Selective denoising autoencoder for classification of noisy gas mixtures using 2D transition metal dichalcogenides.

Electronic nose (E-nose) technology, which is composed of an array of chemical sensors and pattern recognition, has been widely utilized for the quantitative classification of gas mixtures. However, for the practical use of E-nose in real-industry, advanced algorithms are necessary to handle the noise in sensing data caused by various environmental variables. In order to achieve precise measurements even in real-world environments, it is necessary to denoise and classify noisy sensing data.

Synthetic Data Enhancement and Network Compression Technology of Monocular Depth Estimation for Real-Time Autonomous Driving System.

Accurate 3D image recognition, critical for autonomous driving safety, is shifting from the LIDAR-based point cloud to camera-based depth estimation technologies driven by cost considerations and the point cloud's limitations in detecting distant small objects. This research aims to enhance MDE (Monocular Depth Estimation) using a single camera, offering extreme cost-effectiveness in acquiring 3D environmental data. In particular, this paper focuses on novel data augmentation methods designed to enhance the accuracy of MDE.

Optimal Configuration of Multi-Task Learning for Autonomous Driving.

For autonomous driving, it is imperative to perform various high-computation image recognition tasks with high accuracy, utilizing diverse sensors to perceive the surrounding environment. Specifically, cameras are used to perform lane detection, object detection, and segmentation, and, in the absence of lidar, tasks extend to inferring 3D information through depth estimation, 3D object detection, 3D reconstruction, and SLAM. However, accurately processing all these image recognition operations in real-time for autonomous driving under constrained hardware conditions is practically unfeasible.

Numerical Approach to Facial Palsy Using a Novel Registration Method with 3D Facial Landmark.

Treatment of facial palsy is essential because neglecting this disorder can lead to serious sequelae and further damage. For an objective evaluation and consistent rehabilitation training program of facial palsy patients, a clinician's evaluation must be simultaneously performed alongside quantitative evaluation. Recent research has evaluated facial palsy using 68 facial landmarks as features.

Improved Feature-Based Gaze Estimation Using Self-Attention Module and Synthetic Eye Images.

Gaze is an excellent indicator and has utility in that it can express interest or intention and the condition of an object. Recent deep-learning methods are mainly appearance-based methods that estimate gaze based on a simple regression from entire face and eye images. However, sometimes, this method does not give satisfactory results for gaze estimations in low-resolution and noisy images obtained in unconstrained real-world settings (e.

A Novel Method Based on GAN Using a Segmentation Module for Oligodendroglioma Pathological Image Generation.

Digital pathology analysis using deep learning has been the subject of several studies. As with other medical data, pathological data are not easily obtained. Because deep learning-based image analysis requires large amounts of data, augmentation techniques are used to increase the size of pathological datasets.

Efficient Single-Shot Multi-Object Tracking for Vehicles in Traffic Scenarios.

Multi-object tracking is a significant field in computer vision since it provides essential information for video surveillance and analysis. Several different deep learning-based approaches have been developed to improve the performance of multi-object tracking by applying the most accurate and efficient combinations of object detection models and appearance embedding extraction models. However, two-stage methods show a low inference speed since the embedding extraction can only be performed at the end of the object detection.

Robust Extrinsic Calibration of Multiple RGB-D Cameras with Body Tracking and Feature Matching.

RGB-D cameras have been commercialized, and many applications using them have been proposed. In this paper, we propose a robust registration method of multiple RGB-D cameras. We use a human body tracking system provided by Azure Kinect SDK to estimate a coarse global registration between cameras.

CD44-Mediated Methotrexate Delivery by Hyaluronan-Coated Nanoparticles Composed of a Branched Cell-Penetrating Peptide.

