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Kasprzyk, Jean-Paul, and Guénaël Devillet. "A Data Cube Metamodel for Geographic Analysis Involving Heterogeneous Dimensions." ISPRS International Journal of Geo-Information 10, no. 2 (February 19, 2021): 87. http://dx.doi.org/10.3390/ijgi10020087.
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Due to their multiple sources and structures, big spatial data require adapted tools to be efficiently collected, summarized and analyzed. For this purpose, data are archived in data warehouses and explored by spatial online analytical processing (SOLAP) through dynamic maps, charts and tables. Data are thus converted in data cubes characterized by a multidimensional structure on which exploration is based. However, multiple sources often lead to several data cubes defined by heterogeneous dimensions. In particular, dimensions definition can change depending on analyzed scale, territory and time. In order to consider these three issues specific to geographic analysis, this research proposes an original data cube metamodel defined in unified modeling language (UML). Based on concepts like common dimension levels and metadimensions, the metamodel can instantiate constellations of heterogeneous data cubes allowing SOLAP to perform multiscale, multi-territory and time analysis. Afterwards, the metamodel is implemented in a relational data warehouse and validated by an operational tool designed for a social economy case study. This tool, called “Racines”, gathers and compares multidimensional data about social economy business in Belgium and France through interactive cross-border maps, charts and reports. Thanks to the metamodel, users remain independent from IT specialists regarding data exploration and integration.
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Bimonte, Sandro. "A Web-Based Tool for Spatio-Multidimensional Analysis of Geographic and Complex Data." International Journal of Agricultural and Environmental Information Systems 1, no. 2 (July 2010): 42–67. http://dx.doi.org/10.4018/jaeis.2010070103.
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Spatial OLAP (SOLAP) integrates spatial data into OLAP systems, and SOLAP models define spatial dimensions while measuring spatio-multidimensional operators. In this paper, the author presents the concepts of geographic and complex measures that allow integrating geographic and complex information as subjects of analysis in spatial data warehouses. The concept of geographic measure extends the concept of spatial measure to the semantic component of geographic information. The concept of complex measure allows introducing complex data as subjects of multidimensional analysis. To reduce the gap in flexibility between spatial and multidimensional analysis, this paper proposes a symmetrical representation of measures and dimensions. Additionally, the author presents a Web-based SOLAP prototype, GeWOlap, that enriches existing SOLAP tools by effectively and easily supporting symmetrical geographic/complex measures and dimensions for modeling and visualization. To validate this approach, the simulated environmental data concerning the pollution of the Venice lagoon is used.
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Azaiez, Noura, and Jalel Akaichi. "What is the Impact of Mobility Data Integration on Decision Support Systems' Modelling and Evolution?" International Journal of Information Systems in the Service Sector 8, no. 1 (January 2016): 1–12. http://dx.doi.org/10.4018/ijisss.2016010101.
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Classic data seems unable to keep pace with the technology era. In fact, the incredible progress related to geographic information systems, pervasive computing, and positioning technologies have motivated classic data to evolve towards new data kind called mobility data. For decisional purposes, these later have to be analysed; therefore, their integration into a decision support system becomes a must. However, the data warehouse used to store classical data seems to be inadequate for mobility data storage and analysis. This gave the birth of a new central repository type called trajectory data warehouse which is able to support mobility data extraction, transformation, loading, and analysis and/or mining. As classic data warehouses, the trajectory one often changes its content as well as its structure for various reasons such as the organizational business processes progressing over time, the evolving needs of decision makers that lead to DW structure enrichment with additional analyses axes, or even the incompleteness of needs initially captured during the design phase of the DW . This work proposes a survey that gathers the research works that deal with the issue of trajectory data warehouse modelling and evolution; then the authors present comparative study of the proposed solutions.
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Bimonte, Sandro, Omar Boucelma, Olivier Machabert, and Sana Sellami. "A Generic Spatial OLAP Model for Evaluating Natural Hazards in a Volunteered Geographic Information Context." International Journal of Agricultural and Environmental Information Systems 5, no. 4 (October 2014): 40–55. http://dx.doi.org/10.4018/ijaeis.2014100102.
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Spatial data warehouses (SDW) and spatial OLAP (SOLAP) systems are well-known business intelligence technologies that aim to support a multidimensional and online analysis for a large volume of geo-referenced datasets. SOLAP systems are already used in the context of natural hazards for analyzing sensor data and experts' measurements. Recently, new data gathering tools coined as volunteered geographic information systems (VGI) have been adopted especially by non-expert users. Hence, (spatial) application development is facing a new challenge, which is the integration of expert-oriented data with citizen-provided data. In this paper, we propose a new generic spatio-multidimensional model based on the question/answer risk evaluation model that allows the integration of VGI data with classical SDW and SOLAP systems for the online analysis of natural hazards monitored by volunteers.
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Ahanotu, Dike N., Michael J. Fischer, and Hugh W. Louch. "Developing a Commodity Flow Database from Transearch Data." Transportation Research Record: Journal of the Transportation Research Board 1855, no. 1 (January 2003): 14–21. http://dx.doi.org/10.3141/1855-02.
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A procedure is described for analyzing Reebie Transearch data to create a commodity flow database that is useful for transportation planning purposes. Several elements of the procedure were recently applied as part of the development of a commodity flow database for the Portland metropolitan area. The procedure begins with an overview of the robustness of various Transearch data elements. For less robust data elements, specific processes are described to improve on the Transearch data. This process generally includes acquiring additional data from federal and state agencies, acquiring additional information from primary industry sources, and applying these data to the geographic area of concern for the commodity flow database. A methodology for estimating the commodity distribution for goods movement that originates in warehouses and distribution centers is also described. Supplemental freight data sources are identified, and elements of these data sources that can be used to verify and refine the Transearch data are highlighted. In the case of discrepancies between the Transearch data and other freight data sources, a process is described to determine potential sources of the discrepancy and further improve on the Transearch data toward the creation of a full commodity flow database.
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da Silva, Joel, Anjolina G. de Oliveira, Robson N. Fidalgo, Ana Carolina Salgado, and Valéria C. Times. "Modelling and querying geographical data warehouses." Information Systems 35, no. 5 (July 2010): 592–614. http://dx.doi.org/10.1016/j.is.2009.10.005.
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Greenhalgh, Paul, Helen M. King, Kevin Muldoon-Smith, and Josephine Ellis. "The New Distribution: Spatio-Temporal Analysis of Large Distribution Warehouse Premises in England and Wales." Urban Planning 6, no. 3 (September 23, 2021): 399–414. http://dx.doi.org/10.17645/up.v6i3.4222.
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This research addresses the deficit of empirical investigation of changes in industrial and warehouse property markets in the UK. It uses business rates (rating list) data for England and Wales to reveal changes in the quantum and distribution of premises over the last decade. Spatio-temporal analysis using geographical information systems identifies where new industrial and warehouse premises have been developed and examines spatial changes in the distribution of premises between the two sectors. The research focuses on the development of new large distribution warehouses (LDWs) to investigate whether there is a new pattern of warehouse premises located in close proximity to junctions on the national highway network. Findings confirm the emergence of a dynamic distribution warehouse property market where “super sheds” have been developed in areas with high levels of multi-modal connectivity. The comprehensive spatio-temporal analysis of all industrial and warehouse premises in England and Wales reconfigures the previously recognised Midlands “Golden Triangle” of distribution warehouses to a “Golden Pointer” and reveals the emergence of a rival “Northern Dumbbell” of distribution warehouse premises in the North of England. Further analysis using isochrones confirms that 85% of the population of Great Britain is situated within four hours average heavy goods vehicle drive time of these two concentrations of super sheds and over 60% of all LDWs floorspace is within 30 minutes’ drive of intermodal rail freight interchanges.
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Yardley, A. J. "THE NEXT GENERATION SPATIAL DATA WAREHOUSE." APPEA Journal 42, no. 1 (2002): 633. http://dx.doi.org/10.1071/aj01039.
