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Virtual Reality (VR) research is accelerating the development of inexpensive real-time Brain Computer Interface (BCI). Hardware improvements that increase the capability of Virtual Reality displays and Brain Computer wearable sensors have made possible several new software frameworks for developers to use and create applications combining BCI and VR. It also enables multiple sensory pathways for communications...
In this work, we introduce a Deep Neural Network model for automated software categorization. The model is ableto form high-level concepts from low-level code tokens andto distinguish important features such as API calls and identifiersin order to support software categorization. Our empirical evaluationshows that DNN outperformed other machine learning approacheswith 15.9–36.4% higher accuracy in...
Various techniques have been proposed to detect smells in spreadsheets, which are susceptible to errors. These techniques typically detect spreadsheet smells through a mechanism based on a fixed set of patterns or metric thresholds. Unlike conventional programs, tabulation styles vary greatly across spreadsheets. Smell detection based on fixed patterns or metric thresholds, which are insensitive to...
Stack Overflow is one of the most popular question-and-answer sites for programmers. However, there are a great number of duplicate questions that are expected to be detected automatically in a short time. In this paper, we introduce two approaches to improve the detection accuracy: splitting body into different types of data and using word-embedding to treat word ambiguities that are not contained...
Inferring activities on smartphones is a challenging task. Prior works have elaborated on using sensory data from built-in hardware sensors in smartphones or taking advantage of location information to understand human activities. In this paper, we explore two types of data on smartphones to conduct activity inference: 1) Spatial-Temporal: reflecting daily routines from the combination of spatial...
Software defect prediction aims to determine whether a software module is defect-prone by constructing prediction models. The performance of such models is susceptible to the high dimensionality of the datasets that may include irrelevant and redundant features. Feature selection is applied to alleviate this issue. Because many feature selection methods have been proposed, there is an imperative need...
As a basic operation, image saliency detection has been widely used in various applications. Many approaches have been proposed to detect salient regions. In this study, we learn to detect salient curves of cartoon images based on composition rules. We formulate the detection problem as a binary labeling task where we separate salient curves from the whole curve structures extracted from the cartoon...
Online reviews nowadays are an important source of information for consumers to evaluate online services and products before deciding which product and which provider to choose. Therefore, online reviews have significant power to influence consumers' purchase decisions. Being aware of this, an increasing number of companies have organized spammer review campaigns, in order to promote their products...
Feature location is a program comprehension activity in which a developer inspects source code to locate the classes or methods that implement a feature of interest. Many feature location techniques (FLTs) are based on text retrieval models, and in such FLTs it is typical for the models to be trained on source code snapshots. However, source code evolution leads to model obsolescence and thus to the...
Software code review is a process of developers inspecting new code changes made by others, to evaluate their quality and identify and fix defects, before integrating them to the main branch of a version control system. Modern Code Review (MCR), a lightweight and tool-based variant of conventional code review, is widely adopted in both open source and proprietary software projects. One challenge that...
Previous research has shown that hidden Markov model (HMM) is a compelling option for malware identification. However, some advanced metamorphic malware have proven to be more challenging to detect with these techniques. In this paper, we separated the importance of the some part of the malware files to train the HMMs aiming at extracting the significant sequences of malware opcodes. These parts have...
The web becomes a huge repository of data and information. In order to deal with large quantities of data, the users need intelligent-based tools and methods to access data, process it, and make it useful for variety of purposes. Proposed as a part of Semantic Web, Resource Description Framework (RDF) is an important way of representing information. Its intrinsic feature of high connectivity creates...
In recent years, IT Service Providers have been rapidly transforming to an automated service delivery model. This is due to advances in technology and driven by the unrelenting market pressure to reduce cost and maintain quality. Tremendous progress has been made to date towards attainment of truly automated service delivery; that is, the ability to deliver the same service automatically using the...
With the increasing power of the HPC hardware systems, numerical simulations are heading towards exa-scale computing. Early inspection and analysis of on-going large simulations enables domain experts to obtain first insight into their running simulation process and intermediate results. Compared to conventional post-processing, such in-situ processing has the advantage of keeping data in memory,...
Successful software is more and more rarely developed as a one-of-a-kind system. Instead, different system variants are built from a common set of assets and customized for catering to the different functionality or technology needs of the distinct clients and users. The Software Product Line Engineering (SPLE) paradigm has proven effective to cope with the variability described for this scenario...
Feature models and configuration knowledge drive product generation in a Software Product Line (SPL). Mistakes when specifying these models or in the implementation might result in ill-formed products-- the safe composition problem. This work proposes an automated approach for verifying safe composition for SPLs with explicit configuration knowledge models. We translate feature models and configuration...
A software product line is a family of related software products, typically, generated from a set of common assets. Users can select features to derive a product that fulfills their needs. Often, users expect a product to have specific non-functional properties, such as a small footprint or a minimum response time. Because a product line can contain millions of products, it is usually not feasible...
In real time applications or portable devices, software implementation is not enough by itself to evaluate a signal feature analysis technique and a hardware implementation needs to be considered. The selection of the right signal feature analysis technique for an application depends on the algorithmic (software) performance, and also on the hardware efficiency of that technique. However, there are...
Reverse engineering techniques are usually applied to extract concrete architecture models. However, these techniques usually extract diagrams that just reveal static architectures, such as class diagrams. On the other hand, the extraction of dynamic architecture models can be particularly useful for an initial understanding of how a system works or to evaluate the impact of a possible maintenance...
This paper firstly examines the traditional vehicle styling evaluation methods and issues, and then presents a new approach which uses ANN (artificial neural network) to build an expert system for bus styling evaluation. It describes the key technical issues of quasi-three-dimensional bus styling evaluation expert system from data collection, graphical pre-processing, graphics feature extraction,...
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