Multi-dimensional multi-level modeling

Software and Systems Modeling - The growth of multi-level modeling has resulted in an increase of level-organization alternatives which significantly differ from each other with respect to their...     

Extending multimedia languages to support multimodal user interactions

Historically, the Multimedia community research has focused on output modalities, through studies on timing and multimedia processing. The Multimodal Interaction community, on the other hand, has focused on user-generated modalities, through studies on Multimodal User Interfaces (MUI). In this paper, aiming to assist the development of multimedia applications with MUIs, we propose the integration of concepts from those two communities in a unique high-level programming framework. The framework integrates user modalities —both user-generated (e.g., speech, gestures) and user-consumed (e.g., audiovisual, haptic)— in declarative programming languages for the specification of interactive multimedia applications. To illustrate our approach, we instantiate the framework in the NCL (Nested Context Language) multimedia language. NCL is the declarative language for developing interactive applications for Brazilian Digital TV and an ITU-T Recommendation for IPTV services. To help evaluate our approach, we discuss a usage scenario and implement it as an NCL application extended with the proposed multimodal features. Also, we compare the expressiveness of the multimodal NCL against existing multimedia and multimodal languages, for both input and output modalities.

     

Playground for multi-level modeling constructs

Software and Systems Modeling - In recent years, multi-level modeling has become more and more popular. It is mainly due to the fact that multi-level modeling aims to reduce or even totally...     

Guest editorial to the theme section on multi-level modeling

Software and Systems Modeling -     

Identification of Indian languages using multi-level spectral and prosodic features

In this paper spectral and prosodic features extracted from different levels are explored for analyzing the language specific information present in speech. In this work, spectral features extracted from frames of 20 ms (block processing), individual pitch cycles (pitch synchronous analysis) and glottal closure regions are used for discriminating the languages. Prosodic features extracted from syllable, tri-syllable and multi-word (phrase) levels are proposed in addition to spectral features for capturing the language specific information. In this study, language specific prosody is represented by intonation, rhythm and stress features at syllable and tri-syllable (words) levels, whereas temporal variations in fundamental frequency (F ₀ contour), durations of syllables and temporal variations in intensities (energy contour) are used to represent the prosody at multi-word (phrase) level. For analyzing the language specific information in the proposed features, Indian language speech database (IITKGP-MLILSC) is used. Gaussian mixture models are used to capture the language specific information from the proposed features. The evaluation results indicate that language identification performance is improved with combination of features. Performance of proposed features is also analyzed on standard Oregon Graduate Institute Multi-Language Telephone-based Speech (OGI-MLTS) database.     

Reusable abstractions for modeling languages

Model-driven engineering proposes the use of models to describe the relevant aspects of the system to be built and synthesize the final application from them. Models are normally described using Domain-Specific Modeling Languages (DSMLs), which provide primitives and constructs of the domain. Still, the increasing complexity of systems has raised the need for abstraction techniques able to produce simpler versions of the models while retaining some properties of interest. The problem is that developing such abstractions for each DSML from scratch is time and resource consuming.     

Decision confidence-based multi-level support vector machines

Support vector machines (SVM) have been showing high accuracy of prediction in many applications. However, as any statistical learning algorithm, SVM's accuracy drops if some of the training points are contaminated by an unknown source of noise. The choice of clean training points is critical to avoid the overfitting problem which occurs generally when the model is excessively complex, which is reflected by a high accuracy over the training set and a low accuracy over the testing set (unseen points). In this paper we present a new multi-level SVM architecture that splits the training set into points that are labeled as ‘easily classifiable’ which do not cause an increase in the model complexity and ‘non-easily classifiable’ which are responsible for increasing the complexity. This method is used to create an SVM architecture that yields on average a higher accuracy than a traditional soft margin SVM trained with the same training set. The architecture is tested on the well known US postal handwritten digit recognition problem, the Wisconsin breast cancer dataset and on the agitation detection dataset. The results show an increase in the overall accuracy for the three datasets. Throughout this paper the word confidence is used to denote the confidence over the decision as commonly used in the literature.     

