A Deep Learning Approach for Automotive Radar Interference Mitigation

In automotive systems, a radar is a key component of autonomous driving. Using transmit and reflected radar signal by a target, we can capture the target range and velocity. However, when interference signals exist, noise floor increases and it severely affects the detectability of target objects. For these reasons, previous studies have been proposed to cancel interference or reconstruct original signals. However, the conventional signal processing methods for canceling the interference or reconstructing the transmit signals are difficult tasks, and also have many restrictions. In this work, we propose a novel approach to mitigate interference using deep learning. The proposed method provides high performance in various interference conditions and has low processing time. Moreover, we show that our proposed method achieves better performance compared to existing signal processing methods.Comment: Accepted in 2018 VTC worksho

A Deep Learning Approach for Automotive Radar Interference Mitigation

In automotive systems, a radar is a key component of autonomous driving. Using transmit and reflected radar signal by a target, we can capture the target range and velocity. However, when interference signals exist, noise floor increases and it severely affects the detectability of target objects. For these reasons, previous studies have been proposed to cancel interference or reconstruct original signals. However, the conventional signal processing methods for canceling the interference or reconstructing the transmit signals are difficult tasks, and also have many restrictions. In this work, we propose a novel approach to mitigate interference using deep learning. The proposed method provides high performance in various interference conditions and has low processing time. Moreover, we show that our proposed method achieves better performance compared to existing signal processing methods.Comment: Accepted in 2018 VTC worksho

Affective Role of the Future Autonomous Vehicle Interior

Recent advancements in autonomous technology allow for new opportunities in vehicle interior design. Such a shift in in-vehicle activity suggests vehicle interior spaces should provide an adequate manner by considering users' affective desires. Therefore, this study aims to investigate the affective role of future vehicle interiors. Thirty one participants in ten focus groups were interviewed about challenges they face regarding their current vehicle interior and expectations they have for future vehicles. Results from content analyses revealed the affective role of future vehicle interiors. Advanced exclusiveness and advanced convenience were two primary aspects identified. The identified affective roles of each aspect are a total of eight visceral levels, four visceral levels each, including focused, stimulating, amused, pleasant, safe, comfortable, accommodated, and organized. We expect the results from this study to lead to the development of affective vehicle interiors by providing the fundamental knowledge for developing conceptual direction and evaluating its impact on user experiences.Comment: 15 pages, 4 figures, 2 table

Study on Multi-Point Stretch Forming Process for Double Curved Surface

Multi-Point Stretch Forming (MPSF) process is suitable for flexible manufacturing, and it has several advantages including that it could be applied to various forming such as sheet metal forming, single curved surface forming and double curved one. In this study, a systematic numerical simulation was carried out for atypical double curved surface forming using the multiple die stretch forming process. In this simulation, urethane pads were defined based on hyper-elastic material model as a cushion for the smooth forming surface. The deformation behaviour on elastic recovery was also investigated to consider the exact result after the last forming process, and then the experiment was also carried out to confirm the formability of this forming process. By comparing the simulation and experiment results, the suitability of the multiple die stretch forming process for the atypical double curved surface was verified. Consequently, it is confirmed that the multi-point stretch forming process has the capability and feasibility of being used to manufacture the double curved surfaces of sheet metal

Statistical Analysis of Pc1 Pulsations Observed by a BOH Magnetometer

Pc1 pulsations are important to consider for the interpretation of wave-particle interactions in the Earth’s magnetosphere. In fact, the wave properties of these pulsations change dynamically when they propagate from the source region in the space to the ground. A detailed study of the wave features can help understanding their time evolution mechanisms. In this study, we statistically analyzed Pc1 pulsations observed by a Bohyunsan (BOH) magneto-impedance (MI) sensor located in Korea (L = 1.3) for ~one solar cycle (November 2009-August 2018). In particular, we investigated the temporal occurrence ratio of Pc1 pulsations (considering seasonal, diurnal, and annual variations in the solar cycle), their wave properties (e.g., duration, peak frequency, and bandwidth), and their relationship with geomagnetic activities by considering the Kp and Dst indices in correspondence of the Pc1 pulsation events. We found that the Pc1 waves frequently occurred in March in the dawn (1-3 magnetic local time (MLT)) sector, during the declining phase of the solar cycle. They generally continued for 2-5 minutes, reaching a peak frequency of ~0.9 Hz. Finally, most of the pulsations have strong dependence on the geomagnetic storm and observed during the early recovery phase of the geomagnetic storm

The Use of Complementary and Alternative Medicine by Korean Breast Cancer Women: Is It Associated with Severity of Symptoms?

