem and employ a cross-entropy or triplet-based loss to achieve retrieval, which neglect the problems of the domain gap between sketches and natural images and the large intra-class diversity in sketches. Toward this end, we propose a novel Domain-Smoothing Network (DSN) for ZS-SBIR. Specifically, a cross-modal contrastive method is proposed to learn generalized representations to smooth the domain gap by mining relations with additional augmented samples. Furthermore, a category-specific memory bank with sketch features is explored to reduce intra-class diversity in the sketch domain. Extensive experiments demonstrate that our approach notably outperforms the state-of-the-art methods in both Sketchy and TU-Berlin datasets.

Steve Oroszlan: A Personal Perspective

My memories of Steve go back over 50 years. While precise dates are no longer in my memory bank, circumstances and emotions remain alive and easy to recall. These memories tell the story of a remarkable human being, a true practitioner of his craft always, faithful to the basic principles of scientific pursuit, with integrity, honesty, and enthusiasm well beyond the norm. We had a professional symbiotic relationship that lasted over 20 years, resulting in over 50 publications in scientific journals and meeting abstracts. During that time, our fortunes rose in tandem, and when it was time to go our separate ways, he was more than ready to flourish on his own. Our personal friendship remained constant, and we enjoyed sharing meals and stories with family and friends over the years. In retrospect, I take pride in having played a role in a portion of his remarkable scientific journey. A few key anecdotes will illustrate some aspects of this summary. By way of a disclaimer, this is not a comprehensive review of the vast field of viral oncology and the selection of references is intentionally narrow. No slight is intended to the many outstanding investigators that were our contemporaries and at times collaborators during the period from the early 70s to the mid-80s.