A Bayesian modeling approach to multi-dimensional sentiment distributions prediction

Sentiment analysis has long focused on binary classification of text as either positive or negative. There has been few work on mapping sentiments or emotions into multiple dimensions. This paper studies a Bayesian modeling approach to multi-class sentiment classification and multidimensional sentiment distributions prediction. It proposes effective mechanisms to incorporate supervised information such as labeled feature constraints and document-level sentiment distributions derived from the training data into model learning. We have evaluated our approach on the datasets collected from the confession section of the Experience Project website where people share their life experiences and personal stories. Our results show that using the latent representation of the training documents derived from our approach as features to build a maximum entropy classifier outperforms other approaches on multi-class sentiment classification. In the more difficult task of multi-dimensional sentiment distributions prediction, our approach gives superior performance compared to a few competitive baselines. © 2012 ACM.

Modeling naturalistic argumentation in research literatures:representation and interaction design issues

This article characterizes key weaknesses in the ability of current digital libraries to support scholarly inquiry, and as a way to address these, proposes computational services grounded in semiformal models of the naturalistic argumentation commonly found in research literatures. It is argued that a design priority is to balance formal expressiveness with usability, making it critical to coevolve the modeling scheme with appropriate user interfaces for argument construction and analysis. We specify the requirements for an argument modeling scheme for use by untrained researchers and describe the resulting ontology, contrasting it with other domain modeling and semantic web approaches, before discussing passive and intelligent user interfaces designed to support analysts in the construction, navigation, and analysis of scholarly argument structures in a Web-based environment. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 17–47, 2007.

Implications of Recent Trends in Telecommunications on Modeling and Simulation for the Telecommunication Industry

With this paper we would like to trigger a discussion on future needs of modeling and simulation techniques and tools for the telecommunication industry. We claim that the telecommunication market has undergone severe changes that affect the need for and type of simulations in industrial research. We suggest some approaches how to address these new challenges. We believe that there is need for intensive research in the area.

Ontological Multilevel Modeling Language

This paper presents ontological multilevel modeling language O2ML, aimed at using with metadata driven information systems. The first part of this paper briefly surveys existing modeling languages and approaches, while the last part proposes a new language to combine their benefits.

Clogging in subsurface-flow treatment wetlands:measurement, modeling and management

This paper reviews the state of the art in measuring, modeling, and managing clogging in subsurface-flow treatment wetlands. Methods for measuring in situ hydraulic conductivity in treatment wetlands are now available, which provide valuable insight into assessing and evaluating the extent of clogging. These results, paired with the information from more traditional approaches (e.g., tracer testing and composition of the clog matter) are being incorporated into the latest treatment wetland models. Recent finite element analysis models can now simulate clogging development in subsurface-flow treatment wetlands with reasonable accuracy. Various management strategies have been developed to extend the life of clogged treatment wetlands, including gravel excavation and/or washing, chemical treatment, and application of earthworms. These strategies are compared and available cost information is reported. © 2012 Elsevier Ltd.

Interactive Visualization of the Building of University of Economics – Varna via 3D Modeling

The object of this paper is presenting the University of Economics – Varna, using a 3D model with 3Ds MAX. Created in 1920, May 14, University of Economics - Varna is a cultural institution with a place and style of its own. With the emergence of the three-dimensional modeling we entered a new stage of the evolution of computer graphics. The main target is to preserve the historical vision, to demonstrate forward-thinking and using of future-oriented approaches.

Ellátási lánc kapcsolatok modellezése = Modeling of supply chain relationships

A dolgozatban az ellátási láncokban meglévő diadikus kapcsolatok minőségét állítjuk a vizsgálatok középpontjába. Az irodalomban számtalan megközelítés ismert az ellátási lánc kapcsolatok fejlődésének leírására. Ezen fejlődési elméletek inkább elméleti szinten írják le a diadikus kapcsolatok változását, annak empirikus tesztelhetőségét nem vizsgálják. Dolgozatunkban kísérletet teszünk az ellátási lánc kapcsolatok fejlődésének empirikus vizsgálatára. Arra próbálunk választ találni, hogy az életciklus hipotézis az üzleti kapcsolatok időbeli fejlődésére alkalmazható-e. = Our paper combines two approaches using data of an internet based questionnaire and applying quantitative analysis it tests the hypothesis business relationship development in time can be described with the concept of life cycle. The concept of life cycle is widely used in business research. Among others the diffusion of innovation is described using this concept, or the concept of product life cycle just to name a few. All of these researches analyze the life cycle along a specific variable (for example the volume of sales or revenue in case of the product life cycle) which (except the last stage of the cycle, the decline) has a cumulative character resulting in the widely known specific shape of a life cycle. Consequently testing a life cycle hypothesis inevitably means the acceptance of some type cumulativity in the development.

