Comparison of the Effects Stemmer Porter and Nazief-Adriani on the Performance of Winnowing Algorithms for Measuring Plagiarism- - Alam Rahmatulloh; Neng Ika Kurniati; Irfan Darmawan; Adi Zaenal Asyikin; Deden Witarsyah (Journal of Digital Information Management, 2020)
Current technological developments change physical paper patterns into digital, which has a very high impact. Positive impact because paper waste is reduced, on the other hand, the rampant copying of digital data raises the amount of plagiarism that is increasing. At present, there are many efforts made by experts to overcome the problem of plagiarism, one of which is by utilizing the winnowing algorithm as a tool to detect plagiarism data. In its development, many optimizing winnowing algorithms used stemming techniques. The most widely used stemmer algorithms include stemmer porter and nazief-adriani. However, there has not been a discussion on the comparison of the effect of performance using stemmer on the winnowing algorithm in measuring the value of plagiarism. So it is necessary to do research on the effect of stemmer algorithms on winnowing algorithms so that the results of plagiarism detection are more optimal. The results of this study indicate that the effect of nazief-adriani stemmer on the winnowing algorithm is superior to the stemmer porter, only decreasing the detection performance of the 0.28% similarity value while the porter stemmer is superior in increasing the processing time to 69% faster.

Query Expansion in Text Information Retrieval with Local Context and Distributional Model- - Fabiano Tavares da Silva; José E. B. Maia (Journal of Digital Information Management, 2020)
The Semantic Distributional Model is based on the frequency of contexts of use of language terms in large open corpus such as the web, to establish similarity or the relationship between words. These relationships or similarities can be used to add terms when expanding queries. The idea explored in this paper is that, for queries in closed collections of text documents, a posterior filter based on the restricted vocabulary of the collection can improve the effectiveness of automatic query expansion. This idea is developed and evaluated in publicly available benchmarks presenting promising results.

Corpus-Based Techniques for Sentiment Lexicon Generation: A Review- - Mohammad Darwich; Shahrul Azman Mohd Noah; Nazlia Omar; Nurul Aida Osman (Journal of Digital Information Management, 2019)
State-of-the-art sentiment analysis systems rely on a sentiment lexicon, which is the most essential feature that drives their performance. This resource is indispensable for, and greatly contributes to, sentiment analysis tasks. This is evident in the emergence of a large volume of research devoted to the development of automated sentiment lexicon generation algorithms. The task of tagging subjective words with a semantic orientation comprises two core approaches: dictionarybased and corpus-based. The former involves making use of an online dictionary to tag words, while the latter relies on co-occurrence statistics or syntactic patterns embedded in text corpora. The end result is a linguistic resource comprising a priori information about words, across the semantic dimension of sentiment. This paper provides a survey on the most prominent research works that utilize corpus-based techniques for sentiment lexicon generation. We also conduct a comparative analysis on the performance of state-of-the-art algorithms proposed for this task, and shed light on the current progress and challenges in this area.

Applied Management Support for an Efficient WSN Infrastructure - Nilayam Kumar Kamila; Sunil Dhal; Bhagirathi Nayak (Journal of Networking Technology, 2018)
There are many management applications such as disaster management, air pollution management, weather management, traffic control management etc. which requires continuous attentions and prompt actions. Inclusion of theory of management support and timely decision to any un-managed system will improve the performance, usability and sustainability. Wireless Sensor Network is a self build infrastructure which deployed on the areas where there is no continuous power supply to the sensor nodes. There are many researches and approach has been proposed and protocols designed to address the network performance. We analyzed and identified the issue areas where management support and timely organized decisions improve the wireless sensor network performance. We categorized the system based on levels of management and presented our proposed protocols in all levels with process flow and performance comparisons through our simulation models.

