Academic literature on the topic 'ATMS (Advanced Text Management System)'
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Journal articles on the topic "ATMS (Advanced Text Management System)"
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Chen, Chih-Ming, and Chung Chang. "A Chinese ancient book digital humanities research platform to support digital humanities research." Electronic Library 37, no. 2 (April 1, 2019): 314–36. http://dx.doi.org/10.1108/el-10-2018-0213.
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PurposeWith the rapid development of digital humanities, some digital humanities platforms have been successfully developed to support digital humanities research for humanists. However, most of them have still not provided a friendly digital reading environment and practicable social network analysis tool to support humanists on interpreting texts and exploring characters’ social network relationships. Moreover, the advancement of digitization technologies for the retrieval and use of Chinese ancient books is arising an unprecedented challenge and opportunity. For these reasons, this paper aims to present a Chinese ancient books digital humanities research platform (CABDHRP) to support historical China studies. In addition to providing digital archives, digital reading, basic search and advanced search functions for Chinese ancient books, this platform still provides two novel functions that can more effectively support digital humanities research, including an automatic text annotation system (ATAS) for interpreting texts and a character social network relationship map tool (CSNRMT) for exploring characters’ social network relationships.Design/methodology/approachThis study adopted DSpace, an open-source institutional repository system, to serve as a digital archives system for archiving scanned images, metadata, and full texts to develop the CABDHRP for supporting digital humanities (DH) research. Moreover, the ATAS developed in the CABDHRP used the Node.js framework to implement the system’s front- and back-end services, as well as application programming interfaces (APIs) provided by different databases, such as China Biographical Database (CBDB) and TGAZ, used to retrieve the useful linked data (LD) sources for interpreting ancient texts. Also, Neo4j which is an open-source graph database management system was used to implement the CSNRMT of the CABDHRP. Finally, JavaScript and jQuery were applied to develop a monitoring program embedded in the CABDHRP to record the use processes from humanists based on xAPI (experience API). To understand the research participants’ perception when interpreting the historical texts and characters’ social network relationships with the support of ATAS and CSNRMT, semi-structured interviews with 21 research participants were conducted.FindingsAn ATAS embedded in the reading interface of CABDHRP can collect resources from different databases through LD for automatically annotating ancient texts to support digital humanities research. It allows the humanists to refer to resources from diverse databases when interpreting ancient texts, as well as provides a friendly text annotation reader for humanists to interpret ancient text through reading. Additionally, the CSNRMT provided by the CABDHRP can semi-automatically identify characters’ names based on Chinese word segmentation technology and humanists’ support to confirm and analyze characters’ social network relationships from Chinese ancient books based on visualizing characters’ social networks as a knowledge graph. The CABDHRP not only can stimulate humanists to explore new viewpoints in a humanistic research, but also can promote the public to emerge the learning interest and awareness of Chinese ancient books.Originality/valueThis study proposed a novel CABDHRP that provides the advanced features, including the automatic word segmentation of Chinese text, automatic Chinese text annotation, semi-automatic character social network analysis and user behavior analysis, that are different from other existed digital humanities platforms. Currently, there is no this kind of digital humanities platform developed for humanists to support digital humanities research.
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Yang, Qi, Haris N. Koutsopoulos, and Moshe E. Ben-Akiva. "Simulation Laboratory for Evaluating Dynamic Traffic Management Systems." Transportation Research Record: Journal of the Transportation Research Board 1710, no. 1 (January 2000): 122–30. http://dx.doi.org/10.3141/1710-14.
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Advanced traffic management systems (ATMS) and advanced traveler information systems (ATIS) are promising technologies for achieving efficiency in the operation of transportation systems. A simulation-based laboratory environment, MITSIMLab, is presented that is designed for testing and evaluation of dynamic traffic management systems. The core of MITSIMLab is a microscopic traffic simulator (MITSIM) and a traffic management simulator (TMS). MITSIM represents traffic flows in the network, and the TMS represents the traffic management system under evaluation. An important feature of MITSIMLab is its ability to model ATMS or ATIS that generate traffic controls and route guidance based on predicted traffic conditions. A graphical user interface allows visualization of the simulation, including animation of vehicle movements. An ATIS case study with a realistic network is also presented to demonstrate the functionality of MITSIMLab.
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Li, Ruimin, Hongliang Ma, Huapu Lu, and Min Guo. "Research and Application of the Beijing Road Traffic Prediction System." Discrete Dynamics in Nature and Society 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/316032.
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As an important part of the urban Advanced Traffic Management Systems (ATMS) and Advanced Traveler Information Systems (ATIS), short-term road traffic prediction system has received special attention in recent decades. The success of ATMS and ATIS technology deployment is heavily dependent on the availability of timely and accurate estimation or prediction of prevailing and emerging traffic conditions. We studied a real-time road traffic prediction system developed for Beijing based on various traffic detection systems. The logical architecture of the system was presented, including raw data level, data processing and calculation level, and application level. Four key function servers were introduced, namely, the database server, calculation server, Geographic Information System (GIS) server, and web application server. The functions, function modules, and the data flow of the proposed traffic prediction system were analyzed, and subsequently prediction models used in this system are described. Finally, the prediction performance of the system in practice was analyzed. The application of the system in Beijing indicated that the proposed and developed system was feasible, robust, and reliable in practice.