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Woodside Energy, based in Perth, Western Australia, has commenced the implementation of its next generation spatial data warehousing and visualisation system. The warehouse facilitates access to data in various corporate geoscience data sets, as well as up-to-date cultural and environmental data. It expands the capabilities of the existing geoscience database by providing a facility to handle spatial data at the database level rather than in files and maps. Spatial data can now be kept in the database, in its correct spatial location, and with a known provenance.Woodside’s worldwide exploration, development and production activities require the use of a wide variety of geographic data such as seismic, bathymetry, wells, permits, coastlines, political boundaries, navigation charts, remote sensing and geological interpretations.Geo-spatial data comes to Woodside in a variety of formats, datums and conditions. The Geomatics Department, through the Geoscience Database and Spatial Information Management teams, loads, maintains and manages all data considered to be corporate. It is quality controlled and placed into the warehouse, where it is readily accessible to technical and administrative staff.Location is an essential element in most Woodside decisions. Because of the new spatial capabilities, a number of geographic information processes are now possible. Additionally information can also be made available through the internet if required.Reliable geographic information will become more widely available in the organisation, and be more easily merged with traditional data types, enhancing the decision-making process.
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Jordhus-Lier, David, Anders Underthun, and Kristina Zampoukos. "Changing workplace geographies: Restructuring warehouse employment in the Oslo region." Environment and Planning A: Economy and Space 51, no. 1 (July 12, 2018): 69–90. http://dx.doi.org/10.1177/0308518x18787821.
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The article examines changing employment relations in Norwegian warehouses, and conceptualises the increasing use of temporary agency workers as a redrawing of workplace geographies. The empirical basis for the analysis is four qualitative warehouse workplace studies, including focus group and interview data. The theoretical framework of the article combines an adapted version of the territory-place-scale-network (TPSN) framework developed by Bob Jessop, Neil Brenner and Martin Jones with the concepts of labour control and labour agency. The analysis shows how a networked recruitment system based on Swedish labour migrants, mediated via temporary work agencies, encourage workers to work their way through levels of employment insecurity in order to secure permanent employment. The article argues that the blurring and redrawing of legal boundaries through labour hire can be understood as a territorial strategy of control that affects the workplace as a scale of justice for trade unions. Moreover, the analysis shows how managerial control is conditioned by workers’ individual, habitual and collective agency.
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Agapito, Giuseppe, Chiara Zucco, and Mario Cannataro. "COVID-WAREHOUSE: A Data Warehouse of Italian COVID-19, Pollution, and Climate Data." International Journal of Environmental Research and Public Health 17, no. 15 (August 3, 2020): 5596. http://dx.doi.org/10.3390/ijerph17155596.
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The management of the COVID-19 pandemic presents several unprecedented challenges in different fields, from medicine to biology, from public health to social science, that may benefit from computing methods able to integrate the increasing available COVID-19 and related data (e.g., pollution, demographics, climate, etc.). With the aim to face the COVID-19 data collection, harmonization and integration problems, we present the design and development of COVID-WAREHOUSE, a data warehouse that models, integrates and stores the COVID-19 data made available daily by the Italian Protezione Civile Department and several pollution and climate data made available by the Italian Regions. After an automatic ETL (Extraction, Transformation and Loading) step, COVID-19 cases, pollution measures and climate data, are integrated and organized using the Dimensional Fact Model, using two main dimensions: time and geographical location. COVID-WAREHOUSE supports OLAP (On-Line Analytical Processing) analysis, provides a heatmap visualizer, and allows easy extraction of selected data for further analysis. The proposed tool can be used in the context of Public Health to underline how the pandemic is spreading, with respect to time and geographical location, and to correlate the pandemic to pollution and climate data in a specific region. Moreover, public decision-makers could use the tool to discover combinations of pollution and climate conditions correlated to an increase of the pandemic, and thus, they could act in a consequent manner. Case studies based on data cubes built on data from Lombardia and Puglia regions are discussed. Our preliminary findings indicate that COVID-19 pandemic is significantly spread in regions characterized by high concentration of particulate in the air and the absence of rain and wind, as even stated in other works available in literature.
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Zhou, Jie, Ming Fang, and Xin-ran Cao. "Drilling Material Data Warehouse ETL System Research Based on Crowd-Sourcing." MATEC Web of Conferences 232 (2018): 01017. http://dx.doi.org/10.1051/matecconf/201823201017.
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Drilling material data warehouse is an important platform for assisting drilling engineering decision support and data analysis. The construction of high-efficiency and high-quality enterprise-level data warehouse puts high requirements on data quality. The operation targets of oil and gas drilling engineering are buried underground, and there are difficulties in data obtaining. This causes many uncertain data in the oil and gas drilling business database. At the same time, the business database in one area is quite different from those of other areas due to geographical environmental impacts ,so the database selection and integration strategy is uncertain . In order to solve these uncertain problem, this paper proposes building a drilling materials data warehouse ETL system based on crowd-sourcing, and improve the data quality of the data warehouse, thereby improving the efficiency of data warehouse construction.
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Lu, Y. L., C. W. Liu, J. W. Li, and J. W. Jiang. "CONSTRUCTION METHOD OF “CELL-CUBE” SPATIO-TEMPORAL DATA MODEL FOR BIG DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W10 (February 7, 2020): 25–30. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w10-25-2020.
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Abstract. In recent years, with high accuracy, high frequency, considerable coverage of remote sensing images, map tiles, video surveillance, web crawlers, social networking platforms and other types of spatiotemporal data have exploded in geometric progression. Human society has come into the era of big data in time and space. In view of the characteristics of multi-attribute, multi-dimensional, multisource and heterogeneous spatiotemporal big data, how to make use of the emerging information technology means, combined with the geographic information data analysis means, the rapid mining and utilization of spatiotemporal big data has become a key problem to be solved. Built on the background of spatiotemporal big data and the process of geospatial cognition, this paper proposes a "cell-cube" spatiotemporal object data model. This paper constructs a model system of geo-spatiotemporal big data from the aspects of data organization, data storage and data partition, and abstracts the geo-space into an infinite number of geo-cells, and the adjacent geo-cells gather around the core cells to form geographical clusters, and the geographical clusters with similar attributes are clustered into geographical blocks. At the level of data organization, the spatial and temporal characteristics of structured data and unstructured data are considered as organizational dimensions, and a multi-factor extended cube data model is proposed. In the aspect of data storage, the organization model is further abstracted into the cell-cube structure of distributed data warehouse, and then the spatiotemporal data is stored uniformly. At the level of data segmentation, the mathematical table and space calculation method of multi-feature extended cube are proposed, and the geographical cell data division model based on connection is established. It solves the organization and management problem of spatiotemporal big data, provides a more complete data organization framework and solution for the application of geo-spatiotemporal big data, and promotes the development of deep mining of spatiotemporal extensive data in GIS. And to achieve space-time big data in the geographical space microscopic and the macroscopic unification cognition.
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Wisnubhadra, Irya, Safiza Baharin, and Nanna Herman. "Open Spatiotemporal Data Warehouse for Agriculture Production Analytics." International Journal of Intelligent Engineering and Systems 13, no. 6 (December 31, 2020): 419–31. http://dx.doi.org/10.22266/ijies2020.1231.37.
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Business Intelligence (BI) technology with Extract, Transform, and Loading process, Data Warehouse, and OLAP have demonstrated the ability of information and knowledge generation for supporting decision making. In the last decade, the advancement of the Web 2.0 technology is improving the accessibility of web of data across the cloud. Linked Open Data, Linked Open Statistical Data, and Open Government Data is increasing massively, creating a more significant computer-recognizable data available for sharing. In agricultural production analytics, data resources with high availability and accessibility is a primary requirement. However, today’s data accessibility for production analytics is limited in the 2 or 3-stars open data format and rarely has attributes for spatiotemporal analytics. The new data warehouse concept has a new approach to combine the openness of data resources with mobility or spatiotemporal data in nature. This new approach could help the decision-makers to use external data to make a crucial decision more intuitive and flexible. This paper proposed the development of a spatiotemporal data warehouse with an integration process using service-oriented architecture and open data sources. The data sources are originating from the Village and Rural Area Information System (SIDeKa) that capture the agricultural production transaction in a daily manner. This paper also describes the way to spatiotemporal analytics for agricultural production using a new spatiotemporal data warehouse approach. The experiment results, by executing six relevant spatiotemporal query samples on DW with fact table contains 324096 tuples with temporal integer/float for each tuple, 4495 tuples of field dimension with geographic data as polygons, 80 tuples of village dimension, dozens of tuples of the district, subdistrict, province dimensions. The DW time dimension contains 3653 tuples representing a date for ten years, proved that this new approach has a convenient, simple model, and expressive performance for supporting executive to make decisions on agriculture production analytics based on spatiotemporal data. This research also underlines the prospects for scaling and nurturing the spatiotemporal data warehouse initiative.