Are Two Emotion States Distinguishable From Each Other? An Alternative Study - Anilesh Dey; Purnendu B. Acharjee; Tanushrre Ghosh; Pompy R Gogoi (Signals and Telecommunication Journal, 2018)

From Words to Emoticons: Deep Emotion Recognition in Text and Its Wider Implications - Rafal Rzepka; Mitsuru Takizawa; Jordi Vallverdu; Michal Ptaszynski; Pawel Dybala; Kenji Araki (International Journal of Computational Linguistics Research, 2018)

Fusion Model for Traffic Sign Detection, Tracking and Recognition - Hubham Dhingra; Shalini Diwakar; G. Saranya; Manish Kumar (Journal of Electronic Systems, 2018)

A Hybrid Feature Selection Algorithm Based on Information Gain and Sequential Forward Floating Search - Jianli Ding; Liyang Fu (Journal of Intelligent Computing, 2018)

Mathematical Formulation for Programmers to Select Background and Foreground Colors in Designing Websites - Veeresh Duvvuri; Srinivas Laggoni; Shankar Karinga (International Journal of Web Applications, 2018)

NDSOM: Self Organizing Maps Learning Approach to Extract Noisy Data - Vikas Chaudhary; Mesfin Jariso Delbu; R. S. Bhatia (Journal of Intelligent Computing, 2018)

Non-words Spell Corrector of Social Media Data in Message Filtering Systems - Zar Zar Wint; Théo Ducros; Masayoshi Aritsugi (Journal of Digital Information Management, 2018)

A Novel Framework for Context-aware Outlier Detection in Big Data Streams- - Hussien Ahmad; Salah Dowaji (Journal of Digital Information Management, 2018)

A Novel Framework for Context-aware Outlier Detection in Big Data Streams- - Hussien Ahmad; Salah Dowaji (Journal of Digital Information Management, 2018)
Outlier and anomaly detection has always been a critical problem in many fields. Although it has been investigated deeply in data mining, the problem has become more difficult and critical in the Big Data era since the volume, velocity and variety of data change drastically with rather complicated types of outliers. In such an environment, where real-time outlier detection and analysis over data streams is a necessity, the existing solutions are no longer effective and sufficient. While many existing algorithms and approaches consider the content of the data stream, there are few approaches which consider the context and conditions in which the content has been produced. In this paper, we propose a novel framework for contextual outlier detection in big data streams which inject the contextual attributes in the stream content as a primary input for outlier detection rather than using the stream content alone or applying the contextual detection on content anomalies only. The detection algorithm incorporates two approaches; the first, a supervised detection method and the other, an unsupervised, which allows the detection process to adapt to the normal change in the stream behavior over time. The detected outliers are either both content and contextual outliers or contextual outliers only. The proposed contextual detection approach prunes the false positive outliers and detects the true negative outliers at the same time. Moreover, in this framework, the detection engine preserves both outliers and context values in which those outliers were detected to be used in the engine self-training and in outliers modeling in order to enhance the outlier prediction accuracy.

Value Driven Management of Cloud Services - Salah Eddin Murad; Salah Dowaji (International Journal of Web Applications, 2018)

Building consistent UML models for better model driven engineering - Allaki, D.; Dahchour, M.; En-nouaary, A. (Journal of Digital Information Management, 2017)

Improved digital image restoration algorithm based on Criminisi - Dai, L.; Jiang, D.-H.; Ding, B.; Hahn, J.K. (Journal of Digital Information Management, 2016)

A web service-based approach to integrated information management for railway emergency scenario - Zhang, Z.-H.; Xu, Z.-L.; Zhang, Y.-P.; Dang, J.-W.; Shen, L.-X. (Journal of Digital Information Management, 2016)

A 3D audio augmented reality system for a cultural heritage management and fruition - D'Auria, D.; Di Mauro, D.; Calandra, D.M.; Cutugno, F. (Journal of Digital Information Management, 2015)

Construction and application of teaching file management system in institutions of higher learning based on OpenKM - Deng, H. (Journal of Digital Information Management, 2015)

An improved classification scheme with adaptive region growing and Wishart classification algorithm for digital images - Chen, J.; Du, P.; Tan, K.; Borjer, T.H. (Journal of Digital Information Management, 2015)

Paper hijacking: Hijackers are attacking journals for hijacking unpublished papers - Dadkhah, M. (Journal of Digital Information Management, 2015)

Power station flue gas desulfurization system based on automatic online monitoring platform - Liu, X.; Ma, C.; Yang, X.; Yang, C.; Diao, Y. (Journal of Digital Information Management, 2015)

