Research on the Information Management Problems in the Linkage Process of Manufacturing and Logistics Industry

Author(s):  
Qiong Li
Author(s):  
Jean Paoli

Some of us building software need to take a hard look in the mirror. For years, we have promised that technology would solve the world’s information management problems, but 85% of business information is still “dark data,” with potentially useful insights lost in a rising tide of disconnected documents, emails, Slack conversations, voice-to-text messages, etc. We need an effective approach to documents and want to start a public conversation about these issues. We believe that effective solutions should be based on: Declarative Markup; AI sympathetic to “Small Data”; focus on company-specific documents; applying AI to documents as a whole; and solutions that do not disrupt existing workflows or require massive investment. The future is not about AI making human beings obsolete; the future is about AI making human beings and companies more productive, effective, and creative


2011 ◽  
Vol 6 (1) ◽  
pp. 125-138 ◽  
Author(s):  
Youngseek Kim ◽  
Benjamin K. Addom ◽  
Jeffrey M. Stanton

Large, collaboratively managed datasets have become essential to many scientific and engineering endeavors, and their management has increased the need for "eScience professionals" who solve large scale information management problems for researchers and engineers. This paper considers the dimensions of work, worker, and workplace, including the knowledge, skills, and abilities needed for eScience professionals. We used focus groups and interviews to explore the needs of scientific researchers and how these needs may translate into curricular and program development choices. A cohort of five masters students also worked in targeted internship settings and completed internship logs. We organized this evidence into a job analysis that can be used for curriculum and program development at schools of library and information science.


2013 ◽  
Vol 774-776 ◽  
pp. 1653-1656 ◽  
Author(s):  
Zhong Min Yao ◽  
Xia Onan Liu ◽  
Wei Liu

Modern logistics management system brings a significant convenience to commercial activities and our life. Whereas low efficiency and frequent mistakes exert negative influence on the development of logistics industry. The problems exist in the process of logistics management that includes collection, sorting, storing and tracking. RFID technology is of great importance to intelligent logistics management system. This will have a good prospects in railway package management. On the basis of the RFID technology and the proposed problems, a well-performed Railway Package Information Management Platform is proposed. This platform can provide fast, high efficient, intelligent, safe and stable solutions. The Platform consists of five systems, which are handhold terminal system, sorting system, warehouse management system, tracking system and Railway Package information management system respectively. Implementation on the platform shows that it not only reduces package transportation cycle, but it also improves the stability and safety for the logistics management system. Multiple verification demonstrates that the proposed platform has a very good practicality.


2014 ◽  
Vol 484-485 ◽  
pp. 829-832
Author(s):  
Shun Chen ◽  
Fei Fei Zhou ◽  
Hai Hua Li

The modern logistics as the product of the modern scientific and technological progress is to promote the logistics industry toward efficient, fast, low-cost distribution system was further extended. Computers in logistics information management, providing a broad space for development, Article by describing the role of computer technology in the logistics, indicating that the two are interdependent and mutual restraint and mutual development of the relationship.


Author(s):  
Rafael A. Gonzalez

In this chapter, information management problems and some of the computer-based solutions offered to deal with them are presented. The claim is that exploring the information problem as a three-fold issue, composed of heterogeneity, overload, and dynamics, will contribute to an improved understanding of information management problems. On the other hand, it presents a set of computer-based solutions that are available to tackle these problems: information discovery and retrieval, information filtering, information fusion, and information personalization. In addition, this chapter argues that a rich and interesting domain for exploring information management problems is critical incident management, due to its complexity, requirements, and the nature of the information it deals with.


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