The research on hand gestures has attracted many image processing-related studies, as it intuitively conveys the intention of a human as it pertains to motional meaning. Various sensors have been used to exploit the advantages of different modalities for the extraction of important information conveyed by the hand gesture of a user. Although many works have focused on learning the benefits of thermal information from thermal cameras, most have focused on face recognition or human body detection, rather than hand gesture recognition. Additionally, the majority of the works that take advantage of multiple modalities (e.g., the combination of a thermal sensor and a visual sensor), usually adopting simple fusion approaches between the two modalities. As both thermal sensors and visual sensors have their own shortcomings and strengths, we propose a novel joint filter-based hand gesture recognition method to simultaneously exploit the strengths and compensate the shortcomings of each. Our study is motivated by the investigation of the mutual supplementation between thermal and visual information in low feature level for the consistent representation of a hand in the presence of varying lighting conditions. Accordingly, our proposed method leverages the thermal sensor’s stability against luminance and the visual sensors textural detail, while complementing the low resolution and halo effect of thermal sensors and the weakness against illumination of visual sensors. A conventional region tracking method and a deep convolutional neural network have been leveraged to track the trajectory of a hand gesture and to recognize the hand gesture, respectively. Our experimental results show stability in recognizing a hand gesture against varying lighting conditions based on the contribution of the joint kernels of spatial adjacency and thermal range similarity.

This paper examines a low-power consumption 1024 point floating-point fused FFT realized with a Multiple-Constant Multiplier (MCM) and with a Merged Multiple-Constant Multiplier (MMCM). The FFT is constructed using Radix-2 butterfly operations that are implemented with MCMs and with MMCMs to reduce the power consumption and area. Conventional MCMs perform the significand multiplication, but with relatively low precision. To enhance the precision, a new architecture of the butterfly unit has been designed and implemented with MMCMs. The new architecture reduces the error by 65% compared to a fused butterfly unit with MCMs at a slight cost in area and power consumption.

Recently, a new silkworm strain with a peculiar larval marking and rare cocoon colour was bred in Korea for educational learning and exhibition. In order to obtain the genetic information of the newly bred strain, Chilseongjam Bombyx mori (Lepidoptera: Bombycidae), its complete mitochondrial genome (mitogenome) was sequenced. The mitogenome is 15,660 bp in length, contains a typical set of genes, and has gene arrangement and composition typical of Lepidoptera. However, the Chilseongjam strain mitogenome is 4–36 bp longer than 19 other strains originating from other countries and 16 bp shorter than the whole genome of a Korean Hukpyobeom strain. In particular, the Chilseongjam strain has an intergenic spacer sequence that is shorter than that of the Hukpyobeom strain at the tRNA^His and ND4 junction as it has fewer microsatellite-like AT repeats. Phylogenetic analyses conducted using a total of 21 silkworm strains originating from nine countries revealed a few subgroups with moderate-to-high nodal support (80–94%). The Korean Chilseongjam strain formed a relatively strong subgroup (85%) with a Japanese strain (J106) instead of the Korean Hukpyobeom strain.