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Xie, Junping. "A Spiral Development Model for an Advanced Traffic Management System (ATMS) Architecture Based on Prototype." International Journal of Science, Technology and Society 3, no. 6 (2015): 304. http://dx.doi.org/10.11648/j.ijsts.20150306.15.
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Ramakrishna, Maanyam, and Bandaru Ramesh. "Identification and Mitigation of Blackspots and Implementation of An Advanced Traffic Management System on NH-216A (A Spur of National Highway-16)." International Journal for Research in Applied Science and Engineering Technology 10, no. 5 (May 31, 2022): 345–56. http://dx.doi.org/10.22214/ijraset.2022.42177.
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Abstract: As the population is increasing day by day the number of vehicles is also increasing. As the number of vehicles is increasing, the number of accidents also increases. Analysis of previous data indicates that 66% of the accidents occur due to human error and 33% due to road parameters such as road and vehicle interaction, other road users, and environmental factors. Road safety has recently become a major concern in most modern societies. The identification of sites (black spots) that are more dangerous from an accident point of view can help in better scheduling road safety policies. The study includes the collection of accident data and prioritizing the accident-prone locations by using the Weighted Severity Index (WSI) method. This study includes the identification of Accidental Black Spots and improving these Accidental Black Spots by using ATMS. This project emphasizes accident studies on the National Highway-216A (Diwancheruvu to Siddantham) in East Godavari District, State of Andhra Pradesh, India. So the main aim of this study is, therefore, to identify the major accident black spots on National Highway -16 and mitigation of Accidental Black Spots by using Advanced Traffic Management System. Keywords: Accident, National Highway, Black Spots, Advanced Traffic Management System (ATMS), Weighted Severity Index (WSI).
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Akabane, Ademar Takeo, Roger Immich, Richard Wenner Pazzi, Edmundo Roberto Mauro Madeira, and Leandro Aparecido Villas. "Exploiting Vehicular Social Networks and Dynamic Clustering to Enhance Urban Mobility Management." Sensors 19, no. 16 (August 15, 2019): 3558. http://dx.doi.org/10.3390/s19163558.
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Transport authorities are employing advanced traffic management system (ATMS) to improve vehicular traffic management efficiency. ATMS currently uses intelligent traffic lights and sensors distributed along the roads to achieve its goals. Furthermore, there are other promising technologies that can be applied more efficiently in place of the abovementioned ones, such as vehicular networks and 5G. In ATMS, the centralized approach to detect congestion and calculate alternative routes is one of the most adopted because of the difficulty of selecting the most appropriate vehicles in highly dynamic networks. The advantage of this approach is that it takes into consideration the scenario to its full extent at every execution. On the other hand, the distributed solution needs to previously segment the entire scenario to select the vehicles. Additionally, such solutions suggest alternative routes in a selfish fashion, which can lead to secondary congestions. These open issues have inspired the proposal of a distributed system of urban mobility management based on a collaborative approach in vehicular social networks (VSNs), named SOPHIA. The VSN paradigm has emerged from the integration of mobile communication devices and their social relationships in the vehicular environment. Therefore, social network analysis (SNA) and social network concepts (SNC) are two approaches that can be explored in VSNs. Our proposed solution adopts both SNA and SNC approaches for alternative route-planning in a collaborative way. Additionally, we used dynamic clustering to select the most appropriate vehicles in a distributed manner. Simulation results confirmed that the combined use of SNA, SNC, and dynamic clustering, in the vehicular environment, have great potential in increasing system scalability as well as improving urban mobility management efficiency.
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Perez, William A., and Truman M. Mast. "Human Factors and Advanced Traveler Information Systems (ATIS)." Proceedings of the Human Factors Society Annual Meeting 36, no. 15 (October 1992): 1073–77. http://dx.doi.org/10.1518/107118192786749694.
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The nation's motoring public is increasingly burdened by recalcitrant transportation problems, many of them directly attributable to increasing traffic congestion. In response to this, the US. Department of transportation is actively moving on several fronts to address this problem. One of the more promising approaches to relieving congestion is through the design and implementation of new technology in the Intelligent Vehicle/Highway System (IVHS). IVHS is composed of five elements: Advanced Traffic Management Systems (ATMS), Advanced Traveler Information Systems (ATIS), Commercial Vehicle Operations (CVO), Advanced Vehicle Control Systems (AVCS), and Advanced Public Transportation Systems (APTS). This paper will discuss human factors issues associated with ATIS.
