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A Preliminary Study on the Medium-term Plan of Public Universities Transferred from Private Universities 民办大学转办公办大学中期规划初探
Pub Date : 1900-01-01 DOI: 10.29007/56sc
Soichiro Aihara, Toru Sugihara, Kahori Ogashiwa, Kumiko Kanekawa, M. Mori, S. Hirokawa
This preliminary study visualizes the characteristics of the medium-term plan of ten universities that were transferred from private to public ones. The analysis tool is KH Coder version 3. Drawing 2-D maps in three ways: Co-occurrence network, Correspondence analysis, Self-organizing map make it to interpret the whole picture.
通过对十所民办转公办高校中期规划特点的初步研究,揭示了民办转公办高校中期规划的特点。分析工具是KH Coder版本3。用共现网络、对应分析、自组织图三种方法绘制二维地图,使其能够全图解译。
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引用次数: 1
Garment Inventory Management Systems 服装库存管理系统
Pub Date : 1900-01-01 DOI: 10.29007/5tq5
Irfan Luthfi Makarim, Reflia Yusramdaleni, Alif Fathir, Tanty Oktavia, Ford Lumban Gaol, Takaaki Hosoda
One of the difficulties to create stock control is the way to deal with the stockroom and organize stock to satisfy both on the web and offline (retailer) orders. Mostly, the current improvement of stock administration by the garment industry is yet running physically utilizing paper and notes. It causes miscalculation and loss of stock by the piece of clothing industry happened when recording the stock information. Additionally, it influences shrinkage and quality fall flat reduces which prompts the inconsistency between the recorded stock and the actual stock. The fundamental motivation behind this theory is to assemble an answer for stock administration for Garment Industry and encourages the piece of clothing industry with the Buka Gudang – Inventory Management System. Advantage from Buka Gudang – Inventory Management System for an article of the clothing industry is to improve for eliminating bottlenecks and disposal of repetitive advances can without much of a stretch be accomplished, encourage Garment Industry for a mechanized report of stock by checking stock rundown that will be refreshed electronically each time a deal is made and print out the report featuring the stock to be restocked, and Help business for keeping up the stock rundown naturally and give an exactness to each refreshed information, for example, a precise numerical estimation on Buka Gudang – Inventory Management System. Investigation measure for this postulation is finished by Data Gathering through Interview with a few dealers around Tanah Abang Jakarta who possessed a centerpiece of the clothing industry, at that point doing some perception on the stock framework and current piece of clothing industry circumstance that requirements stock administration to have the option to control the stockroom of an article of the clothing industry. Inventory, Control, Garment, Stock, Online
创建库存控制的难点之一是如何处理库存和组织库存以满足网上和离线(零售商)订单。目前,服装行业对库存管理的改善主要是利用纸张和票据进行的。由于服装行业在记录库存信息时发生了误算和库存损失。此外,它还会影响收缩率和质量下降,从而导致记录库存与实际库存不一致。提出这一理论的根本动机是为服装行业的库存管理提供一个答案,并通过布卡鼓当库存管理系统来鼓励服装行业的发展。Buka Gudang的优势-服装行业的库存管理系统是为了消除瓶颈和处理重复的预付款而改进,可以不需要太多的拉伸完成,鼓励服装行业通过检查库存清单来实现库存的机械化报告,每次交易都会以电子方式刷新库存清单,并打印出库存报告。帮助企业保持自然的库存明细表,使每次刷新的信息准确无误,例如,在Buka gu当-库存管理系统上进行精确的数值估算。这一假设的调查措施是通过对雅加达塔那阿邦附近几家拥有服装行业核心产品的经销商进行访谈收集数据来完成的,在此基础上对库存框架和当前服装行业的情况做了一些认识,这些情况要求库存管理部门有权控制服装行业的一件产品的库存。采购产品库存,控制,服装,库存,在线
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引用次数: 0
AI Enabled SaaS Framework for Fashion Designing 基于AI的服装设计SaaS框架
Pub Date : 1900-01-01 DOI: 10.29007/997h
D. Chanda, N. Debnath
This paper proposes a new AI (Artificial Intelligence) enabled SaaS (Software as a Service) Framework to facilitate the work of Fashion Designers to evolve new and innovative Fashion Designs. Fashion Designs are, more often than not, complex; using concepts of Service Choreography using Blackboard Architecture, we propose a new model for facilitating collaborative / individual innovative work of Fashion Designers.
