3225 Chapters
Medium 9781601323200

Ontologies to coordinate multiple views: exploring document collections



Int'l Conf. Artificial Intelligence | ICAI'14 |

Ontologies to coordinate multiple views: exploring document collections

Jorge Marques Prates, Rog´erio Eduardo Garcia, Danilo Medeiros Eler

Departamento de Matem´atica e Computac¸a˜ o – Faculdade de Ciˆencias e Tecnologia

UNESP-Universidade Estadual Paulista “J´ulio de Mesquita Filho”

Presidente Prudente,SP - Brazil jorgemprates@gmail.com, {rogerio,daniloeler}@fct.unesp.br

Abstract—Multiple views of data sets can provide assistance on discovering unforeseen associations among elements contained on these sets. Thus, users are able to explore data in distinct perspectives. Ontologies are formal representations which describe data relations explicitly. Representing the underlying data into ontology, the exploratory visualization can benefit from a semantic representation to create the mappings, and might be helpful to establish relations on multiple views.

In this way, we propose the application of ontology to support the mapping in the coordination process, defining how the data elements are related. Also, we present two case studies applying ontologies on exploring text collections. After these presentation, the results are compared with traditional coordination techniques.

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Medium 9789381159682


Prof. Rachna Sharma and Prof. Sudipto Das Laxmi Publications PDF






Address-depletion is a major concern for the Internet. IPv4 is still widely used as the internet protocol but experts believe that the four billion addresses that could be allocated using the 32-bit

IPv4 address format are all but exhausted now. This situation was happening because government agencies are being allocated multiple large blocks of addresses. Thus, IPv6 came into the scene with an expansion in addressing from 32-bit (4octets) addresses to 128-bit (16 octets) addresses. This could be the answer to all the prayers for more addresses, but it has not become a standard as yet.

The IPv4 protocol could not support real-time audio and video transmissions, and encryption and authentication of data in some applications as well. Another much advanced protocol was overdue. Other interesting facts about IPv6 are the better unicast and broadcasting methods, usage of hexadecimal numbers in the IP address format, and the elimination of decimal dots with the introduction of colons (�:�) as delimiters in the address.

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Medium 9781601323170

An Environment to Promote a Visual Learning of Calculus

Hamid R. Arabnia Azita Bahrami, Leonidas Deligiannidis, George Jandieri, Ashu M. G. Solo, and Fernando G. Tinetti CSREA Press PDF

Int'l Conf. Frontiers in Education: CS and CE | FECS'14 |


An environment to promote a visual learning of Calculus

P. Salinas1, E. Quintero2, and E. González-Mendívil2

Mathematics, ITESM, Monterrey, Nuevo Leon, Mexico


Mathematics, ITESM, Monterrey, Nuevo Leon, Mexico


Abstract - This paper presents a didactical experience taking place at 2012 in a Calculus I course with 24 college students.

The scenario, including the simulation of uniformly accelerated motion over a straight line, is analyzed through a dynamical software. Additional to the simulation, SimCalc educational software allows the graphical interplay between velocity and position graphs, and through this visual perception, the emergence of prediction questions about the motion are promoted. Students should deal with them making use of algebraic and numeric procedures related to linear and quadratic equations. Results make us believe in the potential for the learning of calculus of a new way to deal with the visual perception of graphs, as tools for the mathematical reasoning involving numerical, algebraic and graphical representations of functions involved with the visualization of the motion scenario.

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Medium 9781601322364

SDD: Selective De-Duplication with Index by File Size for Primary File Servers

Hamid R. Arabnia; Leonidas Deligiannidis; Ashu M. G. Solo; and Fernando G. Tinetti (Editors) Mercury Learning and Information PDF

Int'l Conf. Computer Design | CDES'13 |


SDD: Selective De-Duplication with Index by File Size for

Primary File Servers

Hitoshi Kamei1, Tomonori Esaka1, Satoru Kishimoto1, Takayuki Fukatani2,

Takaki Nakamura3 ,and Norihisa Komoda4


Hitachi, Ltd., Yokohama, Kanagawa, Japan


Hitachi Europe Ltd., Bracknell, Berkshire, United Kingdom


Tohoku University, Sendai, Miyagi, Japan


Osaka University, Suita, Osaka, Japan

Abstract – We propose a method, called SDD, for improving performance of file level de-duplication for primary file servers. The processing time of the deduplication is increasing because more and more files are being stored in the servers, therefore the de-duplication process cannot finish during assigned time. According to previous studies, large files stored in the servers are dominant in terms of the storage space, while rather small files are dominant in terms of file count. SDD sets a file size threshold to narrow down target files. We develop and evaluate a prototype system using SDD, which increases the throughput of the de-duplication processes.

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Medium 9781601322548

Robust Model for Vehicle Type Identification in Video Traffic Surveillance

Hamid R. Arabnia; Leonidas Deligiannidis; Joan Lu; Fernando G. Tinetti; Jane You; George Jandieri; Gerald Schaefer; Ashu M. G. Solo; and Vladimir Volkov (Editors) Mercury Learning and Information PDF

Int'l Conf. IP, Comp. Vision, and Pattern Recognition | IPCV'13 |


Robust Model for Vehicle Type Identification in Video Traffic


Rensso Mora Colque1 and Guillermo Camara Chavez2

1 Computer Science Department, Universidad Catolica San Pablo, Arequipa, Peru

2 Computer Science Department, Ouro Preto, Minas-Gerais, Brazil

Abstract— Vehicle classification is an inherently difficult problem. Most of researches for vehicle type recognition use images where there are only one vehicle in restricted conditions. In traffic surveillance videos have many different conditions, which increase the degree of difficulty in recognizing the type of vehicle. Thus, the various restrictions in the conventional models make them limited, creating the need of sophisticated models that combine segmentation techniques that allow to extract the information needed to recognize a vehicle within a complex scenario. This work presents a model for vehicle type recognition in traffic surveillance videos. The main obstacle in this kind of videos is the great quantity of information and the constantly variations in the scene. This work presents a model based on local features.

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