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O’Packi, Paul, Rick Dubois, Nancy Armentrout, and Steve Bower. "Maine’s Approach to Data Warehousing for State Departments of Transportation." Transportation Research Record: Journal of the Transportation Research Board 1719, no. 1 (January 2000): 227–32. http://dx.doi.org/10.3141/1719-30.
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Most transportation agencies are faced with changing needs, challenges, and limited resources. State departments of transportation need tools to address these issues. One such solution combines data warehouse and geographic information systems (GIS) technology to allow easy access to reliable information for systemwide query, analysis, and reporting. To meet these challenges, to be more responsive, and to provide staff and managers with a better platform with which to deliver integrated transportation information to both internal and external customers, the Maine Department of Transportation (MeDOT) has turned to integrating data warehousing and GIS technologies. A detailed overview of MeDOT’s Transportation Information for Decision Enhancement (TIDE), a robust GIS-linked data warehouse, is given. A range of inherent technical issues involved in a project of this nature is discussed. The role that TIDE has played in breaking down the functional boundaries that have existed on both informational and technical fronts and how this robust tool facilitates the growth of agency integration also are discussed.
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Azaiez, Noura, and Jalel Akaichi. "The Model-Driven Architecture for the Trajectory Data Warehouse Modeling." International Journal of Data Warehousing and Mining 16, no. 4 (October 2020): 26–43. http://dx.doi.org/10.4018/ijdwm.2020100102.
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Business Intelligence includes the concept of data warehousing to support decision making. As the ETL process presents the core of the warehousing technology, it is responsible for pulling data out of the source systems and placing it into a data warehouse. Given the technology development in the field of geographical information systems, pervasive systems, and the positioning systems, the traditional warehouse features become unable to handle the mobility aspect integrated in the warehousing chain. Therefore, the trajectory or the mobility data gathered from the mobile object movements have to be managed through what is called the trajectory ELT. For this purpose, the authors emphasize the power of the model-driven architecture approach to achieve the whole transformation task, in this case transforming trajectory data source model that describes the resulting trajectories into trajectory data mart models. The authors illustrate the proposed approach with an epilepsy patient state case study.
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Malinowski, Elzbieta, and Esteban Zimányi. "Logical Representation of a Conceptual Model for Spatial Data Warehouses." GeoInformatica 11, no. 4 (March 27, 2007): 431–57. http://dx.doi.org/10.1007/s10707-007-0022-3.
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Hanser, F., M. Seger, M. Netzer, M. Osl, R. Modre-Osprian, G. Schreier, C. Baumgartner, B. Pfeifer, and M. Wurz. "An Epidemiological Modeling and Data Integration Framework." Methods of Information in Medicine 49, no. 03 (2010): 290–93. http://dx.doi.org/10.3414/me09-02-0025.
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Summary Objectives: In this work, a cellular automaton software package for simulating different infectious diseases, storing the simulation results in a data warehouse system and analyzing the obtained results to generate prediction models as well as contingency plans, is proposed. The Brisbane H3N2 flu virus, which has been spreading during the winter season 2009, was used for simulation in the federal state of Tyrol, Austria. Methods: The simulation-modeling framework consists of an underlying cellular automaton. The cellular automaton model is parameterized by known disease parameters and geographical as well as demographical conditions are included for simulating the spreading. The data generated by simulation are stored in the back room of the data warehouse using the Talend Open Studio software package, and subsequent statistical and data mining tasks are performed using the tool, termed Knowledge Discovery in Database Designer (KD3). Results: The obtained simulation results were used for generating prediction models for all nine federal states of Austria. Conclusion: The proposed framework provides a powerful and easy to handle interface for parameterizing and simulating different infectious diseases in order to generate prediction models and improve contingency plans for future events.
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Timko, Igor, Curtis Dyreson, and Torben Bach Pedersen. "A probabilistic data model and algebra for location-based data warehouses and their implementation." GeoInformatica 18, no. 2 (May 21, 2013): 357–403. http://dx.doi.org/10.1007/s10707-013-0180-4.
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Kembro, Joakim Hans, and Andreas Norrman. "Warehouse configuration in omni-channel retailing: a multiple case study." International Journal of Physical Distribution & Logistics Management 50, no. 5 (December 20, 2019): 509–33. http://dx.doi.org/10.1108/ijpdlm-01-2019-0034.
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Purpose The purpose of this study is to explore warehouse configuration in omni-channel retailing. Design/methodology/approach A multiple case study is conducted with six large omni-channel retailers from three different sectors. Findings The study shows an increase in the number, variation and frequency of flows passing through omni-channel warehouses. Along with an increased variety of stock keeping units (including singles vs multipacks), there is an increase in the complexity of planning and coordination of order fulfillment. Retailers test a mix of different solutions for storage and picking and partly shift focus to advanced sorting operations. The companies already have or plan to invest in substantial automation systems, which emphasize the importance of capturing and using accurate master data. Research limitations/implications The study highlights the need to understand the interrelations and co-development of configuration elements in omni-channel warehousing. The findings also suggest that a successful transformation requires increased collaboration with upstream and downstream partners. Conceptual models are developed to illustrate strategies and development paths in omni-channel warehousing, and suggestions for future research are summarized in a research agenda. A research limitation is the focus on Swedish retailers in three sectors (fashion, consumer electronics and DIY/construction material). Future studies can include additional sectors, extend the geographical scope and explore cross-regional differences. Practical implications As one of the few deeper case studies on omni-channel warehousing, practitioners will find new configurations described and analyzed here. Along with conceptual models, a synthesis of challenges and potential solutions are presented to support retailers’ practical analysis and decision making. Originality/value This is one of the first multiple case studies that go deeper into omni-channel warehouse configuration, which is of increasing importance to both scholars and practitioners in the field.
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Hall, James P., Rob Robinson, and Mary Ann Paulis. "Enterprisewide Spatial Data Integration of Legacy Systems for Asset Management." Transportation Research Record: Journal of the Transportation Research Board 1917, no. 1 (January 2005): 11–17. http://dx.doi.org/10.1177/0361198105191700102.
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This paper describes the spatial information system infrastructure implemented by the Illinois Department of Transportation (IDOT) to enable delivery of information to management decision makers in asset management applications. This spatial data warehouse infrastructure makes extensive use of geographic information system (GIS) technologies to integrate information from a variety of database structures and formats. GIS products and tools have been developed to portray and analyze these data in useful combinations focused on practitioner needs. In June 1999 the Governmental Accounting Standards Board issued Statement 34 requiring governments to have a systematic approach to managing their assets. As a result, transportation agencies have placed an increased emphasis on developing mechanisms to integrate information from disparate management information systems and legacy databases. IDOT has used GIS to develop a spatial data warehouse to enable integration. A valuable characteristic of the department's information systems infrastructure is the embedding of the underlying link–node structure into roadway inventory databases to enable the direct linkage of data through various system identifiers, including differing milepost referencing and project numbering schemes. This direct linkage enables the complex integration of asset management–related data files across the enterprise and provides access to historical asset information. Changes to route referencing systems are readily accommodated, without loss of integrative capabilities. Outputs include a variety of user-developed analyses and output products with accessibility through networks, intranets, and the Internet.
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Yazidi Alaoui, O., S. Hamdoune, H. Zili, H. Boulassal, M. Wahbi, and O. El Kharki. "CREATING STRATEGIC BUSINESS VALUE FROM BIG DATA ANALYSIS – APPLICATION TELECOM NETWORK DATA AND PLANNING DOCUMENTS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W16 (October 1, 2019): 691–95. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w16-691-2019.