Effectiveness of skills- versus metacognitive strategy-based approaches on reading comprehension of college developmental students

This study explored the relative value of behavioral and cognitive psychology as the basis of instruction for underprepared college students enrolled in developmental reading courses. Specifically this study examined the effects of a metacognitive strategy-based instructional approach (MSIA) modeling a metacognitive self-questioning technique (MSQT) versus a traditional skills-based instructional approach (SIA) on the Nelson-Denny reading comprehension scores of college developmental readers and whether there were significant differences in achievement based on instructional method used and on the sex of students. The sample consisted of 100 college developmental reading students who were enrolled in six intact sections of a reading course (REA0002). Participants completed a pretest of the comprehension subtest of the Nelson-Denny Reading Test (Form G). Three of these classes (n = 49) were taught using metacognitive-strategy instruction and three classes (n = 51) were instructed using skills-based instruction. They then received a semester of instruction intended to improve their reading comprehension. At the end of the semester, participants completed a post-test of the Nelson-Denny Reading Comprehension Test (Form H). A two (Between) x one (Within) Repeated Measures Analysis of Variance (ANOVA) was utilized to test each of the hypotheses of this study. Results showed that there were no significant differences in reading comprehension between the groups receiving the different instructional treatments and no differences in reading comprehension between the men and women participants. Based on the findings, implications for research and recommendations for future research were discussed.

Improving novice analyst performance in modeling the sequence diagram in systems analysis: A cognitive complexity approach

The Unified Modeling Language (UML) has quickly become the industry standard for object-oriented software development. It is being widely used in organizations and institutions around the world. However, UML is often found to be too complex for novice systems analysts. Although prior research has identified difficulties novice analysts encounter in learning UML, no viable solution has been proposed to address these difficulties. Sequence-diagram modeling, in particular, has largely been overlooked. The sequence diagram models the behavioral aspects of an object-oriented software system in terms of interactions among its building blocks, i.e. objects and classes. It is one of the most commonly-used UML diagrams in practice. However, there has been little research on sequence-diagram modeling. The current literature scarcely provides effective guidelines for developing a sequence diagram. Such guidelines will be greatly beneficial to novice analysts who, unlike experienced systems analysts, do not possess relevant prior experience to easily learn how to develop a sequence diagram. There is the need for an effective sequence-diagram modeling technique for novices. This dissertation reports a research study that identified novice difficulties in modeling a sequence diagram and proposed a technique called CHOP (CHunking, Ordering, Patterning), which was designed to reduce the cognitive load by addressing the cognitive complexity of sequence-diagram modeling. The CHOP technique was evaluated in a controlled experiment against a technique recommended in a well-known textbook, which was found to be representative of approaches provided in many textbooks as well as practitioner literatures. The results indicated that novice analysts were able to perform better using the CHOP technique. This outcome seems have been enabled by pattern-based heuristics provided by the technique. Meanwhile, novice analysts rated the CHOP technique more useful although not significantly easier to use than the control technique. The study established that the CHOP technique is an effective sequence-diagram modeling technique for novice analysts.

Modeling communication services for rapid realization

The availability and pervasiveness of new communication services, such as mobile networks and multimedia communication over digital networks, has resulted in strong demands for approaches to modeling and realizing customized communication systems. The stovepipe approach used to develop today's communication applications is no longer effective because it results in a lengthy and expensive development cycle. To address this need, the Communication Virtual Machine (CVM) technology has been developed by researchers at Florida International University. The CVM technology includes the Communication Modeling Language (CML) and the platform, CVM, to model and rapidly realize communication models. ^ In this dissertation, we investigate the basic communication primitives needed to capture and specify an end-user's requirements for communication-intensive applications, and how these specifications can be automatically realized. To identify the basic communication primitives, we perform a feature analysis on a set of communication-intensive scenarios from the healthcare domain. Based on the feature analysis, we define a new version of CML that includes the meta-model definition (abstract syntax and static semantics) and a partial behavior model (operational semantics). To validate our CML definition, we present a case study that shows how one of the scenarios from the healthcare domain is modeled and automatically realized. ^

A domain specific modeling approach for coordinating user-centric communication services

