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In this paper, a software toolkit has been developed for in silica prediction of the differentiation destiny of Mesenchymal Stem Cells (MSCs) in vitro. The software toolkit was developed in CLIPS (C Language Integrated Production System) as an expert system, with a java-based GUI. This toolkit utilizes the rules obtained from previous experimental data via data mining techniques, based on which the...
A new test access mechanism (TAM) for multiple identical embedded cores is proposed. It exploits the identical nature of the cores and modular pipelined circuitry to provide scalable and flexible capabilities to make tradeoffs between test time and diagnosis over the manufacturing maturity cycle from low-yield initial production to high-yield, high-volume production. The test throughput gains of various...
The paper tries to step in a forbidden area of software engineering - to achieve the users' requirements specification of ideal quality in DIRPT (do it right the first time) way. The key idea happens to be a trilogy: modeling business relevant to the purpose of the software to be developed with a compact business model, defining a complete set of inhomogeneous users in conformity with the business...
Student performance in middle school math and science is in a perilous state. This crisis is reflected in results on key national assessments such as NAEP that indicate that less than one-third of students in the 8th grade perform at a proficient or higher level in math or science. To address this issue, an innovative Instructional Model, the 4E ?? 2 Model, was recently proposed by us to improve the...
An integrated sensor array system is developed for detection and identification of environmental pollutants in diesel and gasoline exhaust fumes. The system includes a low noise floor analog front-end followed by a signal processing stage. Classification methods are used since the pollutants are often encountered as complex mixtures. In this paper, we present techniques to detect, digitize and classify...
This paper describes the research conducted at Monash University (Australia) to design a new mechatronics fish sorting system. The system consisted of a vision system for fish size identification and control and a sorting mechanism. This paper focuses on the control and sorting mechanism. The conceptual design and implementation of the mechatronics sorting system is discussed. Also the new design...
Exploring brain electrical activity represented by electroencephalogram (EEG) signals for biometric applications has recently attracted increasing research attention since EEG pattern has been shown to be unique for each individual. In this paper, we propose an Independent Component Analysis (ICA) based EEG feature extraction and modeling approach for person authentication. Five dominating Independent...
This paper presents a comprehensive system modeling and analysis approach for both predicting and controlling queuing delay at an expected value under multi-class traffic in a single buffer. This approach could effectively enhance QoS delivery for delay sensitive applications. Six major contributions are given in the paper: (1) a discrete-time analytical model is developed for capturing multi-class...
A wide range of numerical models and tools have been developed over the last decades to support the decision making process in environmental applications, ranging from physical models to a variety of statistically-based methods. In this study, a landslide susceptibility map of a part of Three Gorges Reservoir region of China was produced, employing binary logistic regression analyses. The available...
In this work we present an scientific application that has been given a Hadoop MapReduce implementation. We also discuss other scientific fields of supercomputing that could benefit from a MapReduce implementation. We recognize in this work that Hadoop has potential benefit for more applications than simply data mining, but that it is not a panacea for all data intensive applications. We provide an...
In this paper, we investigate the statistical properties of fluctuations of Chinese stock index. According to the theory of artificial neural network, a stochastic time effective function is introduced in the forecasting model of the index in the present paper, which gives an improved neural network - the stochastic time effective neural network model. In this model, a promising data mining technique...
Halogen-free requirement1 in PCBA and in related materials has been gaining momentum in recent months. Major computer manufacturers had made announcements about intentions to go bromine-free in the next two years2,3. Halogen-free started from RoHS banned substances on PBB4 and PBDE5 initially, however, it has evolved to a broader coverage of detectable halogen level per IEC 61249-2-216, JPCA-ES-01-2003...
In today's advanced manufacturing environments, rapid problem recognition is critical to the financial success of the factory. Automated data mining and analysis routines initially flag more and more factory problems. Unless properly tuned, however, these automated systems can generate a mountain of process control signals and create additional work for engineers who must determine which are worthy...
Zero-day attacks - especially those that hide the attack exploit by using code obfuscation and encryption - remain a formidable challenge to existing network defenses. Many techniques have been developed that can address known attacks and similar new attacks that may arise in the future. Some methods, like Earlybird and Polygraph, focus on string-based content prevalence in payloads; others focus...
Perceptual landmarks are an effective solution for a mobile robot realizing steady and reliable long distance navigation. But the prerequisite is those landmarks must be detected and recognized robustly at a higher speed under various lighting conditions. The image processing is generally made more complicated so that its speed and reliability may not be both satisfied at the same time. Color based...
Parallel Monte Carlo techniques for simulating the evolution of an assembly of charged particles interacting with a background gas medium under the influence of the electrical field are presented. This simulation problem has inherent parallelism in nature. All the particles can be traced independently in a short time interval. We have overcome three major difficulties: 1) the number of particles to...
We simulate three neural networks on a vector multiprocrssor. The training time can be reduced significantly especially when the training data size is large. These three neural networks are: 1) the feedforward network, 2) the recurrent network and 3) the Hopfield network. The training algorithms are programmed in such a way to best utilize 1) the inherent parallelism in neural computing, and 2) the...
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