The thermal imaging pedestrian segmentation system has excellent performance in different illumination conditions, but it has some drawbacks(e.g., weak pedestrian texture information, blurred object boundaries). Meanwhile, high-performance large models have higher latency on edge devices with limited computing performance. To solve the above problems, in this paper, we propose a real-time thermal infrared pedestrian segmentation method. The feature extraction layers of our method consist of two paths. Firstly, we utilize the lossless spatial downsampling to obtain boundary texture details on the spatial path. On the context path, we use atrous convolutions to improve the receptive field and obtain more contextual semantic information. Then, the parameter-free attention mechanism is introduced at the end of the two paths for effective feature selection, respectively. The Feature Fusion Module (FFM) is added to fuse the semantic information of the two paths after selection. Finally, we accelerate method inference through multi-threading techniques on the edge computing device. Besides, we create a high-quality infrared pedestrian segmentation dataset to facilitate research. The comparative experiments on the self-built dataset and two public datasets with other methods show that our method also has certain effectiveness. Our code is available at https://github.com/mcjcs001/LEIPNet.

Energy management in buildings is vital for reducing electricity costs and maximizing the comfort of occupants. Excess solar generation can be used by combining a battery storage system and a heating, ventilation, and air-conditioning (HVAC) system so that occupants feel comfortable. Despite several studies on the scheduling of appliances, batteries, and HVAC, comprehensive and time scalable approaches are required that integrate such predictive information as renewable generation and thermal comfort. In this paper, we propose an thermal-comfort aware online co-scheduling framework that incorporates optimal energy scheduling and a prediction model of PV generation and thermal comfort with the model predictive control (MPC) approach. We introduce a photovoltaic (PV) energy nowcasting and thermal-comfort-estimation model that provides useful information for optimization. The energy management problem is formulated as three coordinated optimization problems that cover fast and slow time-scales by considering predicted information. This approach reduces the time complexity without a significant negative impact on the result's global nature and its quality. Experimental results show that our proposed framework achieves optimal energy management that takes into account the trade-off between electricity expenses and thermal comfort. Our sensitivity analysis indicates that introducing a battery significantly improves the trade-off relationship.

Development of narrowband thermal emitters whose emission wavelengths are dynamically tunable is highly desired for various applications including the sensing of gases and chemical compounds. In this paper, we review our recent demonstration of wavelength-switchable mid-infrared thermal emitters based on multiple quantum wells (MQWs) and photonic crystals (PCs). Through the control of absorptivity by using intersubband transitions in MQWs and optical resonances in PC slabs, we demonstrate novel control of thermal emission, including realization of high-Q (Q>100) thermal emission, dynamic control of thermal emission (∼MHz), and electrical wavelength switching of thermal emission from a single device.

In this paper, we propose a method to generate a three-dimensional (3D) thermal map and RGB + thermal (RGB-T) images of a scene from thermal-infrared and RGB images. The scene images are acquired by moving both a RGB camera and an thermal-infrared camera mounted on a stereo rig. Before capturing the scene with those cameras, we estimate their respective intrinsic parameters and their relative pose. Then, we reconstruct the 3D structures of the scene by using Direct Sparse Odometry (DSO) using the RGB images. In order to superimpose thermal information onto each point generated from DSO, we propose a method for estimating the scale of the point cloud corresponding to the extrinsic parameters between both cameras by matching depth images recovered from the RGB camera and the thermal-infrared camera based on mutual information. We also generate RGB-T images using the 3D structure of the scene and Delaunay triangulation. We do not rely on depth cameras and, therefore, our technique is not limited to scenes within the measurement range of the depth cameras. To demonstrate this technique, we generate 3D thermal maps and RGB-T images for both indoor and outdoor scenes.

With the aim of characterizing the thermal conductivity for nanometer-scale thermoelectric materials, we have constructed a new measurement system based on ac calorimetry. Analysis of the obtained data requires time-evolution of temperature distribution in nanometer-scale material under periodic heating. In this study, we made a simulation using a C#-program for time-dependent temperature distribution, based on 2-dimensional heat-diffusion equation including the influence of heat emission from material edges. The simulation was applied to AlN with millimeter-scale dimensions for confirming the validity and accuracy. The simulated thermal diffusivity for 10×75-mm2-area AlN was 1.3×10-4 m2/s, which was larger than the value set in the heat-diffusion equation. This overestimation was also observed in the experiment. Therefore, our simulation can reproduce the unsteady heat conduction and be used for analyzing the ac calorimetry experiment.