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Abstract. Mobile networks carrier gather and accumulate in their database system a considerable volume of data, that carries geographic information which is crucial for the growth of the company. This work aimed develop a prototype called Spatial On -Line Analytic Processing (SOLAP) to carry out multidimensional analysis and to anticipate the extension of the area of radio antennas.To this end, the researcher started by creating a Data warehouse that allows storing Big Data received from the Radio antennas. Then, doing the OLAP(online analytic processing) in order to perform multidimensional Analysis which used through GIS to represent the Data in different scales in satellite image as a topographic background). As a result, this prototype enables the carriers to receive continuous reports on different scales (Town, city, country) and to identify the BTS that works and performs well or shows the rate of its working (the way behaves) its pitfalls. By the end, it gives a clear image on the future working strategy respecting the urban planning, and the digital terrain model (DTM).
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Ibtisam, Ferrahi Ibtisam, Sandro Bimonte, and Kamel Boukhalfa. "Logical and Physical Design of Spatial Non-Strict Hierarchies in Relational Spatial Data Warehouse." International Journal of Data Warehousing and Mining 15, no. 1 (January 2019): 1–18. http://dx.doi.org/10.4018/ijdwm.2019010101.
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The emergence of spatial or geographic data in DW Systems defines new models that support the storage and manipulation of the data. The need to build an SDW and to optimize SOLAP queries continues to attract the interest of researchers in recent years. Several spatial data models have been investigated to extend classical multidimensional data models with spatial concepts. However, most of existing models do not handle a non-strict spatial hierarchy. Moreover, the complexity of the spatial data makes the execution time of spatial queries very considerable. Often, spatial indexation methods are applied to optimizing access to large volumes of data and helps reduce the cost of spatial OLAP queries. Most of existing indexes support predefined spatial hierarchies. The authors show, in this article, that the logical models proposed in the literature and indexing techniques are not suitable to non-strict hierarchies. The authors propose a new logical schema supporting the non-strict hierarchies and a bitmap index to optimize queries defined by spatial dimensions with several non-strict hierarchies.
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Azaiez, Noura, Jalel Akaichi, and Jeffrey Hsu. "Moving Beyond Traditional Decision Support Systems." International Journal of Information Systems and Social Change 8, no. 2 (April 2017): 74–87. http://dx.doi.org/10.4018/ijissc.2017040104.
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Integrating the concept of mobility into the professional and organizational realm offers the possibility of reducing geographical disparities related to organization services. The advances made in technology, geographic information systems and pervasive systems equipped with global positioning (GPS) technologies have been able to bring about an evolution from classic data approaches towards the modeling of trajectory data resulting from moving activities of moving objects. As such, trajectory data needs first to be loaded into a Data Warehouse for analysis purposes. However, the traditional approaches used are poorly suited to handle spatio-temporal data features and also the decision making tasks related to mobility issues. Because of this mismatch, the authors propose to move beyond traditional approaches and propose a repository that is able to analyse trajectories of moving objects. Improving decision making and extracting pertinent knowledge with reduced costs and time expended are the main goals of this revised analysis approach. Thus, the authors propose an approach in which they employ the Bottom-up approach to modeling a Decision Support System which is designed to support Trajectory Data. As an example to illustrate this approach, the authors use a creamery and dairy milk mobile cistern application to demonstrate the effectiveness of their approach.
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Maase, Simone, Xiomara Dilrosun, Martijn Kooi, and Robert van den Hoed. "Performance of Electric Vehicle Charging Infrastructure: Development of an Assessment Platform Based on Charging Data." World Electric Vehicle Journal 9, no. 2 (July 20, 2018): 25. http://dx.doi.org/10.3390/wevj9020025.
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Developers of charging infrastructure, be it public or private parties, are highly dependent on accurate utilization data in order to make informed decisions where and when to expand charging points. The Amsterdam University of Applied Sciences, in close cooperation with the municipalities of Amsterdam, Rotterdam, The Hague, Utrecht, and the Metropolitan Region of Amsterdam Electric, developed both the back- and front-end of a charging infrastructure assessment platform that processes and represents real-life charging data. Charging infrastructure planning and design methods described in the literature use geographic information system data, traffic flow data of non-EV vehicles, or geographical distributions of, for example, refueling stations for combustion engine vehicles. Only limited methods apply real-life charging data. Rolling out public charging infrastructure is a balancing act between stimulating the transition to zero-emission transport by enabling (candidate) EV drivers to charge, and limiting costly investments in public charging infrastructure. Five key performance indicators for charging infrastructure utilization are derived from literature, workshops, and discussions with practitioners. The paper describes the Data Warehouse architecture designed for processing large amounts of charging data, and the web-based assessment platform by which practitioners get access to relevant knowledge and information about the current performance of existing charging infrastructure represented by the key performance indicators developed. The platform allows stakeholders in the decision-making process of charging point installation to make informed decisions on where and how to expand the already existing charging infrastructure. The results are generalizable beyond the case study regions in the Netherlands and can serve the roll-out of charging infrastructure, both public and semi-public, all over the world.
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Connor, John M. "Evolving Research on Price Competition in the Grocery Retailing Industry: An Appraisal." Agricultural and Resource Economics Review 28, no. 2 (October 1999): 119–27. http://dx.doi.org/10.1017/s106828050000811x.
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With the end of the Supermarket Revolution in the 1970s, new forms of horizontal, vertical, and geographic competition have appeared to challenge the supremacy of the supermarket format. New retail formats like warehouse stores, supercenters, and fast-food outlets appear to affect local retail supermarket prices. Slotting allowances, coupons, and electronic data gathering have intensified retailer-manufacturer rivalry. Foreign direct investment offers the promise of new European-style management styles in U.S. grocery retailing.
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Siqueira, Thiago Luís Lopes, Cristina Dutra de Aguiar Ciferri, Valéria Cesário Times, and Ricardo Rodrigues Ciferri. "The SB-index and the HSB-index: efficient indices for spatial data warehouses." GeoInformatica 16, no. 1 (June 14, 2011): 165–205. http://dx.doi.org/10.1007/s10707-011-0128-5.
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Kalogeras, I. S., G. Marketos, and Y. Theodoridis. "A TOOL FOR COLLECTING, QUERYING AND MINING MACROSEISMIC DATA." Bulletin of the Geological Society of Greece 36, no. 3 (January 1, 2004): 1406. http://dx.doi.org/10.12681/bgsg.16509.
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SEISMO-SURFER is a tool for collecting, querying and mining seismic data being developed in Java programming language using Oracle database system. The objective is to combine recent research trends and results in the fields of spatial and spatio-temporal databases, data warehouses and data mining, as well as well established visualization techniques for geographical information. The database of the tool is automatically updated from remote sources while existing possibilities allow the querying on different earthquakes parameters, the analysis of the data for extraction of useful information and the graphical representation of the results via maps, charts etc. In the present work, we extend SEISMO-SURFER to include macroseismic data collected by the Geodynamic Institute and filled in a relative database. More specifically, the seismic parameters of the strong earthquakes, stored into the SEISMO-SURFER database, are linked to the macroseismic intensities observed at different sites. Administrative information for each site, local surface geology, tectonic lines, damage photographs and detailed descriptions from newspapers are also included. University of Piraeus and Geodynamic Institute are working together to continuously update and develop SEISMO-SURFER, concerning the data included, the variety of parameters stored and the mining algorithms supported for exploiting knowledge.
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Norris, Alison H., Payal Chakraborty, Kaiting Lang, Robert B. Hood, Sarah R. Hayford, Lisa Keder, Danielle Bessett, et al. "Abortion Access in Ohio’s Changing Legislative Context, 2010–2018." American Journal of Public Health 110, no. 8 (August 2020): 1228–34. http://dx.doi.org/10.2105/ajph.2020.305706.
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Objectives. To examine abortion utilization in Ohio from 2010 to 2018, a period when more than 15 abortion-related laws became effective. Methods. We evaluated changes in abortion rates and ratios examining gestation, geographic distribution, and abortion method in Ohio from 2010 to 2018. We used data from Ohio’s Office of Vital Statistics, the Centers for Disease Control and Prevention’s Abortion Surveillance Reports, the American Community Survey, and Ohio’s Public Health Data Warehouse. Results. During 2010 through 2018, abortion rates declined similarly in Ohio, the Midwest, and the United States. In Ohio, the proportion of early first trimester abortions decreased; the proportion of abortions increased in nearly every later gestation category. Abortion ratios decreased sharply in most rural counties. When clinics closed, abortion ratios dropped in nearby counties. Conclusions. More Ohioans had abortions later in the first trimester, compared with national patterns, suggesting delays to care. Steeper decreases in abortion ratios in rural versus urban counties suggest geographic inequity in abortion access. Public Health Implications. Policies restricting abortion access in Ohio co-occur with delays to care and increasing geographic inequities. Restrictive policies do not improve reproductive health.
