Design and Implementation of Oceangoing Ship Scheduling Data Warehouse

E-government allows governments to service citizens in a more timely, effective, and costefficient method. E-Government services focus on four main customers: citizens, the business community, government employees, and government agencies. E-government can provide four types of services, which are Government-to-Citizen (G2C), Government-toBusiness (G2B), Government-to-Employee (G2E), and Government-to-Government (G2G). E-government system has already been very popular all over the world, because Egovernment helps to disseminate information. Further, it aids in the collection of information that helps decision makers serve citizens more effectively. E-Government allows government agencies to centralize decision making. China have started first E-Government program in the late 1980s, in which the governments both at central and local levels built up office automation (OA) systems and established an intranet, subsequently the Central Government of China had formally launched five Golden Projects (Golden Bridge Project, Golden Customs Project, Golden Card Project, Golden Tax Project and Government online Project) aimed at building E-Government in China ever since 1990s. After realizing five Golden Projects, Chinese government has set ambitious visions in the implementation of E-Government: quicken the pace of change in government functions to suit the requirement of reform, opening up and modernization policies, improve the performance of government operation, introduce new government measures in a scientific manner and more effective mechanisms to monitor the economic activities, place a greater emphasis on central co-ordination and transparency of government work, carry out administrative functions in accordance with law and provide better service for the public. To meet above ambitious visions, the Central Government of China have programmed to establish four governance information resource databases in next five years, governance information resource databases consist of four databases: population basic information database, judicial entity basic information database, natural resource and geography basic information database, and macroscopically economy database. A data warehouse has been defined as a collection of data in support of management decisions which is: subject oriented, integrated, nonvolatile, time variant. Data warehouse, as a collection of database or data management technologies, emerged in the early 1990s. The data warehouse has now been more generally seen as a strategy to bring heterogeneous 19

The purpose of this paper is to present an exact solution method for an important planning problem faced by many shipping companies dealing with transportation of bulk cargoes. A bulk shipping company usually has a set of contract cargoes that it is committed to carry and will try to derive additional revenue from optional spot cargoes. Each cargo, either it is a contract or spot cargo, consists of a given quantity to be picked up in a given loading port and delivered in a given unloading port within specified time windows. The shipping company controls a fixed fleet for the purpose of transporting the cargoes. In most of the literature on ship routing and scheduling problems, a cargo cannot be transported by more than one ship. By introducing split loads, this restriction is removed and each cargo can be transported by several ships. The resulting planning problem can be denoted as a maritime pickup and delivery problem with time windows and split loads (PDPTWSL). We present an arc flow formulation of the PDPTWSL. We also suggest a solution method based on a priori generation of single ship schedules and two alternative path flow models that deal with the selection of ship schedules and assignment of cargo quantities to the schedules. Computational results show that the solution method can provide optimal solutions to small realistic planning instances. We also believe this paper provides an important starting point for research on other exact solution methods for the maritime PDPTWSL.

As an efficient data management and analysis technology, the data warehouse realizes centralized storage and management of data by integrating data scattered in educational institutions. It can dig out the laws and trends hidden behind the data and provide more accurate and comprehensive data support for educational evaluation. In the educational evaluation system, the application of data warehouses is embodied in data integration and management, multidimensional evaluation, personalized learning support, and educational decision optimization. Through a multidimensional evaluation model, the school can comprehensively evaluate students' academic performance and comprehensive quality and provide strong support for personalized teaching. Data warehouses can also record and analyze students' learning trajectory and provide customized learning materials and exercises for each student, which significantly improves learning efficiency.

How to build a data warehouse and data mining is constantly worth exploring and optimization, not only technically, in commercial applications as well. This article discusses the introduction of new technologies and concepts, the traditional method of data warehouse technology has changed dramatically, based on data warehouse applications are a new development. Each enterprise data warehouse based on the characteristics of different companies, you can use a very flexible method of selection and design selection, implementation. According to some relatively new technical features, talk about data warehousing and data mining architecture.

Data warehousing is emerging as one of the hottest areas of growth in global business and the critical component and tool for business intelligence. In the data warehouse environment, the level of summarization plays an important role. Some Data Warehouse applications, directly account for the uncertainty and vagueness often associated with time-series and enterprise-wide decision making. In this paper, we enhance the concept of summarization using fuzzy technology, keeping in view the time-series and enterprise-wide data. This enhancement, which extends the aggregation process used in data warehouse, provides insightful information intelligently and allows greater facility for modeling human decision making.

Data warehouse technology is an effective method to use the large amount data with complex correlation. We apply the data warehouse technology to CIPS; it plays a crucial role in process production. In this paper, the basic conception and realization method of data warehouse is summarized. On the basis of this summary, the meaning of building data warehouse in CIPS, the role and function of data warehouse, the method to build data warehouse in CIPS and the steps of building data warehouse, is addressed in detail.

The Small&Medium steel enterprises is relatively weak on information technology, and the information management personnel lack the urgent need for information integration. According to the actual needs of the Small&Medium steel enterprises information management, three-tier architecture of information integration systems is proposed in this paper. By using SQL Server to implement database and data warehouse, data mining models is built and the design of information integration system is completed. The system covers the steel purchase, inventory, sale, distribution, contracts, finance, statistical analysis, decision support and other management functions. The proposed system can meet the Small&Medium steel enterprises scientific and orderly management for information resources, and the needs of managers forecasting, decision-making. Data warehouse and data mining applications can give an excellent support to the implementation of business intelligence in the future.

Through building a data warehouse which is used to support manufacturing inventory analysis, according to the analysis theme, this paper extracted, purified and integrated the historical data which is accumulated by the enterprise in a long term and distributed in the various heterogeneous systems, and store them in the data warehouse fact table; through the establishment of the data cube, it generate the aggregated data with different particle size, as well as provide on-line analytical processing technology (OLAP), to provide users data query analysis with multi-angle, multi-granularity, visualization, which can solve many problems difficult to solve in the inventory analysis in traditional enterprise information processing systems.