We have studied on thermally assisted nano-structured transistors made of superconductor ultra-thin films. These transistors potentially work as interface devices for Josephson-CMOS (complementary metal oxide semiconductor) hybrid memory systems, because they can generate a high output voltage of sub-V enough to drive a CMOS transistor. In addition, our superconductor transistors are formed with very fine lines down to several tens of nm in widths, leading to very small foot print enabling us to make large capacity hybrid memories. Our superconductor transistors are made with niobium titanium nitride (NbTiN) thin films deposited on thermally-oxidized silicon substrates, on which other superconductor circuits or semiconductor circuits can be formed. The NbTiN thickness dependence of the critical temperature and of resistivity suggest thermally activated vortex or anti-vortex behavior in pseudo-two-dimensional superconducting films plays an important role for the operating principle of the transistors. To show the potential that the transistors can drive MOS transistors, we analyzed the driving ability of the superconductor transistors with HSPICE simulation. We also showed the turn-on behavior of a MOS transistor used for readout of a CMOS memory cell experimentally. These results showed the high potential of superconductor transistors for Josephson-CMOS hybrid memories.

Irreversible thermal paints or temperature sensitive paints are a kind of special temperature sensor which can indicate the temperature grad by judging the color change and is widely used for off-line temperature measurement during aero engine test. Unfortunately, the hot gases flow within the engine during measuring always make the paint color degraded, which means a serious saturation reduction and contrast loss of the paint colors. This phenomenon makes it more difficult to interpret the thermal paint test results. Present contrast enhancement algorithms can significantly increase the image contrast but can't protect the hue feature of the paint images effectively, which always cause color shift. In this paper, we propose a color restoration method for thermal paint image. This method utilizes the atmospheric scattering model to restore the lost contrast and saturation information, so that the hue can be protected and the temperature can be precisely interpreted based on the image.

A robust pedestrian detection approach in thermal infrared imageries for an all-day surveillance is proposed. Firstly, the candidate regions which are likely to contain pedestrians are extracted based on a saliency detection method. Then a deep convolutional network with a multi-task loss is constructed to recognize the pedestrians. The experimental results show the superiority of the proposed approach in pedestrian detection.

Hotspots occur frequently in 3D multi-core processors (3D-MCPs), and they may adversely impact both the reliability and lifetime of a system. We present a new thermally constrained task scheduler based on a thermal-pattern-aware voltage assignment (TPAVA) to reduce hotspots in and optimize the performance of 3D-MCPs. By analyzing temperature profiles of different voltage assignments, TPAVA pre-emptively assigns different initial operating-voltage levels to cores for reducing temperature increase in 3D-MCPs. The proposed task scheduler consists of an on-line allocation strategy and a new voltage-scaling strategy. In particular, the proposed on-line allocation strategy uses the temperature-variation rates of the cores and takes into two important thermal behaviors of 3D-MCPs that can effectively minimize occurrences of hotspots in both thermally homogeneous and heterogeneous 3D-MCPs. Furthermore, a new vertical-grouping voltage scaling (VGVS) strategy that considers thermal correlation in 3D-MCPs is used to handle thermal emergencies. Experimental results indicate that, when compared to a previous online thermally constrained task scheduler, the proposed task scheduler can reduce hotspot occurrences by approximately 66% (71%) and improve throughput by approximately 8% (2%) in thermally homogeneous (heterogeneous) 3D-MCPs. These results indicate that the proposed task scheduler is an effective technique for suppressing hotspot occurrences and optimizing throughput for 3D-MCPs subject to thermal constraints.

Recent Network on Chip (NoC) design must take the thermal issue into consideration due to its great impact on the network performance and reliability, especially for 3D NoC. In this work, we design a virtual channel based fully adaptive routing algorithm for the runtime 3D NoC thermal-aware management. To improve the network throughput and latency, we use two virtual channels for each horizontal direction and design a routing function which can not only avoid deadlock and livelock, but also ensure high adaptivity and routability in the throttled network. For path selection, we design a strategy that takes priority to the distance, but also considers path diversity and traffic state. For throttling information collection, instead of transmitting the topology information of the whole network, we use a 12 bits register to reserve the router state for one hop away, which saves the hardware cost largely and decreases the network latency. In the experiments, we test our proposed routing algorithm in different states with different sizes, and the proposed algorithm shows better network latency and throughput with low power compared with traditional algorithms.