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Amin-Naseri, Mostafa, Pranamesh Chakraborty, Anuj Sharma, Stephen B. Gilbert, and Mingyi Hong. "Evaluating the Reliability, Coverage, and Added Value of Crowdsourced Traffic Incident Reports from Waze." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 43 (August 8, 2018): 34–43. http://dx.doi.org/10.1177/0361198118790619.
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Traffic managers strive to have the most accurate information on road conditions, normally by using sensors and cameras, to act effectively in response to incidents. The prevalence of crowdsourced traffic information that has become available to traffic managers brings hope and yet raises important questions about the proper strategy for allocating resources to monitoring methods. Although many researchers have indicated the potential value in crowdsourced data, it is crucial to quantitatively explore its validity and coverage as a new source of data. This research studied crowdsourced data from a smartphone navigation application called Waze to identify the characteristics of this social sensor and provide a comparison with some of the common sources of data in traffic management. Moreover, this work quantifies the potential additional coverage that Waze can provide to existing sources of the advanced traffic management system (ATMS). One year of Waze data was compared with the recorded incidents in the Iowa’s ATMS in the same timeframe. Overall, the findings indicated that the crowdsourced data stream from Waze is an invaluable source of information for traffic monitoring with broad coverage (covering 43.2% of ATMS crash and congestion reports), timely reporting (on average 9.8 minutes earlier than a probe-based alternative), and reasonable geographic accuracy. Waze reports currently make significant contributions to incident detection and were found to have potential for further complementing the ATMS coverage of traffic conditions. In addition to these findings, the crowdsourced data evaluation procedure in this work provides researchers with a flexible framework for data evaluation.
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Murray, John, and Yili Liu. "Operator Support in Traffic Management: A Heuristics Model and Experimental Study." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 40, no. 18 (October 1996): 872–76. http://dx.doi.org/10.1177/154193129604001801.
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The identification of problems from numeric traffic measurements is an important part of control center activities in ATMS (Advanced Traffic Management Systems). However, an information modeling process that relies solely upon ‘traditional’ quantitative data analysis does not reflect faithfully the actual methods used by human operators. In addition to common-sense knowledge and specific contextual information, operators also use various heuristics and rules-of-thumb to supplement the numerical analysis. This paper describes an experiment to examine the effectiveness of an expert system that integrates quantitative and qualitative traffic information using a human-centered knowledge system design. The system's performance was investigated using a data suite of real traffic scenarios; the statistically significant results showed that the integrated process had superior performance compared to the ‘traditional’ quantitative analysis running alone.
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Yang, Zhaosheng, Qichun Bing, Ciyun Lin, Nan Yang, and Duo Mei. "Research on Short-Term Traffic Flow Prediction Method Based on Similarity Search of Time Series." Mathematical Problems in Engineering 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/184632.
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Short-time traffic flow prediction is necessary for advanced traffic management system (ATMS) and advanced traveler information system (ATIS). In order to improve the effect of short-term traffic flow prediction, this paper presents a short-term traffic flow multistep prediction method based on similarity search of time series. Firstly, the landmark model is used to represent time series of traffic flow data. Then the input data of prediction model are determined through searching similar time series. Finally, the echo state networks model is used for traffic flow multistep prediction. The performance of the proposed method is measured with expressway traffic flow data collected from loop detectors in Shanghai, China. The experimental results demonstrate that the proposed method can achieve better multistep prediction performance than conventional methods.
Dissertations / Theses on the topic "ATMS (Advanced Text Management System)"
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Hui, Chen I., and 陳怡惠. "A Study On Intelligent Transportation Systems (ITS) Supply Characteristics and Production Value of Advanced Transportation Management System (ATMS)." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/31019686384028618934.
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碩士淡江大學
運輸管理學系
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Due to the global trend of Intelligent Transportation System, this study try to derivative the potential market on ATMS of ITS by focusing on the supply characteristics of ITS. The supply characteristics of ITS are described in the three following items: the supply items, supply abilities of ITS development of Intelligent Transportation Infrastructure (ITI). First, the items of ITS should be carefully defined. In order to, match Taiwan’s transportation characteristics, we try to set the user services by reviewing a great deal of references. Second, we try to realize ITS ’s supply ability on its technologies and constraints through interviewing among industries, government and academic organizations. Third, we try to define the configuration of ITI. As we know, government takes responsible for all transportation infrastructures. But is an inefficient phenomenon for the government without having enough budgets. So we should make use of the goods and system attributes, set the ITI’s supply items. A large part of them is ATMS (Advanced Transportation Management System). The contribution of ITS will bring about development of the related field, and also will increase the production value. Due to the uncertain characteristics of ATMS, the appropriate way to get the Taiwan’s ATMS total production value is by using the concept of micro-production-value-prediction. Furthermore the formulation is established to predict the production value of ATMS. The formulation includes two parts: (1) The infrastructure facility’s production value is measured by total production value which are pulsing by road lengths, the number of intersections and maintenance cost;(2) The control center’s production value are measured by pulsing the setting cost, scale and functional production value, then we try to use the scenario building way to know the level and usage rate in short, mid, and long term of ATMS’s development. Considering two factors of the other city’s ATMS demand index and relative degree of road length, we treat the Taipei’s production value as a basic value. We also evaluate the production values of the other cities. Furthermore, if we take the production value of transportation control centers into considerations, we can get the total production value of Taiwan’s ATMS. From this study, the optimistic production value are 14.7 billions, 42.9 billions and 87 billions for Taipei city of short, mid and long term respectively. From this base, we can get the optimistic production value of short, mid and log term of Taiwan’s ATM production value is 54.5 billions, 226.7 billions and 481.5 billions. These evaluated results can be a suggestion of setting a budget of building ATMS for government.