Branched polymers as drug delivery carriers have been widely attempted due to their outstanding drug loading capability and complex stability like branched polyethyleneimine (B-PEI). However, branched polymers without biodegradability may cause toxicity as they can accumulate in the body. Herein, we report branched modified nona-arginine (B-mR9) composed of redox-cleavable disulfide bonds to form stable complexes with methotrexate (MTX) as an anticancer agent, which is further coated with hyaluronic acid (HA).

Development of Real-Time Hand Gesture Recognition for Tabletop Holographic Display Interaction Using Azure Kinect.

The use of human gesturing to interact with devices such as computers or smartphones has presented several problems. This form of interaction relies on gesture interaction technology such as Leap Motion from Leap Motion, Inc, which enables humans to use hand gestures to interact with a computer. The technology has excellent hand detection performance, and even allows simple games to be played using gestures.

An Extended Method for Saccadic Eye Movement Measurements Using a Head-Mounted Display.

Saccadic eye movementis an important ability in our daily life and is especially important in driving and sports. Traditionally, the Developmental Eye Movement (DEM) test and the King-Devick (K-D) test have been used to measure saccadic eye movement, but these only involve measurements with "adjusted time". Therefore, a different approach is required to obtain the eye movement speed and reaction rate in detail, as some are rapid eye movements, while others are slow actions, and vice versa.

Real-Time Vehicle-Detection Method in Bird-View Unmanned-Aerial-Vehicle Imagery.

Vehicle detection is an important research area that provides background information for the diversity of unmanned-aerial-vehicle (UAV) applications. In this paper, we propose a vehicle-detection method using a convolutional-neural-network (CNN)-based object detector. We design our method, DRFBNet300, with a Deeper Receptive Field Block (DRFB) module that enhances the expressiveness of feature maps to detect small objects in the UAV imagery.

A Helical Polypeptide-Based Potassium Ionophore Induces Endoplasmic Reticulum Stress-Mediated Apoptosis by Perturbing Ion Homeostasis.

Perturbation of potassium homeostasis can affect various cell functions and lead to the onset of programmed cell death. Although ionophores have been intensively used as an ion homeostasis disturber, the mechanisms of cell death are unclear and the bioapplicability is limited. In this study, helical polypeptide-based potassium ionophores are developed to induce endoplasmic reticulum (ER) stress-mediated apoptosis.

Author Correction: Evaluation of cell penetrating peptide coated Mn:ZnS nanoparticles for paclitaxel delivery to cancer cells.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

Curcumin as a Novel Nanocarrier System for Doxorubicin Delivery to MDR Cancer Cells: In Vitro and In Vivo Evaluation.

Curcumin (CRC) has been widely used as a therapeutic agent for various drug delivery applications. In this work, we focused on the applicability of CRC as a nanodrug delivery agent for doxorubicin hydrochloride (DOX) (commercially known as Adriamycin) coated with poly(ethylene glycol) (PEG) as an effective therapeutic strategy against multidrug-resistant cancer cells. The developed PEG-coated CRC/DOX nanoparticles (NPs) (PEG-CRC/DOX NPs) were well localized within the resistant cancer cells inducing apoptosis confirmed by flow cytometry and DNA fragmentation assays.

Evaluation of cell penetrating peptide coated Mn:ZnS nanoparticles for paclitaxel delivery to cancer cells.

This work aimed at formulating paclitaxel (PTX) loaded cell penetrating peptide (CPP) coated Mn doped ZnS nanoparticles (Mn:ZnS NPs) for improved anti-cancer efficacy in vitro and in vivo. The developed PTX loaded Mn:ZnS NPs with different CPPs (PEN, pVEC and R9) showed enhanced anti-cancer effect compared to bare PTX, which has been validated by MTT assay followed by apoptosis assay and DNA fragmentation analysis. The in vivo bio-distribution and anti-cancer efficacy was studied on breast cancer xenograft model showing maximum tumor localization and enhanced therapeutic efficacy with R9 coated Mn:ZnS NPs (R9:Mn:ZnS NPs) and was confirmed by H/E staining.

360-degree color hologram generation for real 3D objects.

