Probabilistic 3D object recognition and pose estimation using multiple interpretations generation.

Lu, Zhaojin,Lee, Sukhan The Society 2011 Journal of the Optical Society of America. A, Opti Vol.28 No.12

<P>This paper presents a probabilistic object recognition and pose estimation method using multiple interpretation generation in cluttered indoor environments. How to handle pose ambiguity and uncertainty is the main challenge in most recognition systems. In order to solve this problem, we approach it in a probabilistic manner. First, given a three-dimensional (3D) polyhedral object model, the parallel and perpendicular line pairs, which are detected from stereo images and 3D point clouds, generate pose hypotheses as multiple interpretations, with ambiguity from partial occlusion and fragmentation of 3D lines especially taken into account. Different from the previous methods, each pose interpretation is represented as a region instead of a point in pose space reflecting the measurement uncertainty. Then, for each pose interpretation, more features around the estimated pose are further utilized as additional evidence for computing the probability using the Bayesian principle in terms of likelihood and unlikelihood. Finally, fusion strategy is applied to the top ranked interpretations with high probabilities, which are further verified and refined to give a more accurate pose estimation in real time. The experimental results show the performance and potential of the proposed approach in real cluttered domestic environments.</P>

Partner Choice Cooperation in Prisoner’s Dilemma

Qi Wang,Zhaojin Xu,Lianzhong Zhang 한국물리학회 2017 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.71 No.12

In this paper, we investigated the cooperative behavior in prisoner’s dilemma when the individual behaviors and interaction structures could coevolve. Here, we study the model that the individuals can imitate the strategy of their neighbors and rewire their social ties throughout evolution, based exclusively on a fitness comparison. We find that the cooperation can be achieved if the time scale of network adaptation is large enough, even when the social dilemma strength is very strong. Detailed investigation shows that the presence or absence of the network adaptation has a profound impact on the collective behavior in the system.

Evolutionary Public Goods Game on Evolving Random Networks

Qing Liu,Zhaojin Xu,Lianzhong Zhang 한국물리학회 2018 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.72 No.4

In this paper, we investigated the public goods game (PGG) on evolving random networks by introducing informed cooperators (IC) who can adjust their local topology of networks according to the information they obtained at cost. Our research shows that a high rate of network updating may provide a favorable environment for cooperation to emerge and thrive. In particular, we have found that the informed cooperators may separate the defectors (D) out and form an isolated population of cooperative strategies under adverse conditions.

Heterogeneity of Networks Promotes Cooperation in the Prisoner's Dilemma and the Snowdrift Game

Ruyu Li,Zhaojin Xu,Lianzhong Zhang 한국물리학회 2019 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.74 No.9

Complex networks are ubiquitous in real-world systems. In the last decade, the investigation of complex networks has received much attention. Most of this research suggests that the topological properties of networks have an important influence on the evolution of cooperation. In this paper, we used the prisoner's dilemma game and snowdrift game as models to study the problem of cooperation evolution on heterogeneous random networks. We found that the heterogeneity of the networks plays a more important role in promoting cooperation than the average clustering coefficient and average path length of the networks do. The higher the heterogeneity of the networks is, the more conducive the emergence and spread of cooperation is. In addition, we found that increasing the average degree of networks would be detrimental for cooperation to thrive.

Role of Preferential Words in Language Formation

Juan Li,Zhaojin Xu,Zhongwei Wu,Lianzhong Zhang 한국물리학회 2012 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.61 No.1

The Naming Game (NG) describes the emergence of conventions and shared lexicons in a population of agents interacting in a pairwise fashion. In this work, we introduce a new yet simple speakers’ rule into a minimal Naming Game where the speaker is more likely to choose the successful word in her earlier history and to convey it to the hearer. We find that the convergence time decreases with the increasing weight of successful words, which indicates that preferential selection of successful words may accelerate the reaching of consensus.

Non-Fixed Investment in Voluntary Public Goods Games

Shuai Wang,Zhaojin Xu,Lianzhong Zhang 한국물리학회 2018 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.72 No.9

In this work, we introduce a non-fixed investment ratio to the public goods games in which players can determine whether or not to participate and how much money to invest into the common pool, and with it a new mechanism has been established. We explicitly demonstrate a different rockscissors- paper dynamics which is a consequence of this model. Meanwhile, it is shown how the mechanism of non-fixed investment ratio in uences the players' decision. In addition, we found that the length of memory has an important effect on the average payoff of the population by this introduction.

Baveno-VII criteria to predict decompensation and initiate non-selective beta-blocker in compensated advanced chronic liver disease patients

Yu Jun Wong,Chen Zhaojin,Guilia Tosetti,Elisabetta Degasperi,Sanchit Sharma,Samagra Agarwal,Liu Chuan,Chan Yiong Huak,Li Jia,Qi Xiaolong,Anoop Saraya,Massimo Primignani 대한간학회 2023 Clinical and Molecular Hepatology(대한간학회지) Vol.29 No.1