本文提出了一个新的AI(人工智能)支持的SaaS(软件即服务)框架,以促进时装设计师的工作,发展新的和创新的时装设计。时装设计往往是复杂的;利用黑板架构的服务编排概念,我们提出了一种促进时装设计师协作/个人创新工作的新模式。
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引用次数: 0
David against Goliath: How a University Cloud Succeeds in the Niche of Higher Education – a User Survey 大卫对抗歌利亚:大学云如何在高等教育利基市场取得成功——一项用户调查
Pub Date : 1900-01-01 DOI: 10.29007/9mjz
Anne Thoring, Dominik Rudolph, R. Vogl
In the discussion about digital sovereignty, an important goal of the EU, there is always the fear that no one would stand a chance against the big giants from the U.S. which dominate the cloud market thanks to early starts, huge resources and network effects. However, the state-funded open source project “sciebo” proves the opposite, at least in the higher education sector. High data protection is a central argument for using a private cloud service at universities, but this alone does not make it competitive. University-specific functions and integrations – for example in the area of digital teaching or research data management – can be a unique selling point, but for a majority of students and employees the basic sync and share functions seem to be sufficient. So how can a university cloud service compete with commercial offers and what can make it successful in the long term? In a cloud landscape dominated by big players like Microsoft, Apple or Google, who move their established services to the cloud and encourage customers to also use their cloud storage with the arguments of a central account and seamless linkage with their other products, this question needs to be addressed to those at the front line: the users. To investigate the above question, we conducted a user survey, taking the university cloud service “sciebo” as an example, which has been in use at numerous higher education institutions in the German state of North Rhine-Westphalia since 2015.
数字主权是欧盟的一个重要目标,在讨论数字主权时,人们总是担心,美国的巨头们凭借起步早、资源庞大、网络效应等优势,在云市场占据主导地位,无人能敌。然而,国家资助的开源项目“sciebo”证明了相反的情况,至少在高等教育领域是这样。高度的数据保护是在大学使用私有云服务的核心论据,但仅凭这一点并不能使其具有竞争力。大学特有的功能和集成——例如在数字教学或研究数据管理领域——可能是一个独特的卖点,但对大多数学生和员工来说,基本的同步和共享功能似乎已经足够了。那么,大学云服务如何与商业服务竞争呢?从长远来看,怎样才能取得成功呢?在一个由微软、苹果或b谷歌等大公司主导的云环境中,他们将自己的既定服务转移到云上,并以中央账户和与其他产品的无缝链接为理由鼓励客户也使用他们的云存储,这个问题需要向前线的用户解决:用户。为了调查上述问题,我们进行了一项用户调查,以大学云服务“sciebo”为例,该服务自2015年以来一直在德国北莱茵-威斯特伐利亚州的众多高等教育机构中使用。
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引用次数: 0
Title Overlapping Communities Discovery and Improvement 重叠社区的发现和改进
Pub Date : 1900-01-01 DOI: 10.29007/hdl3
Rong Yang
Decomposing a network into communities is one of the most used techniques in network science. Modularity is typically used to measure the goodness of such a decomposition. In this paper we develop a method which allows us to begin with a crisp decomposition (no overlaps) and move to an overlapping decomposition while increasing the modularity. We also show that the same technique can be used to improve existing overlapping decompositions.