This paper describes, for the first time, an experimental study on the layout design considerations of GaAs HBT MMIC switchable-amplifier-chain-based power amplifiers (SWPAs) for CDMA handsets. The transient response of the quiescent current and output power (Pout) in GaAs HBT power amplifiers that consist of a main chain and a sub-chain is often affected by a thermal coupling between power stages and their bias circuits in the same chain or a thermal coupling between power stages and/or their bias circuits in different chains. In particular, excessively strong thermal coupling inside the MMIC SWPA causes failure in 3GPP-compliant inner loop power control tests. An experimental study reveals that both the preheating in the main/sub-chains and appropriate thermal coupling inside the main chain are very effective in reducing the turn-on delay for the two-parallel-amplifier-chain topology; for example, i) the sub-power stage is arranged near the main power stage, ii) the sub-driver stage is placed near the main driver stage and iii) the main driver bias circuit is placed near the main power stage and the sub-power stage. The SWPA operating in Band 9 (1749.9 to 1784.9 MHz), which was designed and fabricated from the foregoing considerations, shows a remarkable improvement in the Pout turn-on delay: a reduced power level error of 0.74 dB from turn-off to turn-on in the sub-amplifier chain and a reduced power level error of over 0.30 dB from turn-off to turn-on in the main amplifier chain. The main RF power measurements conducted with a 3.4-V supply voltage and a Band 9 WCDMA HSDPA modulated signal are as follows. The SWPA delivers a Pout of 28.5 dBm, a power gain (Gp) of 28 dB, and a PAE of 39% while restricting the ACLR1 to less than -40 dBc in the main amplifier chain. In the sub-amplifier chain, 17 dBm of Pout, 23.5 dB of Gp, and 27% of PAE are obtained at the same ACLR1 level.

This paper addresses the attribute recognition problem, a field of research that is dominated by studies in the visible spectrum. Only a few works are available in the thermal spectrum, which is fundamentally different from the visible one. This research performs recognition specifically on wearable attributes, such as glasses and masks. Usually these attributes are relatively small in size when compared with the human body, on top of a large intra-class variation of the human body itself, therefore recognizing them is not an easy task. Our method utilizes a decomposition framework based on Robust Principal Component Analysis (RPCA) to extract the attribute information for recognition. However, because it is difficult to separate the body and the attributes without any prior knowledge, noise is also extracted along with attributes, hampering the recognition capability. We made use of prior knowledge; namely the location where the attribute is likely to be present. The knowledge is referred to as the Probability Map, incorporated as a weight in the decomposition by RPCA. Using the Probability Map, we achieve an attribute-wise decomposition. The results show a significant improvement with this approach compared to the baseline, and the proposed method achieved the highest performance in average with a 0.83 F-score.

Characteristics of the bis-styrylbenzene derivatives with trifluoromethyl or methyl moieties were evaluated in each as-vapor-deposited film, thermally-treated film, and the crystal from the solution. Thermal treatment dramatically changed morphologies and photo-physical properties of the vapor-deposited film.

A highly efficient sky-blue organic light-emitting diode (OLED) based on a thermally-activated delayed fluorescence (TADF) molecule, 1,2-bis(carbazol-9-yl)-4,5-dicyanobenzene (2CzPN), was studied. The sky-blue OLED exhibited a maximum external electroluminescence quantum efficiency (ηEQE) of over 24.0%. In addition, a white OLED using 2CzPN combined with green and orange TADF emitters showed a high ηEQE of 17.3% with a maximum power efficiency of 52.3 lm/W and Commission Internationale de l'Eclairage coordinates of (0.32, 0.43).

The emerging three-dimensional (3D) technology is considered as a promising solution for achieving better performance and easier heterogeneous integration. However, the thermal issue becomes exacerbated primarily due to larger power density and longer heat dissipation paths. The thermal issue would also be critical once FPGAs step into the 3D arena. In this article, we first construct a fine-grained thermal resistive model for 3D FPGAs. We show that merely reducing the total power consumption and/or minimizing the power density in vertical direction is not enough for a thermal-aware 3D FPGA backend (placement and routing) flow. Then, we propose our thermal-aware backend flow named TherWare considering location-based heat balance. In the placement stage, TherWare not only considers power distribution of logic tiles in both lateral and vertical directions but also minimizes the interconnect power. In the routing stage, TherWare concentrates on overall power minimization and evenness of power distribution at the same time. Experimental results show that TherWare can significantly reduce the maximum temperature, the maximum temperature gradient, and the temperature deviation only at the cost of a minor increase in delay and runtime as compared with present arts.

