APPROXIMATE OPTIMAL AUTOSAR SOFTWARE COMPONENTS DEPLOYING APPROACH FOR AUTOMOTIVE E/E SYSTEM

Zheng Ran,Hua Yan,Huimin Zhang,Yun Li 한국자동차공학회 2017 International journal of automotive technology Vol.18 No.6

The AUTOSAR has been developed as the worldwide standard for automotive E/E software systems, making the electronic components of different suppliers to be employed universally. However, as the number of component-based applications in modern automotive embedded systems grows rapidly and the hardware topology becomes increasingly complex, deploying such large number of components in automotive distributed system in manual way is over-dependent on experience of engineers which in turn is time consuming. Furthermore, the resource limitation and scheduling analysis make the problems more complex for developers to find out an approximate optimal deploying approach in system integration. In this paper, we propose a novel method to deploy the AUTOSAR components onto ECUs with the following features. First, a clustering algorithm is designed for deploying components automatically within relatively low time complexity. Second, a fitness function is designed to balance the ECUs load. The goal of our approach is to minimize the communication cost over all the runnable entities while meeting all corresponding timing constraints and balancing all the ECUs load. The experiment results show that our approach is efficient and has well performance by comparing with other existing methods in specific and synthetic data set.

A study on the Performance of Hybrid Normal Mapping Techniques for Real-time Rendering

ZhengRan Liu,김기홍,SANG YUANZI 한국인터넷방송통신학회 2023 International journal of advanced smart convergenc Vol.12 No.4

Achieving realistic visual quality while maintaining optimal real-time rendering performance is a major challenge in evolving computer graphics and interactive 3D applications. Normal mapping, as a core technology in 3D, has matured through continuous optimization and iteration. Hybrid normal mapping as a new mapping model has also made significant progress and has been applied in the 3D asset production pipeline. This study comprehensively explores the hybrid normal techniques, analyzing Linear Blending, Overlay Blending, Whiteout Blending, UDN Blending, and Reoriented Normal Mapping, and focuses on how the various hybrid normal techniques can be used to achieve rendering performance and visual fidelity. performance and visual fidelity. Under the consideration of computational efficiency, visual coherence, and adaptability in different 3D production scenes, we design comparative experiments to explore the optimal solutions of the hybrid normal techniques by analyzing and researching the code, the performance of different hybrid normal mapping in the engine, and analyzing and comparing the data. The purpose of the research and summary of the hybrid normal technology is to find out the most suitable choice for the mainstream workflow based on the objective reality. Provide an understanding of the hybrid normal mapping technique, so that practitioners can choose how to apply different hybrid normal techniques to the corresponding projects. The purpose of our research and summary of mixed normal technology is to find the most suitable choice for mainstream workflows based on objective reality. We summarized the hybrid normal mapping technology and experimentally obtained the advantages and disadvantages of different technologies, so that practitioners can choose to apply different hybrid normal mapping technologies to corresponding projects in a reasonable manner.

Effect of Polymer Molecular Weight on Morphology and Charge Transport of Small‑Molecular Organic Semiconductors

Zhengran He,Ziyang Zhang,Sheng Bi,Jihua Chen 대한금속·재료학회 2020 ELECTRONIC MATERIALS LETTERS Vol.16 No.5

The utilization of polymer additives provides an intriguing pathway to tune the electrical performance of solution-grown,small-molecular organic semiconductors. In this study, we report the effect of different polymer molecular weight on thecrystal growth, phase segregation and charge transport of the organic semiconductors. A semicrystalline polymer additivepolyethylene oxide (PEO) with 8000 and 100 K molecular weight was blended with a well-known organic semiconductor6,13-bis(triisopropylsilylethynyl) pentacene (TIPS pentacene). Distinctively different thin film morphology of the resultantTIPS pentacene/PEO blend film was identified and quantitatively characterized. In particular, PEO with a higher molecularweight of 100 K exerted a stronger effect on enhancing film formation, crystal coverage and likely mechanical properties,whereas PEO with an 8000 molecular weight yielded more superior crystal alignment and larger crystal sizes. Bottom-gate,top-contact TIPS pentacene/PEO OTFTs were fabricated to test the charge transport, which indicated loading the PEOpolymer with molecular weight of 8000 demonstrated a five-fold enhancement in the extracted hole mobilities as comparedto the 100 K counterpart. This work of using polymer additives with different molecular weight can be used to tune thecrystallization of other solution-processed high-mobility small-molecular organic semiconductors.