Background/Aims: The utility of Baveno-VII criteria of clinically significant portal hypertension (CSPH) to predict decompensation in compensated advanced chronic liver disease (cACLD) patient needs validation. We aim to validate the performance of CSPH criteria to predict the risk of decompensation in an international real-world cohort of cACLD patients. Methods: cACLD patients were stratified into three categories (CSPH excluded, grey zone, and CSPH). The risks of decompensation across different CSPH categories were estimated using competing risk regression for clustered data, with death and hepatocellular carcinoma as competing events. The performance of “treating definite CSPH” strategy to prevent decompensation using non-selective beta-blocker (NSBB) was compared against other strategies in decision curve analysis. Results: One thousand one hundred fifty-nine cACLD patients (36.8% had CSPH) were included; 7.2% experienced decompensation over a median follow-up of 40 months. Non-invasive assessment of CSPH predicts a 5-fold higher risk of liver decompensation in cACLD patients (subdistribution hazard ratio, 5.5; 95% confidence interval, 4.0–7.4). “Probable CSPH” is suboptimal to predict decompensation risk in cACLD patients. CSPH exclusion criteria reliably exclude cACLD patients at risk of decompensation, regardless of etiology. Among the grey zone, the decompensation risk was negligible among viral-related cACLD, but was substantially higher among the non-viral cACLD group. Decision curve analysis showed that “treating definite CSPH” strategy is superior to “treating all varices” or “treating probable CSPH” strategy to prevent decompensation using NSBB. Conclusions: Non-invasive assessment of CSPH may stratify decompensation risk and the need for NSBB in cACLD patients.

Silencing of Fanconi Anemia Complementation Group F Exhibits Potent Chemosensitization of Mitomycin C Activity in Breast Cancer Cells

Jiankun Yu,Lin Zhao,Yanlin Li,Na Li,Miao He,Xuefeng Bai,Zhaojin Yu,Zhihong Zheng,Xiaoyi Mi,En-Hua Wang,Minjie Wei 한국유방암학회 2013 Journal of breast cancer Vol.16 No.3

Purpose: Fanconi anemia complementation group F (FANCF) is a key factor to maintaining the function of Fanconi anaemia/BRCA (FA/BRCA) pathway, a DNA-damage response pathway. However,the functional role of FANCF in breast cancer has not been elucidated. In the present study, we evaluated the chemosensitization effect of FANCF in breast cancer cells. Methods: We performed specific knockdown of the endogenous FANCF in breast cancer cells by transfecting the cells with an FANCF short hairpin RNA (shRNA) vector. Cell viability was measured with a Cell Counting Kit-8, and DNA damage was assessed with the alkaline comet assay. The apoptosis, cell cycle, and drug accumulation were measured by flow cytometric analysis. Protein expression levels were determined by Western blot analysis, using specific antibodies. Results: The analyses of two breast cancer cell lines (MCF-7 and MDA-MB-435S) demonstrated that the FANCF shRNA could effectively block the FA/BRCA pathway through the inhibition of Fanconi anemia complementation group D2ubiquitination. Moreover, FANCF silencing potentiated the sensitivity of cells to mitomycin C (MMC), where combined FANCF shRNA/MMC treatment inhibited cell proliferation, induced Sphase arrest, apoptosis, and DNA fragmentation, and reduced the mitochondrial membrane potential, compared with MMC treatment alone. Conclusion: Taken together, this study demonstrates that the inhibition of FANCF by its shRNA leads to a synergistic enhancement of MMC cytotoxicity in breast cancer cells. These results suggest that the inhibition of the FA/BRCA pathway is a useful adjunct to cytotoxic chemotherapy for the treatment of breast cancer.

실외 주행 로봇의 위치 추정을 위한 3차원 물체 인식

백승민 (Seung-Min Baek),김재웅(Jaewoong Kim),이장원(Jangwon Lee),Lu Zhaojin,이석한(Sukhan Lee) 한국HCI학회 2008 한국HCI학회 학술대회 Vol.2008 No.2

본 논문에서는 지능형 무인 운송 시스템의 위치 인식 문계를 풀기 위한 방법으로, 실외환경에서 보이는 건물 혹은 건물 입구의 상대적 위치와 자세 추정이 가능한 파티클 필터 기반 3 차원 물체 인식 방법을 제안한다. 제안하는 파티클 필터에 기반한 인식 시스템은 다양한 인식 증거들을 연속 영상에서 융합 및 모델 매칭을 함으로써 강인한 3 차원 물체 인식 및 자세 추정이 가능하다. 제안하는 방법은, 적합한 인식 증거들을 수집/선택하고, 다양한 인식 중거들로 부터 나타나는 인식 대상의 자세를 3 차원 공간 상의 확률적인 파티클로 표현하며, 파티클 필터링을 통하여 연속 영상 상의 다양한 인식 증거들을 융합하는 것을 특징으로 한다. 스테레오 카메라를 이용한 실험을 통하여, 제안하는 방법이 실외 건물의 기하학적 특징을 인식 증거로 활용한 효율적인 3 차원 인식 및 자세 추정을 수행하는 것은 보여준다. In this paper, to solve localization problem for out-door navigation of robotic vehicles, a particle filter based 3D object recognition framework that can estimate the pose of a building or its entrance is presented. A particle filter framework of multiple evidence fusion and model matching in a sequence of images is presented for robust recognition and pose estimation of 3D objects. The proposed approach features 1) the automatic selection and collection of an optimal set of evidences 2) the derivation of multiple interpretations, as particles representing possible object poses in 3D space, and the assignment of their probabilities based on matching the object model with evidences, and 3) the particle filtering of interpretations in time with the additional evidences obtained from a sequence of images. The proposed approach has been validated by the stereo-camera based experimentation of 3D object recognition and pose estimation, where a combination of photometric and geometric features are used for evidences.