A Flexible Content Adaptation System Using a Rule-Based Approach

The deployment of information appliances is predicted to exceed that of personal computers in the next few years. However, due to the wide range of communication, processing, storage and display capabilities of information appliances, the multimedia content on the Internet needs to be adapted before it can be efficiently delivered to these devices. We present content adaptation framework (CAF), a general framework for customizing Internet content for diverse client devices. The system first analyzes the content to be customized. Next, a variety of transcoders generate multi-resolution, multimodal versions of the content. The transcoded versions of the multimedia content are represented in a novel multi-modal, multi-resolution representation hierarchy called the InfoPyramid. Finally, a selection module uses an extended rate-distortion framework to pick the best content versions from the InfoPyramid while meeting the client device characteristics and resources. The content adaptation system can be deployed at various nodes in the Internet topology, such as at the server, at the client device or at an intermediate proxy. We present examples of proxy and server content adaptation systems based on CAF. Based on the content adaptation framework, we present a description scheme for multimedia and Internet content. This description scheme enables universal access to content. It has been proposed to various standards bodies.

Internet access using mobile handheld devices has surpassed that of fixed Internet, but most web pages are designed for desktop browsers. Mobile devices have resource limitations. Consequently, web pages designed for desktop browsing cannot be well displayed on mobile devices. Thus, dynamically transforming web contents designed for desktops into contents which can be displayed in a mobile device is an important task. Various approaches of content adaptation have been proposed to achieve this goal, but no single content adaptation strategy has been found to be effective. On the other hand, e-learning contents have grown manifold over years. In this paper, we provide a framework for an e-learning content adaptation system that can be used with desktops and mobile devices seamlessly. We combine multiple content adaptation strategies to make e-learning contents appropriate for mobile devices. Among the various content adaptation strategies, the segmentation algorithm plays the most important role. Our experiments demonstrate that the proposed scheme can be successfully utilized for content adaptation in mobile and handheld devices.

In this paper, we propose content adaptation for visual impairments in MPEG-21. The proposed content adaptation aims to give enhanced visual accessibility to users with visual impairment in MPEG-21. In this paper, we consider two major visual impairments: low vision impairment and color vision deficiency. The proposed method includes description for the visual impairments and content adaptation technique based on it. We have developed a symptom-based description of visual impairment characteristics for users with visual impairment in the context of MPEG-21 digital item adaptation (DIA). To verify usefulness of the proposed method, we performed some experiments with the content adaptation based on the description in MPEG-21. The experiment results showed that the proposed method is effective content adaptation for user with visual impairment and gives enhanced visual accessibility to them.

Evolution of mobile technologies and widespread adoption of mobile devices in learning today is momentous. Mobile learning refers to the use of portable devices to study independent of location and time. To allow flexible learning to occur, content adaptation is necessary. Content-adaptation aims at delivering the most suitable learning elements in dynamic conditions using different contextual information from various sources in order to enhance the learners' experiences. This paper describes our ongoing research project, the context-aware mobile learning application, Mobiware that makes use of contextual data in mobile learning for content-adaptation. Important information was gathered from individual learners, the device used and the surrounding to give rise to independent customized learning materials. The aim of developing this mobile application is to set a dynamic system, which instantly acknowledges different user situations, and deliver the best-adapted learning content to the learner. Details about the current trends in mobile learning are reported which leads to the proposed context-aware mobile learning application.

Video adaption is one of the main solutions to offer access to the large array of existing multimedia contents and the variety of terminals and networks. This adaptation can be achieved efficiently using transcoding techniques. The implementation of the various adaptation possibilities and techniques in embedded systems such as home gateway requires flexible and efficient architectures. This paper presents a hardware reconfigurable architecture for the real time adaptation of video contents for different terminals and available bandwidth. This architecture is designed to adapt a compressed stream in advanced video coding standard (H264/AVC) and/or MPEG-2. A system level model of reconfigurable transcoder is developed for IP integration and architectural exploration by taking into account dynamic and partial reconfiguration. The developed simulation model of dynamic partial reconfiguration allowed the early estimation of performances and the design of the suitable solution for the considered transcoding scenarios.