Providing mobile traffic analysis as-a-Service: Design of a service-based infrastructure to offer high-accuracy traffic classifiers based on hardware accelerators - Barbareschi, M.; De Benedictis, A.; Mazzeo, A.; Vespoli, A. (Journal of Digital Information Management, 2015)

Parameters selection in the discrete particle swarm optimization algorithm solving gate and runway combinational optimization problem - Ding, J.; Zhang, Y. (Journal of Digital Information Management, 2013)
Gate and runway combinational optimization (GRCO) problem is of great significance in airport operation. In this paper, experimental analysis is performed on the parameters characteristics of the discrete particle swarm optimization (DPSO) algorithm for combinatorial optimization problems. Inertia weight, acceleration constants and population size all have an important impact on the performance of the algorithm. Optimal values exist in the specific application of the respective parameters. The optimal value interval of the population size does not vary with different acceleration constants when inertia weight is constant. Increasing the population size can improve the solution quality, but the time overhead increases significantly. Finally, each parameters selection guidelines are provided.
Keywords: Airport operation; Discrete particle swarm optimization; Gate and runway combinational optimization; Parameters selection

Creating multi-level class hierarchy for question classification with NP analysis and wordnet - Bakhtyar, M.; Kawtrakul, A.; Baber, J.; Doudpota, S.M. (Journal of Digital Information Management, 2012)
Question answering systems provide answer to the questions using various question processing techniques and extracts answers from a set of documents. Finding the exact answer is more interesting and useful than getting a list of documents to look through and find the answer manually. Question answering is not same as a traditional document retrieval search engine where a set of relevant documents are returned in response of the query, whereas, in the question answering systems the response of the query is a concise and exact answer to the question. Typically, Question Classification (QC) is the first step in a Question Answering (QA) system. This phase is responsible for finding out the type of the expected answer by pruning out the extra information that is not relevant to extract the answer. Almost all the previous QC algorithms evaluated their work on the basis of a common class hierarchy already defined. The coarse grained classes Location, Entity and Numeric in the existing hierarchy have a fine grained class Other. We present the framework to create new fine grained classes to replace the Other classes. We also discuss the motivation behind the replacement and how the new fine grained classes may support the answer extraction. Additionally, we also present an automatic hierarchy creation method to add new class nodes using WordNet and Noun phrase parsing.
Keywords: Meta Information Management; Natural Language Processing; Question Answering4; Question Class Hierarchy; Question Classification

A novel RDB-SW approach for commodities price dynamic trend analysis based on web mining - Zhu, Q.; Zhou, P.; Cao, S.; Yan, Y.; Ding, J. (Journal of Digital Information Management, 2012)
In order to improve the accuracy of price forecasting for dynamic trend analysis on imperfect data by web extracting, a novel repair data algorithm based on dichotomy backfilling is proposed in this paper. The price forecasting algorithm based on the Sliding Window (SW) is utilized to verify the validity of Repair Dichotomy Backfilling (RDB) algorithm. Experiments demonstrated that the mean absolute errors can be achieved to 5.31 percent average. Furthermore, the price forecasting algorithm based on original data and that based on RDB data are explored to compare their accuracy. Experiments demonstrated the reduction of mean absolute errors in the price dynamic trend analysis verification model. The average MAE on original data is 2.38 percent when the average MAE on RDB data is 2.31 percent. Experiment results proved that the proposed RDB-SW approach is meaningful and useful to analyze and to research the price market on imperfect data by Web extracting.
Cited By (since 1996):5Export Date: 10 July 2014
Keywords: Dichotomy backfilling; Disturbance factor; Imperfect data; Price forecast algorithm; Sliding window

A survey on data migration management in cloud environment - Hu, L.; Zhao, J.; Xu, G.; Ding, Y.; Chu, J. (Journal of Digital Information Management, 2012)
Cloud computing has become a hot technology. The virtualization technology, one of its core support technologies, is also developing quickly. In recent years, a lot of research and practice have been done in the virtualization field. Live virtual machine migration has drawn much attention as a representative technology of the virtualization field. This paper summarizes the research progress of live virtual machine migration technology including pre-copy, post-copy and CR/TR-Motion analyzes the future research trend.
Keywords: Cloud computing; Live migration; Virtual machine; Virtualization