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Sousa, Luísa Tavares Muzzi de, and Leise Kelli de Oliveira. "Influence of Characteristics of Metropolitan Areas on the Logistics Sprawl: A Case Study for Metropolitan Areas of the State of Paraná (Brazil)." Sustainability 12, no. 22 (November 23, 2020): 9779. http://dx.doi.org/10.3390/su12229779.
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The concentration of warehouses in peripheral regions of metropolitan areas in a time period is called logistics sprawl (LS). Identifying this phenomenon could help to reduce externalities related to urban freight transport, mainly, the distance traveled. This paper examines the contribution of the characteristics of metropolitan areas on the logistics sprawl indicator. A case study was carried out considering data from eight metropolitan areas of the state of Paraná (Brazil). The research method is based on the data collection procedure proposed, centrographic method, and linear regression. The results of the centrographic method reveal a positive LS in four metropolitan areas and a negative LS in three metropolitan areas. In general, the warehouses are close to the highways that cross the metropolitan area. In addition, the size of the metropolitan area has a negative relationship with the number of warehouses and the logistics sprawl indicator. The findings highlight the importance of public policies relating to urban freight transport and land use at a metropolitan level.
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Kompaniets, Maria, Andrey Plakhin, Maria Selezneva, Tatiana Kochergina, and Maria Khokholush. "Analysis of the scientific and technical level of production and the introduction of innovation technologies in the ore-dressing plant." E3S Web of Conferences 208 (2020): 03018. http://dx.doi.org/10.1051/e3sconf/202020803018.
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The process of obtaining iron ore at ore-dressing plant is a continuous process, so equipment failure at any stage leads to equipment downtime at all other stages. In this case, temporary shipment to the warehouse and from the warehouse of semi-finished raw materials leads to an increase in cost and a decrease in the quality of raw materials. These problems determined the purpose and objectives of the study of the possibilities of using a geographic information system to control moving objects in the main mine of the ore-dressing plant based on the system of automatic positioning using GPS or GPS/AVL (Automatic Vehicle Location). Based on satellite data, it is possible to generate various types of reports that allow to better control the situation - to analyze the qualitative and quantitative side of the ore mining process in quarries, to simulate the situation in order to avoid loss of working time. The basis of the study determined the economic effect of the introduction of GPS navigation in the main mine of the plant.
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Bravo, Mercedes A., Rebecca Anthopolos, and Marie Lynn Miranda. "Characteristics of the built environment and spatial patterning of type 2 diabetes in the urban core of Durham, North Carolina." Journal of Epidemiology and Community Health 73, no. 4 (January 19, 2019): 303–10. http://dx.doi.org/10.1136/jech-2018-211064.
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BackgroundFew studies examine relationships between built environment (BE) and type 2 diabetes mellitus (T2DM) using spatial models, investigate BE domains apart from food environment or physical activity resources or conduct sensitivity analysis of methodological choices made in measuring BE. We examine geographic heterogeneity of T2DM, describe how heterogeneity in T2DM relates to BE and estimate associations of T2DM with BE.MethodsIndividual-level electronic health records (n=41 203) from the Duke Medicine Enterprise Data Warehouse (2007–2011) were linked to BE based on census block. Data on housing damage, property disorder, territoriality, vacancy and public nuisances were used to estimate BE based on four different construction methods (CMs). We used race-stratified aspatial and spatial Bayesian models to assess geographic heterogeneity in T2DM and associations of T2DM with BE.ResultsAmong whites, a 1 SD increase in poor quality BE was associated with a 1.03 (95% credible interval 1.01 to 1.06) and 1.06 (95 % credible interval 1.02 to 1.11) increased risk of T2DM for poor quality BE CM1 and CM2, respectively. Among blacks/African Americans, associations between T2DM and BE overlapped with the null for all CMs. The addition of BE to white models reduced residual geographic heterogeneity in T2DM by 4%–15%, depending on CM. In black/African–American models, BE did not affect residual heterogeneity.ConclusionAssociations of T2DM with BE were sensitive to CM and geographic heterogeneity in T2DM differed by race/ethnicity. Findings underscore the need to consider multiple methods of estimating BE and consider differences in relationships by race/ethnicity.
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Wang, Ying, Fu Jia, Tobias Schoenherr, and Yu Gong. "Supply Chain-Based Business Model Innovation: The Case of a Cross-Border E-Commerce Company." Sustainability 10, no. 12 (November 23, 2018): 4362. http://dx.doi.org/10.3390/su10124362.
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Cross-border e-commerce has gained increasing popularity globally and thrives under the backdrop of the ‘One Belt One Road’ policy of China, which resonates with UN’s sustainable development goals targeting countries in the South. In this study, we investigate Zongteng, which is one of the first cross-border e-commerce companies in China, to assess how supply chain innovation activities can become core to a firm’s business model innovation. Data were collected from Zongteng senior managers, internal company documents, and open online resources. We found that the firm needed changes in its business model, which brought new participants into the business ecosystem and changed their respective positions. We further identified three types of supply chain localisations in cross-border e-commerce for export markets (sales, warehousing, and R&D localisation), which the company’s establishment of overseas warehouses enabled. The three localisation strategies serve as the driving force and the main business model innovation in cross-border e-commerce. This study contributes to the supply chain innovation literature by proposing that overseas warehouses, bonded warehouses, and supply chain finance are capabilities that form part of the business model innovation in cross-border e-commerce.
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Qiu, Yong, Ji Li, Xia Huang, and Hanchang Shi. "A Feasible Data-Driven Mining System to Optimize Wastewater Treatment Process Design and Operation." Water 10, no. 10 (September 28, 2018): 1342. http://dx.doi.org/10.3390/w10101342.
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Achieving low costs and high efficiency in wastewater treatment plants (WWTPs) is a common challenge in developing countries, although many optimizing tools on process design and operation have been well established. A data-driven optimal strategy without the prerequisite of expensive instruments and skilled engineers is thus attractive in practice. In this study, a data mining system was implemented to optimize the process design and operation in WWTPs in China, following an integral procedure including data collection and cleaning, data warehouse, data mining, and web user interface. A data warehouse was demonstrated and analyzed using one-year process data in 30 WWTPs in China. Six sludge removal loading rates on water quality indices, such as chemical oxygen demand (COD), total nitrogen (TN), and total phosphorous (TP), were calculated as derived parameters and organized into fact sheets. A searching algorithm was programmed to find out the five records most similar to the target scenario. A web interface was developed for users to input scenarios, view outputs, and update the database. Two case WWTPs were investigated to verify the data mining system. The results indicated that effluent quality of Case-1 WWTP was improved to meet the discharging criteria through optimal operations, and the process design of Case-2 WWTP could be refined in a feedback loop. A discussion on the gaps, potential, and challenges of data mining in practice was provided. The data mining system in this study is a good candidate for engineers to understand and control their processes in WWTPs.
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Bimonte, Sandro, Michela Bertolotto, Jérôme Gensel, and Omar Boussaid. "Spatial OLAP and Map Generalization." International Journal of Data Warehousing and Mining 8, no. 1 (January 2012): 24–51. http://dx.doi.org/10.4018/jdwm.2012010102.
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Map generalization can be used as a central component of Spatial Decision Support Systems to provide a simplified and more readable cartographic visualization of geographic information. Indeed, it supports the user mental process for discovering important and unknown geospatial relations, trends and patterns. Spatial OLAP (SOLAP) integrates spatial data into OLAP and data warehouse systems. SOLAP models and tools are based on the concepts of spatial dimensions and measures that represent the axes and the subjects of the spatio-multidimensional analysis. Although powerful under some respect, current SOLAP models cannot support map generalization capabilities. This paper provides the first effort to integrate Map Generalization and OLAP. Firstly the authors define all modeling and querying requirements to do this integration, and then present a SOLAP model and algebra that support map generalization concepts. The approach extends SOLAP spatial hierarchies introducing multi-association relationships, supports imprecise measures, and it takes into account spatial dimensions constraints generated by multiple map generalization hierarchies.