Books on the topic "ATMS (Advanced Text Management System)"
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Feldman, Ronen. The text mining handbook: Advanced approaches in analyzing unstructured data. Cambridge: Cambridge University Press, 2007.
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1965-, Sanger James, ed. The text mining handbook: Advanced approaches in analyzing unstructured data. New York: Cambridge University Press, 2006.
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Yen, Michael T., ed. Surgery of the Eyelid, Lacrimal System, and Orbit. Oxford University Press, 2011. http://dx.doi.org/10.1093/oso/9780195340211.001.0001.
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Surgery of the Eyelids, Lacrimal System, and Orbit, second edition is a richly illustrated text of oculofacial plastic surgery, with contributions from over 50 nationally and internationally recognized expert authors. Extensively updated from the first edition, this comprehensive text details the evaluation and surgical management of conditions ranging from basic functional eyelid malpositions to complex aesthetic facial reconstructions. It is an excellent resource for those in training as well as seasoned practitioners wanting to be updated on the newest techniques in eyelid, lacrimal, and orbital surgery. The added section in aesthetic surgery includes both surgical and nonsurgical techniques for facial rejuvenation such as botulinum toxin injections, facial fillers, and chemical and laser resurfacing. With over 350 figures, the reader will be able to gain an in-depth understanding and step-by-step instruction of basic and advanced oculofacial plastic surgical procedures. The recognized expert contributing authors provide readers with trusted insight into new and advanced surgical techniques. The text is intuitively organized into functional sections including eyelid malpositions, eyelid reconstruction, lacrimal surgery, orbital surgery, and aesthetic facial surgery. Topics include eyelid lacerations and acute adnexal trauma, clinical presentation of eyelid lesions, management of periocular neoplasms, reconstruction of the lower eyelid, reconstruction of the upper eyelid, reconstruction of canthal defects, management of entropion and trichiasis, management of ectropion and floppy eyelids, management of blepharoptosis, management of eyelid retraction, management of blepharospasm and hemifacial spasm, management of facial palsy, evaluation of the lacrimal system, management of pediatric nasolacrimal duct obstruction, surgery of the lacrimal system, orbital and periorbital fracture, evaluation & spectrum of orbital disease, surgical exploration of the orbit, surgical decompression of the orbit, optic nerve sheath decompression, management of orbital cellulitis, enucleation and evisceration, orbital Exenteration, complications of the anophthalmic socket, rejuvenation of the forehead and eyebrows, upper eyelid blepharoplasty, lower eyelid and midfacial rejuvenation, chemical and laser resurfacing of the eyelids and face, botulinum toxin injections for facial rhytids, soft tissue fillers for facial aesthetics, and face-lifting techniques.
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Boulton, Jill E., Kevin Coughlin, Debra O'Flaherty, and Alfonso Solimano, eds. ACoRN: Acute Care of at-Risk Newborns. 2nd ed. Oxford University Press, 2021. http://dx.doi.org/10.1093/med/9780197525227.001.0001.
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The Acute Care of at-Risk Newborns (ACoRN) program trains health care providers to stabilize that most challenging and enigmatic of medical patients: the unwell newborn. Early assessment, intervention, and management of at-risk or unstable infants can be critical for their survival and long-term health. Clinical care standards and educational programs to address these requirements are needed. The ACoRN program provides a unique, prioritized, and systematic approach to newborn stabilization for health care professionals with any degree of experience. ACoRN-trained providers learn to gather information, prioritize, intervene appropriately, and deliver high quality care to at-risk and unwell newborns in any setting. Because research and practice have advanced dramatically in recent years, the need for a new ACoRN text, the program’s centrepiece, became essential—hence the development of this new edition, which reflects current guidelines and evidence-based best practices. ACoRN teaches the concepts and skills required to stabilize unwell newborns through system-based algorithms (Sequences), each with its own chapter: respiratory, cardiovascular, neurology, surgical conditions, fluid and glucose, jaundice, thermoregulation, and infection. The ACoRN mnemonic defines stabilization steps and chapter structure: alerting signs, core steps, organization of care, response, next steps, and specific diagnosis and management. Each chapter includes educational objectives, key concepts, learning points, and at least one case scenario with questions and answers to reinforce content and learnings. This book is written for any health professional who may be required to participate in the stabilization of sick or preterm babies within their scope of practice.
