Earticle

This paper presents a new nonlinear method to analyze ventricular arrhythmia(VA) and sinus rhythms(SR). The problem is introduced from the discussion of Fractal Random Walk characteristics of ECG signal. Further, the fractal analysis is used to distinguish ventricular flutter(VFL), ventricular fibrillation(VF), ventricular tachycardia(VT)) and sinus rhythms(SR) from the raw electrocardiogram(ECG) data. The method has a three step processing. First, calculating the slope of permutation entropy(PE) to detect the onset of ventricular arrhythmia; Second, using regularization dimension(RD) to classify SR, VFL and VT/VF; Finally, according to multifractal spectrum(MS) area to distinguish VT and VF. Four databases are used to detect the method, and the accuracy of every step is 93.33%, 100% and 98%. As a whole, the accuracy of detecting onset of ventricular arrhythmia and confirming which ventricular arrhythmia is, is VFL 93.33%, VT and VF 91.47%.

A Simple extended Welch inner product theorem is investigated in this paper. Several functions to find the largest possible minimum Hamming distance of the systematic binary block codes are also derived by using the extended Welch inner product theorem. The results will be useful to estimate or design good codes for communications or other information technology.

ReferencesThe current pervasive middleware is designed to have a monolithic structure according to a ‘one-size-fits-all’ paradigm, which lacks necessary flexibilities for optimization, customization and adaptation to different situations. Ontology evolution is another problem that has not been addressed by the existing pervasive middleware. In this paper, we propose the marriage of software product line and intelligent agent based pervasive middleware in order to alleviate these problems, in the context of an ongoing research project called PLIPerM. Frame based software product line techniques are used together with OWL ontology reasoning enhanced BDI (Belief-Desire-Intention) agents, which are the basic building blocks of PLIPerM. Besides the advantages of a software product line, our approach can handle ontology evolution and keep all related assets in a consistent state. Other advantages include the ability to configure Jadex BDI agents for different purpose and to enhance agent intelligence by adding logic reasoning capabilities indirectly to agent beliefs.

Processes can be executed concurrently in operating systems; they can be created dynamically and then terminate, i.e. process creation and termination are required for program execution. However the costs involved in process creation and termination make this procedure expensive. This procedure expensive, thus degrading the performance of program execution. To solve this problem, a fast process creation and termination mechanism is proposed. This mechanism is implemented by recycling process resources. In order to improve the efficiency of recycling, the management of preserved process resources for recycling is an important factor. In this paper, we propose an improved resource management method for recycling process resources and an adaptive control mechanism. In the method, only one process resource with a program image is preserved for each program that occurs with high frequency of program execution. The proposed method can reduce the amount of memory consumption for preserved process resources in a concurrent execution environment. We also describe the implementation of the proposed method on the Tender operating system and report the results of our experiments.

Increasingly, innovations in miniaturization and embedded systems are making pervasive computing a reality. Meanwhile, similar advancements in robotics have made autonomous mobile robots easier to develop and more cost-efficient. However, since the field of ubiquitous robotics remains relatively unexplored, we develop SMARbot (Stevens Modular Autonomous Robot), as a tool to explore the pervasive capability of miniature robots. The SMARTBot was designed to be a highly modular, adaptable, inexpensive base model to integrate miniature mobile robots into the pervasive computing environment. The hardware and software architecture of the prototype are proposed. The experimental results demonstrate the feasibility and efficiency of the SMARbot in the real-world scenarios

As an optimization technique, particle swarm optimization (PSO) has obtained much attention during the past decade. It is gaining popularity, especially because of the speed of convergence and the fact that it is easy to realize. To enhance the performance of PSO, an improved hybrid particle swarm optimization (IPSO) is proposed to solve complex optimization problems more efficiently, accurately and reliably. It provides a new way of producing new individuals through organically merges the harmony search (HS) method into particle swarm optimization (PSO). During the course of evolvement, harmony search is used to generate new solutions and this makes IPSO algorithm have more powerful exploitation capabilities. Simulation results and comparisons with the standard PSO based on several well-studied benchmarks demonstrate that the IPSO can effectively enhance the searching efficiency and greatly improve the search quality.

In East Asia, the high penetration of student cell phones, with built-in features that include bilingual dictionaries, SMS, Email, Internet access and videocams, already offers ubiquitous computing facilities for pedagogical applications. This paper describes an EFL task that required Korean freshmen of Hyejeon College in Chungnam to make L2 English video guides to their campus. Videos were made on their built-in cell phone videocams, and then emailed to their instructor. After file conversion, their videos were uploaded to the instructor’s vblog on his homepage on the English language social networking site US.Cyworld.com (a sister site to the Hangul social networking site Cyworld.com which most Korean students already use). Students were instructed by email to view the videos there, and to then post responses in his homepage guestbook. This required them to use English to set up a personal account and to navigate the social networking site, as well as to compose and post responses. The task illustrates the developing critical importance of L2 Digital Literacy within EFL pedagogy.

A hybrid genetic scheduling strategy (H-GA) is described in this article, H-GA combines with grouping and load balancing strategy based on traditional genetic algorithm (GA). First, tasks are divided into several different subgroups by task granularity. Then, task subgroup which is selected by granularity from big to small is used to schedule by the genetic algorithm, and during scheduling, the load balancing strategy is used to adjust task distribution in the individual. Grouping can cut down the length of individual, which speeds up convergence of genetic algorithm. Load balancing strategy can make the individual better, which also speeds up convergence of genetic algorithm. The implementation shows that converging speed of H-GA is faster than GA, and result of H-GA is optimal than GA if the iteration times are equal.

Because of the limited capability of mobile devices and lower bandwidth of wireless network, Web-based e-commerce in mobile wireless environments suffers more challenges and it needs an efficient and reliable mechanism to support the process. This paper presents a flexible and configurable mechanism, which uses mobile agents as brokers of mobile device to communicate with Web server, thus to reduce the unnecessary wireless communication costs of mobile client. It can also facilitate mobile device recovery back when suffering a failure to increase the reliability of the whole application process. Compared with other mechanisms through performance analysis, our mechanism shows its efficiency and reliability.

Cell membrane proteins play a vitally important role in influencing the behavior of cells. Knowledge of membrane protein type facilitates the determination of its functions, which has implications in numerous applications including drug design. Due to the increasingly large number of uncharacterized proteins in data-banks such as NCBI’s RefSeq, there is a high desire to replace time and cost consuming experimental methods for membrane protein type classification with computational methods. This paper introduces a new computational method that accurately predicts the type of unclassified membrane proteins based on their sequence. Our method is based on a novel representation of protein sequences that incorporates seven different feature sets. Empirical comparison, which includes twelve competing methods, shows that the presented method generates predictions that result in 8% and 28% error rate reduction when compared with the best existing computational method and when using the jackknife test and testing on an independent dataset, respectively. We also show that the most influential sources of information for making the predictions include the composition of 2-gram exchange groups and the amino acid composition of the underlying sequence.

To manage security level of information system (IS), organizations must select security practices (SP) first, and then apply them according to security level. SP can be divided into 2 groups security management part (SMP) and security technology part (STP), and some SPs in SMP were proposed already by Drs. Tai-hoon Kim and Kouichi Sakurai [1]. In this paper, we propose some SPs in STP to construct STP for Security Level Management Model (SLMM).