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Silva, Vítor, Luís Pinto Ferreira, Francisco J. G. Silva, Benny Tjahjono, and Paulo Ávila. "Simulation-Based Decision Support System to Improve Material Flow of a Textile Company." Sustainability 13, no. 5 (March 9, 2021): 2947. http://dx.doi.org/10.3390/su13052947.
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To remain competitive, companies must continuously improve the processes at hand, be they administrative, production, or logistics. The objective of the study described in this paper was to develop a decision-making tool based on a simulation model to support the production of knits and damask fabrics. The tool was used to test different control strategies for material flow, from the raw material warehouse to the finished product warehouse, and thus can also be used to evaluate the impacts of these strategies on the productivity. The data upon which the decision support tool was built were collected from five sectors of the plant: the raw material warehouse, knit production, damask production, finishing work, and the finished product warehouse. The decision support tool met the objectives of the project, with all five strategies developed showing positive results. Knit and damask production rates increased by up to 8% and 44%, respectively, and a reduction of 75% was observed in the waiting time on the point of entry to the finishing work area, compared to the company’s existing system.
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Raicu, Serban, Dorinela Costescu, and Stefan Burciu. "Distribution System with Flow Consolidation at the Boundary of Urban Congested Areas." Sustainability 12, no. 3 (January 30, 2020): 990. http://dx.doi.org/10.3390/su12030990.
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This paper presents effective and efficient solutions for components of urban logistics. The specificity of such logistics and the multiple limitations led to particular solutions. However, they all share one common feature—the flow consolidation in different variants. This study considers the flow consolidation at the boundary of urban congested areas, through horizontal collaboration between logistic platforms. This way, the urban distribution centers (UDCs) receive all the goods according to the orders addressed to each producer (or group in case of “on-going consolidations”). Deliveries are addressed to a single logistic platform. Thus, the flow consolidation is achieved. Each logistic platform receives part of the consumer goods intended for commercialization, but through collaboration between them (freight exchanges), all the warehouses of the producers have all the ordered goods. Dedicated management of logistics platforms and warehouses within each UDC ensures the confidentiality of distributor data. Three scenarios are presented concerning the same pattern of flow addressed to each UDC. These scenarios differ by the accessibility of the logistics platforms and by the connection between them (due to infrastructure development). The methodology of choosing the variants for composing the flow sent from each logistics platform considered the minimization of transfer times to UDC warehouses. Synthetic indicators allow for comparison between the analyzed scenarios.
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Bullock, Ann, Karen Sheff, Israel Hora, Nilka Rios Burrows, Stephen R. Benoit, Sharon H. Saydah, Carmen Licavoli Hardin, and Edward W. Gregg. "Prevalence of diagnosed diabetes in American Indian and Alaska Native adults, 2006–2017." BMJ Open Diabetes Research & Care 8, no. 1 (April 2020): e001218. http://dx.doi.org/10.1136/bmjdrc-2020-001218.
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IntroductionThe objective of this study was to examine recent trends in diagnosed diabetes prevalence for American Indian and Alaska Native (AI/AN) adults aged 18 years and older in the Indian Health Service (IHS) active clinical population.Research design and methodsData were extracted from the IHS National Data Warehouse for AI/AN adults for each fiscal year from 2006 (n=729 470) through 2017 (n=1 034 814). The prevalence of diagnosed diabetes for each year and the annual percentage change were estimated for adults overall, as well as by sex, age group, and geographic region.ResultsAfter increasing significantly from 2006 to 2013, diabetes prevalence for AI/AN adults in the IHS active clinical population decreased significantly from 2013 to 2017. Prevalence was 14.4% (95% CI 13.9% to 15.0%) in 2006; 15.4% (95% CI 14.8% to 16.0%) in 2013; and 14.6% (95% CI 14.1% to 15.2%) in 2017. Trends for men and women were similar to the overall population, as were those for all age groups. For all geographic regions, prevalence either decreased significantly or leveled off in recent years.ConclusionsDiabetes prevalence in AI/AN adults in the IHS active clinical population has decreased significantly since 2013. While these results cannot be generalized to all AI/AN adults in the USA, this study documents the first known decrease in diabetes prevalence for AI/AN people.
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Kats, Pavel. "Digital publishing as the great leveller." Book 2.0 4, no. 1 (October 1, 2014): 21–30. http://dx.doi.org/10.1386/btwo.4.1-2.21_1.
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Proverbs are a fascinating genre of cultural expression that is studied by folklorists, linguists, philologists, anthropologists, literary scholars, philosophers, logicians, and cognitive psychologists (at least). This multitude of perspectives created in turn a multitude of approaches to how proverbial collections should be organized, classified, and used. These approaches may involve criteria based on alphabetical, chronological, ethnic, geographical, functional, lexicographical, metaphorical, thematic, or stylistic (a partial list) characteristics of proverbial performances. Consequences of this variety of approaches to the classification of subject matter ranged from inconvenience caused by heterogeneous resources to personal discrepancies between scholars.It is exactly here that digital humanities have another edge on traditional humanities. Contemporary information technologies increasingly allow to store data without commiting in advance to how it is structured when used. If in traditional publishing the order of lexicographical entries and their content is predefined, digital publishers can use such technologies as relational databases, data warehouses, semantic ontologies, or faceted search, in order to implement flexible access to data that can satisfy even most exotic research demands.In the proposed contribution I overview traditional challenges, suggest their domain-independent analysis in the perspective of ‘the big data challenge’, and describe some present achievements and future directions.
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Tanaka, Rina, Aya Ishigaki, Tomomichi Suzuki, Masato Hamada, and Wataru Kawai. "Data Analysis of Shipment for Textiles and Apparel from Logistics Warehouse to Store Considering Disposal Risk." Sustainability 11, no. 1 (January 7, 2019): 259. http://dx.doi.org/10.3390/su11010259.
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Given the rapid diversification of products in the textile and apparel industry, manufacturers face significant new challenges in production. The life cycle of apparel products has contracted and is now, generally, a several-week season, during which time a majority of products are supposed to be sold. Products that do not sell well may be sold at a price lower than the fixed price, and products that do not sell at all within the sales period may eventually become forced disposal. This creates long-term management and environmental problems. In practice, shipping personnel determine when to ship products to stores after reviewing product sales information. However, they may not schedule or structure these shipments properly because they cannot effectively monitor sales for a large number of products. In this paper, shipment is considered to reduce the risk of product disposal on the premise of selling at a fixed price. Although shipment quantities are determined by various factors, we only consider the change in inventory at the logistics warehouse, since it is difficult to incorporate all factors into the analysis. From cluster analysis, it is found that shipping personnel should recognize a policy to sell products gradually over time. Furthermore, to reduce the risk of disposal, we forecast the inventory from conditional probability and are able to extract products out of a standard grouping using past data.
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Gunawan, Endro, John K. Kuwornu, Avishek Datta, and Loc Nguyen. "Farmers’ Perceptions of the Warehouse Receipt System in Indonesia." Sustainability 11, no. 6 (March 20, 2019): 1690. http://dx.doi.org/10.3390/su11061690.
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This study assessed farmers’ perceptions of the warehouse receipt system (WRS) in the West Java Province in Indonesia. Primary data were collected from 500 farmers through questionnaire administration. The results of the weighted average index revealed that there was a strong perception that the WRS is not well known, provides easy access to credit, and limited access for smallholder farmers. Moreover, there was a weak perception that the WRS has complicated regulations and slowed delivery of warehouse receipts. The main problems include lack of awareness, lack of facilities and limited access for smallholders. The implications for improving the implementation of the WRS are presented.
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Plischke, Simona, Jana Machutova, Pavel Stasa, and Jakub Unucka. "Development of SW Interface between Healthcare Standards—DASTA and HL7." Sustainability 12, no. 18 (September 16, 2020): 7649. http://dx.doi.org/10.3390/su12187649.