Recently, holographic display and computer-generated holograms calculated from real existing objects have been more actively investigated to support holographic video applications. In this paper, we proposed a method of generating 360-degree color holograms of real 3D objects in an efficient manner. 360-degree 3D images are generated using the actual 3D image acquisition system consisting of a depth camera and a turntable and intermediate view generation.

Protease-activatable cell-penetrating peptide possessing ROS-triggered phase transition for enhanced cancer therapy.

Reactive oxygen species (ROS)- or protease-responsive materials have been utilized as carriers in cancer therapies because ROS and specific proteases are overproduced in cancer cells. Methionine-based polypeptides containing a thioether group are promising candidates due to their ROS-responsiveness which provides a phase transition. Herein, we developed protease-activatable cell-penetrating peptide containing a ROS-responsive methionine, a cell permeable lysine chain, and a matrix metalloproteinase (MMP)-cleavable linker.

Conformation-switchable helical polypeptide eliciting selective pro-apoptotic activity for cancer therapy.

Artificial cationic helical peptides possess an enhanced cell-penetrating property. However, their cell-penetrability is not converted by cellular environmental changes resulting in nonspecific uptake. In this study, pH-sensitive anion-donating groups were added to a helical polypeptide to simultaneously achieve tumor targeting and pro-apoptotic activity.

pH-controllable cell-penetrating polypeptide that exhibits cancer targeting.

Unlabelled: Helical peptides were naturally-occurring ordered conformations that mediated various biological functions essential for biotechnology. However, it was difficult for natural helical polypeptides to be applied in biomedical fields due to low bioavailability. To avoid these problems, synthetic alpha-helical polypeptides have recently been introduced by further modifying pendants in the side chain.

A branched TAT cell-penetrating peptide as a novel delivery carrier for the efficient gene transfection.

Background: Cell penetrating peptides (CPPs) as one class of non-viral vectors, have been widely explored as a delivery tool due to their cell-penetrating capability with low cytotoxicity. However, CPPs have reported to have low gene transfection efficiency mainly due to the fact that DNA is larger than other biomolecules. On the other hand, the conventional linear CPPs are unstable for constructing the DNA complexes with it.

Bioreducible branched poly(modified nona-arginine) cell-penetrating peptide as a novel gene delivery platform.

Cell-penetrating peptides (CPPs) have been widely used to deliver nucleic acid molecules. Generally, CPPs consisting of short amino acid sequences have a linear structure, resulting in a weak complexation and low transfection efficacy. To overcome these drawbacks, a novel type of CPP is required to enhance the delivery efficacy while maintaining its safe use at the same time.

Scalable hologram video coding for adaptive transmitting service.

This paper discusses processing techniques for an adaptive digital holographic video service in various reconstruction environments, and proposes two new scalable coding schemes. The proposed schemes are constructed according to the hologram generation or acquisition schemes: hologram-based resolution-scalable coding (HRS) and light source-based signal-to-noise ratio scalable coding (LSS). HRS is applied for holograms that are already acquired or generated, while LSS is applied to the light sources before generating digital holograms.

Hardware architecture of high-performance digital hologram generator on the basis of a pixel-by-pixel calculation scheme.

In this paper we propose a hardware architecture for high-speed computer-generated hologram generation that significantly reduces the number of memory access times to avoid the bottleneck in the memory access operation. For this, we use three main schemes. The first is pixel-by-pixel calculation, rather than light source-by-source calculation.

Cell-based hardware architecture for full-parallel generation algorithm of digital holograms.

This paper proposes a new hardware architecture to speed-up the digital hologram calculation by parallel computation. To realize it, we modify the computer-generated hologram (CGH) equation and propose a cell-based very large scale integrated circuit architecture. We induce a new equation to calculate the horizontal or vertical hologram pixel values in parallel, after finding the calculation regularity in the horizontal or vertical direction from the basic CGH equation.