Design a seamless texture generation pipeline driven by AI-driven Physically Based Rendering (PBR)

Zhengran Liu,Ki-Hong Kim,David Junesok Lee 한국콘텐츠학회 2023 한국콘텐츠학회 ICCC 논문집 Vol.2023 No.12

Solvent Exchange in Controlling Semiconductor Morphology

Zhengran He,Ziyang Zhang,Kyeiwaa Asare-Yeboah,Sheng Bi 대한금속·재료학회 2022 ELECTRONIC MATERIALS LETTERS Vol.18 No.6

Recent studies in solution processed, small molecular organic semiconductors have reported unparalleled advances in charge carrier mobilities, warranting promising application in organic electronic devices such as organic gas sensors and complimentary circuits. However, the in-solution crystallization of small molecular organic semiconductors has presented specific challenges including crystal misorientation, grain boundary and mobility variation. In this article, we first discuss the effects of these issues on charge transport and highlight the virtues of solvent choices to optimize the semiconductor morphology. Then, we conduct an in-depth review of the miscellaneous solvent exchange methods to effectively palliate these challenges. By discussing various benchmark semiconductor materials such as 6,13-bis(triisopropylsilylethynyl) pentacene (TIPS pentacene) and perylenetetracarboxyldiimide derivatives (PTCDI-Cn), we demonstrate the solvent exchange-based crystallization methods can modulate supramolecular aggregation, promote nucleation formation, improve semiconductor alignment, change crystal dimensionality, and enhance charge transport. We believe this work provides useful comprehension of employing the solvent exchange methods to powerfully regulate the crystallization, morphology and mobility of organic semiconductors, and thereby casts light on high performance organic electronic applications.

Crystal growth of small-molecule organic semiconductors with nucleation additive

He Zhengran,Zhang Ziyang,Asare-Yeboah Kyeiwaa,Bi Sheng,Chen Jihua,Li Dawen 한국물리학회 2021 Current Applied Physics Vol.21 No.-

In this study, we employ a nucleation additive 4-octylbenzoic acid (OBA) with an optimized solvent evaporation method to regulate crystal orientation and grain width of small-molecule organic semiconductors. When 6,13-bis (triisopropylsilylethynyl) pentacene (TIPS pentacene) was utilized as a benchmark material to mix with the additive, a self-assembled OBA interfacial layer was formed and promoted uniform deposition of nucleation seeds. As a result, the TIPS pentacene/OBA blend crystalline film exhibited crystal alignment in long range order, attributing to a 11-fold reduction of the crystal misorientation angle and a 4-fold increase of the grain width. We further discussed the important correlation between the effective hole mobility, grain boundaries, grain width and length, and nucleation sites. Organic thin film transistors were fabricated to test charge transport, yielding a hole mobility of up to 0.17 cm2/V. This work provides a new pathway to modulate the nucleation and crystallization events of organic semiconductors, and can potentially be applied to optimize the thin film morphology and electrical performance of organic semiconducting materials in general.

A Lightweight Pedestrian Intrusion Detection and Warning Method for Intelligent Traffic Security

Xinyun Yan,Zhengran He,Youxiang Huang,Xiaohu Xu,Jie Wang,Xiaofeng Zhou,Chishe Wang,Zhiyi Lu 한국인터넷정보학회 2022 KSII Transactions on Internet and Information Syst Vol.16 No.12

As a research hotspot, pedestrian detection has a wide range of applications in the field of computer vision in recent years. However, current pedestrian detection methods have problems such as insufficient detection accuracy and large models that are not suitable for large-scale deployment. In view of these problems mentioned above, a lightweight pedestrian detection and early warning method using a new model called you only look once (Yolov5) is proposed in this paper, which utilizing advantages of Yolov5s model to achieve accurate and fast pedestrian recognition. In addition, this paper also optimizes the loss function of the batch normalization (BN) layer. After sparsification, pruning and fine-tuning, got a lot of optimization, the size of the model on the edge of the computing power is lower equipment can be deployed. Finally, from the experimental data presented in this paper, under the training of the road pedestrian dataset that we collected and processed independently, the Yolov5s model has certain advantages in terms of precision and other indicators compared with traditional single shot multiBox detector (SSD) model and fast region-convolutional neural network (Fast R-CNN) model. After pruning and lightweight, the size of training model is greatly reduced without a significant reduction in accuracy, and the final precision reaches 87%, while the model size is reduced to 7,723 KB.