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The prescription and administration of drugs are the most common process that takes place in hospitals. Although a relatively simple process, it is considered the riskiest process in hospitals because mistakes during drug administration are among the most common ones. The aim is to introduce technological and process changes that will contribute to maximally increase the safety of the medication process and the efficiency of drug management. To support the automation of the medication process, it is desirable to use the international standard Health Level 7 (HL7). However, the Czech healthcare system currently supports the local healthcare standard—DASTA. For that reason, the paper introduces some of the options how to transfer data from DASTA to HL7 and deals with the development of a software (SW) interface that converts data necessary for robotic preparation of patient medication from the Czech DASTA data standard to the HL7 international standard used by selected robotics. Based on the performed analyses, a combination of robotics for the preparation of single-dose packages of drugs with one of the automated warehouses is recommended.
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Mariana, Mariana, and Muh Rasyid Ridha. "Ekspansi Bisnis Pergudangan Dusun Patte’ne Desa Temmapadduae Kabupaten Maros, 1995-2017." Jurnal Pattingalloang 7, no. 1 (April 1, 2020): 89. http://dx.doi.org/10.26858/pattingalloang.v7i1.12537.
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Penelitian ini bertujuan untuk mengetahui latar belakang terbentuknya pergudangan di Dusun Patte’ne Desa Temmapadduae Kabupaten Maros, perkembangan Pergudangan serta dampaknya terhadap masyarakat di kabupaten Maros. Hasil penelitian ini menunjukan bahwa latar belakang terbentuknya Gudang di Patte’ne dikarenakan letak geografis yang dekat dengan pusat kota dan kepadatan penduduk kota serta banyaknya lahan kosong untuk pembangunan gudang dan banyaknya bahan baku dari luar yang membutuhkan tempat penyimpanan. Kehadiran pergudangan bagi pemerintah memberikan keuntungan terhadap Pajak serta membantu Pemerintah Setempat untuk mengurangi Pengangguran. Kemudian bagi masyarakat membantu dalam hal peningkatan kualitas peluang usaha yang dulunya hanya mendirikan warung-warung kecil kini menjadi cukup besar. Masyarakat juga terbantu dalam hal menunaikan ibadah haji dan umrah dari penjualan lahan mereka. Ratusan orang telah menunaikan haji dan umrah karena dari penjualan tersebut. Penelitian ini adalah penelitian sejarah dengan metodologi sejarah yang memiliki tahap yaitu, heuristik (pengumpulan data), kritik (verifikasi), interpretasi (penafsiran), dan historiografi (penulisan sejarah). Kata Kunci:Perkembangan, Pergudangan dan Desa Patte’ne AbstractThis research aims to find out the background of warehousing formation in the village of Patte'ne Temmapadduae, Maros Regency, development of warehouse and its impact on people in Maros district. The results of this study showed that the background was formed by the warehouse in Patte'ne because of the geographical location that is close to the city center and city population density as well as the number of vacant land for warehouse development and many raw materials from outside Requiring a storage space. The presence of warehousing for the government provides benefits to taxes and helps the local government to reduce unemployment. Then for the community to help in terms of improving the quality of business opportunities that used to only set up small stalls now become large enough. People are also helped in doing Hajj and Umrah from the sale of their land. Hundreds of people have performed Hajj and Umrah because of the sale. This research is a historical study with historical methodologies that have the stage that is, heuristics (data collection), criticism (verification), interpretation (interpretation), and historiography (historical writing). Keywords: Developments, Warehousing and Patte'ne Village.
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Wang, Zhixin, and Yue Wang. "Measuring Risks of Confirming Warehouse Financing from the Third Party Logistics Perspective." Sustainability 11, no. 23 (November 21, 2019): 6573. http://dx.doi.org/10.3390/su11236573.
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Confirmation warehouse financing is an important model in supply chain finance. This type of financing has special characteristics due to the existence of the reverse repurchase link, and it increases the risk commitment of the core enterprise at a certain level. Previous research on supply chain financial risk mostly settled in ‘all-industry, multi-model’, ignoring the special risks of single mode. To supplement the vacancies in the current research, the special risks of supply chain finance should be identified under a single model. On this basis, a measurement index system for confirmation warehouse financing risk is created. The article uses a Back Propagation (BP) neural network to build a Third Party Logistics (3PL) perspective of the risk measurement model for confirmation warehouse financing. The said network is combined with the 24 sets of actual cases from ZY Logistics. MATLAB is used to train the sample data. Results show that the absolute errors—0.042998, −0.011102, 0.020514 and 0.039448—between the training value and the predicted value are smaller than the preset error value. Among the 24 cases, high-risk businesses reached 41.7%, whereas low-risk businesses only accounted for 29.2%. The ZY enterprise confirms that warehouse financial business risk is high, and this situation should be revised. Research shows that the risk measurement indicator system has good risk prediction ability. This study establishes and verifies the rationality of the risk measurement index system and provides a reliable reference for 3PL risk aversion in supply chain finance.
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Dzemydienė, Dalė, Saulius Maskeliūnas, and Ignas Dzemyda. "INTEROPERABILITY OF INFORMATION SYSTEM COMPONENTS FOR MONITORING OF SEWAGE AND INTELLIGENT ANALYSIS OF WATER RESOURCES / INFORMACINIŲ SISTEMŲ KOMPONENTŲ SĄVEIKUMAS VYKDANT NUTEKAMŲJŲ VANDENŲ STEBĖSENĄ IR INTELEKTINĘ VANDENS IŠTEKLIŲ ANALIZĘ." Technological and Economic Development of Economy 14, no. 3 (September 30, 2008): 260–78. http://dx.doi.org/10.3846/1392-8619.2008.14.260-278.
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The interoperability problems of distributed databases are important in the developing of the operatively working web services aimed for all sectors of public administration. The following web services are designed for solving tasks in water resource management and contamination evaluation sector with a due attention to the international environment protection context. The paper is devoted to problems of developing the component‐based architecture of the integrated decision‐support system that afford ground for the monitoring and intellectual analysis of water management. Such investigations are made according to the requirements of European Union (EU) Water Framework Directive, Sustainable development Directives and EIONET ReportNet infrastructure. The main components of decision‐support system are analyzed by using different knowledge modelling and web service development techniques. The structure of water resource management information system (WRMIS) becomes the core of the decision‐support system in which web services are implemented. The main components for evaluation of processes of contamination and water monitoring are represented by data warehouse structures. The solutions to satisfy the interoperability requirements are demonstrated by architectural design decisions of the system, integrating the distributed data warehouses and geographical information system means. The web services are based on common portal technology. The organizational and political arrangements require deeper and stronger participation activities by all member states of EU in reporting, understanding the importance of sustainable development problems and risk evaluation possibilities. Santrauka Vandens išteklių valdymas ir nutekamojo vandens kokybės vertinimas yra viena svarbiausių problemų, susijusių su aplinkos apsaugos ir žmonių sveikatos uždaviniais. Vanduo yra vienas iš pagrindinių išteklių visiems biologinės įvairovės gyvavimo ciklams egzistuoti. Vandens kokybės reikalavimai daro įtaką daugeliui darniosios plėtros reikalavimų. Aplinkos apsaugos principai susideda iš daugelio tarpusavyje sąveikaujančių komponentų. Didelių įmonių, institucijų ir organizacijų veikla turėtų būti grindžiama įvairiopa atsakomybe už daromos veiklos ir žalos aplinkai padarinius. Nagrinėjami informacinių sistemų, vykdančių vandens užterštumo stebėseną ir analizę, sąveikumo užtikrinimo klausimai. Informacijos perteikimo metodai yra svarbūs kuriant konsultacines sistemas, kurios padėtų spręsti daugelį sprendimų priėmimo problemų, vertinant kompleksinius aplinkos taršos procesus. Šiame straipsnyje analizuojami pagrindiniai sprendimų paramos sistemos kūrimo komponentai aplinkos vertinimo sektoriuje, leidžiantys efektyviau spręsti šias problemas naudojant E-tinklus (vertinimo tinklus, t. y. Petri tinklų praplėtimą). Modeliai, leidžiantys atvaizduoti ir vertinti sprendimų priėmimo procesus, projektuojami keliais detalumo lygmenimis, taikant semantinio informacijos struktūrizavimo ir imitacinio modeliavimo priemones. Taršos procesai stebimi vykdant monitoringą, pirminius duomenis fiksuojant daugiamatėse duomenų saugyklose ir perteikiant vartotojams sprendimų paramos sistemos analizės priemonėmis. Aprašomi vandens išteklių ir nuotekų kontrolės duomenų analizės modeliai ir gauti rezultatai. Straipsnyje analizuojami pagrindiniai sprendimų paramos sistemos komponentai ir spendimams priimti svarbūs vandens ir aplinkos vertinimo rezultatai.
