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Genetic algorithm‐based content distribution strategy for F‐RAN architectures
Xujie Li,Ziya Wang,Ying Sun,Siyuan Zhou,Yanli Xu,Guoping Tan 한국전자통신연구원 2019 ETRI Journal Vol.41 No.3
Fog radio access network (F‐RAN) architectures provide markedly improved performance compared to conventional approaches. In this paper, an efficient genetic algorithm‐based content distribution scheme is proposed that improves the throughput and reduces the transmission delay of a F‐RAN. First, an F‐RAN system model is presented that includes a certain number of randomly distributed fog access points (F‐APs) that cache popular content from cloud and other sources. Second, the problem of efficient content distribution in F‐RANs is described. Third, the details of the proposed optimal genetic algorithm‐based content distribution scheme are presented. Finally, simulation results are presented that show the performance of the proposed algorithm rapidly approaches the optimal throughput. When compared with the performance of existing random and exhaustive algorithms, that of the proposed method is demonstrably superior.
Research on metal flow law of micro-riblets based on multi-pass rolling
Xujie Gao,Huihang Wang,Guangming Zhu,Zheng Chang,Nana Guo,Zongshen Wang,Lihua Zhu 대한기계학회 2022 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.36 No.5
Micro-riblets (grooves) can reduce surface friction in turbulent flow by up to 10 %. Furthermore, roll forming is an effective method for manufacturing large-area groove structures. In this study, the fluidity of metal during the multi-pass rolling of microgrooves was studied, and the reason for the accumulation of materials at the end of rolling was explained. A comparative analysis was conducted between single-pass rolling and multi-pass rolling. Then, according to the distribution of stress field and strain field, the force and flow tendency of the metal during rolling were studied. The gradually changing streamlined roller tooth profile promoted the flow of metal to both sides of the gear hob. Given the same reduction, the forming height of micro-grains during multi-pass rolling was 64.2 % higher than that during single-pass rolling.
Cooperative Coevolution Differential Evolution Based on Spark for Large-Scale Optimization Problems
Tan, Xujie,Lee, Hyun-Ae,Shin, Seong-Yoon The Korea Institute of Information and Commucation 2021 Journal of information and communication convergen Vol.19 No.3
Differential evolution is an efficient algorithm for solving continuous optimization problems. However, its performance deteriorates rapidly, and the runtime increases exponentially when differential evolution is applied for solving large-scale optimization problems. Hence, a novel cooperative coevolution differential evolution based on Spark (known as SparkDECC) is proposed. The divide-and-conquer strategy is used in SparkDECC. First, the large-scale problem is decomposed into several low-dimensional subproblems using the random grouping strategy. Subsequently, each subproblem can be addressed in a parallel manner by exploiting the parallel computation capability of the resilient distributed datasets model in Spark. Finally, the optimal solution of the entire problem is obtained using the cooperation mechanism. The experimental results on 13 high-benchmark functions show that the new algorithm performs well in terms of speedup and scalability. The effectiveness and applicability of the proposed algorithm are verified.
Differential Evolution with Multi-strategies based Soft Island Model
Tan, Xujie,Shin, Seong-Yoon The Korea Institute of Information and Commucation 2019 Journal of information and communication convergen Vol.17 No.4
Differential evolution (DE) is an uncomplicated and serviceable developmental algorithm. Nevertheless, its execution depends on strategies and regulating structures. The combination of several strategies between subpopulations helps to stabilize the probing on DE. In this paper, we propose a unique k-mean soft island model DE(KSDE) algorithm which maintains population diversity through soft island model (SIM). A combination of various approaches, called KSDE, intended for migrating the subpopulation information through SIM is developed in this study. First, the population is divided into k subpopulations using the k-means clustering algorithm. Second, the mutation pattern is singled randomly from a strategy pool. Third, the subpopulation information is migrated using SIM. The performance of KSDE was analyzed using 13 benchmark indices and compared with those of high-technology DE variants. The results demonstrate the efficiency and suitability of the KSDE system, and confirm that KSDE is a cost-effective algorithm compared with four other DE algorithms.