The mobile environment presents numerous challenges to users and developers alike. Ideally, mobile content should be designed to enhance a user's experience rather than simply serve up the same content originally designed for other platforms. This chapter presents a study of techniques for “content adaptation”, the process of reformatting content and displaying it optimized for a mobile device. Adaptation techniques consist of a varied number of mechanisms by which content is adapted into a format more “friendly” to mobile devices. The idea of “friendly” can range from simple accessibility requirements to a dynamic redesign. Included in this discussion is a summary of the advantages and disadvantages of current techniques. Examples of different techniques are presented and illustrated along with the system framework necessary to implement them.

This paper presents a novel hybrid RTSP, SIP and HTTP solution for providing converged WebTV services with automatic Rate Adaptation of multimedia content. The prototypical solution, being developed under the scope of the My-eDirector 2012 european project, was deployed in a high-bandwidth LAN and some preliminary tests were performed.

Application of a fuzzy controller in adaptive e-learning content used to evaluate student activity

Rule-based systems that are easily testable are required for high reliability applications. However, as a rule base evolves, developers prefer incremental evaluation owing to the high cost of regression testing. For quality and reliability improvement, researchers advocate that the evaluation phase be integrated with development: thus, incremental evaluation becomes more important in this context. In this paper, we propose a three-tiered life-cycle model for integrating evaluation in a rule-based system life cycle. We then outline its use to facilitate knowledge acquisition using “goal specification” and its realization in a rule base using “paths.” Path-based validation has been well-accepted in the literature as a reliable method for structural testing. However, extracting paths for every rule base modification for its evaluation incurs an enormous effort. In this paper, we identify situations that can help in incremental path extraction and present some issues that are important for integrating evaluation into the life-cycle of rule-based systems. We also outline how our approach can facilitate handling these issues.KeywordsExpert SystemsVerification & Validation

The realization of highly bandwidth-efficient wireless communications over frequency-selective multipath fading channels will be one of the key enabling technologies for future high-speed communication systems that offer ubiquitous access to information. Such bandwidth-efficient communication over broadband wireless channels can be accomplished by a number of different coding, modulation, and framing strategies; in particular, (1) the system can employ a single-carrier or a multicarrier framework, (2) the system can employ adaptive or non-adaptive signaling techniques, and (3) the system can employ iterative or traditional non-iterative decoding. The goal of this ongoing project is to understand the similarities, differences, and applicability of these various techniques in high-speed wireless communications. Such as investigation services not only the specific system design goals here but also aids in the consideration of a number of open issues in the communication theory literature, such as the applicability of adaptive techniques in systems that employ iterative decoding and the robustness to channel uncertainty of iterative single-carrier techniques typically employed in magnetic recording. In this paper, preliminary numerical results from this study are presented for various logical combinations of the aforementioned strategies motivated by previous work of the authors. These numerical results, combined with a complexity and delay analysis of the various receivers, allows the comparison and contrast of the aforementioned techniques for various applications.

Non-stationary time series plays a prominent role in the analysis of performance time series of many real-world systems. Recently, fuzzy time series models have been extended to forecast non-stationary time series. Over different phases of time, performance time series may show drastic changes. Therefore, a non-stationary time series is partitioned according to different phases of time. These phases may be taken as weeks, months, or years. Over different phases of time, the universe of discourse, knowledge base, and rule base may vary. A common constraint in the modelling of time-variant fuzzy time series is their incapability to address the phase change of time in the model and accordingly incorporate the necessary changes in the universe of discourse, knowledge base, and rule base over different time phases. To address this issue, a Phase-cum-Time Variant Fuzzy Time Series Model (PTVFTS) is presented in this paper. The PTVFTS model is developed so that it will address the problem of phase change as well as the time variations within each phase simultaneously. The concept of the model rebuilding process is applied to handle changes over each phase and the modified parameter adaptation technique is used for the time variations within each phase. The developed model is applied to the daily closing price time series for the years 2017, 2018, 2019, 2020, 2021, and 2022 separately of stock market indices, NASDAQ, S&P 500, Dow Jones, and TAIEX. The comparison of the developed model is made with the time-variant fuzzy time series model known as the non-stationary fuzzy time series model (NSFTS), Dynamic Evolving Neural-Fuzzy Inference System (DENFIS) model, Long Short-Term Memory (LSTM) model, and the classical Auto-Regressive Integrated Moving Average (ARIMA) model. The efficiency of the developed PTVFTS model is tested using forecasting metrics and statistical tests. The comparison shows that the developed model is more efficient in forecasting phase-cum-time variant non-stationary time series.