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Muñuzuri, Jesús, Alejandro Escudero-Santana, and Pablo Aparicio-Ruiz. "UNDER WHICH CONDITIONS IS CARRIER COOPERATION POSSIBLE? A CASE STUDY IN A SEVILLE MARKETPLACE." Transport 33, no. 4 (December 5, 2018): 881–89. http://dx.doi.org/10.3846/transport.2018.6590.
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The high volume of traffic originates two well-known problems in many cities: congestion and pollution. In recent years, a social phenomenon is emerging cooperation. This work is aimed at evaluating the circumstances under which transport cooperation is possible between different stakeholders operating in the same geographical area. To this end, a double survey process was conducted in a marketplace situated in the Seville City (Spain) centre. The first survey was designed to know the characteristics of the retailers and their preferences with respect to cooperation and regulations. A relational analysis between retailer features and their willingness to cooperate was carried out. After analysing the motivations for non-cooperation, a mixed proposal was designed and surveyed. Although the research was limited to a marketplace, the relevant data gathered from this double survey process highlights some implications: (a) the importance of personal relations in retailer cooperation; (b) a high volume of freight and the use of vans as on-street warehouses appear as significant motivations for non-cooperation; (c) forcing changes in the statu quo encourages cooperation.
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Górny, Kasper, Natalia Idaszewska, Zuzanna Sydow, and Krzysztof Bieńczak. "Modelling the Carbon Footprint of Various Fruit and Vegetable Products Based on a Company’s Internal Transport Data." Sustainability 13, no. 14 (July 7, 2021): 7579. http://dx.doi.org/10.3390/su13147579.
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Many organisations consider environmentally friendly activities, including the reduction of their carbon footprint, to be a significant aspect of their operation. In this study, a mathematical model was used to calculate the carbon footprint of food products at different stages of internal transport, using data on internal transport energy consumption. It was shown that for most products, the highest carbon footprint was related to the raw material transport stage from the loading/unloading point to the workstations on the production line. Broccoli showed the highest carbon footprint for internal transport per tonne of raw material. The study proposes methods of reducing the internal transport-related carbon footprint, which involves reorganising the distribution of goods in the warehouse and using nutritionally valuable vegetable waste in the production of food products.
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Curto, Rocco, and Elena Fregonara. "Monitoring and Analysis of the Real Estate Market in a Social Perspective: Results from the Turin’s (Italy) Experience." Sustainability 11, no. 11 (June 4, 2019): 3150. http://dx.doi.org/10.3390/su11113150.
Full textAbstract:
In Italy, it has always been difficult to collect reliable data on real estate given the opacity of the information available. Keeping into consideration the actual availability of data and information, the possibility to have a structure for permanently monitoring and analysing the real estate market is fundamental. Focusing on developing and disseminating knowledge related to practices in this context, in this paper the Turin’s (Northern Italy) experience is presented, through the Real Estate Market Observatory (TREMO): This structure is based on a data-warehouse, implemented over time, with databases that lead to historic price observations of the residential market. The data warehouse is the basis for investigating methodologies and analyses, assuming the spatial requisites of the data and its georeferencing as the main discriminant in choosing among descriptive statistics, multi-varied or spatial analysis methods. In twenty years, several studies have been developed, allowing us not only to explore the applicability of models and operative modalities, but also to obtain results with a high potential impact under a social viewpoint. In this paper, the methodologies developed for implementing the monitoring structure are presented, specifically the “quality process” and computerized analysis procedures, followed by some representative research experiences with reference to aims, models and results.
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Zhou, Li, Zhaochan Li, Ning Shi, Shaohua Liu, and Ke Xiong. "Performance Analysis of Three Intelligent Algorithms on Route Selection of Fishbone Layout." Sustainability 11, no. 4 (February 21, 2019): 1148. http://dx.doi.org/10.3390/su11041148.
Full textAbstract:
The Internet of Things (IoT) has become an important strategy in the current round of global economic growth and technological development and provides a new path for the intelligent development of the logistics industry. With the development of the economy, the demand for logistics benefits is becoming more important. The appropriate use of technologies related to IoT to improve logistics efficiency, such as cloud computing, mobile computing and data mining, has become a topic of considerable research interest. Picking operations are currently an extremely important and cumbersome aspect of logistics center tasks. To shorten the picking distance and improve work efficiency, this paper uses the genetic algorithm, ant colony algorithm and cuckoo algorithm to optimize the picking path in a fishbone-layout warehouse and establishes an optimized model of the warehouse picking path under the fishbone layout. Data-mining technology is used to simulate the model and obtain the simulation data under the condition of multiple orders. The results provide a theoretical basis for the study of the fishbone-layout picking path model and has certain practical significance for the efficient operation of logistics enterprises. Through optimization, it is conducive to the sustainable development of enterprises and to achieving long-term profitability.
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Jones, Stephen, William Conner, and Bo Song. "Spatially Explicit Nonlinear Models for Explaining the Occurrence of Infectious Zoonotic Diseases." ISRN Biomathematics 2012 (October 23, 2012): 1–12. http://dx.doi.org/10.5402/2012/132342.
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Zoonotic diseases can be transmitted via an arthropod vector, and disease risk maps are often created based on underlying associative factors within the surrounding landscape of known occurrences. A limitation however is the ability to map disease risk at a meaningful geographic scale, and traditional regression modeling approaches may not always be appropriate. Our objective was to determine if nonlinear modeling could improve explanatory power in describing the occurrence of 2 tick-borne diseases (Lyme disease (LD) and Rocky Mountain spotted fever (RMSF)) known to occur in Tennessee. Medically diagnosed cases of LD (ICD-9: 088.81) and RMSF (ICD-9: 082.0) were extracted from a managed care organization data warehouse for the 2000–2009 time period. Four separate modeling techniques were constructed (logistic regression, classification and regression tree (CART), gradient boosted tree (GBT), and neural network (NNET)) and compared for accuracy. Results suggest that areas higher in disease prevalence were not necessarily the same areas having high predicted disease risk. GBT best explained LD occurrence (misclassification rate: 0.232; ROC: 0.789). RMSF prevalence was best explained with an NNET algorithm (misclassification rate: 0.288; ROC: 0.696). Covariates explaining disease risk included forested wetlands, urbanization, and median income. Nonlinear modeling may provide better results than traditional regression-based approaches.
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Howard, J. R., J. Lucas, J. Maitland, P. Tarrant, and T. Watson. "WaterScope: an innovative water quality information management system." Water Supply 4, no. 5-6 (December 1, 2004): 409–14. http://dx.doi.org/10.2166/ws.2004.0132.
Full textAbstract:
SA Water is a State owned organisation that owns and manages South Australia's water supplies, providing reliable drinking water to nearly 1.4 million South Australians. A major issue affecting SA Water's ability to manage water quality effectively has been the difficulty accessing water quality information which has been stored in separate, generally inaccessible databases with poor reporting and decision support capability. To improve SA Water's ability to make timely and effective decisions regarding water quality, an integrated business system has been developed which provides water managers with direct access to comprehensive water quality information. The system includes improved field data collection units which incorporate a barcode system; sample point images and workflow support tools; an integrated water quality data warehouse with automated standard and ad hoc reporting capabilities; a geographical information system containing comprehensive coverages of natural resources and system infrastructure information; and water incident exception reporting and incident management support through a corporate incident management system. Major benefits of the system will include improved management of public health risk through quicker and more accurate reporting of incidents; improved customer confidence in SA Water; improved knowledge capture and visibility of water quality information; increased efficiency of capital utilisation and better understanding of system performance through spatial representation of data and trending of results. WaterScope can also be used and shared by data partners and regulators, making optimal use of the State's limited water quality data sets. It can also be made available commercially to other water management organisations. Future challenges include the integration of wastewater and recycled water data, linking of continuous (on-line) water quality data and links to water demand management systems.