True: A trust evaluation service for mobile ad hoc networks resistant to malicious attacks - Da Silva, E.; Misaghi, M.; Albini, L.C.P. (Journal of Digital Information Management, 2012)
Trust evaluation is an essential service to ensure reliability on security relationships on networks, including Mobile Ad Hoc Networks (MANETs). However, the implementation of an effective trust evaluation service is very difficult in these networks, due to their dynamic characteristics. Though many trust evaluation services for MANETs can be found in the literature, they were not designed considering malicious attacks or were not evaluated under these attacks. This work presents TRUE, a distributed trust evaluation service for MANETs which creates a self-organized context-based trust network. To estimate the trustworthiness of other nodes, nodes form trust chains based on behavior evidences maintained within the context-based trust network. Periodically, nodes exchange trust information with the neighbors, providing an efficient method to disseminate these information through the network. Simulation results show that TRUE is very efficient on gathering evidences to build the trust networks, maintaining a small communication and memory overhead. Further, it is the first trust evaluation scheme evaluated under bad mouthing and newcomers attacks and it maintains its effectiveness in such scenarios.
Keywords: Attacks; MANETs; Security; Selforganization; Trust evaluation

University teachers' performance appraisals model based on DEA and AHP - Bei, W.; Dongsheng, L. (Journal of Digital Information Management, 2012)
The university teachers' performance appraisals model decides the development of scientific research. And a set of scientific, reasonable and comprehensive model is the premise and foundation to evaluate it. First, this article analyses the domestic and foreign university teachers' performance appraisals model. Second, it combines the current teachers' performance appraisals theory and practice research, and discusses the questionnaire suitable for the university teachers' performance appraisals model in our country. Third, through the questionnaire data analysis, the paper uses factor-analysis-method to screen indexes. Fourth, the paper uses AHP method and calculates the index weights for all levels. Finally, the paper establishes the university teachers' performance appraisals index model based on DEA.
Keywords: AHP; Index system; Performance appraisals; Quantization

An ontology-based approach for detecting knowledge intensive tasks - Rath, A.S.; Devaurs, D.; Lindstaedt, S.N. (Journal of Digital Information Management, 2011)
In the context detection field, an important challenge is automatically detecting the user's task, for providing contextualized and personalized user support. Several approaches have been proposed to perform task classification, all advocating the window title as the best discriminative feature. In this paper we present a new ontology-based task detection approach, and evaluate it against previous work. We show that knowledge intensive tasks cannot be accurately classified using only the window title. We argue that our approach allows classifying such tasks better, by providing feature combinations that can adapt to the domain and the degree of freedom in task execution.
Cited By (since 1996):2Export Date: 10 July 2014
Keywords: Classification; Context-awareness; Task detection; User context detection; User context ontology

The performance analysis of a service deployment system based on the centralized storage - Dong, Z.X. (Journal of Digital Information Management, 2011)
Because of its data centralized management characteristic, which conveniently realize resources sharing and the data fast clone, the service deployment technology based on the centralized storage can achieve fast deployment for the system service through the network boot methed or the method of downloading disk image from the remote storage server. However, for the data centralism the I/O load is also congested on the storage server, which creates the drop of the overall system performance and the reducing of the service quality. So we need to test and analyze its performance factors, which provide the clue for the solution of the performance bottleneck. In this paper, we use the SonD deployment system, which is based on the centralized storage, as the analysis prototype to carry on the analysis to the client boot process, evaluate its performance influence factors such as the memory size of storage server, data distribution on the storage server through the real or simulated method, and give suggestion of the performance optimized.
Keywords: Centralized Storage; Performance Analysis; Service Deployment

A semantic annotation model for indexing and retrieving learning objects - Smine, B.; Faiz, R.; Desclés, J.-P. (Journal of Digital Information Management, 2011)
The internet is an important part of our world. Offering a large and increasing amount of information, people can use it for learning, teaching, etc. Automatic tools for learning information retrieval based on semantic tags have not been effective yet. We propose here a model which aims at automatically annotating texts with semantic metadata. These metadata would allow us to index and extract learning objects from texts. This model is composed of two parts. While the first part consists of a semantic annotation of learning objects according to their categories (definition, example, exercise, etc.), the second one uses automatic semantic annotation. Generated by the first part, the latter aims at creating a semantic inverted index able to find relevant learning objects for queries. To sort the results according to their relevance, we apply the Rocchio's classification technique to the learning objects. We have implemented a system called SRIDoP, on the basis of the proposed model and we have verified its effectiveness.
Cited By (since 1996):1Export Date: 10 July 2014
Keywords: Contextual exploration; Learning objects; Rocchio algorithm; Semantic annotation