Book chapters on the topic "ATMS (Advanced Text Management System)"
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Srinivasan, Srividhya, Priya Krishnamoorthy, and Raghuraman Koteeswaran. "Safeguarding of ATM." In Advanced Methodologies and Technologies in Business Operations and Management, 94–105. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-7362-3.ch007.
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An automated teller machine (ATM) is a kiosk that is used widely for money transactions across the globe. Several banking sectors have showed interest in deploying ATMs. The cash dispenser system manages the transaction services with less manual effort. When it comes to deploying an ATM, two methods are practiced: onsite ATM and offsite ATM. Safeguarding cash kept inside the ATM is a challenge. Researchers suggested several built-in security measures to secure the money in ATMs. Nevertheless, burglars still loot the money. Some widely used looting methods include card skimming, cash trapping, and phishing. So, it is time to give intelligence to the ATM itself to react to the situation. Proposed is a system that implements the idea of making machines to identify the situation and perform actions accordingly. This mechanism is not only about giving intelligence to it, but also a cost-effective one.
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H. Suhail, Adeel, Fiseha M. Guangul, and Abdul Nazeer. "Advanced System Diagnostics Tools: Innovations and Applications." In Industrial Engineering and Management. IntechOpen, 2024. http://dx.doi.org/10.5772/intechopen.114378.
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This chapter explores the evolution and significance of advanced diagnostics tools in complex system management, emphasizing the shift toward integrated, intelligent, and predictive diagnostics. It covers the application of artificial intelligence (AI) and machine learning (ML) for predictive maintenance, real-time monitoring, and the integration of sensor technologies with the Internet of Things (IoT). The text examines the use of diagnostic tools in various fields, including mechanical, electrical, software, and network systems, with specific attention to industry applications in automotive, aerospace, and healthcare sectors. These examples illustrate how diagnostics are transforming these industries by enhancing efficiency, safety, and reliability. The chapter also discusses the role of diagnostics in system design, the importance of built-in diagnostics, and the challenges of managing and interpreting the large volumes of data these tools generate. It highlights innovative data analysis and visualization techniques and looks ahead to future trends in diagnostics, such as the potential impact of quantum computing and concerns over cybersecurity and data privacy. Overall, the chapter provides a comprehensive overview of the current state and future directions of advanced system diagnostics.
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Jaurez, James J. "Advanced Feedback Using Dynamic Rubrics, Video, and Audio." In Increasing Productivity and Efficiency in Online Teaching, 264–89. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-5225-0347-7.ch015.
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The advanced Online Grading System (OGS) allows for multimedia input including video, audio, and text along with interactive rubrics. These types of feedback systems can be standalone or integrated into a learning management system. Utilizing a media system can provide deeper engagement and higher quality of grading for students. In this chapter, an integrated grading system was used in order to test the amount of feedback, time to give feedback, and satisfaction for students with multimedia feedback.
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Assal, Hisham, Franz Kurfess, Kym Pohl, Emily Schwarz, and John Seng. "Enhancing Information Extraction with Context and Inference." In Advancing Information Management through Semantic Web Concepts and Ontologies, 195–220. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2494-8.ch011.
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Natural Language Processing (NLP) provides tools to extract explicitly stated information from text documents. These tools include Named Entity Recognition (NER) and Parts-Of-Speech (POS). The extracted information represents discrete entities in the text and some relationships that may exist among them. To perform intelligent analysis on the extracted information a context has to exist in which this information is placed. The context provides an environment to link information that is extracted from multiple documents and offers a big picture of the domain. Analysis can then be provided by adding inference capabilities to the environment. The ODIX platform provides an environment for bringing together information extraction, ontology, and intelligent analysis. The platform design relies on existing NLP tools to provide the information extraction capabilities. It also utilizes a Web crawler to collect text documents from the Web. The context is provided by a domain ontology that is loaded at run time. The ontology offers limited inference capabilities and external intelligent agents offer more advanced reasoning capabilities. User involvement is key to the success of the analysis process. At every step of the process, the user has the opportunity to direct the system, set selection criteria, correct errors, or add additional information.
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Duarte, Cristiane dos Santos, Laura Rossi Rosa, and Eloiza Toledo Bauduina. "Chronic pain due to low back pain and public policies focused on the health area." In INNOVATION IN HEALTH RESEARCH ADVANCING THE BOUNDARIES OF KNOWLEDGE. Seven Editora, 2023. http://dx.doi.org/10.56238/innovhealthknow-006.
