SITUATION-DEPENDENT METAPHOR FOR PERSONAL MULTIMEDIA INFORMATION

1999 ◽  
Vol 09 (06) ◽  
pp. 725-743 ◽  
Author(s):  
K. PRIYANTHA HEWAGAMAGE ◽  
MASAHITO HIRAKAWA ◽  
TADAO ICHIKAWA
Keyword(s):  
Theoretical Foundation ◽  
Personal Information ◽  
Low Cost ◽  
Contextual Information ◽  
Multimedia Data ◽  
Information Organization ◽  
Digital Data ◽  
Computing Environment ◽  
Novel Approach ◽  
Mobile Computing Environment

Recently available low-cost personal computers and mechanisms to produce digital data have caused a staggering increase in the amount of multimedia data acquired by the user. Hence, the user's personal information space that consists of a large collection of files, may distribute over a number of computers. Situation-dependent metaphor methodology, described in this paper, provides a novel approach to managing such a collection with respect to the context of user's interactions with data. By considering the mobile computing environment, the physical location, time periods and activities are primarily used in modeling the situation metaphor. Sensors and software agents are used in capturing contextual factors automatically. Situation Space describes the theoretical foundation for the situation metaphor based information organization. We also presents our prototype engineered model, Situated Information Filing and Filtering (SIFF), to demonstrate the situation-dependent data management. The SIFF provides the framework for organizing the personal information and developing applications that require contextual information.

Using Context to Discern User Tasks on Desktop

2014 ◽  
Vol 519-520 ◽  
pp. 318-321
Author(s):  
Ning Lv ◽  
Jing Li Zhou ◽  
Lei Hua Qin
Keyword(s):  
Support Vector Machine ◽  
Information Management ◽  
User Behavior ◽  
Personal Information ◽  
Contextual Information ◽  
Support Vector ◽  
Novel Approach ◽  
Information User ◽  
User Tasks ◽  
The Impact

The precise context of user tasks helps to ameliorate personal information management on desktop. This paper introduces a novel approach to discern user tasks using contextual information which is divided into two categories, user behavior based context and text based context. With the contextual information, user tasks are discerned by support vector machine (SVM) method. Experimental results showed the impact of distinct attributes of files on the performance of user task identification.

Location Leveling

2012 ◽  
Vol 4 (4) ◽  
pp. 36-61
Author(s):  
Ayse Yasemin Seydim ◽  
Margaret H. Dunham ◽  
Yu Meng
Keyword(s):  
Software Architecture ◽  
Theoretical Foundation ◽  
Mobile User ◽  
Multidimensional Data ◽  
Location Based Service ◽  
Mobile Unit ◽  
Computing Environment ◽  
Location Service ◽  
Mobile Computing Environment ◽  
Location Dependent Query

Location based service (LBS) is an appealing technology in the pervasive mobile computing environment. In this environment, the answer to a location dependent query depends on the location of the mobile user. However, the location granularity to which the mobile unit is bound by a location service may differ from that stored in the content provider’s database. As a result, a location granularity mismatch occurs. The authors propose a general software architecture, location leveling, to solve this problem. As their layered location leveling solution is independent of the support provided by the wireless provider and the content provider, it is flexible enough to be used by any. The location leveling (ll) model can be implemented as an independent agent or broker in the middleware layer. The proposed approach is developed with solid theoretical foundation found in previous multidimensional data modeling studies.

Experience with Disconnected Operation in a Mobile Computing Environment

1993 ◽  
Author(s):  
M. Satyanarayanan ◽  
James J. Kistler ◽  
Lily B. Mummert ◽  
Maria R. Ebling ◽  
Puneet Kumar
Keyword(s):  
Mobile Computing ◽  
Computing Environment ◽  
Disconnected Operation ◽  
Mobile Computing Environment

scholarly journals HPM: A Hybrid Model for User’s Behavior Prediction Based on N-Gram Parsing and Access Logs

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Sonia Setia ◽  
Verma Jyoti ◽  
Neelam Duhan
Keyword(s):  
Web Mining ◽  
Contextual Information ◽  
Hybrid Approach ◽  
Web Pages ◽  
Continuous Growth ◽  
Novel Approach ◽  
Content Mining ◽  
Long Access ◽  
N Gram ◽  
The Individual

The continuous growth of the World Wide Web has led to the problem of long access delays. To reduce this delay, prefetching techniques have been used to predict the users’ browsing behavior to fetch the web pages before the user explicitly demands that web page. To make near accurate predictions for users’ search behavior is a complex task faced by researchers for many years. For this, various web mining techniques have been used. However, it is observed that either of the methods has its own set of drawbacks. In this paper, a novel approach has been proposed to make a hybrid prediction model that integrates usage mining and content mining techniques to tackle the individual challenges of both these approaches. The proposed method uses N-gram parsing along with the click count of the queries to capture more contextual information as an effort to improve the prediction of web pages. Evaluation of the proposed hybrid approach has been done by using AOL search logs, which shows a 26% increase in precision of prediction and a 10% increase in hit ratio on average as compared to other mining techniques.

scholarly journals Novel approach to enhance coastal habitat and biotope mapping with drone aerial imagery analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
João Gama Monteiro ◽  
Jesús L. Jiménez ◽  
Francesca Gizzi ◽  
Petr Přikryl ◽  
Jonathan S. Lefcheck ◽  
...  
Keyword(s):  
Anthropogenic Impacts ◽  
Spatial Scales ◽  
Low Cost ◽  
Human Populations ◽  
Coastal Habitat ◽  
Coastal Monitoring ◽  
Monitoring Programs ◽  
Novel Approach ◽  
Aerial Platforms ◽  
Rocky Habitats

