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Emotion cause extraction is one of the promising research topics in sentiment analysis, but has not been well-investigated so far. This task enables us to obtain useful information for sentiment classification and possibly to gain further insights about human emotion as well. This paper proposes a bootstrapping technique to automatically acquire conjunctive phrases as textual cue patterns for emotion...
A hierarchical model is presented for the implementation of a qualitative assessment of the system's operability. The system consists of objects. Objects are characterized by their parameters. The estimation is based on the determination of the state of the parameters. The procedure is carried out by introducing intermediate scales of numerical estimation. Qualitative assessments are aligned with...
Software Development Effort Estimation (SDEE) plays a primary role in software project management. Among several techniques suggested for estimating software development effort, analogy-based software effort estimation approaches stand out as promising techniques.In this paper, the performance of Fuzzy Analogy is compared with that of six other SDEE techniques (Linear Regression, Support Vector Regression,...
In the safety engineering, risk estimation is in practice confronted with difficulties connected with shortage of data. In such cases, we have to rely on subjective estimations made by persons with practical knowledge in the field of interest, i.e. experts. However, in some realistic situations, the decision makers might be reluctant or unable to assign the crisp values to the evaluation judgments...
In this study the plausibility of automated human translation quality estimation is investigated to tackle the slowness, expensiveness and inconsistency of human evaluation. A reference free approach using machine learning is advanced to address four research questions. The methodology characteristic of this approach is then presented in detail. Finally, the author reports the latest progress of the...
In this paper identification of electroencephalogram (EEG) based brain-computer interface (BCI) for motor imagery (MI) task is planned by an efficient adaptive neuro-fuzzy classifier (NFC). The linguistic hedge (LH) is used for proper elicitation and pruning of the fuzzy rules and network is trained using scaled conjugate gradient (SCG) and speeding up SCG (SSCG) techniques. The performance of the...
An important challenge in speech processing involves extracting non-linguistic information from a fundamental frequency (F0) contour of speech. We propose a fast algorithm for estimating the model parameters of the Fujisaki model, namely, the timings and magnitudes of the phrase and accent commands. Although a powerful parameter estimation framework based on a stochastic counterpart of the Fujisaki...
Defects uncovered during software testing usually consume a considerable amount of the overall project's budget. Unfortunately, project managers are not well-equipped with techniques to estimate such cost overrun. Moreover, incorporating defects removal process as part of the software testing activities has made the project managers overlook this important cost component during their planning processes...
The results of research and application of fuzzy logic on the control systems in the «atypical» (not in technical) area are offered. This is an estimation of testing diagnosis results within control system of education quality. To increase the accuracy and reliability of estimation of results of a given study in competence-based format, it is possible to use approved approaches and methods from contiguous...
Feature selection has been recently used in the area of software development effort estimation for improving the accuracy and robustness of prediction techniques. The idea behind selecting the most informative subset of features from a pool of available effort drivers stems from the hypothesis that reducing the dimensionality of datasets may significantly minimize the complexity and time required...
We address the problem of estimation of the Fujisaki model parameters for F0 synthesis. For this, we propose the use of a very efficient search and optimization method termed the ‘direct-search’ (Hooke and Jeeves, 1961) which belongs to the class of derivative-free unconstrained optimization methods, in the sense that it is applicable for non-linear optimization problems which are not amenable for...
Missing Data (MD) is a widespread problem that can affect the ability to use data to construct effective software development effort prediction systems. This paper investigates the use of missing data (MD) techniques with Fuzzy Analogy. More specifically, this study analyze the predictive performance of this analogy-based technique when using toleration, deletion or k-nearest neighbors (KNN) imputation...
The conventional crowdsourcing paradigm requires an explicit task description and payment scheme. Requesters can then easily determine whether the crowdsourced results are satisfactory, and workers will have a fairly clear expectation of the monetary reward once the task is accomplished. However, such a paradigm becomes problematic when it is applied to Object Identification (OI) tasks. First, for...
This study presents an innovative approach to develop a course specification that considers the effect of the covered topics in a course on the entire program learning outcomes. This study presents a practical methodology enabling instructors to design an efficient course specification based on the national academic accreditation and assessment standards of the Kingdom of Saudi Arabia. Fuzzy linguistic...
Steganography is the art of hiding data in data in an untraceable way. Main concern of steganography is hiding the existence of hidden message. Steganalysis is the art and science of detecting hidden messages from stego-systems. It also attempts to find hidden message such as the type of embedding algorithm, the length of the message, the content of the message or the secret key used from the carrier...
Fujisaki’s intonation model parameterizes the F0’s contour efficiently and because of its strong physiological basis has been successfully tested in different languages. One problem that has not been fully addressed is the extraction of the model’s parameters, i.e., given a sentence, which model’s parameter values best describe its intonation. Most of the proposed methods strive to optimize the parameters...
The research activities on group decision making has dramatically increased in last decade. Especially the application of multiple attribute decision making methods to group decision making problems occupies a vast area in the related literature. However there is no systematical classification scheme for these researches. This paper presents a taxonomy for multiple attribute group decision making...
Compounding is one of the most productive word formation processes in many languages and is therefore a main source of data sparsity in language modeling. Many solutions have been suggested to model compound words, most of which break the compound into its constituents and train a new model with them. In earlier work, we argued that this approach is suboptimal and we presented a novel technique that...
We propose in this paper, a gender recognition solution under the presence of occlusion and using the very restrict samples in the learning base. The developed approach is based on the extraction of pertinent 3D depth-radial curves that cover the nose region and combined dimensionality reduction using sparse random projection method; furthermore we propose an extension of similarity based classification...
To meet the huge traffic growth, heterogeneous networks composed of wireless local area networks (WLAN) and cellular networks are used to provide higher capacity and coverage. When the two networks are available, switching from one network to the other when downloading data is needed to provide good system performance. This paper proposes a fuzzy logic based approach for an automated network selection...
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