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Obesity is increasing globally and is a risk factor for many chronic conditions such as such as heart disease, sleep apnea, type-2 diabetes, and some cancers. Research shows that food logging is beneficial in promoting weight loss. Crowdsourcing has also been used in promoting dietary feedback for food logging. This work investigates the feasibility of crowdsourcing to provide support in accurately...
This paper presents a methodology for reducing functional test time in subthreshold SoCs targeting ultra-low power (ULP) internet-of-things (IoT) devices. Due to their low operating speed and voltage, subthreshold SoCs require significantly longer time to test than traditional SoCs. The proposed method models trans-threshold correlations to allow high voltage, high speed testing while accurately predicting...
Automatic image aesthetics rating has received a growing interest with the recent breakthrough in deep learning. Although many studies exist for learning a generic or universal aesthetics model, investigation of aesthetics models incorporating individual user’s preference is quite limited. We address this personalized aesthetics problem by showing that individual’s aesthetic preferences exhibit strong...
The purpose of this research is proposing a theory to verify the influence of virtual props trading sites to game loyalty of players. The objects of sampling aims at users who are actually engaged in online games props trading sites. A survey of 459 game players in Taiwan was conducted; research results were generated through the use of descriptive analysis, reliability analysis, correlation analysis,...
This paper proposes the SVDNet for retrieval problems, with focus on the application of person re-identification (reID). We view each weight vector within a fully connected (FC) layer in a convolutional neuron network (CNN) as a projection basis. It is observed that the weight vectors are usually highly correlated. This problem leads to correlations among entries of the FC descriptor, and compromises...
Use of online applications in day-to-day life is increasing. In parallel to this increase the threat to the security of these applications is also increasing. The security of these applications is breached by different cyber attacks. Denial-of-Service (DoS) is one such type of cyber attack. DoS makes the online application or the resources of the server unavailable to the intended users. For detecting...
Available sensing measurements in modern industrial process include two significant characteristics: distribution and autocorrelation. Different types of sensing measurements exhibit different characteristics. Moreover, different feature extraction methods are suitable for data with corresponding characteristics. This paper proposes a novel dual-step subspace partition method in order to establish...
In many research areas where the hypothetical based study is performed p-value is most commonly used statistical measure for null hypothesis testing. This p-value is deciding factor in considering the hypothesis validity for given population. Such a critical value can sometimes mislead the entire research. So there is always scope in understanding such factors in all possible directions. One of such...
In this paper, a target detection procedure with global error control is proposed. The novelty of this approach consists in taking into account spatial structures of the target while ensuring proper error control over pixelwise errors. A generic framework is discussed and a method based on this framework is implemented. Results on simulated data show conclusive gains in detection power for a nominal...
Unit testing has been considered as having a key role in building high quality software, and therefore it has been widely used in practice. However, data on the relationship between unit testing and aspects of software quality remain scarce. A survey study with 235 survey responses from seven organizations was conducted in order to understand the correlation between practitioners' perception of code...
This Transformer experiences aging everyday as it gets older. The aging of transformer can be detected by assessing the condition of its oil insulation. Every transformer has its own aging rate which is influenced by many factors. This paper discusses about effects of lifetime and loading factor on DGA using regression linear method. 219 sample data including DGA and transformer age were collected...
Customers need to know how reliable a new release is, and whether or not the new release has substantially different, either better or worse, reliability than the one currently in production. Customers are demanding quantitative evidence, based on pre-release metrics, to help them decide whether or not to upgrade (and thereby offer new features and capabilities to their customers). Finding ways to...
Spreadsheets often contain faults that are difficult to localize. Spectrum-based Fault Localization (SFL) assists users in the fault localization process by ranking cells by their suspiciousness to contain a fault. Since the ranking of the basic SFL approach is often imprecise, we propose three techniques to improve it, i.e., dynamic cones, grouping, and tie-breaking. We evaluate these techniques...
Employing the Theory of Planned Behavior (TPB), this study aims to find determinant factors that have influence over individuals' intention to cyberbully others. Using a scenario-based questionnaire, the data were collected from 96 students in Universiti Teknologi Malaysia. According to the results, only subjective norms reflected to be significant over cyberbullying intention, while the rest of variables...
This paper presents a service-oriented paradigm for building next generation services using Internet of Things (IoT). In the future, there will be many IoT devices deployed in our environments, such as smart homes, smart offices, and smart factories. Our study proposes the paradigm of Service-Oriented Things (SOT) which can recognize user activities and compose, map and deploy context aware services...
Fault localization defines information models from raw runtime information as the input, depicting program behaviors for supporting localization algorithms. It is natural that an elaborate information model is desirable and likely to improve the effectiveness of fault localization, because it typically depicts subtle and more program runtime behaviors. In fact, much work on fault localization assumes...
Traditional neuropsychological tests of executive function are designed to assess a range of behavioral competencies necessary for the cognitive control of behavior in the real world. Though considered the ‘gold standard’, these pen-and-paper tests have been criticized for questionable relevance to everyday functioning. Immersive virtual reality (VR) technologies may be a viable tool for developing...
Electromagnetic interference is a most important cause for wrong alarming and failing to alarm of on-line PD detection in substation. The characteristics of electromagnetic interferences are dynamic change under the influence of many factors, thus the difficulty of its identification and suppression is increased. Therefore, typical substations in geographical position and voltage level was selected...
Over the last decade, machine learning algorithms have proven to be useful tools for exploring neural representations of percepts and concepts in the brain. An important but often neglected next step is it to relate neural representations to human behavior. Here, we introduce a novel approach to definitively linking neural representations to structural properties of stimuli as well as human behavior...
The problem of determining the sensitization probability of a path by a test vector is investigated. It is important when testing for delay defects due to process variations. An algorithm is presented which has high accuracy. Gate delays are modeled as probability mass functions, and novel operations are introduced that take into consideration circuit reconvergences and path correlations. Experimental...
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