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When analyzing one of the most recurrent types of pain, low back pain is one of the most common complaints related to the musculoskeletal system and affects a large part of the population at some point in their lives. In the context of the Unified Health System (SUS), pain is a significant concern. Chronic pain can have a negative effect on individuals' lives, affecting their ability to work, perform daily activities, and enjoy a full life. Thus, this text explores the epidemiological profile of these patients, including information on prevalence, risk factors, associated comorbidities and demographic properties. Chronic low back pain is most common in people between the ages of 30 and 60. It is evident that the incidence and prevalence are higher in females and lower in males. Advanced age, obesity, sedentary lifestyle, smoking, heavy physical labor, and a family history of low back pain are factors that can increase an individual's likelihood of developing this condition. Certain occupations can increase the risk of developing chronic low back pain. Thus, in addition to the direct costs associated with health services, chronic low back pain also generates indirect costs. It is crucial to adopt effective prevention and management strategies to minimize the burden of chronic low back pain for the State, investing in health education programs inside and outside the work environment and promoting the reintegration and adequate professional rehabilitation of affected individuals, bringing benefits both to patients and to the economy in general.
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García, F. J., A. J. Berlanga, and J. García. "A Semantic Learning Objects Authoring Tool." In Encyclopedia of Human Computer Interaction, 504–10. IGI Global, 2006. http://dx.doi.org/10.4018/978-1-59140-562-7.ch075.
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The introduction of computers is recreating a new criterion of differentiation between those who become integrated as a matter of course in the technocratic trend deriving from the daily use of these machines and those who become isolated by not using them. This difference increases when computer science and communications merge to introduce virtual education areas, where the conjunction of teacher and student in the space-time dimension is no longer an essential requirement and where the written text becomes replaced (or rather complemented) by the digital text (García & García, 2005). In order to rescue those educators who have much to offer in an educational system, whether virtual or presential, as authors of teaching resources, suitable authoring tools should be designed, thinking more in the pedagogical process than in the technical aspects. Hypertext Composer, or simply HyCo, is one of these authoring tools, which presents a pedagogical interaction model that makes easier the creation of educational resources for every teacher/author, independently of his or her computer expertise level. At the same time, HyCo is an authoring tool and a retrieval tool, in that it encapsulates all the complexity in handling current tools within the facilities that the author needs and offers, as a result, a hypermedia teaching product that can be distributed in different formats for the user’s access. HyCo has an important semantic basis that nears this tool to the Semantic Web concept (Berners-Lee, Hendler & Lassila, 2001) and allows creating Semantic Learning Objects (SLO) that could be imported for more specialized Learning Management Systems (LMS). In order to achieve the semantic definition of the created educational resources, HyCo uses Learning Technology Standards or Specifications (LTS), looking for obtaining contents that are able to work in other systems (interoperability), follow-up information about learners and contents (manageability), usability in other contexts (reusability), and avoiding obsolescence (durability). This article is devoted to introducing HyCo as an authoring/retrieval tool of SLOs, which presents an interaction model that hides all the technical complexity to the authors but, at same time, offers all the power of semantic definitions in order to publish or use the contents in advanced e-learning environments. The rest of the article is organized as follows: the Background section establishes the background of the presented topic, making a comparison with related works; the HyCo Authoring Tool section presents the HyCo authoring tool; finally, the sections Future Trends and Conclusion provide the future trends and the remarks of the article, respectively.
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Koh, Elizabeth. "Online Education and Cultural Background." In Encyclopedia of Multimedia Technology and Networking, Second Edition, 1080–85. IGI Global, 2009. http://dx.doi.org/10.4018/978-1-60566-014-1.ch146.
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Online education is growing rapidly. Online education is a Web-based form of education where students gain access to online materials and communicate with instructors and other students. There are four distinguishing characteristics that separate it from e-learning and other modes of learning (Paulsen, 2003). First, there is a physical separation of teachers and learners in online education. This differentiates it from face-toface education. Second, online education is regulated or instituted by an educational organization, hence disqualifying it from the self-study mode of learning. Third, educational content is distributed over a computer network, unlike e-learning, which includes educational content distributed by CD-ROMS and DVD-ROMS. Fourth, students and instructors communicate with each other over a computer network. There is a twoway flow of information which is not always available in e-learning. Indeed, the communicative element is a unique feature of online education and is an extension of the individualized experience of earlier technologies (Piccoli, Ahmad, & Ives, 2001). Not solely an interaction between the student and the system, online education allows communication between peers and instructors and even collaborative learning communities. Online education also provides high levels of student control and supports participant contact and interaction continuously during the learning process. There are different levels of “onlineness” (Hosie & Schibeci, 2005). The most basic level is Web supplemented. It is optional for students to interact with the education content, and to communicate with instructors and other students. These online learning resources are a component in addition to their face-to-face learning. The intermediate level is Web dependent. Students need to participate online as part of the course requirement, besides some face-to-face component. Students should utilize the online education content, which includes course descriptions, study guides, examination details, assessment overview, reading lists, and online quizzes. Also, students are expected to interact with lecturers and peers by participating in the online discussion forum or other computer-mediated communications (CMC). This is the most popular form of online education today. The advanced level is fully online. This final level requires no face-to-face meetings with the students. Education content, learning activities, assessment, and support services can only be referred to vis-à-vis the computer network. Distance education could occur in this manner, but the term “distance education” also includes the use of other types of media which may not be electronic. Online education is supported by various systems. The core system in most educational institutes is the learning management system or the virtual learning environment. Learning management systems grant access to online learning resources for students and instructors; they register users, provide communication tools for users, manage courses, evaluate learners, and provide administrative reports (Paulsen, 2003). They can be commercial software like Blackboard or developed in-house. Online education can also require library and digital resources, learner support services, accounting, security, the Internet and e-commerce technology, which may be integrated with the core system Online educational technologies can be categorized into synchronous or asynchronous. Synchronous applications require users to be available at the same time. They include networked group decision support systems (GDSS), e-meetings, e-conferences, and features like whiteboards, text-based chat, and video conferencing. Asynchronous technologies are time independent and comprise discussion boards or Web boards, document repositories, Web logging, podcast audio content, and Web cast lectures.