AbstractUnderstanding the complex factors and mechanisms driving the functioning of coastal ecosystems is vital towards assessing how organisms, ecosystems, and ultimately human populations will cope with the ecological consequences of natural and anthropogenic impacts. Towards this goal, coastal monitoring programs and studies must deliver information on a range of variables and factors, from taxonomic/functional diversity and spatial distribution of habitats, to anthropogenic stress indicators such as land use, fisheries use, and pollution. Effective monitoring programs must therefore integrate observations from different sources and spatial scales to provide a comprehensive view to managers. Here we explore integrating aerial surveys from a low-cost Remotely Piloted Aircraft System (RPAS) with concurrent underwater surveys to deliver a novel approach to coastal monitoring. We: (i) map depth and substrate of shallow rocky habitats, and; (ii) classify the major biotopes associated with these environmental axes; and (iii) combine data from i and ii to assess the likely distribution of common sessile organismal assemblages over the survey area. Finally, we propose a general workflow that can be adapted to different needs and aerial platforms, which can be used as blueprints for further integration of remote-sensing with in situ surveys to produce spatially-explicit biotope maps.

A Novel Approach With Bayesian Networks to Multi-Robot Task Allocation in Dynamic Environments

2021 ◽  
Author(s):  
Ching-Wei Chuang ◽  
Harry H. Cheng
Keyword(s):  
Bayesian Networks ◽  
Task Allocation ◽  
Low Cost ◽  
Dynamic Environments ◽  
Modern World ◽  
Robot System ◽  
Novel Approach ◽  
Robot Systems ◽  
Robot Task ◽  
Multi Robot

Abstract In the modern world, building an autonomous multi-robot system is essential to coordinate and control robots to help humans because using several low-cost robots becomes more robust and efficient than using one expensive, powerful robot to execute tasks to achieve the overall goal of a mission. One research area, multi-robot task allocation (MRTA), becomes substantial in a multi-robot system. Assigning suitable tasks to suitable robots is crucial in coordination, which may directly influence the result of a mission. In the past few decades, although numerous researchers have addressed various algorithms or approaches to solve MRTA problems in different multi-robot systems, it is still difficult to overcome certain challenges, such as dynamic environments, changeable task information, miscellaneous robot abilities, the dynamic condition of a robot, or uncertainties from sensors or actuators. In this paper, we propose a novel approach to handle MRTA problems with Bayesian Networks (BNs) under these challenging circumstances. Our experiments exhibit that the proposed approach may effectively solve real problems in a search-and-rescue mission in centralized, decentralized, and distributed multi-robot systems with real, low-cost robots in dynamic environments. In the future, we will demonstrate that our approach is trainable and can be utilized in a large-scale, complicated environment. Researchers might be able to apply our approach to other applications to explore its extensibility.

LED Light Sources in Organic Synthesis: An Entry to A Novel Approach

2021 ◽  
Vol 18 ◽  
Author(s):  
Aparna Das
Keyword(s):  
Organic Compounds ◽  
Organic Synthesis ◽  
Photochemical Reaction ◽  
Low Cost ◽  
Environmentally Friendly ◽  
Photochemical Reactions ◽  
Light Sources ◽  
Blue Led ◽  
Oxidation Reduction ◽  
Novel Approach

: In recent years, photocatalytic technology has shown great potential as a low-cost, environmentally friendly, and sustainable technology. Compared to other light sources in photochemical reaction, LEDs have advantages in terms of efficiency, power, compatibility, and environmentally-friendly nature. This review highlights the most recent advances in LED-induced photochemical reactions. The effect of white and blue LEDs in reactions such as oxidation, reduction, cycloaddition, isomerization, and sensitization is discussed in detail. No other reviews have been published on the importance of white and blue LED sources in the photocatalysis of organic compounds. Considering all the facts, this review is highly significant and timely.

From Coarse to Fine: An Augmented Reality Based Dynamic Inspection Method for Visualized Railway Routing of Freight Cars

2021 ◽  
Author(s):  
Bing Yi ◽  
Renkai Sun ◽  
Long Liu ◽  
Yongfeng Song ◽  
Yinggui Zhang
Keyword(s):  
Augmented Reality ◽  
High Efficiency ◽  
Low Cost ◽  
Digital Data ◽  
Route Selection ◽  
Inspection Method ◽  
Envelope Model ◽  
Freight Car ◽  
Cargo Transportation ◽  
Selection Of

Abstract It is a challenge for the dynamic inspection of railway route for freight car transporting cargo that out-of-gauge. One possible way is using the inspection frame installed in the inspection train to simulate the whole procedure for cargo transportation, which costs a lot of manpower and material resources as well as time. To overcome the above problem, this paper proposes an augmented reality (AR) based dynamic inspection method for visualized railway routing of freight car with out-of-gauge. First, the envelope model of the dynamic moving train with out-of-gauge cargo is generated by using the orbital spectrum of the railway, and the envelope model is matched with a piece of homemade calibration equipment located on the position of the railway that needs to be inspected. Then, the structure from motion (SFM) algorithm is used to reconstruct the environment where the virtual envelope model occludes the buildings or equipment along the railway. Finally, the distance function is adopted to calculate the distance between the obstacle and the envelope of the freight car with out-of-gauge, determining whether the freight car can pass a certain line. The experimental results show that the proposed method performs well for the route selection of out-of-gauge cargo transportation with low cost, high precision, and high efficiency. Moreover, the digital data of the environments along the railway and the envelope of the freight car can be reused, which will increase the digitalization and intelligence for route selection of out-of-gauge cargo transportation.

Sign in / Sign up

Export Citation Format

Share Document