Bidirectional recommendation technology for web digital texts - Wada, Y.; Matsuzawa, S.; Yamaguchi, M.; Dohi, S. (Journal of Digital Information Management, 2010)
Recently, e-learning systems have begun to be used in companies and education institutions. The spread of e-learning is mainly due to development of the learning management system (LMS), which includes SCORM and WebCT. Therefore, the introduction of learning the web digital web digital texts have become much simpler. The increase of contents of the web digital texts has realized a wider range of learning. As a result, we are concerned that learners will be confused with selecting the best learning web digital texts. In our research, we are developing a bidirectional recommendation system that extracts the relationship among learning the web digital texts with historical logs and recommends an effective web digital text for learners. In this paper, we first discuss the design of the bidirectional recommendation system, and second, we show its evaluation results. Finally, we conclude that our recommendation system is useful for learners.
Keywords: Bidirectional recommendation; Collaborative filtering

Editorial preface: Special issue on context-aware and mobile multimedia databases and services - Grigoras, R.; Charvillat, V.; Chbeir, R.; Kosch, H.; Bailer, W.; Boll, S.; Brunie, L.; Cao, Y.; Delgado, J.; Granitzer, M.; Hausenblas, M.; Eidenberger, H.; et al. (Journal of Digital Information Management, 2010)

Exploiting multi-word similarity for retrieval in medical document collections: The TSRM approach - Drymonas, E.; Zervanou, K.; Petrakis, E.G.M. (Journal of Digital Information Management, 2010)
In this paper, we investigate on potential improvements to Information Retrieval (IR) models related to document representation and conceptual, topic retrieval, in medical document collections. We propose the TSRM1 (Term Similarity and Retrieval Model) approach, where document representations are based on multi-word domain terms, rather than mere single key-words, typically applied in traditional IR. The proposed representation is semantically compact and more efficient, being reduced to a limited number of meaningful multi-word terms (phrases), rather than large vectors of single-words, part of which may be void of distinctive content semantics. In computing document similarity, contrary to other state-of-theart methods examined in this work, TSRM adopts a knowledge poor solution, namely an approach which does not require any existing knowledge resources, such as ontologies, or thesauri. The evaluation of TSRM is based on OHSUMED, a standard TREC collection of medical documents and illustrated the effciency of TSRM over other well established general purpose IR models.
Cited By (since 1996):1Export Date: 10 July 2014
Keywords: Document representation; Information retrieval; Medical information retrieval; Term extraction; Term Similarity

A MPEG-based architecture for generic distributed multimedia scenarios - Carreras, A.; Tous, R.; Rodríguez, E.; Delgado, J.; Cordara, G.; Francini, G.; Gibellino, D. (Journal of Digital Information Management, 2010)
This paper presents a standards-based architecture for a complex and generic distributed multimedia scenario, which combines content search and retrieval, DRM, and context-based content adaptation together. It is an innovative and totally generic approach trying to narrow the semantic-gap by integrating a fl exible language for multimedia search based on MPEG Query Format (MPQF) standard with the application of video analysis algorithms for the automatic extraction of low level features and with the use of contextual information.
Keywords: Context-based adaptation; Digital Rights Management-Rights Expression Language; Features extraction; MPEG query format

A generic context model enhanced with self-configuring features - Cioara, T.; Anghel, L.; Salomie, L.; Dinsoreanu, M. (Journal of Digital Information Management, 2009)
This paper addresses two fundamental research problems in the domain of context aware autonomic systems: the development of a generic context model that can be used to represent general purpose contexts in a system interpretable way and the autonomic context model management. The proposed context model uses two equivalent and synchronized ways of representing the context: a set based representation and an ontology based representation. The set based representation is used to evaluate the conditions under which the self-* processes should be executed in order to enforce the autonomic properties. The ontology representation is used by context aware applications for reasoning and learning purposes. The increasing complexity of execution environments of the context aware systems and the difficulties of their management have headed us towards the necessity of defining and integrating the self-configuring autonomic paradigm in the context model management process. The self-configuring property is enforced by monitoring the real world context in order to detect context variations or conditions for which the context artifacts must be updated.
Cited By (since 1996):3Export Date: 10 July 2014
Keywords: Autonomic computing; Context awareness; Pervasive middleware; Self-configuring