Rapid advances in electronic communication devices and technologies have resulted in a shift in the way communication applications are being developed. These new development strategies provide abstract views of the underlying communication technologies and lead to the so-called user-centric communication applications. One user-centric communication (UCC) initiative is the Communication Virtual Machine (CVM) technology, which uses the Communication Modeling Language (CML) for modeling communication services and the CVM for realizing these services. In communication-intensive domains such as telemedicine and disaster management, there is an increasing need for user-centric communication applications that are domain-specific and that support the dynamic coordination of communication services commonly found in collaborative communication scenarios. However, UCC approaches like the CVM offer little support for the dynamic coordination of communication services resulting from inherent dependencies between individual steps of a collaboration task. Users either have to manually coordinate communication services, or reply on a process modeling technique to build customized solutions for services in a specific domain that are usually costly, rigidly defined and technology specific. ^ This dissertation proposes a domain-specific modeling approach to address this problem by extending the CVM technology with communication-specific abstractions of workflow concepts commonly found in business processes. The extension involves (1) the definition of the Workflow Communication Modeling Language (WF-CML), a superset of CML, and (2) the extension of the functionality of CVM to process communication-specific workflows. The definition of WF-CML includes the meta-model and the dynamic semantics for control constructs and concurrency. We also extended the CVM prototype to handle the modeling and realization of WF-CML models. A comparative study of the proposed approach with other workflow environments validates the claimed benefits of WF-CML and CVM.^

Monitoring Ecosystems: Interdisciplinary Approaches For Evaluating Ecoregional Initiatives

Monitoring Ecosystems brings together leading scientists and researchers to offer a ground-breaking synthesis of lessons learned about ecological monitoring in major ecoregional initiatives around the United States. Contributors present insights and experiences gained from their work in designing, developing, and implementing comprehensive ecosystem monitoring programs in the Pacific Northwest, the lower Colorado River Basin, and the Florida Everglades. The book: outlines the conceptual and scientific underpinnings for regional-scale ecosystem monitoring examines the role and importance of data management, modeling, and integrative analyses considers techniques for and experience with monitoring habitats, populations, and communities Chapters by the editors synthesize and expand on points made throughout the volume and present recommendations for establishing frameworks for monitoring across scales, from local to international. Monitoring Ecosystems presents a critical examination of the lessons learned from direct experience along with generalized conclusions that can be applied to monitoring programs in the United States and around the world. It is a vital contribution to science-based monitoring efforts that will allow those responsible for developing and implementing ecoregional initiatives to make use of knowledge gained in previous efforts.

The inclusion of differentially assessed lands in urban growth model calibration: a comparison of two approaches using SLEUTH

This research sought to understand the role that differentially assessed lands (lands in the United States given tax breaks in return for their guarantee to remain in agriculture) play in influencing urban growth. Our method was to calibrate the SLEUTH urban growth model under two different conditions. The first used an excluded layer that ignored such lands, effectively rendering them available for development. The second treated those lands as totally excluded from development. Our hypothesis was that excluding those lands would yield better metrics of fit with past data. Our results validate our hypothesis since two different metrics that evaluate goodness of fit both yielded higher values when differentially assessed lands are treated as excluded. This suggests that, at least in our study area, differential assessment, which protects farm and ranch lands for tenuous periods of time, has indeed allowed farmland to resist urban development. Including differentially assessed lands also yielded very different calibrated coefficients of growth as the model tried to account for the same growth patterns over two very different excluded areas. Excluded layer design can greatly affect model behavior. Since differentially assessed lands are quite common through the United States and are often ignored in urban growth modeling, the findings of this research can assist other urban growth modelers in designing excluded layers that result in more accurate model calibration and thus forecasting.

Menu Analysis: A Review of Techniques and Approaches

This review discusses menu analysis models in depth to identify the models strengths and weaknesses in attempt to discover opportunities to enhance existing models and evolve menu analysis toward a comprehensive analytical model.

Comparing novice designer performance using a rule -based approach versus a pattern -based approach in conceptual data modeling tasks

Conceptual database design is an unusually difficult and error-prone task for novice designers. This study examined how two training approaches---rule-based and pattern-based---might improve performance on database design tasks. A rule-based approach prescribes a sequence of rules for modeling conceptual constructs, and the action to be taken at various stages while developing a conceptual model. A pattern-based approach presents data modeling structures that occur frequently in practice, and prescribes guidelines on how to recognize and use these structures. This study describes the conceptual framework, experimental design, and results of a laboratory experiment that employed novice designers to compare the effectiveness of the two training approaches (between-subjects) at three levels of task complexity (within subjects). Results indicate an interaction effect between treatment and task complexity. The rule-based approach was significantly better in the low-complexity and the high-complexity cases; there was no statistical difference in the medium-complexity case. Designer performance fell significantly as complexity increased. Overall, though the rule-based approach was not significantly superior to the pattern-based approach in all instances, it out-performed the pattern-based approach at two out of three complexity levels. The primary contributions of the study are (1) the operationalization of the complexity construct to a degree not addressed in previous studies; (2) the development of a pattern-based instructional approach to database design; and (3) the finding that the effectiveness of a particular training approach may depend on the complexity of the task.