Background. Use of complementary and alternative medicine (CAM) among patients with breast cancer could be associated with severity of the cancer symptoms experienced, but there is little evidence to prove this. This study tried to investigate any difference in the severity of breast cancer symptoms between CAM users and nonusers. Methods. The study followed cross-sectional design using structured survey questionnaire. Survey participants were recruited from four different healthcare settings in Seoul, South Korea. The survey instrument comprised 39 items including questions on demographics, use of CAM, and six main symptoms associated with breast cancer and cancer treatment. Results. Out of 288 participants, 67% stated using one or more modalities of CAM. Age, education, and time duration since diagnosis of cancer were significantly associated with use of CAM. About 90% of the CAM users experienced side effects of cancer treatment. CAM users reported more severe anxiety and skin/hair changes than nonusers. Conclusions. CAM was used by those breast cancer patients who experience more severe symptoms to alleviate the conditions associated with breast cancer and cancer treatment. Our findings revealed motivation behind the CAM use, which has profound implications for clinicians to recognize patient-perceived needs

Comparative metabolic profiling of posterior parietal cortex, amygdala, and hippocampus in conditioned fear memory

Fear conditioning and retrieval are suitable models to investigate the biological basis of various mental disorders. Hippocampus and amygdala neurons consolidate conditioned stimulus (CS)-dependent fear memory. Posterior parietal cortex is considered important for the CS-dependent conditioning and retrieval of fear memory. Metabolomic screening among functionally related brain areas provides molecular signatures and biomarkers to improve the treatment of psychopathologies. Herein, we analyzed and compared changes of metabolites in the hippocampus, amygdala, and posterior parietal cortex under the fear retrieval condition. Metabolite profiles of posterior parietal cortex and amygdala were similarly changed after fear memory retrieval. While the retrieval of fear memory perturbed various metabolic pathways, most metabolic pathways that overlapped among the three brain regions had high ranks in the enrichment analysis of posterior parietal cortex. In posterior parietal cortex, the most perturbed pathways were pantothenate and CoA biosynthesis, purine metabolism, glutathione metabolism, and NAD+ dependent signaling. Metabolites of posterior parietal cortex including 4′-phosphopantetheine, xanthine, glutathione, ADP-ribose, ADP-ribose 2′-phosphate, and cyclic ADP-ribose were significantly regulated in these metabolic pathways. These results point to the importance of metabolites of posterior parietal cortex in conditioned fear memory retrieval and may provide potential biomarker candidates for traumatic memory-related mental disorders. © 2021, The Author(s).1

Three-dimensional digital microfluidic manipulation of droplets in oil medium

We here develop a three-dimensional DMF (3D DMF) platform with patterned electrodes submerged in an oil medium to provide fundamental solutions to the technical limitations of 2D DMF platforms and water-air systems. 3D droplet manipulation on patterned electrodes is demonstrated by programmably controlling electrical signals. We also demonstrate the formation of precipitates on the 3D DMF platform through the reaction of different chemical samples. A droplet containing precipitates, hanging on the top electrode, can be manipulated without adhesion of precipitates to the solid surface. This method could be a good alternative strategy to alleviate the existing problems of 2D DMF systems such as cross-contamination and solute adsorption. In addition, we ascertain the feasibility of temperature-controlled chemical reaction on the 3D DMF platform by introducing a simple heating process. To demonstrate applicability of the 3D DMF system to 3D biological process, we examine the 3D manipulation of droplets containing mouse fibroblasts in the 3D DMF platform. Finally, we show detachment of droplets wrapped by a flexible thin film by adopting the electro-elasto-capillarity ( EEC). The employment of the EEC may offer a strong potential in the development of 3D DMF platforms for drug encapsulation and actuation of microelectromechanical devices.open111416sciescopu