Machine learning based work task classification - Granitzer, M.; Rath, A.S.; Kröll, M.; Seifert, C.; Ipsmiller, D.; Devaurs, D.; Weber, N.; Lindstaedt, S. (Journal of Digital Information Management, 2009)
Increasing the productivity of a knowledge worker via intelligent applications requires the identification of a user's current work task, i.e. the current work context a user resides in. In this work we present and evaluate machine learning based work task detection methods. By viewing a work task as sequence of digital interaction patterns of mouse clicks and key strokes, we present (i) a methodology for recording those user interactions and (ii) an in-depth analysis of supervised classification models for classifying work tasks in two different scenarios: a task centric scenario and a user centric scenario. We analyze different supervised classification models, feature types and feature selection methods on a laboratory as well as a real world data set. Results show satisfiable accuracy and high user acceptance by using relatively simple types of features.
Cited By (since 1996):6Export Date: 10 July 2014
Keywords: Data model; Data structure; Work task classification user interaction

Citation auctions as a method to improve selection of scientific papers - De La Rosa, J.L.; Szymanski, B.K. (Journal of Digital Information Management, 2008)
This paper describes the basis of citation auctions that are introduced as a new approach to selecting scientific papers for publication. Unlike the state of the art in paper selection that relies on peer reviews, our main idea is to use an auction in which bids consist of the number of citations that an author expects to receive if the paper is published. Hence, a citation auction is the selection process itself, and no reviewers are involved. The benefits of the proposed approach are two-fold. First, the cost of refereeing will be either totally eliminated or significantly reduced, because the process of citation auction does not need prior understanding of the paper's content to judge the quality of its contribution. Additionally, the method does not prejudge the content of the paper, so it will increase the openness of publications to new ideas. Second, scientists will be much more committed to the quality of their submitted papers, paying close attention to distributing and explaining their papers in detail to maximize the number of citations that the paper receives when published. Sample analyses of the number of citations collected via Google scholar for papers published in years 1999-2004 in a series of proceedings, and in years 2003-2005 in a series of conferences (in a totally different discipline) are provided. Finally, a simple simulation of an auction is given to outline the behaviour of the citation auction approach.

Map integrity constraint verification by using visual language parsing - Del Fatto, V.; Deufemia, V.; Paolino, L. (Journal of Digital Information Management, 2008)
In the last decade there has been an increasing interest in the use of tools for the creation of geographic maps. However, these tools include functionalities that allow users to insert information without verifying their consistency with the constraints defined by the designer. In this paper we propose an approach based on visual language parsing for guaranteeing the integrity of data produced during the map editing process. According to our approach, constraints are expressed by using high-level data model, such as OMT-G, and converted in a proper visual language grammar automatically. From such a grammar, a parser able to identify incorrect aggregation of spatial data input is generated. The grammar formalism also allows us to associate suitable semantic actions with productions in order to perform automatic corrections of inconsistent input data, error recognition and visualization, prompting actions for error recovery. We also present a system prototype supporting the proposed process.
Keywords: Data Quality; Grammar Formalism; Integrity Constraint Checking; Spatial Consistency; Topologicalrelationships; Visual Language Parsing

Map integrity constraint verification by using visual language parsing - Fatto, V.D.; Deufemia, V.; Paolino, L. (Journal of Digital Information Management, 2008)
In the last decade there has been an increasing interest in the use of tools for the creation of geographic maps. However, these tools include functionalities that allow users to insert information without verifying their consistency with the constraints defined by the designer. In this paper we propose an approach based on visual language parsing for guaranteeing the integrity of data produced during the map editing process. According to our approach, constraints are expressed by using high-level data model, such as OMT-G, and converted in a proper visual language grammar automatically. From such a grammar, a parser able to identify incorrect aggregation of spatial data input is generated. The grammar formalism also allows us to associate suitable semantic actions with productions in order to perform automatic corrections of inconsistent input data, error recognition and visualization, prompting actions for error recovery. We also present a system prototype supporting the proposed process.
Keywords: Data Quality; Grammar Formalism; Integrity Constraint Checking; Spatial Consistency; Topological Relationships; Visual Language Parsing

