To surmount the difficulties encountered by standard display devices in displaying high dynamic range (HDR) images, this study developed a modified tone-mapping operator (TMO) anchored in the iCAM06 image color appearance model. By combining iCAM06 with a multi-scale enhancement algorithm, the iCAM06-m model improved image chroma accuracy through the compensation of saturation and hue drift. selleck compound Subsequently, a subjective evaluation exercise was undertaken to analyze iCAM06-m and three other TMOs, using a rating system for the tones in the mapped images. selleck compound In closing, the objective and subjective evaluation results were carefully compared and analyzed. The research findings validated the iCAM06-m's enhanced performance over other models. The chroma compensation system effectively countered the detrimental effects of saturation reduction and hue changes in iCAM06 HDR image tone mapping applications. Beyond that, the introduction of multi-scale decomposition fostered the delineation of image specifics and an elevated sharpness. Consequently, the suggested algorithm successfully addresses the limitations inherent in other algorithms, making it a strong contender for a universal TMO.
This paper introduces a sequential variational autoencoder for video disentanglement, a representation learning technique enabling the isolation of static and dynamic video features. selleck compound Employing a two-stream architecture within sequential variational autoencoders fosters inductive biases conducive to disentangling video data. Despite our preliminary experiment, the two-stream architecture proved insufficient for video disentanglement, as static visual information frequently includes dynamic components. Subsequently, we discovered that dynamic aspects are not effective in distinguishing elements in the latent space. Employing supervised learning, an adversarial classifier was incorporated into the two-stream architecture to mitigate these problems. Supervision's strong inductive bias isolates dynamic features from static ones, resulting in discriminative representations that capture the dynamic aspects. A comparative analysis of the proposed method with other sequential variational autoencoders reveals its effectiveness on the Sprites and MUG datasets, through both qualitative and quantitative measures.
We propose a novel approach to robotic industrial insertion tasks, employing the Programming by Demonstration method. With our method, a single demonstration by a human is sufficient for robots to learn a high-precision task, completely independent of any previous knowledge regarding the object. We introduce a fine-tuned imitation approach, starting with cloning human hand movements to create imitation trajectories, then adjusting the target location precisely using a visual servoing method. Modeling object tracking as a moving object detection problem facilitates the identification of object features for visual servoing. Each frame of the demonstration video is separated into a moving foreground (containing the object and the demonstrator's hand) and a stationary background. A hand keypoints estimation function is then utilized to remove any unnecessary features on the hand. The experiment confirms that the proposed method empowers robots to learn precise industrial insertion tasks from a single human demonstration.
The direction of arrival (DOA) of signals is frequently estimated using classifications derived from deep learning methodologies. The limited course selection hinders the DOA classification's ability to achieve the desired prediction accuracy for signals originating from random azimuths in actual applications. The deep neural network classification method, CO-DNNC, is presented in this paper for enhancing the accuracy of direction-of-arrival (DOA) estimations. CO-DNNC leverages signal preprocessing, a classification network, and centroid optimization to achieve its intended function. A convolutional neural network, incorporating convolutional and fully connected layers, forms the basis of the DNN classification network. By using the probabilities from the Softmax output, the Centroid Optimization algorithm determines the azimuth of the received signal, considering the classified labels as coordinates. CO-DNNC's experimental performance showcases its ability to provide highly precise and accurate DOA estimations, demonstrating its resilience in low signal-to-noise environments. CO-DNNC's advantage lies in requiring a smaller number of classes, while upholding the same prediction accuracy and signal-to-noise ratio (SNR). This simplifies the DNN network's design and consequently shortens training and processing times.