Exploring the Process of Avatar Identification in Role-Playing Games : a Case of <The Last of Us>

SANG YUANZI,김기홍,ZhengRan Liu 사단법인 한국융합기술연구학회 2024 아시아태평양융합연구교류논문지 Vol.10 No.2

With the advancement of media technology, it has become increasingly challenging to study new media contents and mechanics through traditional narrative theories. The emergence of video games once sparked intense debates between narratologists and ludologists. In video games, Role-Playing Games are particularly notable for creating a strong sense of immersion and identification with game characters. Furthermore, an avatar is the representation of the player that is projected to other players. During the gameplay experience, players tend to identify with the characters they control, leading to a profound state of flow. Through theoretical analysis and the process of developing avatar identification this study explores the beneficial impact of player avatar recognition on RPG gaming experience. It posits that the process of experiencing the game and the process of avatar identification largely overlap. To make the research results more obvious, the study analyzed the game <The Last of Us>(2013) by examining the avatar identification process in this game. Due to the single storyline of this game, it can more specifically demonstrate the role of avatar identification. The study aimed to illustrate how such a psychological mechanism emerges during the gameplay experience. Furthermore, avatar identification can stimulate a stronger desire for exploration within players during the game and suggests that players form an attachment to, or focus on the construction of avatar identity in games.

Application of Virtual Studio Technology and Digital Human Monocular Motion Capture Technology -Based on <Beast Town> as an Example-

SANG YUANZI,김기홍,이준석,탕지추,장가오허,ZhengRan Liu,QianRu Liu,선시지에,YuTing Wang,KaiXing Wang 한국인터넷방송통신학회 2024 International Journal of Internet, Broadcasting an Vol.16 No.1

This article takes the talk show "Beast Town" as an example to introduce the overall technical solution, technical difficulties and countermeasures for the combination of cartoon virtual characters and virtual studio technology, providing reference and experience for the multi-scenario application of digital humans. Compared with the live broadcast that combines reality and reality, we have further upgraded our virtual production technology and digital human-driven technology, adopted industry-leading real-time virtual production technology and monocular camera driving technology, and launched a virtual cartoon character talk show - "Beast Town" to achieve real Perfectly combined with virtuality, it further enhances program immersion and audio-visual experience, and expands infinite boundaries for virtual manufacturing. In the talk show, motion capture shooting technology is used for final picture synthesis. The virtual scene needs to present dynamic effects, and at the same time realize the driving of the digital human and the movement with the push, pull and pan of the overall picture. This puts forward very high requirements for multi-party data synchronization, real-time driving of digital people, and synthetic picture rendering. We focus on issues such as virtual and real data docking and monocular camera motion capture effects. We combine camera outward tracking, multi-scene picture perspective, multi-machine rendering and other solutions to effectively solve picture linkage and rendering quality problems in a deeply immersive space environment. , presenting users with visual effects of linkage between digital people and live guests.

Deep Learning-Enhanced Hand Grip and Release Test for Degenerative Cervical Myelopathy: Shortening Assessment Duration to 6 Seconds

Yongyu Ye,Yunbing Chang,Weihao Wu,Tianying Liao,Tao Yu,Chong Chen,Zhengran Yu,Junying Chen,Guoyan Liang 대한척추신경외과학회 2024 Neurospine Vol.21 No.1

Objective: Hand clumsiness and reduced hand dexterity can signal early signs of degenerative cervical myelopathy (DCM). While the 10-second grip and release (10-s G&R) test is a common clinical tool for evaluating hand function, a more accessible method is warranted. This study explores the use of deep learning-enhanced hand grip and release test (DL-HGRT) for predicting DCM and evaluates its capability to reduce the duration of the 10-s G&R test. Methods: The retrospective study included 508 DCM patients and 1,194 control subjects. Propensity score matching (PSM) was utilized to minimize the confounding effects related to age and sex. Videos of the 10-s G&R test were captured using a smartphone application. The 3D-MobileNetV2 was utilized for analysis, generating a series of parameters. Additionally, receiver operating characteristic curves were employed to assess the performance of the 10-s G&R test in predicting DCM and to evaluate the effectiveness of a shortened testing duration. Results: Patients with DCM exhibited impairments in most 10-s G&R test parameters. Before PSM, the number of cycles achieved the best diagnostic performance (area under the curve [AUC], 0.85; sensitivity, 80.12%; specificity, 74.29% at 20 cycles), followed by average grip time. Following PSM for age and gender, the AUC remained above 0.80. The average grip time achieved the highest AUC of 0.83 after 6 seconds, plateauing with no significant improvement in extending the duration to 10 seconds, indicating that 6 seconds is an adequate timeframe to efficiently evaluate hand motor dysfunction in DCM based on DLHGRT. Conclusion: DL-HGRT demonstrates potential as a promising supplementary tool for predicting DCM. Notably, a testing duration of 6 seconds appears to be sufficient for accurate assessment, enhancing the test more feasible and practical without compromising diagnostic performance.