Robust video watermarking based on dual-plane correlation for immunity to rotation, scale, translation, and random distortion - Atomori, Y.; Echizen, I.; Dainaka, M.; Nakayama, S.; Yoshiura, H. (Journal of Digital Information Management, 2008)
A robust video watermarking method is described that can embed watermarks immune to not only rotation, scaling, and translation but also to random geometric distortion and any of their combinations. It can detect watermarks without any search for canceling the effect of random distortion. Rotation, scale, and translation are canceled by searching for the angle, size, and origin of the original picture. The search for the angle and size is combinatorial but is independent of the search for the origin. That is, the angle and size of the target picture can be restored without restoring the picture's origin. Furthermore, the search for the origin is divided into horizontal and vertical searches that can be carried out independently. The number of searches is thus drastically reduced, making the processing speed high enough for practical application. Experimental evaluation using actual video samples demonstrated that the proposed method can embed watermarks immune to all four types of transformations.
Cited By (since 1996):5Export Date: 10 July 2014
Keywords: Random distortion; RST; Survivability; Video watermarking

Standardized multimedia retrieval based on web service technologies and the MPEG query format - D'Oller, M.; Bauer, K.; Kosch, H.; Gruhne, M. (Journal of Digital Information Management, 2008)
In recent years, the growing number of digital audiovisual media files available over the internet or even on users hard discs is overwhelming. In order to support efficient storage and retrieval of those data, several comprehensive and rich multimedia retrieval systems (MMRS) have been introduced. Unfortunately, a standardized query format does not yet exist and almost every retrieval framework provides its own proprietary solution. Therefore, the ISO/IEC SC29 WG11 committee decided to contribute to this application by establishing the MPEG Query Format (MPQF). The MPQF is currently in Final Committee Draft (FCD) status and provides besides the standardization of messages from and to multimedia services also functionalities for service discovery, aggregated services and definition of service capability descriptions. In this context, the paper briefly introduces the MPQF and concentrates thereby on the management part. Based on this, a Web Service based framework is presented that realizes the management functionalities of MPQF. One of its central novel features is the distribution of a MPQF request to multiple multimedia services and the aggregation of individual result sets.
Cited By (since 1996):6Export Date: 10 July 2014
Keywords: Audio visual media; ISO multimedia standards; MPEG query format

Impact of node mobility on MANET routing protocols models - Divecha, B.; Abraham, A.; Grosan, C.; Sanyal, S. (Journal of Digital Information Management, 2007)
A Mobile Ad-Hoc Network (MANET) is a self-configuring network of mobile nodes connected by wireless links to form an arbitrary topology without the use of existing infrastructure. In this paper, we have studied the effects of various mobility models on the performance of two routing protocols Dynamic Source Routing (DSR-Reactive Protocol) and Destination-Sequenced Distance-Vector (DSDV-Proactive Protocol). For experiment purposes, we have considered four mobility scenarios: Random Waypoint, Group Mobility, Freeway and Manhattan models. These four Mobility Models are selected to represent possibility of practical application in future. Performance comparison has also been conducted across varying node densities and number of hops. Experiment results illustrate that performance of the routing protocol varies across different mobility models, node densities and length of data paths.
Cited By (since 1996):36Export Date: 10 July 2014
Keywords: MANET; Mobile adhoc networks; Mobility models

A non reference fingerpint image validity via statistical weight calculation - Altarawneh, M.S.; Khor, L.C.; Woo, W.L.; Dlay, S.S. (Journal of Digital Information Management, 2007)
Clarity of fingerprint image structure is crucial for many fingerprint applications, as well as the performance of built systems which relies on the validity and quality of captured images. Validity check will eliminate invalid images before starting the life cycle of fingerprint metadata enrolling for system processing cycle; therefore the overall benchmarking system accuracy will not be affected by rejecting an invalid image before getting in the system cycle. In this paper we propose a validity check algorithm (VCA). The VCA is applied to the base image eiement statistical weight calculation because the image element (pixel) describes an image object with the contrast, brightness, clarity and noising attributes. Our algorithm depends on fingerprint object segmentation, background subtraction, total image thresholding and pixel weight calculation. A VTC200ODB1_B, TIMA databases was used to evaluate the VCA and it has been compared with NIST fingerprint image quality results. Correlation results indicate that the proposed algorithm is feasible in detecting low quality as well as non-fingerprint images.
Keywords: Fingerprint; Image quality; Image subtraction; Otsu threshold; Segmentation