Despite unplanned and haphazard expansion of shrimp cultivation that immensely affects on the coastal regions of Bangladesh, the exploration of its adverse effects has not received significant attention from the researcher community yet. There were few researches and studies in Bangladesh conducted to elicit the colossal effects of shrimp production at different times that did not particularize its focus on proposing an ecological design of shrimp production. In order to elicit the concomitant impacts and propose an ecological model of shrimp cultivation based on secondary data, the present study was conducted by applying ‘Systematic Review and Content Analysis’ as research method. The study findings manifest that the continuous and unregulated shrimp farming has immense impacts on human health, ecology, environment and sustainability though few of them directly benefit the shrimp farmers and the people who live around them. The extensive farming systems negatively expedite the processes: infringement of mangroves, intrusion of salinity, degradation of land, de-stabilization of coastal ecosystems. The major socio-economic effects challenge the patterns of livelihood pattern, displacement of family and social structure, internal migration, and livestock. The coastal regions suffer from environmental degradation due to increased salinity of soil, canals and ponds within dams, reduction in grazing field and livestock, changes in the cropping calendar and its pattern, bio-diversity. Ecological aspects and sustainability are also overlooked during the shrimp cultivation. In conclusion, proper implementation of the resilient strategies designed in an ecological model can minimize the adverse effects on the coastal dwellers and local environment, and improve the unplanned shrimp cultivation process in similar areas of Bangladesh.

This paper proposes a new approach to automatic retrieval and composition of Learning Objects (LOs) in an Adaptive Educational Hypermedia System (AEHS) using multidimensional learner characteristics to enhance learning effectiveness. The approach focuses on adaptive techniques in four components of AEHS: Learning Paths, LO Retrieval, LO Sequencing, and Examination Difficulty Levels. This approach has been designed to enable the adaptation of rules to become generic. Hence, the application to various domains is possible. The approach dynamically selects, sequences, and composes LOs into an individual learning package based on the use of domain ontology, learner profiles, and LO metadata. The Sharable Content Object Reference Model is employed to represent LO metadata and learning packages in order to support LO sharing. The IMS Learner Information Package Specification is used to represent learner profiles. A preliminary evaluation of the developed system indicates the system’s effectiveness in terms of learners’ satisfaction.

Multi-core organizations increasingly support multiple threads per core. Threads on a core usually share a single first-level data cache, so thread schedulers must try to minimize cache contention among threads. While this has been studied for concurrent threads with disjoint working sets, the problem has not been addressed for multi-threaded data-parallel workloads in which threads can be scheduled or constructed to improve inter-thread cache sharing. This paper proposes the symbiotic affinity scheduling (SAS) algorithm in which work is first partitioned according to the number of cores (i.e., the number of caches), and these partitions are then subdivided and scheduled among each core's available thread contexts so that threads sharing a core operate on neighboring elements to maximize cache locality. We demonstrate this concept with a series of data-parallel benchmarks. Simulations on M5 achieve an average speedup of 1.69× and 36% energy savings over conventional scheduling techniques that are oblivious to whether threads share a cache. Even compared to an approach that extends oblivious scheduling to ensure that the sum of the threads' working sets fits in the cache, symbiotic affinity scheduling is able to exploit greater temporal locality and provide 30% performance gains on average. Symbiosis also outperforms adaptive contention reduction techniques by 17%.

In this paper we present an experimental content adaptation system for mobile devices. The system enables the presentation of multimedia content and considers the problem of small screen display of mobile terminals. The approach combines structural and media adaptation with the content formatting and proposes a system that handles the user interaction and the content navigation.