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JUMP

JUMP的相关文献在1992年到2021年内共计104篇,主要集中在自动化技术、计算机技术、数学、肿瘤学 等领域,其中期刊论文103篇、专利文献1篇;相关期刊67种,包括信息安全与通信保密、微型计算机、计算机安全等; JUMP的相关文献由133位作者贡献,包括Jump、三味线1、宇宙人等。

JUMP—发文量

期刊论文>

论文:103 占比:99.04%

专利文献>

论文:1 占比:0.96%

总计:104篇

JUMP—发文趋势图

JUMP

-研究学者

  • Jump
  • 三味线1
  • 宇宙人
  • 王睿悦
  • 80后写稿佬&初心者
  • Adejoke O. Dele-Rotimi
  • Aiqing Zhang
  • Alex Potapov
  • Andrew Luong
  • Andrew Miller
  • 期刊论文
  • 专利文献

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    • Jake
    • 摘要: Thick-billed murres are the largest living species in their family(f4)The mother murres lay their eggs on cliffs(悬崖)This makes the murres''first flight already as risky as bungee jumping(蹦极).The chicks jump from the cliffs and fly towards the sea.
    • 许嵩(编译)
    • 摘要: 自然界中有不少动物都是天生的运动健将。那么它们是借助什么来移动的呢?With strong back legs用强壮的后腿This kangaroo can jump high.Strong back legs help it jump.这只袋鼠可以跳得很高。强壮的后腿帮助它跳跃。
    • 沐枫(文)1
    • 摘要: 在本作中世界被设定为JUMP世界与现实突然相融合的世界,本不应该出现的巨大异形建筑、宇宙船、海盗船突然出现在人们的视野里,与之同时漫画世界中的邪恶势力迅速让现实世界陷入混沌.
    • 三味线1
    • 摘要: 如果二次元IP也能量化成战斗力数值,那么作为漫画杂志《周刊少年JUMP》50周年纪念作的《JUMP战队》毫无疑问就是“赛亚人”级的水平。本作的40名登场角色当中没有无名之辈,他们来自《龙珠》《海贼王》《火影忍者》等大家耳熟能详的动漫作品,玩家可以操作自己喜欢的角色,在不同的世界战场上展开梦幻级的对决。本期UCG将为大家奉上这款版权大作的详尽攻略,从系统详解到连招推荐无一遗漏,预祝各位早日拿下全成就/白金。
    • 六等星1
    • 摘要: 本作是以《周刊少年JUMP》知名搞笑漫画《银魂》改编而成的动作无双类游戏,玩家将扮演《银魂》中知名角色,横扫战场,体验以一当百的爽快感,特有系统觉醒乱舞发动后,水墨画风格的战斗特效与打击感酣畅淋漓。
    • 三味线1
    • 摘要: 本作是由《周刊少年Jump》上连载的超人气漫画《七大罪》改编而来。在游戏中,玩家需要操作梅里奥达斯、黛安等角色探索整个布里塔尼亚,在地图的各处找到作为据点的“猪帽子亭”,一边收集情报一边完成支线任务,进而推动主线剧情是游戏的基本玩法。
    • 摘要: 《我的英雄学院》首部剧场版(中文片名《我的英雄学院:两位英雄》)正在全国火热公映中,其原著漫画自2014年7月在《周刊少年Jump》连载以来,人气一路扶摇直上,收获“次世代少年漫画中的实力之作”等赞誉。据了解,剧场版将故事场景从雄英学院搬到移动科研都市“我之岛”,全新原创剧情,讲述了在人人都有超能力的未来时代,“我之岛”突然遇袭,卷入其中的职业英雄们,与滥用异能作恶的反派随即展开终极对决,然而随着战斗升级,隐秘真相接连被揭开……
    • Martín Mundo-Molina; José Luis Díaz Pérez
    • 摘要: A hydraulic jump is a localized phenomenon that generates on an open hydraulic channel;however, its mathematical demonstration is not possible in the turbulent area of the phenomenon, especially in the area where the jump occurs and where its length is measured, so the data must be obtained with direct measurements in a laboratory and through empiric equations. This work presents the results of the generated hydraulic jumps and the measure of its length in a series of tests, where we input different flow rates in a transportable open channel hydraulic with a constant gate opening “a” and a slope of S = 0.0035, in the Engineering Faculty Research Centre of the Autonomous University of Chiapas. We also present the experimental method to generate a hydraulic jump, the measure of its length and a comparison with seven empirical equations, including the Sieñchi equation used in H-Canales, the most used software for hydraulic channels design in Latin America. The results show that the calculus of L with the proposed equation has a mean squared error (MSE) of 0.1337, a Bias of -0.0049, a model efficiency (ME) of 0.9991 and a determination coefficient (R2) of 0.9993 when compared with the experimental model. Meanwhile, the comparison of L calculated with the Sieñchi equation versus the experimental model resulted in a MSE of 0.1741, a bias of -0.0437, a ME of 0.9984 and a R2 of 0.9997. Both equations are highly recommended to estimate L in rectangular channels under the conditions presented in this paper, thus, the proposed equation can be applied if??y . Finally, it must be stated that we also proved that the Pavlosky equation is comparable in precision and accuracy concerning to proposed equation and Sieñchi equation.
    • Kayode J. Adebayo; Felix M. Aderibigbe; Adejoke O. Dele-Rotimi
    • 摘要: This paper proposes a Hybridized Ant Colony Optimization (HACO) algorithm. It integrates the advantages of Ant System (AS) and Ant Colony System (ACS) of solving optimization problems. The main focus and core of the HACO algorithm are based on annexing the strengths of the AS, ACO and the Max-Min Ant System (MMAS) previously proposed by various researchers at one time or the order. In this paper, the HACO algorithm for solving optimization problems employs new Transition Probability relations with a Jump transition probability relation which indicates the point or path at which the desired optimum value has been met. Also, it brings to play a new pheromone updating rule and introduces the pheromone evaporation residue that calculates the amount of pheromone left after updating which serves as a guide to the successive ant traversing the path and diverse local search approaches. Regarding the computational efficiency of the HACO algorithm, we observe that the HACO algorithm can find very good solutions in a short time, as the algorithm has been tested on a number of combinatorial optimization problems and results shown to compare favourably with analytical results. This strength can be combined with other metaheuristic approaches in the future work to solve complex combinatorial optimization problems.
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