Social search with missing data: Which ranking algorithm? - Zhu, J.; Eisenstadt, M.; Gonçalves, A.; Denham, C.; Uren, V.; Song, D. (Journal of Digital Information Management, 2007)
Online social networking tools are extremely popular, but can miss potential discoveries latent in the social 'fabric'. Matchmaking services which can do naive profile matching with old database technology are too brittle in the absence of key data, and even modern ontological markup, though powerful, can be onerous at data-input time. In this paper, we present a system called BuddyFinder which can automatically identify buddies who can best match a user's search requirements specified in a term-based query, even in the absence of stored user-profiles. We deploy and compare five statistical measures, namely, our own CORDER, mutual information (MI), phi-squared, improved MI and Z score, and two TF/IDF based baseline methods to find online users who best match the search requirements based on 'inferred profiles' of these users in the form of scavenged web pages. These measures identify statistically significant relationships between online users and a term-based query. Our user evaluation on two groups of users shows that BuddyFinder can find users highly relevant to search queries, and that CORDER achieved the best average ranking correlations among all seven algorithms and improved the performance of both baseline methods.
Keywords: Instant messaging; Ranking algorithms; Relation discovery; Social software

A method for incorporating user modelling - de Vrieze, P.; van Bommel, P.; van der Weide, T. (Journal of Digital Information Management, 2006)
In this paper a method is presented for adding user modelling to (existing) software systems. The method consists of seven steps that lead from initial analysis to the definition and evaluation of the elements needed for the adaptive behaviour. Along with the method, the central concepts of adaptation elements and adaptation graphs are introduced. An adaptation element can be used to determine the impact of personalisations, while adaptation graphs describe the adaptation in a system as a whole.
Keywords: Adaptation graphs; Adaptive hyper media; Software systems; User modeling techniques

Semantic indexing and hyperlinking of multimedia news: The RitroveRAI system - Basili, R.; Cammisa, M.; Donati, E.; Moschitti, A. (Journal of Digital Information Management, 2006)
Web services tend to offer functional and non-functional requirements and capabilities in an agreed, machine-readable format. The target is to provide automated services for discovering, selection and binding of information as a native capability of middleware and applications. However, the major limitations are due to the lack of clear and processable semantics. In this paper, a system, RitroveRAI, addressing the general problem of enriching a multimedia news stream with semantic metadata is presented. News metadata are explicitly derived from transcribed sentences or implicitly expressed into a topical category automatically detected. The enrichment process is accomplished by aligning individual audiovisual segments with news or journal articles reachable trough the Web. This distributed process designed for RitroveRAI enables several extensions in light of large scale and public access performance as suggested in the discussion of the evaluation results of our current system.
Keywords: Hyper link structure; Meta data; Multimedia indexing; RitroveRAI; Semantic web; Web services

Some issues in the art image database systems - Stanchev, P.L.; Green Jr., D.; Dimitrov, B. (Journal of Digital Information Management, 2006)
In this paper we illustrate several aspects of art databases, such as: the spread of the multimedia art images; the main characteristics of art images; main art images search models; unique characteristics for art image retrieval; the importance of the sensory and semantic gaps. In addition, we present several interesting features of an art image database, such as: image indexing; feature extraction; analysis on various levels of precision; style classification. We stress color features and their base, painting analysis and painting styles. We study also which MPEG-7 descriptors are best for fine painting images retrieval. An experimental system is developed to see how these descriptors work on 900 art images from several remarkable art periods. On the base of our experiments some suggestions for improving the process of searching and analysis of fine art images are given.
Cited By (since 1996):5Export Date: 10 July 2014
Keywords: Art databases; Image processing; Image search and analysis; MPEG 7; Multimedia databases