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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...
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...
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...
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...
In previous studies, no consensus has been reached on the existence of significant correlation between perception and production. A large number of empirical studies have been done upon first and second languages from different language families. However, few studies were carried out on the perception-production relation of Chinese English learners. Therefore, in the current study, under the theoretical...
A design optimization method based on dependency model is proposed for Built-in test design in Prognostics and Health Management. Firstly, simplify the dependency model, eliminate the redundant test and merge the fuzzy fault model. Secondly identify the minimum test vector matrix to each fault mode. Under the principles of reliability and costs, determine the optimal test vector, which is used as...
The approach proposed in this paper engages FFT to the linear analog circuit specifications determination. The method allows to calculate the observed circuit under test parameter based on the step response analysis. The approximating equation that models the relationship between the selected frequency components and the observed specification is determined by means of multiple linear regression....
This preliminary study investigates feasibility of a running speed based heart rate (HR) prediction. It is basically motivated from the assumption that there is a significant relationship between HR and the running speed. In order to verify the assumption, HR and running speed data from 217 subjects of varying aerobic capabilities were simultaneously collected during an incremental treadmill exercise...
In the state of the art development of chip manufacturing (FinFet technology for example) both optical inspection and inline electrical test are deployed to monitor and facilitate the process development. While optical inspection provides critical process evaluation at the sector inline electrical test (ILT) at M1 provides the information of process impact on the electrical signal, which ultimately...
A novel block Bayesian hypothesis testing algorithm (BBHTA) is presented for reconstructing block-sparse signals with unknown block structures. The BBHTA detects and recovers the supports and then estimates the amplitudes of block sparse signal. The support detection and recovery are performed by a Bayesian hypothesis testing. Using the detected and reconstructed supports, the nonzero amplitudes are...
Machine-learning test strategy has been developed in the last decade as an alternative to costly specification-driven tests for Analog, Mixed-Signal and RF circuits (AMS-RF). The concept is simple: powerful algorithms are used to map simple measurements onto specifications. But the proper execution requires an information-rich input space. This paper presents an efficient hybrid algorithm to select...
The objective of the work described is to accurately predict, as early as possible in the software lifecycle, how reliably a new software release will behave in the field. The initiative is based on a set of innovative mathematical models that have consistently shown a high correlation between key in-process metrics and our primary customer experience metric, SWDPMH (Software Defects per Million Hours...
Aflatoxin is one of the mycotoxins released by Aspergillus flavus and Aspergillus parasiticus. It is carcinogenic and has stringent regulations in terms of residue limit across the globe. Various food commodities like chilli, groundnut, maize and nutmeg are susceptible to aflatoxin and face challenges in meeting the residue limits set by various importing countries. ITC Limited, an FMCG Conglomerate...
Modeling sensitivity to anti-cancer drugs is a significant challenge in the area of systems medicine. Majority of current approaches generate a deterministic predictive model for each drug based on the genetic characterization of the cell lines and ignores the relationship between different drug sensitivities during model generation. In this article, we approach the problem of modeling the relationship...
Malicious information like harassment, slander or bogus news is becoming a serious problem on social networking sites, and solving it requires profound insight into user behaviors of malicious and victim accounts. In this paper, we conduct a preliminary study on a whistleblowing network, constructed from 328472 whistleblowing (complaining) reports. To evaluate its efficiency, we perform a series of...
The hidden Markov model is supposed as the most common and effective method used in speech recognition for all languages including Vietnamese. However, this method is quite cumbersome and difficult to implement in many embedded systems that have limited resources. Dynamic Time Warping (DTW) method, whereas, has been in much study by many scientists and is proved to be simple and efficient for a relatively...
This work proposes a generic methodology for selecting meaningful subsets of indirect measurements (signatures). This allows precise predictions of the DUT performances and/or precise pass/fail classification of the DUT, while minimizing the number of necessary measurements. Two simple figures of merit are provided for ranking sets of signatures a priori, before training any machine learning model...
When it was originally introduced, Partial Least Squares (PLS) was designed primarily for exploratory studies focusing on prediction (rather than hypothesis testing). Over time, however, PLS has become a very popular statistical analysis technique for testing hypothesized relationships (confirmatory studies) within MIS research. In this paper we note some challenges that have been raised relative...
This paper presents an application of the Radial Basis Function Neural Network (RBFNN)-based identification of an essential oil extraction using Non-Linear Autoregressive Model with Exogenous Inputs (NARX) model. The dataset consisted of a Pseudo-Random Binary Sequence (PRBS) inputs as the control signal, and outputs depicting temperatures inside the distillation column. One Step Ahead (OSA) model...
In this paper, we present a Radial Basis Function Neural Network (RBFNN)-based Nonlinear Auto-Regressive Model with Exegeneous Inputs (NARX) model of a DC motor drive controller model by (Rahim, 2004). Tests were conducted to measure the accuracy of the model (using One Step Ahead (OSA) and its validity (using correlation tests and histogram analysis). The resulting model produced Mean Square Error...
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