The combination of a halogen-free solvent 1,2,4-trimethylbenzene and unmodified fullerene potentially provides a way to develop environmentally-friendly and cost-effective solution-processed organic photocells. In this paper, the thermal annealing effect on the optical absorption spectra in poly(3-hexylthiophene):unmodified-C$_{60}$ composites with various compositions is reported. It is found that the onset temperature of the absorption spectrum change is higher in the composites with higher fullerene content. It is speculated that strong interaction between the polymer main chain and C$_{60}$ tends to suppress the reorientation of polymer main chains in a composite with high C$_{60}$ content.

The excessively high temperature in a chip may cause circuit malfunction and performance degradation, and thus should be avoided to improve system reliability. In this paper, a novel oscillation-based on-chip thermal sensing architecture for dynamically adjusting supply voltage and clock frequency in System-on-a-Chip (SoC) is proposed. It is shown that the oscillation frequency of a ring oscillator reduces linearly as the temperature rises, and thus provides a good on-chip temperature sensing mechanism. An efficient Dynamic Voltage-to-Frequency Scaling (DF2VS) algorithm is proposed to dynamically adjust supply voltage according to the oscillation frequencies of the ring oscillators distributed in SoC so that thermal sensing can be carried at all potential hot spots. An on-chip Dynamic Voltage Scaling or Dynamic Voltage and Frequency Scaling (DVS or DVFS) monitor selects the supply voltage level and clock frequency according to the outputs of all thermal sensors. Experimental results on SoC benchmark circuits show the effectiveness of the algorithm that a 10% reduction in supply voltage alone can achieve about 20% power reduction (DVS scheme), and nearly 50% reduction in power is achievable if the clock frequency is also scaled down (DVFS scheme). The chip temperature will be significant lower due to the reduced power consumption.

With process technology scaling, a heat problem in ICs is becoming a serious issue. Since high temperature adversely impacts on reliability, design costs, and leakage power, it is necessary to incorporate thermal-aware synthesis into IC design flows. In particular, hot spots are serious concerns where a chip is locally too much heated and reducing the peak temperature inside a chip is very important. On the other hand, increasing the average interconnect delays is also becoming a serious issue. By using RDR architectures (Regular-Distributed-Register architectures), the interconnect delays can be easily estimated and their influence can be much reduced even in high-level synthesis. In this paper, we propose a thermal-aware high-level synthesis algorithm for RDR architectures. The RDR architecture divides the entire chip into islands and each island has uniform area. Our algorithm balances the energy consumption among islands through re-binding to functional units. By allocating some new additional functional units to vacant areas on islands, our algorithm further balances the energy consumption among islands and thus reduces the peak temperature. Experimental results demonstrate that our algorithm reduces the peak temperature by up to 9.1% compared with the conventional approach.

This paper presents a response time acceleration technique in a high-gain capacitive-feedback frontend amplifier (FA) for high output impedance sensors. Using an auxiliary amplifier as a unity-gain buffer, a sample-and-hold capacitor which is used for band-limiting and sampling the FA output is driven at the beginning of the transient response to make the response faster and then it is re-charged directly by the FA output. A condition and parameters for the response time acceleration using this technique while maintaining the noise level unaffected are discussed. Theoretical analysis and simulation results show that the response time can be less than half of the case without the acceleration technique for the specified settling error of less than 0.5%.

We investigate in detail the scattering properties and heating characteristics in various commercially available optical fibers and fiber cables when a bubble train forms in the middle of the fiber as a result of the fiber fuse phenomenon that occurs when a high power signal is launched into the fiber. We found theoretically and experimentally that almost all the optical light is scattered at the top of the bubble train. The scattered light heats UV coated fiber, nylon jacketed silica fiber, fire-retardant jacketed fiber (PVC or FRPE jacketed fiber) and fire-retardant fiber cable (PVC or FRPE fiber cable), to around 100, over 200 and over 600, respectively, and finally the fiber burns and is destroyed at a launched optical power of 3 W. Furthermore, it is confirmed that the combustion does not spread when we use fire retardant jacketed fibers.