Conference papers on the topic "ATMS (Advanced Text Management System)"
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Li, Ji-Rui, and Kai Yang. "News clustering system based on text mining." In 2010 IEEE International Conference on Advanced Management Science (ICAMS). IEEE, 2010. http://dx.doi.org/10.1109/icams.2010.5553112.
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Jiang, Delin, Lifeng Lin, Xiaohui Duan, Yiming Lei, and Bingli Jiao. "Campus Lecture System Based on Chinese Text Classification." In 2018 2nd IEEE Advanced Information Management,Communicates, Electronic and Automation Control Conference (IMCEC). IEEE, 2018. http://dx.doi.org/10.1109/imcec.2018.8469695.
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Wei, Qingfeng, Chenxue Zhong, Jun Yu, Changshou Luo, and Lei Chen. "Agricultural Human-Machine Dialogue System Development Based on Semantic and Location Similarity of Short Text Model." In 2018 2nd IEEE Advanced Information Management,Communicates, Electronic and Automation Control Conference (IMCEC). IEEE, 2018. http://dx.doi.org/10.1109/imcec.2018.8469594.
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Groh, Alex, Trevor Olson, Carter Nenninger, Anil Godumagadda, and Evan Corne. "Rules Engine Exchange: Driving Operational Excellence Through an Advanced Real-Time Alerting System." In IADC/SPE International Drilling Conference and Exhibition. SPE, 2022. http://dx.doi.org/10.2118/208755-ms.
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Abstract The purpose of this paper is to discuss the development and application of the Rules Engine Exchange (REX®), an ongoing implementation of a real-time alerting system for onshore drilling operations. REX® is an interactive feature integrated into a company-wide analytics platform where users can create and subscribe to alerts monitoring several data sets. Notifications are delivered via SMS/text, email, and web portal. The system is unique in that it simultaneously utilizes data from electronic drilling recorders (EDR), drilling controls systems, morning reports, and results from real-time models calculated on the rig site. All users can activate pre-written alerts that are quality-controlled by an in-house team of analysts to greater than 95% accuracy. Additionally, any user can write custom, complex alerts written in common programming languages, with minimal training or the need to work with subject matter experts. This platform offers flexibility and speed to users, of varying technical background needing access to high-quality information regarding operational events. Initial work consisted of interviewing key stakeholders and gathering requirements for a real-time alerting system, with end users in the field and supporting office personnel being a primary focus. The system was closely field followed in the beta test phase, with multiple iterations being completed to prepare for production release. The system was deployed to all company departments with one-on-one training of key users and ongoing support as needed. For this paper, the authors have chosen two areas of focus to discuss how REX® impacted operations at the field level: 1) optimal generator usage, to allow operations management to be notified of suboptimal generator management, enabling more fuel-efficient operations and lower greenhouse gas emissions and 2) procedural compliance, to allow company personnel to standardize connection practices and prevent BHA damages while coming on and off bottom. The overall usage and adoption of REX®, impact on the above operations, and lessons learned from the perspective of an onshore drilling contractor are discussed below.
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Chollet, Gérard, Hugues Sansen, Yannis Tevissen, Jérôme Boudy, Mossaab Hariz, Christophe Lohr, and Fathy Yassa. "Privacy Preserving Personal Assistant with On-Device Diarization and Spoken Dialogue System for Home and beyond." In Human Interaction and Emerging Technologies (IHIET-AI 2024). AHFE International, 2024. http://dx.doi.org/10.54941/ahfe1004577.