多层次用户兴趣模式的动态捕捉

为了得到更多的用户兴趣信息,提出了一种新的高效的用户兴趣模式获取方法,面向层次结构的信息网站,提供动态的多层次用户兴趣模式。该方法根据网站和用户兴趣所具有的层次性特征,利用蚁群算法,将用户对网站结点的一次浏览过程,对应于蚂蚁的一次觅食活动周期,从各个层次求出相应路径的信息素浓度和支持度,从而得到用户对该结点的偏好函数值,再依据此值求得用户兴趣模式。实验表明了该方法的有效性。     

Utilizing multi-level concepts for multi-phase modeling

Software and Systems Modeling - In model-based systems engineering projects, engineers from multiple domains collaborate by establishing a common system model. Multi-level modeling is a technique...     

A support system for interactive languages

The implementation of a support system for interactive languages is described, which include a controlling routine, a macro processor, lexical and syntactic analysis routines, semantic actions, error handling and analysis, log and code generation routines. There are also utility programs for generating the state tables for the syntax analysis. By using a structured programming approach these routines have been developed very quickly, but can still be developed and enhanced due to a well-defined working environment, a simple approach to coding and reasonable internal documentation.     

Modern modeling of a classic multiperiod problem

In this paper we discuss the integration of modeling and programming in order to solve problems in operations research and decision support. Our goal is to integrate modeling into the larger programming scheme of things and, conversely, to inject programming into modeling. This integration leads to a technologically open way to handle problems in OR, AI, etc. since the full programming arsenal can be brought to bear on these problems and since both problem solving and model management can be abetted by software engineering techniques. Here, by means of variations on a single example, we will illustrate the solution of a linear program, a goal program, a disjunctive program, a hill climbing search, a branch and bound search, and a parallel solution to a stochastic problem.     

An intermediate database language and its rule-based transformation to different database languages

A user or a comptuter system which extracts information from heterogeneous DBMSs faces the hard problem of dealing with different target database languages for each DBMS. We propose a solution for this problem based on an intermediate database language and its rule-based transformation to target languages. This solution is implemented in the database access module of the Intelligent Database Assistant, developed at GTE Laboratories.We describe the intermediate database language GTE DELPHI, which combines the power of relational algebra with practically important database operations, including output to a file, grouping, aggregate computations, and nested queries. We show how to convert GTE DELPHI to different relational and 4th generation database languages by a rule-based transformation system and indicate how a conversion program can be generated from examples. Translation from a high-level user language (such as English) to GTE DELPHI is simplified by using a universal relation version of GTE DELPHI as an intermediate step.     

A multi-level approach to modeling language extension in the Enterprise Systems Domain

As the number and diversity of technologies involved in building enterprise systems continues to grow so does the importance of modeling tools that are able to present customized views of enterprise systems to different stakeholders according to their needs and skills. Moreover, since the range of required view types is continuously evolving, it must be possible to extend and enhance the languages and services offered by such tools on an ongoing basis. However, this can be difficult with today׳s modeling tools because the meta-models that define the languages, views and services they support are usually hardwired and thus not amenable to extensions. In practice, therefore, various workarounds have to be used to extend a tool׳s underlying meta-model. Some of these are built into the implemented modeling standards (e.g. UML 2, BPMN 2.0 and ArchiMate 2.0) while others have to be applied by complementary, external tools (e.g. annotation models). These techniques not only increase accidental complexity, they also reduce the ability of the modeling tool to ensure adherence to enterprise rules and constraints. In this paper we discuss the strengths and weaknesses of the various approaches for language extension and propose a modeling framework best able to support the main extension scenarios currently found in practice today.     

Model clone detection for rule-based model transformation languages

Software and Systems Modeling - Cloning is a convenient mechanism to enable reuse across and within software artifacts. On the downside, it is also a practice related to severe long-term...