In a short time, the data warehouse (DW) technology took an important place in the academic and industrial landscapes. This place materialized in the large majority of engineering and management schools that adopted it in their curriculum and in the small, medium-size and large companies that enhanced their decision making capabilities thanks to it. The 1990s saw the advent of conferences such as DaWaK and DOLAP that carried the acronyms DW and OLAP in their titles. Then, all of a sudden, this technology has been upset by the arrival of Big Data. Consequently, those actors have replaced DW and OLAP by Big Data Analytics. We are well placed to assert that this brutal move may have a negative impact on schools, academia, and industry. This technology is not dead, today’s context, with the connected world and Web of Data, is more favorable than when building DW merely stemmed from company internal sources. In this invited paper, we attempt to answer the following question: how does DW technology interact with Linked Open Data (LOD)? To answer the question, we provide a complete vision to augment the traditional DW with LOD, to capture and quantify the added value generated through this interaction. This vision covers the main steps of the DW life-cycle. This value is estimated through two different perspectives: (i) a source-oriented vision, by calculating the rate of the DW augmentation in terms of multidimensional concepts and instances, and (ii) a goal-oriented vision where the value is calculated according to the ability of the DW to estimate the performance levels of defined goals that reflect the strategy of a company, using the defined DW of the case study of a leading Algerian company.

Data warehousing is an emerging technology that greatly extends the capabilities of relational databases specifically in the analysis of very large sets of time-oriented data. The emergence of data warehousing has been somewhat eclipsed over the past decade by the simultaneous emergence of Web technologies. However, Web technologies and data warehousing have some natural synergies that are not immediately obvious. First, Web technologies make data warehouse data more easily available to a much wider variety of users. Second, data warehouse technologies can be used to analyze traffic to a Web site in order to gain a much better understanding of the visitors to the Web site. It is this second synergy that is the focus of this article.

The purpose of this research is to assist in providing information to support decision-making processes in sales, purchasing and inventory control at PT Tatamas Pelita Jaya. With the support of data warehouse, business leaders can be more helpful in making decisions more quickly and precisely. Research methodology includes analysis of current systems, library research, designing a data warehousing schema using bintang. The result of this research is the availability of a data warehouse that can generate information quickly and precisely, thus helping the company in making decisions. The conclusion of this research is the application of data warehouse can be a media aide related parties on PT Tatamas Pelita Jaya in decision making.

This paper discusses the concepts of data warehouse technology and its importance for decision support system (DSS). The DSS as one kind smart software system of the important application value, provides, each kind of decision information as well as the commercial question solution for the enterprise. Thus Data warehouse can meet the requirements of the database management subsystems of DSS, and is fitted to form its technology frame. Then we put forth the structure of data warehouse and its main functional components. Along with widespread application of the data warehouse, DSS based on data warehouse arises at the historic moment. Begin with actual demand of the DSS, characteristic and the structure of the data warehouse have been analyzed. DSS based on the data warehouse technology is elaborated, and finally give the application example.

Marine environmental information is the main decision-making basis on ocean development, marine environmental protection and marine management. With the rapid development of ocean science technology and requirement of ocean application, human beings are more relay on the marine environmental information, and the requirement for the management and service on marine environmental information becomes higher and higher. SOA (Service Oriented Architecture) encapsulate information in the shape of service, now is the one of the most concernful themes in the IT field, and is the trend for marine data information construction. This article recommends the concept and technology of data warehouse, SOA and Web Service, does deep research on the traditional data warehouse architecture and the features of current marine heterogeneous data informatization, does analysis on the status and existing problems of marine data warehouse, and proposed a information integration architecture strategy based on SOA and marine environmental data warehouse.

Power transformers' failures carry great costs to electric companies since they need resources to recover from them and to perform periodical maintenance. To avoid this problem in four working 40 MVA transformers, the authors have implemented the measurement system of a failure prediction tool, that is the basis of a predictive maintenance infrastructure. The prediction models obtain their inputs from sensors, whose values must be previously conditioned, sampled and filtered, since the forecasting algorithms need clean data to work properly. Applying data warehouse (DW) techniques, the models have been provided with an abstraction of sensors the authors have called virtual cards (VC). By means of these virtual devices, models have access to clean data, both fresh and historic, from the set of sensors they need. Besides, several characteristics of the data flow coming from the VCs, such as the sample rate or the set of sensors itself, can be dynamically reconfigured. A replication scheme was implemented to allow the distribution of demanding processing tasks and the remote management of the prediction applications. VCs and the modular architecture proposed make the system scalable, reconfigurable and easy to maintain.

Internal audit activities are carried out to meet and implement the Safety Management System (SMS) rules so that safety on board ships is implemented in accordance with the ISM Code. In addition, an internal audit conducted by a shipping company can minimize the findings of an external audit of the Safety Management System (SMS). The purpose of this research is to find out the implementation process, obstacles and solutions for the implementation of MV internal audit. Dewi Shinta Manggala. The method carried out in this study is qualitative descriptive. Data collection was carried out by in-depth interviews, observations, and documentation. The results of the study show that the obstacles faced in the obstacles experienced in the internal audit process are the unsuitable time between the ship's schedule and the auditor resulting in delays, crew ratings that are not optimal in implementing the Safety Management System (SMS), and the crew's understanding of the Safety Management System (SMS) on board the ship which is considered to be still lacking. So that the efforts that must be made, namely the company's internal parties communicate well with each other, the company gives strict sanctions to crews who do not optimally implement SMS, the company requires crews to attend SMS training.