将网络分解为社区是网络科学中最常用的技术之一。模块化通常用于度量这种分解的好坏。在本文中,我们开发了一种方法,允许我们从一个清晰的分解(没有重叠)开始,并在增加模块化的同时移动到一个重叠的分解。我们还表明,同样的技术可以用于改进现有的重叠分解。
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引用次数: 0
Development of a Prototype for a Process Support and Analysis Platform for Small and Medium-sized Enterprises 中小企业流程支持与分析平台原型的开发
Pub Date : 1900-01-01 DOI: 10.29007/jmrk
Jonas Kallisch, Christoph Wunck
This paper presents a prototype for an information exchange system, which allows information exchange between companies without actually sharing data. First, the need for such an intercompany exchange platform is explained and the value for supply chains resulting from such a platform is described. A literature review presents the existing concepts and techniques contributing to the development of an architecture. Finally. The information exchange concept and the prototype implementation are explained in detail.*
本文提出了一个信息交换系统的原型,它允许公司之间在不实际共享数据的情况下进行信息交换。首先,解释了对这样一个公司间交流平台的需求,并描述了这样一个平台对供应链的价值。文献综述展示了对体系结构开发有贡献的现有概念和技术。最后。详细阐述了信息交换的概念和原型实现
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引用次数: 0
Selecting a Knowledge Management Methodology in Society 5.0 5.0社会中知识管理方法论的选择
Pub Date : 1900-01-01 DOI: 10.29007/ljbz
B. Simelane, Hanlie Smuts
Society 5.0 is a knowledge-driven society that is impacted by rapid changes in the digital world. Due to the influence of the tools and technologies introduced by Industry 4.0 or the Fourth Industrial Revolution (4IR), Society 5.0 is challenged by the amount of knowledge created through the integration of cyber and physical spaces. The exploitation of the 4IR’s technological advancements increases the potential of knowledge creation, presenting with it a knowledge management (KM) challenge. Therefore, the purpose of this research was to identify the KM methodologies available for adoption in Society 5.0. In this research, systematic literature review was used to identify and evaluate existing KM methodologies from academic reviewed papers published between 2006 and 2020. It was found that some of the KM methodologies are industry specific and derived from best practice, while others focused on the development and implementation of KM systems. Based on the findings, elements of a potential KM methodology for knowledge management in Society 5.0 are presented.
社会5.0是一个知识驱动的社会,受到数字世界快速变化的影响。由于工业4.0或第四次工业革命(4IR)引入的工具和技术的影响,社会5.0面临着通过网络和物理空间的整合创造的知识量的挑战。利用第四次工业革命的技术进步增加了知识创造的潜力,随之而来的是知识管理(KM)的挑战。因此,本研究的目的是确定社会5.0中可用的知识管理方法。本研究采用系统文献综述的方法,从2006年至2020年发表的学术综述论文中,对现有的知识管理方法进行了识别和评价。研究发现,一些知识管理方法是特定于行业的,源自最佳实践,而另一些则侧重于知识管理系统的开发和实施。基于这些发现,提出了社会5.0中知识管理的潜在知识管理方法的要素。
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引用次数: 0
Forced Selective Information Reduction for Interpreting Multi-Layered Neural Networks 多层神经网络的强制选择信息约简
Pub Date : 1900-01-01 DOI: 10.29007/n4kz
R. Kamimura, Ryozo Kitajima
The present paper aims to reduce unnecessary information obtained through inputs, supposed to be inappropriately encoded, for producing easily interpretable networks with better generalization. The proposed method lies mainly in forced reduction of selective information even at the expense of a larger cost to eliminate unnecessary information coming from the inputs in the initial stage of learning. Then, in the later stage of learning, selective information is increased to produce a small number of really important connection weights for learning. The method was preliminarily applied to two business data sets: the bankruptcy and the mission statement data sets, in which the interpretation is considered as important as generalization performance. The results show that selective information could be decreased, though the cost to realize this reduction became larger. However, the accompa- nying selective information increase could be used to compensate for the expensive cost to produce simpler and interpretable internal representations with better generalization performance.