Pressure-induced dramatic changes in organic–inorganic halide perovskites
Lü,, Xujie,Yang, Wenge,Jia, Quanxi,Xu, Hongwu Royal Society of Chemistry 2017 Chemical Science Vol.8 No.10
<▼1><P>We summarise cutting-edge discoveries and provide insights into the important theme of halide perovskites using pressure as a tuning tool.</P></▼1><▼2><P>Organic–inorganic halide perovskites have emerged as a promising family of functional materials for advanced photovoltaic and optoelectronic applications with high performances and low costs. Various chemical methods and processing approaches have been employed to modify the compositions, structures, morphologies, and electronic properties of hybrid perovskites. However, challenges still remain in terms of their stability, the use of environmentally unfriendly chemicals, and the lack of an insightful understanding into structure–property relationships. Alternatively, pressure, a fundamental thermodynamic parameter that can significantly alter the atomic and electronic structures of functional materials, has been widely utilized to further our understanding of structure–property relationships, and also to enable emergent or enhanced properties of given materials. In this perspective, we describe the recent progress of high-pressure research on hybrid perovskites, particularly regarding pressure-induced novel phenomena and pressure-enhanced properties. We discuss the effect of pressure on structures and properties, their relationships and the underlying mechanisms. Finally, we give an outlook on future research avenues in which high pressure and related alternative methods such as chemical tailoring and interfacial engineering may lead to novel hybrid perovskites uniquely suited for high-performance energy applications.</P></▼2>
Task offloading under deterministic demand for vehicular edge computing
Haotian Li,Xujie Li,Fei Shen Electronics and Telecommunications Research Instit 2023 ETRI Journal Vol.45 No.4
In vehicular edge computing (VEC) networks, the rapid expansion of intelligent transportation and the corresponding enormous numbers of tasks bring stringent requirements on timely task offloading. However, many tasks typically appear within a short period rather than arriving simultaneously, which makes it difficult to realize effective and efficient resource scheduling. In addition, some key information about tasks could be learned due to the regular data collection and uploading processes of sensors, which may contribute to developing effective offloading strategies. Thus, in this paper, we propose a model that considers the deterministic demand of multiple tasks. It is possible to generate effective resource reservations or early preparation decisions in offloading strategies if some feature information of the deterministic demand can be obtained in advance. We formulate our scenario as a 0-1 programming problem to minimize the average delay of tasks and transform it into a convex form. Finally, we proposed an efficient optimal offloading algorithm that uses the interior point method. Simulation results demonstrate that the proposed algorithm has great advantages in optimizing offloading utility.
( Mulan Wei ),( Xujie Liu ),( Chunyu Cao ),( Jianlin Yang ),( Yafeng Lv ),( Jiaojiao Huang ),( Yanlin Wang ),( Ye Qin ) 생화학분자생물학회(구 한국생화학분자생물학회) 2018 BMB Reports Vol.51 No.11
Recent studies showed that the PD-1/PD-L1 checkpoint blockade is a dramatic therapy for melanoma by enhancing antitumor immune activity. Currently, major strategies for the PD-1/PD-L1 blockade have mainly focused on the use of antibodies and compounds. Seeking an alternative approach, others employ endogenous proteins as blocking agents. The extracellular domain of PD-1 (ePD1) includes the binding site with PD-L1. Accordingly, we constructed a PD-1-based recombinantly tailored fusion protein (dFv-ePD1) that consists of bivalent variable fragments (dFv) of an MMP-2/9-targeted antibody and ePD1. The melanoma-binding intensity and antitumor activity were also investigated. We found the intense and selective binding capability of the protein dFv-ePD1 to human melanoma specimens was confirmed by a tissue microarray. In addition, dFv-ePD1 significantly suppressed the migration and invasion of mouse melanoma B16-F1 cells, and displayed cytotoxicity to cancer cells in vitro. Notably, dFv-ePD1 significantly inhibited the growth of mouse melanoma B16-F1 tumor cells in mice and in vivo fluorescence imaging showed that dFv-ePD was gradually accumulated into the B16-F1 tumor. Also the B16-F1 tumor fluorescence intensity at the tumor site was stronger than that of dFv. This study indicates that the recombinant protein dFv-ePD1 has an intensive melanoma-binding capability and exerts potent therapeutic efficacy against melanoma. The novel format of the PD-L1-blocked agent may play an active role in antitumor immunotherapy. [BMB Reports 2018; 51(11): 572-577]
Hybrid Differential Evolution Technique
Liu Xiao-Wen,Xujie Tan,Hyun-Chang Lee,Oh-Hyung Kang,Seong-Yoon Shin 한국정보통신학회 2021 2016 INTERNATIONAL CONFERENCE Vol.12 No.1
In this paper, we proposed a hybrid DE based on an ecological model algorithm called SparkHDE-EM, where we introduced a Spark-based island model to implement parallelization of different DE transformations and maintain a balance between resources using the Monod model. It includes three DE variants: jDE, JADE and CUDE.