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In the age of personal voice assistants, we have witnessed the proliferation of "personal" vocal companions across smartphones, smart speakers, and other smart devices. Yet, the question arises: Are these virtual assistants genuinely "personal"? The answer may surprise you. Most of these digital companions lack the ability to remember past interactions or truly understand who you are. They heavily rely on an internet connection to process your spoken words in remote servers. Even though users provide informed consent for these interactions, concerns linger regarding potential misuse of speech data, like invasive targeted advertising. The advent of high-performance co-processors, such as GPUs and TPUs, in modern smartphones has rendered cloud-based speech processing obsolete, paving the way for local, on-device solutions.Personal assistants for the elderly serve a unique role, requiring functionalities distinct from those catering to digital natives. Notably, they must excel at aiding memory recall during conversations, making them invaluable in scenarios like medical examinations. By documenting and contextualizing exchanges during medical visits through diarization, a personal assistant can empower individuals or caregivers to revisit and understand the details at their convenience. This autonomy necessitates operation without an internet connection, ensuring utmost privacy during such sensitive interactions.The e-ViTA project has successfully developed a versatile conversational application with a rich set of features:• Local use on both Android and iOS smartphones, no internet connection required.• The capability to remember previous interactions.• Speaker recognition for personalized experiences.• Local processing for automatic speech recognition, spoken language understanding, dialogue management, and speech synthesis.• Secure web searches after anonymizing requests.• The ability to handle telephone calls, read emails, SMS, and messages.• Text preparation through voice dictation.• Assistance with daily activities and acting as a companion or butler.• Facilitating inter-lingual communication via integration with TalkMondo, among other functions.Unlike facial recognition, vocal recognition, and speaker differentiation provide a less invasive and cost-effective solution. Being based on the smartphone's microphone, they do not rely on the camera, which would necessitate complex mechanisms to track the speaker's position.This paper highlights the critical importance of speaker diarization, which allows the system to preserve users' conversations while ensuring the highest level of privacy. Additionally, when deployed on embedded devices, this technology can contribute to monitoring the well-being of the elderly, offering vital contextual information enriched by domotics sensors (motion, intrusion, door or window sensors), actimetry sensors from smartphones or smartwatches, or weather station. The data fusion of these different data streams leverages more personalized and optimized assistance and services, through user-adapted dialogues, or the elderly based on his context and activity.In conclusion, the ability of a system to generate personalized dialogue synthesis is pivotal in the realm of personal voice assistants. With secure, local processing and advanced features, such as speaker differentiation and diarization, enriched by sensor data fusion, we can ensure that virtual companions truly cater to the individual needs of users, without compromising their privacy or data security. This marks a significant step towards a more "personal" experience with our digital assistants.
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Bhawna, Ahuja, Gandikota Gurunath, Verma Shashwat, and Sharma Yogesh. "Natural Language Processing Based Two-Stage Machine Learning Model for Automatic Mapping of Activity Codes Using Drilling Descriptions." In SPE/IADC Middle East Drilling Technology Conference and Exhibition. SPE, 2023. http://dx.doi.org/10.2118/214522-ms.
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Abstract The daily drilling report (DDR) contains information on daily activities and parameters from the well operations. The inputs are classified using activity codes to evaluate the field performance with improved decision-making. The coding levels support hierarchy in activity code sets. However, it requires information about a substantial number of codes and subcodes. Thus, accurate and consistent identification of codes for operation activities becomes challenging and time-consuming. This work proposes a novel approach to automatically suggest the activity code for drilling activities in well information management system (IMS), with the aim of facilitating the digitization of well operations. We propose a natural language processing (NLP) based two-stage machine learning (ML) model for prediction of activity codes using drilling activities descriptions. The methodology consists of data analysis to identify critical factors for developing ML model. To handle challenges of the diversity of the larger dataset, sampling approach is adopted. Augmentation via contextual embeddings is also explored for minority class. The term frequency-inverse document frequency (TFIDF) is used for feature extraction from text. The classifier is first trained to predict the main activity codes. Predicted main codes in the first stage become the feature space for the second stage training for enhanced accuracy. To improve the accuracy further, related subcodes are grouped according to confusion matrix, performance, and expert advice. This ML model is then integrated with IMS. This method was implemented on a large dataset consisting of 3000+ wells with 1M+ rows. With 70% of the dataset for the training, accuracies achieved for subcode prediction include 66% for the conventional model, 83% for grouped subcode prediction, and 92% for the proposed two-stage grouped subcode prediction. Hence, the proposed model outperforms the conventional model significantly. It is observed that the number of codes/subcodes affects the accuracy. During microservice development, memory requirement and latency are also examined. Increasing tree depths of the ML model after a certain point does not offer significant accuracy improvement though it leads to greater memory requirement and latency. Compression reduces the memory requirement significantly but at increased latency. Hence, an optimal trade-off between accuracy, latency and memory requirement may be attained by selecting model features. It is, therefore, established that the proposed workflow can be used to assist the digitalization of activity code mapping with potential benefits of improving performance, efficiency and reduced manual efforts in database information system for improving efficiency. Novelty of this approach lies in the use of two stage prediction where hierarchical nature of codes is utilized for enhancing accuracy with the help of advanced technologies such as NLP and ML. Grouping of related codes with expert knowledge and performance also provides a realistic solution for reducing the manual efforts.
Reports on the topic "ATMS (Advanced Text Management System)"
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Mears, Brad. Advanced Traffic Management Systems (ATMS) Research Analysis Database System. Fort Belvoir, VA: Defense Technical Information Center, June 2001. http://dx.doi.org/10.21236/ada388177.
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