本文旨在减少通过输入获得的不必要的信息,这些信息被认为是不适当的编码,以产生具有更好泛化的易于解释的网络。本文提出的方法主要是在学习的初始阶段,以较大的代价对选择性信息进行强制约简,以消除来自输入的不必要信息。然后,在学习的后期,增加选择性信息,产生少量真正重要的学习连接权值。该方法初步应用于两个业务数据集:破产和使命陈述数据集,其中解释与泛化性能同等重要。结果表明,选择性信息可以减少,但实现这种减少的成本变大。然而,伴随的选择性信息的增加可以用来补偿昂贵的成本,以产生更简单和可解释的内部表示,具有更好的泛化性能。
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引用次数: 0
User Ontology for Intelligent Decision Support Based on User Digital Life 基于用户数字生活的智能决策支持用户本体
Pub Date : 1900-01-01 DOI: 10.29007/vbbq
A. Smirnov, T. Levashova
The research is aimed at the development of an ontology that classifies the users into user types based on which personalized decisions are recommended. A user type represents a category of users distinguished by common preferences and decision-making behaviours. The ontology is intended to be used in a decision support system implemented following an earlier proposed conceptual framework of intelligent decision support based on user digital life. The paper briefly introduces this framework and provides the formalization for main framework components. The major research result is a multi-aspect user ontology that models a user via three aspects: user profile, user segment, and user digital life model. Users’ digital traces is the framework’s component that provides information about the users to determine their types. Suggestions on ontology usage for intelligent decision recommendation are provided.
该研究旨在开发一个本体,该本体将用户分类为用户类型,并根据用户类型推荐个性化决策。用户类型表示由共同偏好和决策行为区分的一类用户。该本体旨在用于决策支持系统,该系统遵循先前提出的基于用户数字生活的智能决策支持概念框架实现。本文简要介绍了该框架,并给出了框架主要组件的形式化描述。主要研究成果是通过用户概况、用户段和用户数字生活模型三个方面对用户进行建模的多面向用户本体。用户的数字跟踪是框架的组件,它提供有关用户的信息以确定其类型。提出了利用本体进行智能决策推荐的建议。
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引用次数: 0
Reliable Night Bear and Boar Detection Based on Training with Pseudo Infrared Images 基于伪红外图像训练的可靠夜熊和野猪检测
Pub Date : 1900-01-01 DOI: 10.29007/xghf
Keigo Fusaka, Yoichi Tomioka, Hiroshi Saito, Y. Kohira
In recent years, accidents and damages caused by wild animals have been serious prob- lems. It has become important to detect wild animals accurately at an early stage. A sufficient number of training infrared images is required to detect wild animals taking various postures at night time using deep learning techniques. In this study, we propose a method to increase appropriate training samples for night wild animal detection using annotated daytime images. We employ a model based on Cycle Generative Adversarial Network (CycleGAN) to be able to generate pseudo infrared images from daytime images. In our experiments, we apply the proposed method to bear and boar detection. The exper- imental results show that the proposed method achieves significant improvements in bear detection accuracy taking various postures.
近年来,野生动物造成的事故和损害已经成为严重的问题。在早期阶段准确地发现野生动物已经变得很重要。利用深度学习技术检测夜间各种姿态的野生动物,需要足够数量的训练红外图像。在这项研究中,我们提出了一种方法来增加适当的训练样本,用于夜间野生动物的检测使用带注释的白天图像。我们采用了一种基于循环生成对抗网络(CycleGAN)的模型,能够从白天的图像中生成伪红外图像。在我们的实验中,我们将该方法应用于熊和野猪的检测。实验结果表明,该方法在不同姿态下的熊检测精度均有显著提高。
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引用次数: 0
期刊
EPiC series in computing
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