We describe novel UVC sensors, functioning on the floating gate (FG) discharge principle. The device functions in a manner analogous to EPROM non-volatile memories' UV erasure, but the responsiveness to ultraviolet light is exceptionally amplified by the employment of single polysilicon devices with low FG capacitance and an extensive gate periphery (grilled cells). In a standard CMOS process flow with a UV-transparent back end, the devices were integrated without requiring any additional masks. UVC sterilization systems benefited from optimized low-cost, integrated solar blind UVC sensors, which provided data on the radiation dosage necessary for effective disinfection. Measurements of ~10 J/cm2 doses at 220 nm could be accomplished in under one second. This device enables the control of UVC radiation doses, typically in the 10-50 mJ/cm2 range, for the disinfection of surfaces or air, with a reprogramming capacity of up to 10,000 times. Integrated solutions, comprising UV light sources, sensors, logical components, and communication systems, were put to the test through fabricated demonstrations. Silicon-based UVC sensing devices currently available did not demonstrate any degradation that hindered their intended applications. The developed sensors have diverse uses, and the use of these sensors in UVC imaging is explored.
Morton's extension, as an orthopedic intervention for bilateral foot pronation, is the subject of this study, which evaluates the mechanical impact of the intervention on hindfoot and forefoot pronation-supination forces during the stance phase of gait. Using a Bertec force plate, a quasi-experimental, cross-sectional study compared three conditions: (A) barefoot, (B) footwear with a 3 mm EVA flat insole, and (C) a 3 mm EVA flat insole with a 3 mm thick Morton's extension. This study focused on the force or time relationship to maximum subtalar joint (STJ) supination or pronation time. Regarding the subtalar joint (STJ)'s maximum pronation force, Morton's extension failed to elicit notable differences in the gait phase at which this force peaked, nor in the magnitude of the force itself, despite a decrease in its value. A substantial and timely increase in the maximum supination force was observed. Implementing Morton's extension method seemingly leads to a decrease in the peak pronation force and an increase in the subtalar joint's supination. Consequently, this could potentially refine the biomechanical response of foot orthoses, effectively managing excessive pronation.
Control systems for automated, intelligent, and self-aware crewless vehicles and reusable spacecraft within future space revolutions heavily rely on the functionality of sensors. Specifically, aerospace applications stand to benefit greatly from fiber optic sensors' small form factor and electromagnetic shielding. The demanding conditions and the presence of radiation in the operating environment for these sensors pose a challenge for both aerospace vehicle designers and fiber optic sensor specialists. Within this review, we aim to provide a foundational understanding of fiber optic sensors in aerospace radiation environments. A critical analysis of essential aerospace requirements is undertaken, and their ties to fiber optic systems are determined. In addition, we offer a succinct overview of fiber optic technology and the sensors derived from it. Lastly, we display a range of application instances in aerospace, subject to radiation environments.
Currently, electrochemical biosensors and other bioelectrochemical devices predominantly rely on Ag/AgCl-based reference electrodes for their operation. Standard reference electrodes, while fundamental, frequently prove too substantial for electrochemical cells constructed for the analysis of analytes in reduced-volume portions. Hence, a wide range of designs and improvements to reference electrodes are essential for the future progression of electrochemical biosensors and other bioelectrochemical devices. We describe in this study a process for the application of common laboratory polyacrylamide hydrogel in a semipermeable junction membrane, situating it between the Ag/AgCl reference electrode and the electrochemical cell. During this study, we have developed disposable, easily scalable, and reproducible membranes, which are appropriate for the design and construction of reference electrodes. Ultimately, we arrived at castable semipermeable membranes as a solution for reference electrodes. Through experimentation, the most suitable gel formation conditions for achieving optimum porosity were determined. A study was conducted to evaluate the movement of Cl⁻ ions within the constructed polymeric junctions. Utilizing a three-electrode flow system, the designed reference electrode was subjected to rigorous testing. Home-built electrodes demonstrate comparable performance to commercial ones because of their minuscule reference electrode potential fluctuation (~3 mV), long shelf-life (up to six months), superior stability, reduced cost, and disposable nature. The results demonstrate a strong response rate, solidifying the position of in-house manufactured polyacrylamide gel junctions as viable membrane alternatives for reference electrodes, particularly in scenarios requiring the use of disposable electrodes for high-intensity dye or toxic compound applications.
The aim of the 6th generation (6G) wireless network is to achieve global connectivity using environmentally friendly networks, which will consequently elevate the overall quality of life.